id	sid	tid	token	lemma	pos
ma-100	1	1	2023	2023	NUM
ma-100	1	2	ada	ada	PROPN
ma-100	1	3	academica	academica	PROPN
ma-100	1	4	https://adac.eeeur	https://adac.eeeur	PROPN
ma-100	1	5	.	.	PUNCT
ma-100	2	1	j.	j.	PROPN
ma-100	2	2	math	math	PROPN
ma-100	2	3	.	.	PUNCT
ma-100	3	1	anal	anal	ADJ
ma-100	3	2	.	.	PUNCT
ma-100	4	1	3	3	NUM
ma-100	4	2	(	(	PUNCT
ma-100	4	3	2023	2023	NUM
ma-100	4	4	)	)	PUNCT
ma-100	5	1	2doi	2doi	NUM
ma-100	5	2	:	:	PUNCT
ma-100	5	3	10.28924	10.28924	NUM
ma-100	5	4	/	/	SYM
ma-100	5	5	ada	ada	PROPN
ma-100	5	6	/	/	SYM
ma-100	5	7	ma.3.2	ma.3.2	PROPN
ma-100	5	8	analysis	analysis	NOUN
ma-100	5	9	of	of	ADP
ma-100	5	10	neuronal	neuronal	ADJ
ma-100	5	11	oscillations	oscillation	NOUN
ma-100	5	12	of	of	ADP
ma-100	5	13	fractional	fractional	ADJ
ma-100	5	14	-	-	PUNCT
ma-100	5	15	order	order	NOUN
ma-100	5	16	morris	morris	ADJ
ma-100	5	17	-	-	PUNCT
ma-100	5	18	lecar	lecar	ADJ
ma-100	5	19	model	model	NOUN
ma-100	5	20	tahmineh	tahmineh	PROPN
ma-100	5	21	azizi	azizi	PROPN
ma-100	5	22	department	department	PROPN
ma-100	5	23	of	of	ADP
ma-100	5	24	mechanical	mechanical	ADJ
ma-100	5	25	engineering	engineering	NOUN
ma-100	5	26	,	,	PUNCT
ma-100	5	27	florida	florida	PROPN
ma-100	5	28	state	state	PROPN
ma-100	5	29	university	university	PROPN
ma-100	5	30	,	,	PUNCT
ma-100	5	31	usa	usa	PROPN
ma-100	5	32	correspondence	correspondence	NOUN
ma-100	5	33	:	:	PUNCT
ma-100	5	34	tazizi@fsu.edu	tazizi@fsu.edu	PROPN
ma-100	5	35	abstract	abstract	ADJ
ma-100	5	36	.	.	PUNCT
ma-100	6	1	fractional	fractional	ADJ
ma-100	6	2	calculus	calculus	NOUN
ma-100	6	3	is	be	AUX
ma-100	6	4	a	a	DET
ma-100	6	5	new	new	ADJ
ma-100	6	6	approach	approach	NOUN
ma-100	6	7	for	for	ADP
ma-100	6	8	modeling	model	VERB
ma-100	6	9	biological	biological	ADJ
ma-100	6	10	and	and	CCONJ
ma-100	6	11	physical	physical	ADJ
ma-100	6	12	phenomena	phenomenon	NOUN
ma-100	6	13	withmemory	withmemory	NOUN
ma-100	6	14	effects	effect	NOUN
ma-100	6	15	.	.	PUNCT
ma-100	7	1	fractional	fractional	ADJ
ma-100	7	2	calculus	calculus	NOUN
ma-100	7	3	uses	use	VERB
ma-100	7	4	differential	differential	ADJ
ma-100	7	5	and	and	CCONJ
ma-100	7	6	integral	integral	ADJ
ma-100	7	7	operators	operator	NOUN
ma-100	7	8	including	include	VERB
ma-100	7	9	non	non	NOUN
ma-100	7	10	-	-	NOUN
ma-100	7	11	integerorders	integerorder	NOUN
ma-100	7	12	to	to	PART
ma-100	7	13	study	study	VERB
ma-100	7	14	the	the	DET
ma-100	7	15	non	non	ADJ
ma-100	7	16	-	-	ADJ
ma-100	7	17	linear	linear	ADJ
ma-100	7	18	behavior	behavior	NOUN
ma-100	7	19	of	of	ADP
ma-100	7	20	physical	physical	ADJ
ma-100	7	21	and	and	CCONJ
ma-100	7	22	biological	biological	ADJ
ma-100	7	23	systems	system	NOUN
ma-100	7	24	with	with	ADP
ma-100	7	25	some	some	DET
ma-100	7	26	degrees	degree	NOUN
ma-100	7	27	offractionality	offractionality	NOUN
ma-100	7	28	or	or	CCONJ
ma-100	7	29	fractality	fractality	NOUN
ma-100	7	30	.	.	PUNCT
ma-100	8	1	since	since	SCONJ
ma-100	8	2	the	the	DET
ma-100	8	3	long	long	ADJ
ma-100	8	4	memory	memory	NOUN
ma-100	8	5	properties	property	NOUN
ma-100	8	6	of	of	ADP
ma-100	8	7	neuronal	neuronal	ADJ
ma-100	8	8	responses	response	NOUN
ma-100	8	9	can	can	AUX
ma-100	8	10	be	be	AUX
ma-100	8	11	betterexplained	betterexplaine	VERB
ma-100	8	12	using	use	VERB
ma-100	8	13	fractional	fractional	ADJ
ma-100	8	14	derivative	derivative	NOUN
ma-100	8	15	,	,	PUNCT
ma-100	8	16	in	in	ADP
ma-100	8	17	this	this	DET
ma-100	8	18	study	study	NOUN
ma-100	8	19	we	we	PRON
ma-100	8	20	generalize	generalize	VERB
ma-100	8	21	the	the	DET
ma-100	8	22	integer	integer	NOUN
ma-100	8	23	-	-	PUNCT
ma-100	8	24	order	order	NOUN
ma-100	8	25	morris	morris	NOUN
ma-100	8	26	-	-	PUNCT
ma-100	8	27	lecarmodel	lecarmodel	NOUN
ma-100	8	28	in	in	ADP
ma-100	8	29	the	the	DET
ma-100	8	30	fractional	fractional	ADJ
ma-100	8	31	-	-	PUNCT
ma-100	8	32	order	order	NOUN
ma-100	8	33	domain	domain	NOUN
ma-100	8	34	to	to	ADP
ma-100	8	35	better	well	ADJ
ma-100	8	36	modeling	modeling	NOUN
ma-100	8	37	of	of	ADP
ma-100	8	38	neuron	neuron	NOUN
ma-100	8	39	dynamics	dynamic	NOUN
ma-100	8	40	.	.	PUNCT
ma-100	9	1	to	to	PART
ma-100	9	2	investigate	investigate	VERB
ma-100	9	3	thecomplex	thecomplex	NOUN
ma-100	9	4	spiking	spike	VERB
ma-100	9	5	patterns	pattern	NOUN
ma-100	9	6	of	of	ADP
ma-100	9	7	fractional	fractional	ADJ
ma-100	9	8	-	-	PUNCT
ma-100	9	9	order	order	NOUN
ma-100	9	10	morris	morris	ADJ
ma-100	9	11	-	-	PUNCT
ma-100	9	12	lecar	lecar	ADJ
ma-100	9	13	neural	neural	ADJ
ma-100	9	14	system	system	NOUN
ma-100	9	15	the	the	DET
ma-100	9	16	fractional	fractional	ADJ
ma-100	9	17	calculus	calculus	NOUN
ma-100	9	18	hasbeen	hasbeen	NOUN
ma-100	9	19	applied	apply	VERB
ma-100	9	20	to	to	PART
ma-100	9	21	build	build	VERB
ma-100	9	22	this	this	DET
ma-100	9	23	new	new	ADJ
ma-100	9	24	mathematical	mathematical	ADJ
ma-100	9	25	model	model	NOUN
ma-100	9	26	.	.	PUNCT
ma-100	10	1	we	we	PRON
ma-100	10	2	compare	compare	VERB
ma-100	10	3	the	the	DET
ma-100	10	4	results	result	NOUN
ma-100	10	5	with	with	ADP
ma-100	10	6	integer	integer	NOUN
ma-100	10	7	-	-	PUNCT
ma-100	10	8	order	order	NOUN
ma-100	10	9	morris	morris	ADJ
ma-100	10	10	-	-	PUNCT
ma-100	10	11	lecar	lecar	NOUN
ma-100	10	12	model	model	NOUN
ma-100	10	13	.	.	PUNCT
ma-100	11	1	the	the	DET
ma-100	11	2	analytical	analytical	ADJ
ma-100	11	3	solutions	solution	NOUN
ma-100	11	4	of	of	ADP
ma-100	11	5	these	these	DET
ma-100	11	6	equations	equation	NOUN
ma-100	11	7	can	can	AUX
ma-100	11	8	not	not	PART
ma-100	11	9	explicitly	explicitly	ADV
ma-100	11	10	be	be	AUX
ma-100	11	11	obtained	obtain	VERB
ma-100	11	12	.	.	PUNCT
ma-100	12	1	therefore	therefore	ADV
ma-100	12	2	,	,	PUNCT
ma-100	12	3	tofind	tofind	VERB
ma-100	12	4	the	the	DET
ma-100	12	5	dynamical	dynamical	ADJ
ma-100	12	6	behaviors	behavior	NOUN
ma-100	12	7	of	of	ADP
ma-100	12	8	solutions	solution	NOUN
ma-100	12	9	,	,	PUNCT
ma-100	12	10	we	we	PRON
ma-100	12	11	used	use	VERB
ma-100	12	12	approximation	approximation	NOUN
ma-100	12	13	and	and	CCONJ
ma-100	12	14	numerical	numerical	ADJ
ma-100	12	15	schemes	scheme	NOUN
ma-100	12	16	.	.	PUNCT
ma-100	13	1	dependingon	dependingon	PROPN
ma-100	13	2	the	the	DET
ma-100	13	3	different	different	ADJ
ma-100	13	4	parameters	parameter	NOUN
ma-100	13	5	values	value	NOUN
ma-100	13	6	for	for	ADP
ma-100	13	7	0	0	NUM
ma-100	13	8	<	<	X
ma-100	13	9	η	η	PROPN
ma-100	13	10	≤	≤	PROPN
ma-100	13	11	1	1	NUM
ma-100	13	12	,	,	PUNCT
ma-100	13	13	the	the	DET
ma-100	13	14	fractional	fractional	ADJ
ma-100	13	15	-	-	PUNCT
ma-100	13	16	order	order	NOUN
ma-100	13	17	morris	morris	ADJ
ma-100	13	18	-	-	PUNCT
ma-100	13	19	lecar	lecar	ADJ
ma-100	13	20	reproducesquiescent	reproducesquiescent	NOUN
ma-100	13	21	,	,	PUNCT
ma-100	13	22	spiking	spike	VERB
ma-100	13	23	and	and	CCONJ
ma-100	13	24	bursting	bursting	NOUN
ma-100	13	25	activities	activity	NOUN
ma-100	13	26	the	the	DET
ma-100	13	27	same	same	ADJ
ma-100	13	28	as	as	ADP
ma-100	13	29	its	its	PRON
ma-100	13	30	original	original	ADJ
ma-100	13	31	model	model	NOUN
ma-100	13	32	but	but	CCONJ
ma-100	13	33	for	for	ADP
ma-100	13	34	higher	high	ADJ
ma-100	13	35	input	input	NOUN
ma-100	13	36	current.we	current.we	PRON
ma-100	13	37	numerically	numerically	ADV
ma-100	13	38	discover	discover	VERB
ma-100	13	39	the	the	DET
ma-100	13	40	hopf	hopf	ADJ
ma-100	13	41	bifurcation	bifurcation	NOUN
ma-100	13	42	,	,	PUNCT
ma-100	13	43	saddle	saddle	ADJ
ma-100	13	44	node	node	ADJ
ma-100	13	45	bifurcation	bifurcation	NOUN
ma-100	13	46	of	of	ADP
ma-100	13	47	limit	limit	NOUN
ma-100	13	48	cycle	cycle	NOUN
ma-100	13	49	and	and	CCONJ
ma-100	13	50	homoclinicbifurcation	homoclinicbifurcation	NOUN
ma-100	13	51	for	for	ADP
ma-100	13	52	this	this	DET
ma-100	13	53	model	model	NOUN
ma-100	13	54	for	for	ADP
ma-100	13	55	different	different	ADJ
ma-100	13	56	input	input	NOUN
ma-100	13	57	current	current	ADJ
ma-100	13	58	and	and	CCONJ
ma-100	13	59	derivative	derivative	ADJ
ma-100	13	60	orders	order	NOUN
ma-100	13	61	.	.	PUNCT
ma-100	14	1	taking	take	VERB
ma-100	14	2	the	the	DET
ma-100	14	3	advantages	advantage	NOUN
ma-100	14	4	ofthe	ofthe	VERB
ma-100	14	5	fractional	fractional	ADJ
ma-100	14	6	order	order	NOUN
ma-100	14	7	derivative	derivative	NOUN
ma-100	14	8	,	,	PUNCT
ma-100	14	9	for	for	ADP
ma-100	14	10	a	a	DET
ma-100	14	11	variety	variety	NOUN
ma-100	14	12	of	of	ADP
ma-100	14	13	orders	order	NOUN
ma-100	14	14	,	,	PUNCT
ma-100	14	15	we	we	PRON
ma-100	14	16	define	define	VERB
ma-100	14	17	different	different	ADJ
ma-100	14	18	classes	class	NOUN
ma-100	14	19	of	of	ADP
ma-100	14	20	this	this	DET
ma-100	14	21	model	model	NOUN
ma-100	14	22	whichhelps	whichhelp	NOUN
ma-100	14	23	to	to	PART
ma-100	14	24	better	well	ADV
ma-100	14	25	extract	extract	VERB
ma-100	14	26	all	all	DET
ma-100	14	27	the	the	DET
ma-100	14	28	complicated	complicated	ADJ
ma-100	14	29	dynamics	dynamic	NOUN
ma-100	14	30	of	of	ADP
ma-100	14	31	this	this	DET
ma-100	14	32	single	single	ADJ
ma-100	14	33	neuron	neuron	PROPN
ma-100	14	34	model	model	NOUN
ma-100	14	35	.	.	PUNCT
ma-100	15	1	1	1	X
ma-100	15	2	.	.	X
ma-100	15	3	introduction	introduction	NOUN
ma-100	15	4	recently	recently	ADV
ma-100	15	5	,	,	PUNCT
ma-100	15	6	fractional	fractional	ADJ
ma-100	15	7	calculus	calculus	NOUN
ma-100	15	8	has	have	AUX
ma-100	15	9	been	be	AUX
ma-100	15	10	frequently	frequently	ADV
ma-100	15	11	used	use	VERB
ma-100	15	12	by	by	ADP
ma-100	15	13	many	many	ADJ
ma-100	15	14	researchers	researcher	NOUN
ma-100	15	15	in	in	ADP
ma-100	15	16	biology	biology	NOUN
ma-100	15	17	,	,	PUNCT
ma-100	15	18	physics	physics	NOUN
ma-100	15	19	,	,	PUNCT
ma-100	15	20	chemistry	chemistry	NOUN
ma-100	15	21	and	and	CCONJ
ma-100	15	22	biochemistry	biochemistry	NOUN
ma-100	15	23	,	,	PUNCT
ma-100	15	24	hydrology	hydrology	NOUN
ma-100	15	25	,	,	PUNCT
ma-100	15	26	medicine	medicine	NOUN
ma-100	15	27	,	,	PUNCT
ma-100	15	28	and	and	CCONJ
ma-100	15	29	finance	finance	NOUN
ma-100	15	30	and	and	CCONJ
ma-100	15	31	its	its	PRON
ma-100	15	32	application	application	NOUN
ma-100	15	33	in	in	ADP
ma-100	15	34	modelingcomplex	modelingcomplex	ADJ
ma-100	15	35	phenomena	phenomenon	NOUN
ma-100	15	36	has	have	AUX
ma-100	15	37	increased	increase	VERB
ma-100	15	38	its	its	PRON
ma-100	15	39	popularity	popularity	NOUN
ma-100	15	40	and	and	CCONJ
ma-100	15	41	the	the	DET
ma-100	15	42	number	number	NOUN
ma-100	15	43	of	of	ADP
ma-100	15	44	publications	publication	NOUN
ma-100	15	45	in	in	ADP
ma-100	15	46	above	above	ADP
ma-100	15	47	area	area	NOUN
ma-100	15	48	[	[	X
ma-100	15	49	1–6].the	1–6].the	DET
ma-100	15	50	main	main	ADJ
ma-100	15	51	characteristic	characteristic	NOUN
ma-100	15	52	of	of	ADP
ma-100	15	53	fractional	fractional	ADJ
ma-100	15	54	order	order	NOUN
ma-100	15	55	derivative	derivative	NOUN
ma-100	15	56	is	be	AUX
ma-100	15	57	called	call	VERB
ma-100	15	58	the	the	DET
ma-100	15	59	"	"	PUNCT
ma-100	15	60	memory	memory	NOUN
ma-100	15	61	effect	effect	NOUN
ma-100	15	62	"	"	PUNCT
ma-100	15	63	and	and	CCONJ
ma-100	15	64	it	it	PRON
ma-100	15	65	has	have	AUX
ma-100	15	66	beenexperimentally	beenexperimentally	ADV
ma-100	15	67	proved	prove	VERB
ma-100	15	68	that	that	SCONJ
ma-100	15	69	the	the	DET
ma-100	15	70	fractional	fractional	ADJ
ma-100	15	71	order	order	NOUN
ma-100	15	72	differential	differential	NOUN
ma-100	15	73	or	or	CCONJ
ma-100	15	74	integral	integral	ADJ
ma-100	15	75	equations	equation	NOUN
ma-100	15	76	models	model	NOUN
ma-100	15	77	are	be	AUX
ma-100	15	78	morerealistic	morerealistic	ADJ
ma-100	15	79	to	to	PART
ma-100	15	80	demonstrate	demonstrate	VERB
ma-100	15	81	the	the	DET
ma-100	15	82	complex	complex	ADJ
ma-100	15	83	behavior	behavior	NOUN
ma-100	15	84	of	of	ADP
ma-100	15	85	some	some	DET
ma-100	15	86	biological	biological	ADJ
ma-100	15	87	or	or	CCONJ
ma-100	15	88	physical	physical	ADJ
ma-100	15	89	systems	system	NOUN
ma-100	15	90	includingfractality	includingfractality	NOUN
ma-100	15	91	and	and	CCONJ
ma-100	15	92	memory	memory	NOUN
ma-100	15	93	compared	compare	VERB
ma-100	15	94	to	to	ADP
ma-100	15	95	their	their	PRON
ma-100	15	96	odes	ode	NOUN
ma-100	15	97	of	of	ADP
ma-100	15	98	integer	integer	NOUN
ma-100	15	99	-	-	PUNCT
ma-100	15	100	order	order	NOUN
ma-100	15	101	systems	system	NOUN
ma-100	16	1	[	[	X
ma-100	16	2	2	2	NUM
ma-100	16	3	,	,	PUNCT
ma-100	16	4	6	6	NUM
ma-100	16	5	]	]	PUNCT
ma-100	16	6	.	.	PUNCT
ma-100	17	1	complexity	complexity	NOUN
ma-100	17	2	in	in	ADP
ma-100	17	3	thiscontext	thiscontext	NOUN
ma-100	17	4	combined	combine	VERB
ma-100	17	5	the	the	DET
ma-100	17	6	recent	recent	ADJ
ma-100	17	7	advances	advance	NOUN
ma-100	17	8	in	in	ADP
ma-100	17	9	neuroscience	neuroscience	NOUN
ma-100	17	10	with	with	ADP
ma-100	17	11	the	the	DET
ma-100	17	12	concepts	concept	NOUN
ma-100	17	13	from	from	ADP
ma-100	17	14	fractal	fractal	ADJ
ma-100	17	15	geometry	geometry	NOUN
ma-100	17	16	andnonlinear	andnonlinear	NOUN
ma-100	17	17	dynamics	dynamic	NOUN
ma-100	17	18	to	to	PART
ma-100	17	19	form	form	VERB
ma-100	17	20	a	a	DET
ma-100	17	21	new	new	ADJ
ma-100	17	22	approach	approach	NOUN
ma-100	17	23	within	within	ADP
ma-100	17	24	the	the	DET
ma-100	17	25	life	life	NOUN
ma-100	17	26	sciences	science	NOUN
ma-100	17	27	which	which	PRON
ma-100	17	28	is	be	AUX
ma-100	17	29	useful	useful	ADJ
ma-100	17	30	in	in	ADP
ma-100	17	31	controlling	control	VERB
ma-100	17	32	received	receive	VERB
ma-100	17	33	:	:	PUNCT
ma-100	17	34	17	17	NUM
ma-100	17	35	apr	apr	NOUN
ma-100	17	36	2022	2022	NUM
ma-100	17	37	.	.	PUNCT
ma-100	18	1	key	key	ADJ
ma-100	18	2	words	word	NOUN
ma-100	18	3	and	and	CCONJ
ma-100	18	4	phrases	phrase	NOUN
ma-100	18	5	.	.	PUNCT
ma-100	19	1	fractional	fractional	ADJ
ma-100	19	2	calculus	calculus	NOUN
ma-100	19	3	;	;	PUNCT
ma-100	19	4	nsfd	nsfd	ADJ
ma-100	19	5	method	method	NOUN
ma-100	19	6	;	;	PUNCT
ma-100	19	7	hopf	hopf	ADJ
ma-100	19	8	bifurcation	bifurcation	NOUN
ma-100	19	9	;	;	PUNCT
ma-100	19	10	homoclinic	homoclinic	ADJ
ma-100	19	11	bifurcation	bifurcation	NOUN
ma-100	19	12	;	;	PUNCT
ma-100	19	13	grunwald	grunwald	NOUN
ma-100	19	14	-	-	PUNCT
ma-100	19	15	letinkov	letinkov	NOUN
ma-100	19	16	method	method	NOUN
ma-100	19	17	.	.	PUNCT
ma-100	20	1	1	1	NUM
ma-100	20	2	https://adac.ee	https://adac.ee	PROPN
ma-100	20	3	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	20	4	eur	eur	NOUN
ma-100	20	5	.	.	PUNCT
ma-100	21	1	j.	j.	PROPN
ma-100	21	2	math	math	PROPN
ma-100	21	3	.	.	PUNCT
ma-100	22	1	anal	anal	PROPN
ma-100	22	2	.	.	PUNCT
ma-100	23	1	10.28924	10.28924	NUM
ma-100	23	2	/	/	SYM
ma-100	23	3	ada	ada	PROPN
ma-100	23	4	/	/	SYM
ma-100	23	5	ma.3.2	ma.3.2	PROPN
ma-100	23	6	2the	2the	NUM
ma-100	23	7	dynamics	dynamic	NOUN
ma-100	23	8	of	of	ADP
ma-100	23	9	fractal	fractal	ADJ
ma-100	23	10	processes	process	NOUN
ma-100	23	11	in	in	ADP
ma-100	23	12	this	this	DET
ma-100	23	13	area	area	NOUN
ma-100	24	1	[	[	X
ma-100	24	2	7	7	NUM
ma-100	24	3	,	,	PUNCT
ma-100	24	4	8].understanding	8].understande	VERB
ma-100	24	5	the	the	DET
ma-100	24	6	complicated	complicated	ADJ
ma-100	24	7	functioning	functioning	NOUN
ma-100	24	8	of	of	ADP
ma-100	24	9	the	the	DET
ma-100	24	10	neuronal	neuronal	ADJ
ma-100	24	11	cells	cell	NOUN
ma-100	24	12	and	and	CCONJ
ma-100	24	13	exploring	explore	VERB
ma-100	24	14	the	the	DET
ma-100	24	15	molecular	molecular	ADJ
ma-100	24	16	andcellular	andcellular	ADJ
ma-100	24	17	mechanisms	mechanism	NOUN
ma-100	24	18	of	of	ADP
ma-100	24	19	their	their	PRON
ma-100	24	20	network	network	NOUN
ma-100	24	21	have	have	AUX
ma-100	24	22	been	be	AUX
ma-100	24	23	one	one	NUM
ma-100	24	24	of	of	ADP
ma-100	24	25	the	the	DET
ma-100	24	26	greatest	great	ADJ
ma-100	24	27	challenges	challenge	NOUN
ma-100	24	28	in	in	ADP
ma-100	24	29	different	different	ADJ
ma-100	24	30	fieldsof	fieldsof	ADJ
ma-100	24	31	science	science	NOUN
ma-100	24	32	.	.	PUNCT
ma-100	25	1	the	the	DET
ma-100	25	2	progress	progress	NOUN
ma-100	25	3	and	and	CCONJ
ma-100	25	4	advances	advance	NOUN
ma-100	25	5	in	in	ADP
ma-100	25	6	computational	computational	ADJ
ma-100	25	7	neuroscience	neuroscience	NOUN
ma-100	25	8	could	could	AUX
ma-100	25	9	help	help	VERB
ma-100	25	10	scientists	scientist	NOUN
ma-100	25	11	tobetter	tobetter	ADJ
ma-100	25	12	understanding	understanding	NOUN
ma-100	25	13	of	of	ADP
ma-100	25	14	the	the	DET
ma-100	25	15	performance	performance	NOUN
ma-100	25	16	of	of	ADP
ma-100	25	17	brain	brain	NOUN
ma-100	25	18	and	and	CCONJ
ma-100	25	19	neuron	neuron	NOUN
ma-100	25	20	cells	cell	NOUN
ma-100	25	21	and	and	CCONJ
ma-100	25	22	better	well	ADJ
ma-100	25	23	fighting	fighting	NOUN
ma-100	25	24	with	with	ADP
ma-100	25	25	diseasesrelated	diseasesrelate	VERB
ma-100	25	26	to	to	PART
ma-100	25	27	neuron	neuron	VERB
ma-100	25	28	cells	cell	NOUN
ma-100	25	29	such	such	ADJ
ma-100	25	30	as	as	ADP
ma-100	25	31	parkinson	parkinson	NOUN
ma-100	25	32	’s	’s	PART
ma-100	25	33	and	and	CCONJ
ma-100	25	34	depression.non	depression.non	NOUN
ma-100	25	35	-	-	ADJ
ma-100	25	36	linear	linear	ADJ
ma-100	25	37	dynamical	dynamical	ADJ
ma-100	25	38	system	system	NOUN
ma-100	25	39	theory	theory	NOUN
ma-100	25	40	has	have	VERB
ma-100	25	41	a	a	DET
ma-100	25	42	very	very	ADV
ma-100	25	43	important	important	ADJ
ma-100	25	44	role	role	NOUN
ma-100	25	45	in	in	ADP
ma-100	25	46	the	the	DET
ma-100	25	47	computational	computational	ADJ
ma-100	25	48	neuroscienceresearch	neuroscienceresearch	NOUN
ma-100	26	1	[	[	X
ma-100	26	2	9–13	9–13	NOUN
ma-100	26	3	]	]	PUNCT
ma-100	26	4	.	.	PUNCT
ma-100	27	1	in	in	ADP
ma-100	27	2	1948	1948	NUM
ma-100	27	3	hodgkin	hodgkin	NOUN
ma-100	27	4	by	by	ADP
ma-100	27	5	injecting	inject	VERB
ma-100	27	6	a	a	DET
ma-100	27	7	dc	dc	PROPN
ma-100	27	8	-	-	PUNCT
ma-100	27	9	current	current	NOUN
ma-100	27	10	of	of	ADP
ma-100	27	11	varying	vary	VERB
ma-100	27	12	amplitude	amplitude	NOUN
ma-100	27	13	discovered	discover	VERB
ma-100	27	14	thatsome	thatsome	NOUN
ma-100	27	15	preparations	preparation	NOUN
ma-100	27	16	could	could	AUX
ma-100	27	17	show	show	VERB
ma-100	27	18	repetitive	repetitive	ADJ
ma-100	27	19	spiking	spike	VERB
ma-100	27	20	activities	activity	NOUN
ma-100	27	21	with	with	ADP
ma-100	27	22	arbitrarily	arbitrarily	ADV
ma-100	27	23	low	low	ADJ
ma-100	27	24	frequencies	frequency	NOUN
ma-100	27	25	,	,	PUNCT
ma-100	27	26	whilethe	whilethe	ADJ
ma-100	27	27	others	other	NOUN
ma-100	27	28	discharged	discharge	VERB
ma-100	27	29	in	in	ADP
ma-100	27	30	a	a	DET
ma-100	27	31	narrow	narrow	ADJ
ma-100	27	32	frequency	frequency	NOUN
ma-100	27	33	band	band	NOUN
ma-100	28	1	[	[	X
ma-100	28	2	9	9	NUM
ma-100	28	3	,	,	PUNCT
ma-100	28	4	13–15	13–15	NUM
ma-100	28	5	]	]	PUNCT
ma-100	28	6	.	.	PUNCT
ma-100	29	1	his	his	PRON
ma-100	29	2	finding	find	VERB
ma-100	29	3	motivated	motivated	ADJ
ma-100	29	4	rinzel	rinzel	NOUN
ma-100	29	5	andermentrout	andermentrout	NOUN
ma-100	29	6	to	to	PART
ma-100	29	7	discover	discover	VERB
ma-100	29	8	that	that	DET
ma-100	29	9	different	different	ADJ
ma-100	29	10	bifurcation	bifurcation	NOUN
ma-100	29	11	mechanisms	mechanism	NOUN
ma-100	29	12	of	of	ADP
ma-100	29	13	excitability	excitability	NOUN
ma-100	29	14	may	may	AUX
ma-100	29	15	cause	cause	VERB
ma-100	29	16	the	the	DET
ma-100	29	17	differencein	differencein	ADJ
ma-100	29	18	neuronal	neuronal	ADJ
ma-100	29	19	behavior	behavior	NOUN
ma-100	29	20	[	[	X
ma-100	29	21	9,16,17	9,16,17	NUM
ma-100	29	22	]	]	PUNCT
ma-100	29	23	.	.	PUNCT
ma-100	30	1	basically	basically	ADV
ma-100	30	2	,	,	PUNCT
ma-100	30	3	if	if	SCONJ
ma-100	30	4	assume	assume	VERB
ma-100	30	5	the	the	DET
ma-100	30	6	applied	applied	ADJ
ma-100	30	7	current	current	ADJ
ma-100	30	8	iapp	iapp	NOUN
ma-100	30	9	as	as	ADP
ma-100	30	10	a	a	DET
ma-100	30	11	control	control	NOUN
ma-100	30	12	parameter	parameter	NOUN
ma-100	30	13	,	,	PUNCT
ma-100	30	14	we	we	PRON
ma-100	30	15	can	can	AUX
ma-100	30	16	easily	easily	ADV
ma-100	30	17	see	see	VERB
ma-100	30	18	the	the	DET
ma-100	30	19	transition	transition	NOUN
ma-100	30	20	in	in	ADP
ma-100	30	21	behavior	behavior	NOUN
ma-100	30	22	of	of	ADP
ma-100	30	23	a	a	DET
ma-100	30	24	neuron	neuron	NOUN
ma-100	30	25	which	which	PRON
ma-100	30	26	corresponds	correspond	VERB
ma-100	30	27	to	to	ADP
ma-100	30	28	a	a	DET
ma-100	30	29	bifurcation	bifurcation	NOUN
ma-100	30	30	fromequilibrium	fromequilibrium	NOUN
ma-100	30	31	to	to	ADP
ma-100	30	32	a	a	DET
ma-100	30	33	limit	limit	NOUN
ma-100	30	34	cycle	cycle	NOUN
ma-100	30	35	attractor	attractor	NOUN
ma-100	30	36	.	.	PUNCT
ma-100	31	1	that	that	PRON
ma-100	31	2	is	be	AUX
ma-100	31	3	when	when	SCONJ
ma-100	31	4	iapp	iapp	NOUN
ma-100	31	5	is	be	AUX
ma-100	31	6	small	small	ADJ
ma-100	31	7	,	,	PUNCT
ma-100	31	8	the	the	DET
ma-100	31	9	cell	cell	NOUN
ma-100	31	10	remains	remain	VERB
ma-100	31	11	quiescent	quiescent	ADJ
ma-100	31	12	andwith	andwith	ADP
ma-100	31	13	increasing	increase	VERB
ma-100	31	14	the	the	DET
ma-100	31	15	injected	inject	VERB
ma-100	31	16	current	current	NOUN
ma-100	31	17	,	,	PUNCT
ma-100	31	18	the	the	DET
ma-100	31	19	cell	cell	NOUN
ma-100	31	20	starts	start	VERB
ma-100	31	21	to	to	PART
ma-100	31	22	fire	fire	VERB
ma-100	31	23	repetitive	repetitive	ADJ
ma-100	31	24	spikes	spike	NOUN
ma-100	32	1	[	[	X
ma-100	32	2	9–13,18,19].according	9–13,18,19].according	NUM
ma-100	32	3	to	to	PART
ma-100	32	4	moaddy	moaddy	VERB
ma-100	32	5	.	.	PUNCT
ma-100	33	1	k	k	X
ma-100	33	2	,	,	PUNCT
ma-100	33	3	et	et	PROPN
ma-100	33	4	.	.	PUNCT
ma-100	34	1	al	al	PROPN
ma-100	35	1	[	[	X
ma-100	35	2	20	20	NUM
ma-100	35	3	]	]	PUNCT
ma-100	35	4	,	,	PUNCT
ma-100	35	5	the	the	DET
ma-100	35	6	fractional	fractional	ADJ
ma-100	35	7	-	-	PUNCT
ma-100	35	8	order	order	NOUN
ma-100	35	9	models	model	NOUN
ma-100	35	10	can	can	AUX
ma-100	35	11	better	well	ADV
ma-100	35	12	explain	explain	VERB
ma-100	35	13	the	the	DET
ma-100	35	14	long	long	ADJ
ma-100	35	15	memorydependence	memorydependence	NOUN
ma-100	35	16	of	of	ADP
ma-100	35	17	the	the	DET
ma-100	35	18	neuron	neuron	NOUN
ma-100	35	19	response	response	NOUN
ma-100	35	20	.	.	PUNCT
ma-100	36	1	one	one	NUM
ma-100	36	2	of	of	ADP
ma-100	36	3	the	the	DET
ma-100	36	4	most	most	ADV
ma-100	36	5	interesting	interesting	ADJ
ma-100	36	6	properties	property	NOUN
ma-100	36	7	of	of	ADP
ma-100	36	8	neural	neural	ADJ
ma-100	36	9	system	system	NOUN
ma-100	36	10	isadaptation	isadaptation	NOUN
ma-100	36	11	to	to	PART
ma-100	36	12	changes	change	NOUN
ma-100	36	13	in	in	ADP
ma-100	36	14	stimulus	stimulus	NOUN
ma-100	36	15	.	.	PUNCT
ma-100	37	1	it	it	PRON
ma-100	37	2	has	have	AUX
ma-100	37	3	been	be	AUX
ma-100	37	4	shown	show	VERB
ma-100	37	5	that	that	SCONJ
ma-100	37	6	a	a	DET
ma-100	37	7	single	single	ADJ
ma-100	37	8	neuron	neuron	NOUN
ma-100	37	9	has	have	VERB
ma-100	37	10	a	a	DET
ma-100	37	11	single	single	ADJ
ma-100	37	12	time	time	NOUN
ma-100	37	13	scaleadaptation	scaleadaptation	NOUN
ma-100	37	14	,	,	PUNCT
ma-100	37	15	however	however	ADV
ma-100	37	16	,	,	PUNCT
ma-100	37	17	there	there	PRON
ma-100	37	18	are	be	VERB
ma-100	37	19	some	some	DET
ma-100	37	20	neurons	neuron	NOUN
ma-100	37	21	with	with	ADP
ma-100	37	22	multiple	multiple	ADJ
ma-100	37	23	time	time	NOUN
ma-100	37	24	scale	scale	NOUN
ma-100	37	25	adaptation	adaptation	NOUN
ma-100	37	26	to	to	PART
ma-100	37	27	responsesconsistent	responsesconsistent	VERB
ma-100	37	28	with	with	ADP
ma-100	37	29	fractional	fractional	ADJ
ma-100	37	30	-	-	PUNCT
ma-100	37	31	order	order	NOUN
ma-100	37	32	derivatives	derivative	NOUN
ma-100	37	33	,	,	PUNCT
ma-100	37	34	means	mean	VERB
ma-100	37	35	that	that	SCONJ
ma-100	37	36	the	the	DET
ma-100	37	37	firing	firing	NOUN
ma-100	37	38	rate	rate	NOUN
ma-100	37	39	for	for	ADP
ma-100	37	40	these	these	DET
ma-100	37	41	neurons	neuron	NOUN
ma-100	37	42	acts	act	VERB
ma-100	37	43	asfractional	asfractional	ADJ
ma-100	37	44	derivative	derivative	NOUN
ma-100	37	45	of	of	ADP
ma-100	37	46	slowly	slowly	ADV
ma-100	37	47	varying	vary	VERB
ma-100	37	48	stimulus	stimulus	ADJ
ma-100	37	49	parameters	parameter	NOUN
ma-100	37	50	[	[	X
ma-100	37	51	21,22	21,22	X
ma-100	37	52	]	]	X
ma-100	37	53	.	.	PUNCT
ma-100	38	1	therefore	therefore	ADV
ma-100	38	2	,	,	PUNCT
ma-100	38	3	the	the	DET
ma-100	38	4	other	other	ADJ
ma-100	38	5	advantagesof	advantagesof	NOUN
ma-100	38	6	neuronal	neuronal	ADJ
ma-100	38	7	fractional	fractional	ADJ
ma-100	38	8	derivatives	derivative	NOUN
ma-100	38	9	is	be	AUX
ma-100	38	10	their	their	PRON
ma-100	38	11	ability	ability	NOUN
ma-100	38	12	to	to	PART
ma-100	38	13	adapt	adapt	VERB
ma-100	38	14	to	to	ADP
ma-100	38	15	changes	change	NOUN
ma-100	38	16	in	in	ADP
ma-100	38	17	stimulus	stimulus	NOUN
ma-100	38	18	in	in	ADP
ma-100	38	19	different	different	ADJ
ma-100	38	20	timescales	timescale	NOUN
ma-100	38	21	.	.	PUNCT
ma-100	39	1	moreover	moreover	ADV
ma-100	39	2	,	,	PUNCT
ma-100	39	3	shi	shi	PROPN
ma-100	39	4	.	.	PUNCT
ma-100	40	1	m	m	PROPN
ma-100	40	2	,	,	PUNCT
ma-100	40	3	et	et	PROPN
ma-100	40	4	.	.	PUNCT
ma-100	41	1	al	al	PROPN
ma-100	42	1	[	[	X
ma-100	42	2	23	23	NUM
ma-100	42	3	]	]	PUNCT
ma-100	42	4	proved	prove	VERB
ma-100	42	5	that	that	SCONJ
ma-100	42	6	the	the	DET
ma-100	42	7	fractional	fractional	ADJ
ma-100	42	8	-	-	PUNCT
ma-100	42	9	order	order	NOUN
ma-100	42	10	derivative	derivative	NOUN
ma-100	42	11	demonstrates	demonstrate	VERB
ma-100	42	12	thereal	thereal	NOUN
ma-100	42	13	dielectric	dielectric	ADJ
ma-100	42	14	behaviors	behavior	NOUN
ma-100	42	15	and	and	CCONJ
ma-100	42	16	the	the	DET
ma-100	42	17	history	history	NOUN
ma-100	42	18	memory	memory	NOUN
ma-100	42	19	property	property	NOUN
ma-100	42	20	of	of	ADP
ma-100	42	21	membranes	membrane	NOUN
ma-100	42	22	,	,	PUNCT
ma-100	42	23	cells	cell	NOUN
ma-100	42	24	and	and	CCONJ
ma-100	42	25	so	so	ADV
ma-100	42	26	on	on	ADV
ma-100	42	27	.	.	PUNCT
ma-100	43	1	accordingto	accordingto	NOUN
ma-100	43	2	their	their	PRON
ma-100	43	3	finding	finding	NOUN
ma-100	43	4	,	,	PUNCT
ma-100	43	5	non	non	ADJ
ma-100	43	6	integer	integer	NOUN
ma-100	43	7	derivative	derivative	NOUN
ma-100	43	8	activates	activate	VERB
ma-100	43	9	the	the	DET
ma-100	43	10	slow	slow	ADJ
ma-100	43	11	ion	ion	NOUN
ma-100	43	12	channel	channel	NOUN
ma-100	43	13	with	with	ADP
ma-100	43	14	higher	high	ADJ
ma-100	43	15	speed	speed	NOUN
ma-100	43	16	,	,	PUNCT
ma-100	43	17	and	and	CCONJ
ma-100	43	18	helpsto	helpsto	PROPN
ma-100	43	19	activate	activate	VERB
ma-100	43	20	fast	fast	ADV
ma-100	43	21	spiking	spike	VERB
ma-100	43	22	modulation	modulation	NOUN
ma-100	43	23	which	which	PRON
ma-100	43	24	forms	form	VERB
ma-100	43	25	different	different	ADJ
ma-100	43	26	kinds	kind	NOUN
ma-100	43	27	of	of	ADP
ma-100	43	28	bursting	bursting	NOUN
ma-100	43	29	behaviors	behavior	NOUN
ma-100	43	30	.	.	PUNCT
ma-100	44	1	one	one	NUM
ma-100	44	2	importantfact	importantfact	NOUN
ma-100	44	3	about	about	ADP
ma-100	44	4	using	use	VERB
ma-100	44	5	fractional	fractional	ADJ
ma-100	44	6	order	order	NOUN
ma-100	44	7	model	model	VERB
ma-100	44	8	their	their	PRON
ma-100	44	9	ability	ability	NOUN
ma-100	44	10	to	to	PART
ma-100	44	11	display	display	VERB
ma-100	44	12	different	different	ADJ
ma-100	44	13	dynamical	dynamical	ADJ
ma-100	44	14	behaviors	behavior	NOUN
ma-100	44	15	such	such	ADJ
ma-100	44	16	aschaotic	aschaotic	NOUN
ma-100	44	17	and	and	CCONJ
ma-100	44	18	periodic	periodic	ADJ
ma-100	44	19	firing	firing	NOUN
ma-100	44	20	for	for	ADP
ma-100	44	21	the	the	DET
ma-100	44	22	same	same	ADJ
ma-100	44	23	parameter	parameter	NOUN
ma-100	44	24	values	value	NOUN
ma-100	44	25	as	as	SCONJ
ma-100	44	26	the	the	DET
ma-100	44	27	order	order	NOUN
ma-100	44	28	of	of	ADP
ma-100	44	29	derivative	derivative	NOUN
ma-100	44	30	is	be	AUX
ma-100	44	31	varying	vary	VERB
ma-100	44	32	[	[	PUNCT
ma-100	44	33	24].on	24].on	NUM
ma-100	44	34	the	the	DET
ma-100	44	35	other	other	ADJ
ma-100	44	36	hand	hand	NOUN
ma-100	44	37	,	,	PUNCT
ma-100	44	38	using	use	VERB
ma-100	44	39	these	these	DET
ma-100	44	40	new	new	ADJ
ma-100	44	41	parameters	parameter	NOUN
ma-100	44	42	as	as	ADP
ma-100	44	43	the	the	DET
ma-100	44	44	order	order	NOUN
ma-100	44	45	of	of	ADP
ma-100	44	46	fractional	fractional	ADJ
ma-100	44	47	derivative	derivative	ADJ
ma-100	44	48	operatorsenhances	operatorsenhance	NOUN
ma-100	44	49	the	the	DET
ma-100	44	50	controllability	controllability	NOUN
ma-100	44	51	of	of	ADP
ma-100	44	52	behavior	behavior	NOUN
ma-100	44	53	of	of	ADP
ma-100	44	54	the	the	DET
ma-100	44	55	neuron	neuron	NOUN
ma-100	44	56	cells	cell	NOUN
ma-100	44	57	[	[	X
ma-100	44	58	25	25	NUM
ma-100	44	59	]	]	PUNCT
ma-100	44	60	.	.	PUNCT
ma-100	45	1	the	the	DET
ma-100	45	2	fractional	fractional	ADJ
ma-100	45	3	order	order	NOUN
ma-100	45	4	models	model	NOUN
ma-100	45	5	playan	playan	VERB
ma-100	45	6	important	important	ADJ
ma-100	45	7	role	role	NOUN
ma-100	45	8	in	in	ADP
ma-100	45	9	determining	determine	VERB
ma-100	45	10	the	the	DET
ma-100	45	11	firing	firing	NOUN
ma-100	45	12	properties	property	NOUN
ma-100	45	13	of	of	ADP
ma-100	45	14	neuronal	neuronal	ADJ
ma-100	45	15	models	model	NOUN
ma-100	45	16	and	and	CCONJ
ma-100	45	17	these	these	DET
ma-100	45	18	importantproperties	importantpropertie	NOUN
ma-100	45	19	of	of	ADP
ma-100	45	20	models	model	NOUN
ma-100	45	21	with	with	ADP
ma-100	45	22	fractional	fractional	ADJ
ma-100	45	23	order	order	NOUN
ma-100	45	24	derivatives	derivative	NOUN
ma-100	45	25	including	include	VERB
ma-100	45	26	depiction	depiction	NOUN
ma-100	45	27	of	of	ADP
ma-100	45	28	long	long	ADJ
ma-100	45	29	term	term	NOUN
ma-100	45	30	memory	memory	NOUN
ma-100	45	31	andthe	andthe	ADJ
ma-100	45	32	multiple	multiple	ADJ
ma-100	45	33	time	time	NOUN
ma-100	45	34	scale	scale	NOUN
ma-100	45	35	adaptation	adaptation	NOUN
ma-100	45	36	have	have	AUX
ma-100	45	37	motivated	motivate	VERB
ma-100	45	38	many	many	ADJ
ma-100	45	39	efforts	effort	NOUN
ma-100	45	40	to	to	PART
ma-100	45	41	use	use	VERB
ma-100	45	42	them	they	PRON
ma-100	45	43	as	as	ADP
ma-100	45	44	a	a	DET
ma-100	45	45	perfect	perfect	ADJ
ma-100	45	46	frameworkto	frameworkto	NOUN
ma-100	45	47	cover	cover	VERB
ma-100	45	48	the	the	DET
ma-100	45	49	complicated	complicated	ADJ
ma-100	45	50	dynamics	dynamic	NOUN
ma-100	45	51	of	of	ADP
ma-100	45	52	many	many	ADJ
ma-100	45	53	different	different	ADJ
ma-100	45	54	neuronal	neuronal	ADJ
ma-100	45	55	cells	cell	NOUN
ma-100	45	56	such	such	ADJ
ma-100	45	57	as	as	ADP
ma-100	45	58	fractional	fractional	ADJ
ma-100	45	59	cable	cable	NOUN
ma-100	45	60	model	model	NOUN
ma-100	45	61	,	,	PUNCT
ma-100	45	62	izhikevich	izhikevich	PROPN
ma-100	45	63	neuron	neuron	PROPN
ma-100	45	64	model	model	NOUN
ma-100	45	65	,	,	PUNCT
ma-100	45	66	and	and	CCONJ
ma-100	45	67	fitzhugh	fitzhugh	NOUN
ma-100	45	68	-	-	PUNCT
ma-100	45	69	rinzel	rinzel	NOUN
ma-100	45	70	bursting	bursting	NOUN
ma-100	45	71	neuron	neuron	NOUN
ma-100	45	72	model	model	NOUN
ma-100	46	1	[	[	X
ma-100	46	2	26–28].due	26–28].due	NUM
ma-100	46	3	to	to	ADP
ma-100	46	4	the	the	DET
ma-100	46	5	complexity	complexity	NOUN
ma-100	46	6	of	of	ADP
ma-100	46	7	nerve	nerve	NOUN
ma-100	46	8	systems	system	NOUN
ma-100	46	9	,	,	PUNCT
ma-100	46	10	it	it	PRON
ma-100	46	11	is	be	AUX
ma-100	46	12	impossible	impossible	ADJ
ma-100	46	13	to	to	PART
ma-100	46	14	fully	fully	ADV
ma-100	46	15	understand	understand	VERB
ma-100	46	16	the	the	DET
ma-100	46	17	various	various	ADJ
ma-100	46	18	phenomena	phenomenon	NOUN
ma-100	46	19	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	SYM
ma-100	46	20	eur	eur	PROPN
ma-100	46	21	.	.	PUNCT
ma-100	47	1	j.	j.	PROPN
ma-100	47	2	math	math	PROPN
ma-100	47	3	.	.	PUNCT
ma-100	48	1	anal	anal	PROPN
ma-100	48	2	.	.	PUNCT
ma-100	49	1	10.28924	10.28924	NUM
ma-100	49	2	/	/	SYM
ma-100	49	3	ada	ada	PROPN
ma-100	49	4	/	/	SYM
ma-100	49	5	ma.3.2	ma.3.2	PROPN
ma-100	49	6	3	3	NUM
ma-100	49	7	in	in	ADP
ma-100	49	8	neuroscience	neuroscience	NOUN
ma-100	49	9	only	only	ADV
ma-100	49	10	using	use	VERB
ma-100	49	11	the	the	DET
ma-100	49	12	integer	integer	NOUN
ma-100	49	13	order	order	NOUN
ma-100	49	14	models	model	NOUN
ma-100	49	15	,	,	PUNCT
ma-100	49	16	since	since	SCONJ
ma-100	49	17	it	it	PRON
ma-100	49	18	does	do	AUX
ma-100	49	19	not	not	PART
ma-100	49	20	meet	meet	VERB
ma-100	49	21	all	all	DET
ma-100	49	22	neuronal	neuronal	ADJ
ma-100	49	23	propertiesand	propertiesand	NOUN
ma-100	49	24	complicated	complicate	VERB
ma-100	49	25	behaviors	behavior	NOUN
ma-100	49	26	of	of	ADP
ma-100	49	27	neurons	neuron	NOUN
ma-100	49	28	.	.	PUNCT
ma-100	50	1	thus	thus	ADV
ma-100	50	2	,	,	PUNCT
ma-100	50	3	in	in	ADP
ma-100	50	4	this	this	DET
ma-100	50	5	study	study	NOUN
ma-100	50	6	we	we	PRON
ma-100	50	7	use	use	VERB
ma-100	50	8	the	the	DET
ma-100	50	9	fractional	fractional	ADJ
ma-100	50	10	calculus	calculus	NOUN
ma-100	50	11	to	to	ADP
ma-100	50	12	explorethe	explorethe	ADJ
ma-100	50	13	dynamics	dynamic	NOUN
ma-100	50	14	of	of	ADP
ma-100	50	15	fractal	fractal	ADJ
ma-100	50	16	processes	process	NOUN
ma-100	50	17	using	use	VERB
ma-100	50	18	the	the	DET
ma-100	50	19	fractional	fractional	ADJ
ma-100	50	20	calculus	calculus	NOUN
ma-100	50	21	and	and	CCONJ
ma-100	50	22	apply	apply	VERB
ma-100	50	23	this	this	DET
ma-100	50	24	dynamical	dynamical	ADJ
ma-100	50	25	approach	approach	NOUN
ma-100	50	26	onmorris	onmorris	NOUN
ma-100	50	27	-	-	PUNCT
ma-100	50	28	lecar	lecar	NOUN
ma-100	50	29	model	model	NOUN
ma-100	50	30	to	to	PART
ma-100	50	31	catch	catch	VERB
ma-100	50	32	all	all	DET
ma-100	50	33	the	the	DET
ma-100	50	34	spiking	spike	VERB
ma-100	50	35	properties	property	NOUN
ma-100	50	36	of	of	ADP
ma-100	50	37	this	this	DET
ma-100	50	38	neuron	neuron	NOUN
ma-100	50	39	and	and	CCONJ
ma-100	50	40	to	to	PART
ma-100	50	41	simulate	simulate	VERB
ma-100	50	42	the	the	DET
ma-100	50	43	fluctuationsof	fluctuationsof	NOUN
ma-100	50	44	this	this	DET
ma-100	50	45	single	single	ADJ
ma-100	50	46	neuron	neuron	NOUN
ma-100	50	47	cell	cell	NOUN
ma-100	50	48	and	and	CCONJ
ma-100	50	49	obtain	obtain	VERB
ma-100	50	50	biological	biological	ADJ
ma-100	50	51	physiological	physiological	ADJ
ma-100	50	52	characteristics	characteristic	NOUN
ma-100	50	53	of	of	ADP
ma-100	50	54	it	it	PRON
ma-100	50	55	.	.	PUNCT
ma-100	51	1	we	we	PRON
ma-100	51	2	have	have	VERB
ma-100	51	3	selectedmorris	selectedmorris	NOUN
ma-100	51	4	-	-	PUNCT
ma-100	51	5	lecar	lecar	NOUN
ma-100	51	6	model	model	NOUN
ma-100	51	7	because	because	SCONJ
ma-100	51	8	it	it	PRON
ma-100	51	9	is	be	AUX
ma-100	51	10	a	a	DET
ma-100	51	11	reduced	reduce	VERB
ma-100	51	12	and	and	CCONJ
ma-100	51	13	simpler	simple	ADJ
ma-100	51	14	version	version	NOUN
ma-100	51	15	of	of	ADP
ma-100	51	16	the	the	DET
ma-100	51	17	hodgkin	hodgkin	PROPN
ma-100	51	18	-	-	PUNCT
ma-100	51	19	huxley	huxley	PROPN
ma-100	51	20	equationsand	equationsand	PROPN
ma-100	51	21	preserves	preserve	VERB
ma-100	51	22	many	many	ADJ
ma-100	51	23	important	important	ADJ
ma-100	51	24	characteristics	characteristic	NOUN
ma-100	51	25	of	of	ADP
ma-100	51	26	neuronal	neuronal	ADJ
ma-100	51	27	dynamics	dynamic	NOUN
ma-100	51	28	such	such	ADJ
ma-100	51	29	as	as	ADP
ma-100	51	30	generation	generation	NOUN
ma-100	51	31	of	of	ADP
ma-100	51	32	actionpotentials	actionpotential	NOUN
ma-100	51	33	,	,	PUNCT
ma-100	51	34	threshold	threshold	NOUN
ma-100	51	35	for	for	ADP
ma-100	51	36	firing	fire	VERB
ma-100	51	37	spike	spike	NOUN
ma-100	51	38	,	,	PUNCT
ma-100	51	39	and	and	CCONJ
ma-100	51	40	sustained	sustain	VERB
ma-100	51	41	oscillations	oscillation	NOUN
ma-100	51	42	with	with	ADP
ma-100	51	43	increasing	increase	VERB
ma-100	51	44	the	the	DET
ma-100	51	45	applied	apply	VERB
ma-100	51	46	current.because	current.because	PROPN
ma-100	51	47	the	the	DET
ma-100	51	48	solutions	solution	NOUN
ma-100	51	49	of	of	ADP
ma-100	51	50	fractional	fractional	ADJ
ma-100	51	51	morris	morris	PROPN
ma-100	51	52	lecar	lecar	PROPN
ma-100	51	53	model	model	NOUN
ma-100	51	54	(	(	PUNCT
ma-100	51	55	fml	fml	PROPN
ma-100	51	56	)	)	PUNCT
ma-100	51	57	may	may	AUX
ma-100	51	58	not	not	PART
ma-100	51	59	be	be	AUX
ma-100	51	60	explicitly	explicitly	ADV
ma-100	51	61	obtained	obtain	VERB
ma-100	51	62	,	,	PUNCT
ma-100	51	63	weuse	weuse	VERB
ma-100	51	64	numerical	numerical	ADJ
ma-100	51	65	methods	method	NOUN
ma-100	51	66	to	to	PART
ma-100	51	67	approximate	approximate	VERB
ma-100	51	68	the	the	DET
ma-100	51	69	solutions	solution	NOUN
ma-100	51	70	of	of	ADP
ma-100	51	71	this	this	DET
ma-100	51	72	model	model	NOUN
ma-100	51	73	.	.	PUNCT
ma-100	52	1	we	we	PRON
ma-100	52	2	compare	compare	VERB
ma-100	52	3	these	these	DET
ma-100	52	4	results	result	NOUN
ma-100	52	5	withits	withit	NOUN
ma-100	52	6	original	original	ADJ
ma-100	52	7	integer	integer	NOUN
ma-100	52	8	order	order	NOUN
ma-100	52	9	model	model	NOUN
ma-100	52	10	using	use	VERB
ma-100	52	11	phase	phase	NOUN
ma-100	52	12	portrait	portrait	NOUN
ma-100	52	13	analysis	analysis	NOUN
ma-100	52	14	.	.	PUNCT
ma-100	53	1	by	by	ADP
ma-100	53	2	considering	consider	VERB
ma-100	53	3	this	this	DET
ma-100	53	4	fractional	fractional	ADJ
ma-100	53	5	ordermodel	ordermodel	NOUN
ma-100	53	6	,	,	PUNCT
ma-100	53	7	we	we	PRON
ma-100	53	8	can	can	AUX
ma-100	53	9	explain	explain	VERB
ma-100	53	10	all	all	DET
ma-100	53	11	the	the	DET
ma-100	53	12	possible	possible	ADJ
ma-100	53	13	geometric	geometric	ADJ
ma-100	53	14	mechanisms	mechanism	NOUN
ma-100	53	15	underlying	underlie	VERB
ma-100	53	16	each	each	PRON
ma-100	53	17	of	of	ADP
ma-100	53	18	neuronal	neuronal	ADJ
ma-100	53	19	activitiesof	activitiesof	NOUN
ma-100	53	20	morris	morris	ADJ
ma-100	53	21	-	-	PUNCT
ma-100	53	22	lecar	lecar	NOUN
ma-100	53	23	model	model	NOUN
ma-100	53	24	.	.	PUNCT
ma-100	54	1	2	2	X
ma-100	54	2	.	.	X
ma-100	54	3	grünwald	grünwald	NOUN
ma-100	54	4	-	-	PUNCT
ma-100	54	5	letinkov	letinkov	NOUN
ma-100	54	6	approximation	approximation	NOUN
ma-100	54	7	we	we	PRON
ma-100	54	8	define	define	VERB
ma-100	54	9	the	the	DET
ma-100	54	10	fractional	fractional	ADJ
ma-100	54	11	differential	differential	NOUN
ma-100	54	12	as	as	ADP
ma-100	54	13	the	the	DET
ma-100	54	14	following	follow	VERB
ma-100	54	15	form	form	NOUN
ma-100	54	16	[	[	X
ma-100	54	17	29,30	29,30	NUM
ma-100	54	18	]	]	X
ma-100	54	19	dγy	dγy	NOUN
ma-100	54	20	(	(	PUNCT
ma-100	54	21	t	t	NOUN
ma-100	54	22	)	)	PUNCT
ma-100	54	23	=	=	SYM
ma-100	55	1	f	f	PROPN
ma-100	55	2	(	(	PUNCT
ma-100	55	3	t	t	PROPN
ma-100	55	4	,	,	PUNCT
ma-100	55	5	y	y	PROPN
ma-100	55	6	(	(	PUNCT
ma-100	55	7	t	t	PROPN
ma-100	55	8	)	)	PUNCT
ma-100	55	9	)	)	PUNCT
ma-100	55	10	,	,	PUNCT
ma-100	55	11	y	y	PROPN
ma-100	55	12	(	(	PUNCT
ma-100	55	13	t0	t0	PROPN
ma-100	55	14	)	)	PUNCT
ma-100	55	15	=	=	SYM
ma-100	56	1	y0	y0	NOUN
ma-100	56	2	where	where	SCONJ
ma-100	56	3	γ	γ	X
ma-100	56	4	>	>	X
ma-100	56	5	0	0	NUM
ma-100	56	6	represents	represent	VERB
ma-100	56	7	the	the	DET
ma-100	56	8	order	order	NOUN
ma-100	56	9	of	of	ADP
ma-100	56	10	derivative	derivative	ADJ
ma-100	56	11	and	and	CCONJ
ma-100	56	12	dγ	dγ	ADP
ma-100	56	13	denotes	denote	NOUN
ma-100	56	14	the	the	DET
ma-100	56	15	fractional	fractional	ADJ
ma-100	56	16	derivative	derivative	NOUN
ma-100	56	17	which	which	PRON
ma-100	56	18	isgiven	isgiven	VERB
ma-100	56	19	by	by	ADP
ma-100	56	20	:	:	PUNCT
ma-100	56	21	dγy	dγy	INTJ
ma-100	56	22	(	(	PUNCT
ma-100	56	23	t	t	NOUN
ma-100	56	24	)	)	PUNCT
ma-100	57	1	=	=	PUNCT
ma-100	57	2	jk−γdky	jk−γdky	NOUN
ma-100	57	3	(	(	PUNCT
ma-100	57	4	t	t	PROPN
ma-100	57	5	)	)	PUNCT
ma-100	57	6	where	where	SCONJ
ma-100	57	7	γ	γ	X
ma-100	57	8	∈	∈	PROPN
ma-100	57	9	(	(	PUNCT
ma-100	57	10	k	k	NOUN
ma-100	57	11	−	−	PROPN
ma-100	57	12	1	1	NUM
ma-100	57	13	,	,	PUNCT
ma-100	57	14	k	k	X
ma-100	57	15	]	]	X
ma-100	57	16	,	,	PUNCT
ma-100	57	17	for	for	ADP
ma-100	57	18	k	k	PROPN
ma-100	57	19	=	=	SYM
ma-100	57	20	1	1	NUM
ma-100	57	21	,	,	PUNCT
ma-100	57	22	2	2	NUM
ma-100	57	23	,	,	PUNCT
ma-100	57	24	.	.	PUNCT
ma-100	57	25	.	.	PUNCT
ma-100	58	1	.	.	PUNCT
ma-100	59	1	and	and	CCONJ
ma-100	59	2	integral	integral	ADJ
ma-100	59	3	operator	operator	NOUN
ma-100	59	4	jk	jk	PROPN
ma-100	59	5	called	call	VERB
ma-100	59	6	the	the	DET
ma-100	59	7	riemann	riemann	PROPN
ma-100	59	8	-	-	PUNCT
ma-100	59	9	liouville	liouville	NOUN
ma-100	59	10	of	of	ADP
ma-100	59	11	kth	kth	NOUN
ma-100	59	12	-	-	PUNCT
ma-100	59	13	order	order	NOUN
ma-100	59	14	which	which	PRON
ma-100	59	15	is	be	AUX
ma-100	59	16	obtained	obtain	VERB
ma-100	59	17	by	by	ADP
ma-100	59	18	the	the	DET
ma-100	59	19	following	follow	VERB
ma-100	59	20	formula	formula	NOUN
ma-100	59	21	jky	jky	PROPN
ma-100	59	22	(	(	PUNCT
ma-100	59	23	t	t	NOUN
ma-100	59	24	)	)	PUNCT
ma-100	59	25	=	=	SYM
ma-100	59	26	1	1	NUM
ma-100	59	27	γ(k	γ(k	PROPN
ma-100	59	28	)	)	PUNCT
ma-100	60	1	∫	∫	PROPN
ma-100	60	2	t	t	PROPN
ma-100	60	3	0	0	NUM
ma-100	61	1	(	(	PUNCT
ma-100	61	2	t	t	NOUN
ma-100	61	3	−	−	PROPN
ma-100	61	4	τ)(k−1)y	τ)(k−1)y	PROPN
ma-100	61	5	(	(	PUNCT
ma-100	61	6	τ	τ	NOUN
ma-100	61	7	)	)	PUNCT
ma-100	61	8	dτ	dτ	PROPN
ma-100	61	9	,	,	PUNCT
ma-100	61	10	t	t	PROPN
ma-100	61	11	>	>	X
ma-100	61	12	0	0	NUM
ma-100	61	13	where	where	SCONJ
ma-100	61	14	γ	γ	X
ma-100	61	15	(	(	PUNCT
ma-100	61	16	.	.	PUNCT
ma-100	61	17	)	)	PUNCT
ma-100	61	18	denotes	denote	VERB
ma-100	61	19	the	the	DET
ma-100	61	20	gamma	gamma	PROPN
ma-100	61	21	function.to	function.to	PROPN
ma-100	61	22	apply	apply	VERB
ma-100	61	23	the	the	DET
ma-100	61	24	micken	micken	PROPN
ma-100	61	25	’s	’s	PART
ma-100	61	26	(	(	PUNCT
ma-100	61	27	nsfd	nsfd	ADJ
ma-100	61	28	)	)	PUNCT
ma-100	62	1	[	[	X
ma-100	62	2	31–33	31–33	NUM
ma-100	62	3	]	]	PUNCT
ma-100	62	4	,	,	PUNCT
ma-100	62	5	we	we	PRON
ma-100	62	6	need	need	VERB
ma-100	62	7	to	to	PART
ma-100	62	8	find	find	VERB
ma-100	62	9	the	the	DET
ma-100	62	10	fractional	fractional	ADJ
ma-100	62	11	order	order	NOUN
ma-100	62	12	derivative	derivative	NOUN
ma-100	62	13	using	use	VERB
ma-100	62	14	thegrünwaldletinkov	thegrünwaldletinkov	NOUN
ma-100	62	15	(	(	PUNCT
ma-100	62	16	g	g	NOUN
ma-100	62	17	-	-	PUNCT
ma-100	62	18	l	l	NOUN
ma-100	62	19	)	)	PUNCT
ma-100	62	20	approximation	approximation	NOUN
ma-100	62	21	for	for	ADP
ma-100	62	22	model	model	NOUN
ma-100	62	23	equations	equation	NOUN
ma-100	62	24	as	as	ADP
ma-100	62	25	the	the	DET
ma-100	62	26	form	form	NOUN
ma-100	62	27	dγy	dγy	NOUN
ma-100	62	28	(	(	PUNCT
ma-100	62	29	t	t	NOUN
ma-100	62	30	)	)	PUNCT
ma-100	63	1	=	=	PROPN
ma-100	63	2	lim	lim	PROPN
ma-100	63	3	s→0	s→0	PROPN
ma-100	63	4	s−γ	s−γ	PROPN
ma-100	63	5	t∑	t∑	PROPN
ma-100	63	6	i=0	i=0	PROPN
ma-100	63	7	(	(	PUNCT
ma-100	63	8	−1)i	−1)i	X
ma-100	63	9	(	(	PUNCT
ma-100	63	10	γ	γ	X
ma-100	63	11	i	i	PROPN
ma-100	63	12	)	)	PUNCT
ma-100	63	13	y	y	PROPN
ma-100	63	14	(	(	PUNCT
ma-100	63	15	t	t	PROPN
ma-100	63	16	−	−	PUNCT
ma-100	64	1	i	i	PRON
ma-100	64	2	s	s	VERB
ma-100	64	3	)	)	PUNCT
ma-100	64	4	(	(	PUNCT
ma-100	64	5	1	1	X
ma-100	64	6	)	)	PUNCT
ma-100	65	1	where	where	SCONJ
ma-100	65	2	t	t	NOUN
ma-100	65	3	=	=	PUNCT
ma-100	66	1	[	[	X
ma-100	66	2	t]/s	t]/s	NOUN
ma-100	66	3	and	and	CCONJ
ma-100	66	4	[	[	X
ma-100	66	5	.	.	X
ma-100	66	6	]	]	PUNCT
ma-100	66	7	used	use	VERB
ma-100	66	8	to	to	PART
ma-100	66	9	show	show	VERB
ma-100	66	10	the	the	DET
ma-100	66	11	integer	integer	NOUN
ma-100	66	12	value	value	NOUN
ma-100	66	13	and	and	CCONJ
ma-100	66	14	s	s	NOUN
ma-100	66	15	represents	represent	VERB
ma-100	66	16	the	the	DET
ma-100	66	17	step	step	NOUN
ma-100	66	18	size	size	NOUN
ma-100	66	19	.	.	PUNCT
ma-100	67	1	thus	thus	ADV
ma-100	67	2	,	,	PUNCT
ma-100	67	3	equation	equation	NOUN
ma-100	67	4	(	(	PUNCT
ma-100	67	5	1	1	X
ma-100	67	6	)	)	PUNCT
ma-100	67	7	would	would	AUX
ma-100	67	8	be	be	AUX
ma-100	67	9	discretized	discretize	VERB
ma-100	67	10	as	as	ADP
ma-100	67	11	t∑	t∑	PROPN
ma-100	67	12	i=0	i=0	ADJ
ma-100	67	13	cγi	cγi	NOUN
ma-100	67	14	y	y	PROPN
ma-100	67	15	(	(	PUNCT
ma-100	67	16	tk−i	tk−i	PROPN
ma-100	67	17	)	)	PUNCT
ma-100	67	18	=	=	SYM
ma-100	68	1	f	f	PROPN
ma-100	68	2	(	(	PUNCT
ma-100	68	3	tk	tk	PROPN
ma-100	68	4	,	,	PUNCT
ma-100	68	5	y	y	PROPN
ma-100	68	6	(	(	PUNCT
ma-100	68	7	tk	tk	PROPN
ma-100	68	8	)	)	PUNCT
ma-100	68	9	)	)	PUNCT
ma-100	69	1	(	(	PUNCT
ma-100	69	2	2	2	X
ma-100	69	3	)	)	PUNCT
ma-100	69	4	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	69	5	eur	eur	PROPN
ma-100	69	6	.	.	PUNCT
ma-100	70	1	j.	j.	PROPN
ma-100	70	2	math	math	PROPN
ma-100	70	3	.	.	PUNCT
ma-100	71	1	anal	anal	PROPN
ma-100	71	2	.	.	PUNCT
ma-100	72	1	10.28924	10.28924	NUM
ma-100	72	2	/	/	SYM
ma-100	72	3	ada	ada	PROPN
ma-100	72	4	/	/	SYM
ma-100	72	5	ma.3.2	ma.3.2	PROPN
ma-100	72	6	4where	4where	NUM
ma-100	72	7	tk	tk	NOUN
ma-100	72	8	=	=	PROPN
ma-100	72	9	k	k	PROPN
ma-100	72	10	s	s	X
ma-100	72	11	and	and	CCONJ
ma-100	72	12	cγi	cγi	PRON
ma-100	72	13	are	be	AUX
ma-100	72	14	the	the	DET
ma-100	72	15	coefficients	coefficient	NOUN
ma-100	72	16	for	for	ADP
ma-100	72	17	(	(	PUNCT
ma-100	72	18	g	g	NOUN
ma-100	72	19	-	-	PUNCT
ma-100	72	20	l	l	NOUN
ma-100	72	21	)	)	PUNCT
ma-100	72	22	approximation	approximation	NOUN
ma-100	72	23	written	write	VERB
ma-100	72	24	as	as	ADP
ma-100	72	25	cγi	cγi	ADV
ma-100	72	26	=	=	PUNCT
ma-100	73	1	[	[	PUNCT
ma-100	73	2	i	i	PRON
ma-100	73	3	−	−	PROPN
ma-100	73	4	1−	1−	NUM
ma-100	73	5	γ	γ	X
ma-100	73	6	i	i	X
ma-100	73	7	]	]	PUNCT
ma-100	73	8	cγi−1	cγi−1	PROPN
ma-100	73	9	,	,	PUNCT
ma-100	73	10	cγ0	cγ0	NOUN
ma-100	73	11	=	=	PUNCT
ma-100	74	1	s−γ	s−γ	NOUN
ma-100	74	2	i	i	NOUN
ma-100	74	3	=	=	NOUN
ma-100	74	4	1	1	NUM
ma-100	74	5	,	,	PUNCT
ma-100	74	6	2	2	NUM
ma-100	74	7	,	,	PUNCT
ma-100	74	8	.	.	PUNCT
ma-100	74	9	.	.	PUNCT
ma-100	75	1	.	.	PUNCT
ma-100	76	1	next	next	ADV
ma-100	76	2	we	we	PRON
ma-100	76	3	introduce	introduce	VERB
ma-100	76	4	the	the	DET
ma-100	76	5	non	non	ADJ
ma-100	76	6	-	-	ADJ
ma-100	76	7	standard	standard	ADJ
ma-100	76	8	finite	finite	ADJ
ma-100	76	9	difference	difference	NOUN
ma-100	76	10	schemes.to	schemes.to	PRON
ma-100	76	11	discretize	discretize	VERB
ma-100	76	12	a	a	DET
ma-100	76	13	systems	system	NOUN
ma-100	76	14	of	of	ADP
ma-100	76	15	differential	differential	ADJ
ma-100	76	16	equations	equation	NOUN
ma-100	76	17	,	,	PUNCT
ma-100	76	18	both	both	DET
ma-100	76	19	ordinary	ordinary	ADJ
ma-100	76	20	differential	differential	ADJ
ma-100	76	21	equations	equation	NOUN
ma-100	76	22	(	(	PUNCT
ma-100	76	23	odes	ode	NOUN
ma-100	76	24	)	)	PUNCT
ma-100	76	25	andpartial	andpartial	ADJ
ma-100	76	26	differential	differential	ADJ
ma-100	76	27	equations	equation	NOUN
ma-100	76	28	(	(	PUNCT
ma-100	76	29	pdes	pde	NOUN
ma-100	76	30	)	)	PUNCT
ma-100	76	31	,	,	PUNCT
ma-100	76	32	one	one	PRON
ma-100	76	33	may	may	AUX
ma-100	76	34	apply	apply	VERB
ma-100	76	35	the	the	DET
ma-100	76	36	mickens	micken	NOUN
ma-100	76	37	nsfd	nsfd	ADJ
ma-100	76	38	discretization	discretization	NOUN
ma-100	76	39	methodwhich	methodwhich	NOUN
ma-100	76	40	is	be	AUX
ma-100	76	41	more	more	ADV
ma-100	76	42	flexible	flexible	ADJ
ma-100	76	43	in	in	ADP
ma-100	76	44	construction	construction	NOUN
ma-100	76	45	rather	rather	ADV
ma-100	76	46	than	than	ADP
ma-100	76	47	standard	standard	ADJ
ma-100	76	48	finite	finite	ADJ
ma-100	76	49	difference	difference	NOUN
ma-100	76	50	method	method	NOUN
ma-100	76	51	and	and	CCONJ
ma-100	76	52	thereforehas	thereforehas	X
ma-100	76	53	better	well	ADJ
ma-100	76	54	performance	performance	NOUN
ma-100	76	55	.	.	PUNCT
ma-100	77	1	this	this	DET
ma-100	77	2	method	method	NOUN
ma-100	77	3	checks	check	VERB
ma-100	77	4	the	the	DET
ma-100	77	5	positivity	positivity	NOUN
ma-100	77	6	of	of	ADP
ma-100	77	7	solutions	solution	NOUN
ma-100	77	8	and	and	CCONJ
ma-100	77	9	is	be	AUX
ma-100	77	10	concerned	concern	VERB
ma-100	77	11	aboutboundedness	aboutboundedness	ADJ
ma-100	77	12	and	and	CCONJ
ma-100	77	13	monotonicity	monotonicity	NOUN
ma-100	77	14	of	of	ADP
ma-100	77	15	them	they	PRON
ma-100	77	16	.	.	PUNCT
ma-100	78	1	another	another	DET
ma-100	78	2	advantage	advantage	NOUN
ma-100	78	3	of	of	ADP
ma-100	78	4	using	use	VERB
ma-100	78	5	nsfd	nsfd	ADJ
ma-100	78	6	schemes	scheme	NOUN
ma-100	78	7	is	be	AUX
ma-100	78	8	their	their	PRON
ma-100	78	9	abilityto	abilityto	ADV
ma-100	78	10	preserve	preserve	VERB
ma-100	78	11	the	the	DET
ma-100	78	12	structure	structure	NOUN
ma-100	78	13	and	and	CCONJ
ma-100	78	14	properties	property	NOUN
ma-100	78	15	of	of	ADP
ma-100	78	16	the	the	DET
ma-100	78	17	systems	system	NOUN
ma-100	78	18	of	of	ADP
ma-100	78	19	differential	differential	ADJ
ma-100	78	20	equations	equation	NOUN
ma-100	78	21	and	and	CCONJ
ma-100	78	22	therefore	therefore	ADV
ma-100	78	23	,	,	PUNCT
ma-100	78	24	weapply	weapply	ADV
ma-100	78	25	nsfd	nsfd	ADJ
ma-100	78	26	schemes	scheme	NOUN
ma-100	78	27	on	on	ADP
ma-100	78	28	the	the	DET
ma-100	78	29	general	general	ADJ
ma-100	78	30	compartmental	compartmental	ADJ
ma-100	78	31	model	model	NOUN
ma-100	78	32	in	in	ADP
ma-100	78	33	the	the	DET
ma-100	78	34	form	form	NOUN
ma-100	78	35	:	:	PUNCT
ma-100	79	1	d	d	X
ma-100	79	2	y	y	NOUN
ma-100	79	3	dt	dt	X
ma-100	79	4	=	=	SYM
ma-100	80	1	f	f	PROPN
ma-100	80	2	(	(	PUNCT
ma-100	80	3	y	y	PROPN
ma-100	80	4	)	)	PUNCT
ma-100	80	5	(	(	PUNCT
ma-100	80	6	3	3	X
ma-100	80	7	)	)	PUNCT
ma-100	80	8	however	however	ADV
ma-100	80	9	,	,	PUNCT
ma-100	80	10	to	to	PART
ma-100	80	11	use	use	VERB
ma-100	80	12	the	the	DET
ma-100	80	13	non	non	ADJ
ma-100	80	14	-	-	ADJ
ma-100	80	15	standard	standard	ADJ
ma-100	80	16	scheme	scheme	NOUN
ma-100	80	17	we	we	PRON
ma-100	80	18	need	need	VERB
ma-100	80	19	to	to	PART
ma-100	80	20	check	check	VERB
ma-100	80	21	that	that	SCONJ
ma-100	80	22	if	if	SCONJ
ma-100	80	23	non	non	ADJ
ma-100	80	24	-	-	ADJ
ma-100	80	25	local	local	ADJ
ma-100	80	26	approximation	approximation	NOUN
ma-100	80	27	is	be	AUX
ma-100	80	28	usedand	usedand	NOUN
ma-100	80	29	or	or	CCONJ
ma-100	80	30	we	we	PRON
ma-100	80	31	need	need	VERB
ma-100	80	32	to	to	PART
ma-100	80	33	have	have	VERB
ma-100	80	34	a	a	DET
ma-100	80	35	non	non	ADJ
ma-100	80	36	traditional	traditional	ADJ
ma-100	80	37	discretization	discretization	NOUN
ma-100	80	38	of	of	ADP
ma-100	80	39	derivatives	derivative	NOUN
ma-100	80	40	and	and	CCONJ
ma-100	80	41	also	also	ADV
ma-100	80	42	we	we	PRON
ma-100	80	43	may	may	AUX
ma-100	80	44	need	need	VERB
ma-100	80	45	to	to	PART
ma-100	80	46	use	use	VERB
ma-100	80	47	anon	anon	ADJ
ma-100	80	48	-	-	ADJ
ma-100	80	49	negative	negative	ADJ
ma-100	80	50	function	function	NOUN
ma-100	80	51	φ(h	φ(h	NOUN
ma-100	80	52	)	)	PUNCT
ma-100	80	53	=	=	SYM
ma-100	80	54	s+o(s2	s+o(s2	NOUN
ma-100	80	55	)	)	PUNCT
ma-100	80	56	.	.	PUNCT
ma-100	81	1	to	to	PART
ma-100	81	2	apply	apply	VERB
ma-100	81	3	nsfd	nsfd	ADJ
ma-100	81	4	scheme	scheme	NOUN
ma-100	81	5	,	,	PUNCT
ma-100	81	6	we	we	PRON
ma-100	81	7	consider	consider	VERB
ma-100	81	8	a	a	DET
ma-100	81	9	grid	grid	NOUN
ma-100	81	10	tk	tk	NOUN
ma-100	81	11	=	=	PUNCT
ma-100	81	12	t0+k	t0+k	PROPN
ma-100	81	13	s	s	PROPN
ma-100	81	14	,	,	PUNCT
ma-100	81	15	such	such	ADJ
ma-100	81	16	that	that	PRON
ma-100	81	17	s	s	VERB
ma-100	81	18	>	>	X
ma-100	81	19	0	0	NUM
ma-100	81	20	,	,	PUNCT
ma-100	81	21	and	and	CCONJ
ma-100	81	22	we	we	PRON
ma-100	81	23	approximately	approximately	ADV
ma-100	81	24	write	write	VERB
ma-100	81	25	the	the	DET
ma-100	81	26	discretized	discretized	ADJ
ma-100	81	27	function	function	NOUN
ma-100	81	28	y	y	PROPN
ma-100	81	29	as	as	ADP
ma-100	81	30	yk	yk	PROPN
ma-100	81	31	≈	≈	PROPN
ma-100	81	32	y	y	PROPN
ma-100	81	33	(	(	PUNCT
ma-100	81	34	tk	tk	PROPN
ma-100	81	35	)	)	PUNCT
ma-100	81	36	.	.	PUNCT
ma-100	82	1	next	next	ADV
ma-100	82	2	,	,	PUNCT
ma-100	82	3	wediscretize	wediscretize	NOUN
ma-100	82	4	(	(	PUNCT
ma-100	82	5	3	3	NUM
ma-100	82	6	):	):	PUNCT
ma-100	82	7	d	d	PROPN
ma-100	82	8	y	y	NOUN
ma-100	82	9	dt	dt	NOUN
ma-100	83	1	=	=	SYM
ma-100	83	2	yk+1	yk+1	PRON
ma-100	83	3	−	−	PROPN
ma-100	83	4	yk	yk	PROPN
ma-100	83	5	φ(s	φ(s	NOUN
ma-100	83	6	)	)	PUNCT
ma-100	84	1	+	+	NOUN
ma-100	84	2	o(φ(s	o(φ(s	NOUN
ma-100	84	3	)	)	PUNCT
ma-100	84	4	)	)	PUNCT
ma-100	84	5	(	(	PUNCT
ma-100	84	6	4	4	X
ma-100	84	7	)	)	PUNCT
ma-100	84	8	when	when	SCONJ
ma-100	84	9	s	s	AUX
ma-100	84	10	→	→	SYM
ma-100	84	11	0	0	NUM
ma-100	84	12	we	we	PRON
ma-100	84	13	have	have	VERB
ma-100	84	14	d	d	X
ma-100	84	15	y	y	NOUN
ma-100	85	1	dt	dt	X
ma-100	85	2	≈	≈	PROPN
ma-100	85	3	yk+1	yk+1	PRON
ma-100	86	1	−	−	PROPN
ma-100	86	2	yk	yk	PROPN
ma-100	86	3	φ(s	φ(s	NOUN
ma-100	86	4	)	)	PUNCT
ma-100	86	5	(	(	PUNCT
ma-100	86	6	5	5	X
ma-100	86	7	)	)	PUNCT
ma-100	86	8	where	where	SCONJ
ma-100	86	9	real	real	ADV
ma-100	86	10	valued	value	VERB
ma-100	86	11	φ(s	φ(s	NOUN
ma-100	86	12	)	)	PUNCT
ma-100	86	13	as	as	ADP
ma-100	86	14	a	a	DET
ma-100	86	15	function	function	NOUN
ma-100	86	16	of	of	ADP
ma-100	86	17	the	the	DET
ma-100	86	18	step	step	NOUN
ma-100	86	19	size	size	NOUN
ma-100	86	20	s	s	PART
ma-100	86	21	need	need	NOUN
ma-100	86	22	to	to	PART
ma-100	86	23	satisfy	satisfy	VERB
ma-100	86	24	the	the	DET
ma-100	86	25	following	follow	VERB
ma-100	86	26	properties	property	NOUN
ma-100	86	27	[	[	X
ma-100	86	28	34]:(i	34]:(i	NUM
ma-100	86	29	)	)	PUNCT
ma-100	86	30	φ(s	φ(s	NOUN
ma-100	86	31	)	)	PUNCT
ma-100	87	1	=	=	SYM
ma-100	87	2	s	s	PART
ma-100	87	3	+	+	NOUN
ma-100	87	4	o(s2),(ii	o(s2),(ii	PROPN
ma-100	87	5	)	)	PUNCT
ma-100	87	6	φ(s	φ(s	NOUN
ma-100	87	7	)	)	PUNCT
ma-100	87	8	∈	∈	PROPN
ma-100	87	9	(	(	PUNCT
ma-100	87	10	0	0	NUM
ma-100	87	11	,	,	PUNCT
ma-100	87	12	1	1	NUM
ma-100	87	13	)	)	PUNCT
ma-100	87	14	,	,	PUNCT
ma-100	87	15	∀	∀	X
ma-100	87	16	s	s	NOUN
ma-100	87	17	∈	∈	PROPN
ma-100	87	18	(	(	PUNCT
ma-100	87	19	0,∞)here	0,∞)here	NUM
ma-100	87	20	,	,	PUNCT
ma-100	87	21	the	the	DET
ma-100	87	22	equality	equality	NOUN
ma-100	87	23	(	(	PUNCT
ma-100	87	24	4	4	NUM
ma-100	87	25	)	)	PUNCT
ma-100	87	26	is	be	AUX
ma-100	87	27	equivalent	equivalent	ADJ
ma-100	87	28	with	with	ADP
ma-100	87	29	the	the	DET
ma-100	87	30	integer	integer	NOUN
ma-100	87	31	order	order	NOUN
ma-100	87	32	derivative	derivative	NOUN
ma-100	87	33	as	as	ADP
ma-100	87	34	follow	follow	NOUN
ma-100	87	35	:	:	PUNCT
ma-100	88	1	d	d	X
ma-100	88	2	y	y	NOUN
ma-100	88	3	dt	dt	PROPN
ma-100	88	4	=	=	PROPN
ma-100	88	5	lim	lim	PROPN
ma-100	88	6	s→0	s→0	PROPN
ma-100	89	1	[	[	PUNCT
ma-100	89	2	y	y	PROPN
ma-100	89	3	(	(	PUNCT
ma-100	89	4	t	t	PROPN
ma-100	89	5	+	+	PROPN
ma-100	89	6	s)−	s)−	PROPN
ma-100	89	7	y	y	PROPN
ma-100	89	8	(	(	PUNCT
ma-100	89	9	t	t	PROPN
ma-100	89	10	)	)	PUNCT
ma-100	89	11	φ(s	φ(s	NOUN
ma-100	89	12	)	)	PUNCT
ma-100	90	1	+	+	NOUN
ma-100	90	2	o(φ(s	o(φ(s	NOUN
ma-100	90	3	)	)	PUNCT
ma-100	90	4	)	)	PUNCT
ma-100	90	5	]	]	PUNCT
ma-100	91	1	=	=	PUNCT
ma-100	91	2	lim	lim	PROPN
ma-100	91	3	s→0	s→0	PROPN
ma-100	92	1	[	[	PUNCT
ma-100	92	2	y	y	PROPN
ma-100	92	3	(	(	PUNCT
ma-100	92	4	t	t	PROPN
ma-100	92	5	+	+	PROPN
ma-100	92	6	s)−	s)−	PROPN
ma-100	92	7	y	y	PROPN
ma-100	92	8	(	(	PUNCT
ma-100	92	9	t	t	PROPN
ma-100	92	10	)	)	PUNCT
ma-100	92	11	s	s	PART
ma-100	92	12	]	]	X
ma-100	92	13	lim	lim	PROPN
ma-100	92	14	s→0	s→0	PROPN
ma-100	92	15	[	[	PUNCT
ma-100	92	16	s	s	X
ma-100	92	17	φ(s	φ(s	NOUN
ma-100	92	18	)	)	PUNCT
ma-100	92	19	]	]	PUNCT
ma-100	93	1	+	+	CCONJ
ma-100	93	2	lim	lim	NOUN
ma-100	93	3	s→0	s→0	PUNCT
ma-100	93	4	o(φ(s	o(φ(s	PROPN
ma-100	93	5	)	)	PUNCT
ma-100	93	6	)	)	PUNCT
ma-100	94	1	=	=	SYM
ma-100	94	2	ẏ	ẏ	PROPN
ma-100	94	3	(	(	PUNCT
ma-100	94	4	t	t	PROPN
ma-100	94	5	)	)	PUNCT
ma-100	94	6	as	as	ADP
ma-100	94	7	s	s	PROPN
ma-100	94	8	→	→	SYM
ma-100	94	9	0	0	NUM
ma-100	94	10	the	the	DET
ma-100	94	11	discrete	discrete	ADJ
ma-100	94	12	form	form	NOUN
ma-100	94	13	in	in	ADP
ma-100	94	14	(	(	PUNCT
ma-100	94	15	4	4	X
ma-100	94	16	)	)	PUNCT
ma-100	94	17	converges	converge	NOUN
ma-100	94	18	to	to	ADP
ma-100	94	19	its	its	PRON
ma-100	94	20	associated	associated	ADJ
ma-100	94	21	continuous	continuous	ADJ
ma-100	94	22	derivative	derivative	NOUN
ma-100	94	23	.	.	PUNCT
ma-100	95	1	nsfd	nsfd	PROPN
ma-100	95	2	methodsare	methodsare	PROPN
ma-100	95	3	convergent	convergent	NOUN
ma-100	95	4	without	without	ADP
ma-100	95	5	any	any	DET
ma-100	95	6	restriction	restriction	NOUN
ma-100	95	7	related	relate	VERB
ma-100	95	8	to	to	PART
ma-100	95	9	step	step	VERB
ma-100	95	10	size	size	NOUN
ma-100	95	11	s	s	PART
ma-100	95	12	but	but	CCONJ
ma-100	95	13	this	this	PRON
ma-100	95	14	is	be	AUX
ma-100	95	15	not	not	PART
ma-100	95	16	always	always	ADV
ma-100	95	17	true	true	ADJ
ma-100	95	18	for	for	ADP
ma-100	95	19	sfdmethods	sfdmethod	NOUN
ma-100	95	20	which	which	PRON
ma-100	95	21	depend	depend	VERB
ma-100	95	22	on	on	ADP
ma-100	95	23	the	the	DET
ma-100	95	24	step	step	NOUN
ma-100	95	25	size	size	NOUN
ma-100	95	26	s	s	PART
ma-100	95	27	.	.	PUNCT
ma-100	96	1	moreover	moreover	ADV
ma-100	96	2	,	,	PUNCT
ma-100	96	3	when	when	SCONJ
ma-100	96	4	we	we	PRON
ma-100	96	5	discretize	discretize	VERB
ma-100	96	6	a	a	DET
ma-100	96	7	system	system	NOUN
ma-100	96	8	using	use	VERB
ma-100	96	9	nsfd	nsfd	PROPN
ma-100	96	10	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	96	11	eur	eur	PROPN
ma-100	96	12	.	.	PUNCT
ma-100	97	1	j.	j.	PROPN
ma-100	97	2	math	math	PROPN
ma-100	97	3	.	.	PUNCT
ma-100	98	1	anal	anal	PROPN
ma-100	98	2	.	.	PUNCT
ma-100	99	1	10.28924	10.28924	NUM
ma-100	99	2	/	/	SYM
ma-100	99	3	ada	ada	PROPN
ma-100	99	4	/	/	SYM
ma-100	99	5	ma.3.2	ma.3.2	PROPN
ma-100	99	6	5method	5method	NUM
ma-100	99	7	,	,	PUNCT
ma-100	99	8	if	if	SCONJ
ma-100	99	9	the	the	DET
ma-100	99	10	original	original	ADJ
ma-100	99	11	system	system	NOUN
ma-100	99	12	is	be	AUX
ma-100	99	13	persistent	persistent	ADJ
ma-100	99	14	,	,	PUNCT
ma-100	99	15	and	and	CCONJ
ma-100	99	16	solutions	solution	NOUN
ma-100	99	17	are	be	AUX
ma-100	99	18	stable	stable	ADJ
ma-100	99	19	and	and	CCONJ
ma-100	99	20	convergent	convergent	NOUN
ma-100	99	21	,	,	PUNCT
ma-100	99	22	these	these	DET
ma-100	99	23	proper	proper	ADJ
ma-100	99	24	-	-	PUNCT
ma-100	99	25	ties	tie	NOUN
ma-100	99	26	remain	remain	VERB
ma-100	99	27	the	the	DET
ma-100	99	28	same	same	ADJ
ma-100	99	29	after	after	ADP
ma-100	99	30	discretization	discretization	NOUN
ma-100	99	31	,	,	PUNCT
ma-100	99	32	but	but	CCONJ
ma-100	99	33	not	not	PART
ma-100	99	34	for	for	ADP
ma-100	99	35	the	the	DET
ma-100	99	36	case	case	NOUN
ma-100	99	37	we	we	PRON
ma-100	99	38	use	use	VERB
ma-100	99	39	sfd	sfd	NOUN
ma-100	99	40	to	to	PART
ma-100	99	41	discretize	discretize	VERB
ma-100	99	42	the	the	DET
ma-100	99	43	systemof	systemof	ADJ
ma-100	99	44	differential	differential	NOUN
ma-100	99	45	equations	equation	NOUN
ma-100	99	46	.	.	PUNCT
ma-100	100	1	3	3	X
ma-100	100	2	.	.	X
ma-100	100	3	description	description	NOUN
ma-100	100	4	of	of	ADP
ma-100	100	5	model	model	NOUN
ma-100	100	6	equations	equation	NOUN
ma-100	100	7	to	to	PART
ma-100	100	8	demonstrate	demonstrate	VERB
ma-100	100	9	the	the	DET
ma-100	100	10	generation	generation	NOUN
ma-100	100	11	of	of	ADP
ma-100	100	12	action	action	NOUN
ma-100	100	13	potential	potential	NOUN
ma-100	100	14	,	,	PUNCT
ma-100	100	15	kathleen	kathleen	PROPN
ma-100	100	16	morris	morris	PROPN
ma-100	100	17	and	and	CCONJ
ma-100	100	18	harold	harold	PROPN
ma-100	100	19	lecar	lecar	PROPN
ma-100	100	20	proposeda	proposeda	PROPN
ma-100	100	21	simple	simple	ADJ
ma-100	100	22	model	model	NOUN
ma-100	100	23	,	,	PUNCT
ma-100	100	24	morris	morris	ADJ
ma-100	100	25	-	-	PUNCT
ma-100	100	26	lecar	lecar	NOUN
ma-100	100	27	model	model	NOUN
ma-100	100	28	,	,	PUNCT
ma-100	100	29	in	in	ADP
ma-100	100	30	1981	1981	NUM
ma-100	100	31	[	[	X
ma-100	100	32	35	35	NUM
ma-100	100	33	]	]	PUNCT
ma-100	100	34	that	that	PRON
ma-100	100	35	is	be	AUX
ma-100	100	36	a	a	DET
ma-100	100	37	reduction	reduction	NOUN
ma-100	100	38	version	version	NOUN
ma-100	100	39	of	of	ADP
ma-100	100	40	the	the	DET
ma-100	100	41	four	four	NUM
ma-100	100	42	dimensionalhodgkin	dimensionalhodgkin	PROPN
ma-100	100	43	-	-	PUNCT
ma-100	100	44	huxley	huxley	PROPN
ma-100	100	45	model	model	NOUN
ma-100	100	46	preserving	preserve	VERB
ma-100	100	47	the	the	DET
ma-100	100	48	main	main	ADJ
ma-100	100	49	properties	property	NOUN
ma-100	100	50	of	of	ADP
ma-100	100	51	spike	spike	ADJ
ma-100	100	52	generations	generation	NOUN
ma-100	100	53	with	with	ADP
ma-100	100	54	much	much	ADJ
ma-100	100	55	simplermathematical	simplermathematical	ADJ
ma-100	100	56	and	and	CCONJ
ma-100	100	57	computational	computational	ADJ
ma-100	100	58	analysis	analysis	NOUN
ma-100	100	59	[	[	X
ma-100	100	60	35	35	NUM
ma-100	100	61	,	,	PUNCT
ma-100	100	62	36	36	NUM
ma-100	100	63	]	]	PUNCT
ma-100	100	64	.	.	PUNCT
ma-100	101	1	this	this	DET
ma-100	101	2	model	model	NOUN
ma-100	101	3	describes	describe	VERB
ma-100	101	4	the	the	DET
ma-100	101	5	electrical	electrical	ADJ
ma-100	101	6	activities	activity	NOUN
ma-100	101	7	ofneurons	ofneuron	NOUN
ma-100	101	8	using	use	VERB
ma-100	101	9	a	a	DET
ma-100	101	10	system	system	NOUN
ma-100	101	11	of	of	ADP
ma-100	101	12	non	non	ADJ
ma-100	101	13	-	-	ADJ
ma-100	101	14	linear	linear	ADJ
ma-100	101	15	ordinary	ordinary	ADJ
ma-100	101	16	differential	differential	ADJ
ma-100	101	17	equations	equation	NOUN
ma-100	101	18	and	and	CCONJ
ma-100	101	19	includes	include	VERB
ma-100	101	20	three	three	NUM
ma-100	101	21	channelsa	channelsa	ADJ
ma-100	101	22	potassium	potassium	NOUN
ma-100	101	23	channel	channel	NOUN
ma-100	101	24	,	,	PUNCT
ma-100	101	25	a	a	DET
ma-100	101	26	leak	leak	NOUN
ma-100	101	27	and	and	CCONJ
ma-100	101	28	a	a	DET
ma-100	101	29	calcium	calcium	NOUN
ma-100	101	30	channel	channel	NOUN
ma-100	101	31	and	and	CCONJ
ma-100	101	32	has	have	VERB
ma-100	101	33	the	the	DET
ma-100	101	34	following	follow	VERB
ma-100	101	35	form	form	PROPN
ma-100	101	36	cm	cm	PROPN
ma-100	101	37	dv	dv	PROPN
ma-100	101	38	dt	dt	PROPN
ma-100	101	39	=	=	SYM
ma-100	101	40	iapp	iapp	PROPN
ma-100	101	41	−	−	PROPN
ma-100	101	42	gl(v	gl(v	PUNCT
ma-100	101	43	−	−	PROPN
ma-100	101	44	el)−	el)−	NOUN
ma-100	102	1	gkw(v	gkw(v	PROPN
ma-100	102	2	−	−	PROPN
ma-100	102	3	ek)−	ek)−	ADJ
ma-100	102	4	gcam∞(v	gcam∞(v	PROPN
ma-100	102	5	)	)	PUNCT
ma-100	102	6	(	(	PUNCT
ma-100	102	7	v	v	NOUN
ma-100	102	8	−	−	PROPN
ma-100	102	9	eca	eca	NOUN
ma-100	102	10	)	)	PUNCT
ma-100	103	1	=	=	NOUN
ma-100	103	2	iapp	iapp	NOUN
ma-100	103	3	−	−	PROPN
ma-100	103	4	iion(v	iion(v	PROPN
ma-100	103	5	,	,	PUNCT
ma-100	103	6	w	w	PROPN
ma-100	103	7	)	)	PUNCT
ma-100	103	8	,	,	PUNCT
ma-100	103	9	dw	dw	PROPN
ma-100	103	10	dt	dt	NOUN
ma-100	103	11	=	=	SYM
ma-100	103	12	φ(n∞(v	φ(n∞(v	PROPN
ma-100	103	13	)	)	PUNCT
ma-100	103	14	−	−	PROPN
ma-100	104	1	w)/τw	w)/τw	PROPN
ma-100	104	2	(	(	PUNCT
ma-100	104	3	v	v	NOUN
ma-100	104	4	)	)	PUNCT
ma-100	104	5	,	,	PUNCT
ma-100	104	6	(	(	PUNCT
ma-100	104	7	6	6	X
ma-100	104	8	)	)	PUNCT
ma-100	104	9	where	where	SCONJ
ma-100	104	10	m∞(v	m∞(v	ADV
ma-100	104	11	)	)	PUNCT
ma-100	104	12	=	=	SYM
ma-100	104	13	1	1	NUM
ma-100	104	14	2	2	NUM
ma-100	105	1	[	[	SYM
ma-100	105	2	1	1	NUM
ma-100	105	3	+	+	NUM
ma-100	105	4	tanh((v	tanh((v	NOUN
ma-100	105	5	−	−	PROPN
ma-100	105	6	v1)/v2	v1)/v2	NOUN
ma-100	105	7	)	)	PUNCT
ma-100	105	8	]	]	PUNCT
ma-100	105	9	,	,	PUNCT
ma-100	105	10	(	(	PUNCT
ma-100	105	11	7	7	NUM
ma-100	105	12	)	)	PUNCT
ma-100	105	13	τn(v	τn(v	PUNCT
ma-100	105	14	)	)	PUNCT
ma-100	105	15	=	=	SYM
ma-100	105	16	1	1	NUM
ma-100	105	17	/	/	SYM
ma-100	105	18	cosh((v	cosh((v	NOUN
ma-100	105	19	−	−	NOUN
ma-100	105	20	v3)/(2v4	v3)/(2v4	NUM
ma-100	105	21	)	)	PUNCT
ma-100	105	22	)	)	PUNCT
ma-100	105	23	,	,	PUNCT
ma-100	105	24	(	(	PUNCT
ma-100	105	25	8)	8)	NUM
ma-100	105	26	n∞(v	n∞(v	NUM
ma-100	105	27	)	)	PUNCT
ma-100	105	28	=	=	SYM
ma-100	105	29	1	1	NUM
ma-100	105	30	2	2	NUM
ma-100	106	1	[	[	SYM
ma-100	106	2	1	1	NUM
ma-100	106	3	+	+	NUM
ma-100	106	4	tanh((v	tanh((v	NOUN
ma-100	106	5	−	−	PROPN
ma-100	106	6	v3)/v4	v3)/v4	PROPN
ma-100	106	7	)	)	PUNCT
ma-100	106	8	]	]	PUNCT
ma-100	106	9	.	.	PUNCT
ma-100	107	1	(	(	PUNCT
ma-100	107	2	9	9	NUM
ma-100	107	3	)	)	PUNCT
ma-100	107	4	and	and	CCONJ
ma-100	107	5	iion(v	iion(v	PROPN
ma-100	107	6	,	,	PUNCT
ma-100	107	7	w	w	NOUN
ma-100	107	8	)	)	PUNCT
ma-100	107	9	=	=	NOUN
ma-100	107	10	gl(v	gl(v	NUM
ma-100	107	11	−	−	PROPN
ma-100	107	12	el	el	PROPN
ma-100	107	13	)	)	PUNCT
ma-100	108	1	+	+	CCONJ
ma-100	108	2	gkw(v	gkw(v	PROPN
ma-100	108	3	−	−	PROPN
ma-100	108	4	ek	ek	NOUN
ma-100	108	5	)	)	PUNCT
ma-100	108	6	+	+	CCONJ
ma-100	108	7	gcam∞(v	gcam∞(v	PROPN
ma-100	108	8	)	)	PUNCT
ma-100	108	9	(	(	PUNCT
ma-100	108	10	v	v	NOUN
ma-100	108	11	−	−	PROPN
ma-100	108	12	eca	eca	NOUN
ma-100	108	13	)	)	PUNCT
ma-100	108	14	(	(	PUNCT
ma-100	108	15	10	10	NUM
ma-100	108	16	)	)	PUNCT
ma-100	108	17	where	where	SCONJ
ma-100	108	18	v	v	NOUN
ma-100	108	19	demonstrates	demonstrate	VERB
ma-100	108	20	membrane	membrane	NOUN
ma-100	108	21	potential	potential	NOUN
ma-100	108	22	,	,	PUNCT
ma-100	108	23	and	and	CCONJ
ma-100	108	24	w	w	ADP
ma-100	108	25	the	the	DET
ma-100	108	26	activation	activation	NOUN
ma-100	108	27	variable	variable	NOUN
ma-100	108	28	of	of	ADP
ma-100	108	29	the	the	DET
ma-100	108	30	persistent	persistent	ADJ
ma-100	108	31	k+current	k+current	PROPN
ma-100	108	32	,	,	PUNCT
ma-100	108	33	so	so	SCONJ
ma-100	108	34	it	it	PRON
ma-100	108	35	is	be	AUX
ma-100	108	36	a	a	DET
ma-100	108	37	two	two	NUM
ma-100	108	38	-	-	PUNCT
ma-100	108	39	dimensional	dimensional	ADJ
ma-100	108	40	vector	vector	NOUN
ma-100	108	41	(	(	PUNCT
ma-100	108	42	v	v	NOUN
ma-100	108	43	,	,	PUNCT
ma-100	108	44	w	w	NOUN
ma-100	108	45	)	)	PUNCT
ma-100	108	46	.	.	PUNCT
ma-100	109	1	ek	ek	PROPN
ma-100	109	2	,	,	PUNCT
ma-100	109	3	eca	eca	PROPN
ma-100	109	4	,	,	PUNCT
ma-100	109	5	and	and	CCONJ
ma-100	109	6	el	el	PROPN
ma-100	109	7	denote	denote	VERB
ma-100	109	8	the	the	DET
ma-100	109	9	nernst	nernst	PROPN
ma-100	109	10	equilibriumpotentials	equilibriumpotentials	PROPN
ma-100	109	11	.	.	PUNCT
ma-100	110	1	iapp	iapp	PROPN
ma-100	110	2	demonstrates	demonstrate	VERB
ma-100	110	3	the	the	DET
ma-100	110	4	injected	inject	VERB
ma-100	110	5	current	current	NOUN
ma-100	110	6	and	and	CCONJ
ma-100	110	7	iion	iion	VERB
ma-100	110	8	the	the	DET
ma-100	110	9	ionic	ionic	ADJ
ma-100	110	10	current	current	NOUN
ma-100	110	11	.	.	PUNCT
ma-100	111	1	parameter	parameter	PROPN
ma-100	111	2	φ	φ	PROPN
ma-100	111	3	is	be	AUX
ma-100	111	4	atemperature	atemperature	NOUN
ma-100	111	5	factor	factor	NOUN
ma-100	111	6	.	.	PUNCT
ma-100	112	1	gl	gl	PROPN
ma-100	112	2	is	be	AUX
ma-100	112	3	leak	leak	VERB
ma-100	112	4	membrane	membrane	NOUN
ma-100	112	5	conductance	conductance	NOUN
ma-100	112	6	,	,	PUNCT
ma-100	112	7	gk	gk	PROPN
ma-100	112	8	is	be	AUX
ma-100	112	9	potassium	potassium	NOUN
ma-100	112	10	membrane	membrane	NOUN
ma-100	112	11	conductance	conductance	NOUN
ma-100	112	12	and	and	CCONJ
ma-100	112	13	gca	gca	PROPN
ma-100	112	14	is	be	AUX
ma-100	112	15	calcium	calcium	NOUN
ma-100	112	16	membrane	membrane	NOUN
ma-100	112	17	conductance	conductance	NOUN
ma-100	112	18	.	.	PUNCT
ma-100	113	1	moreover	moreover	ADV
ma-100	113	2	,	,	PUNCT
ma-100	113	3	cm	cm	PROPN
ma-100	113	4	is	be	AUX
ma-100	113	5	the	the	DET
ma-100	113	6	total	total	ADJ
ma-100	113	7	membrane	membrane	NOUN
ma-100	113	8	capacitance	capacitance	NOUN
ma-100	113	9	.	.	PUNCT
ma-100	114	1	also	also	ADV
ma-100	114	2	,	,	PUNCT
ma-100	114	3	thevoltage	thevoltage	NOUN
ma-100	114	4	-	-	PUNCT
ma-100	114	5	sensitive	sensitive	ADJ
ma-100	114	6	steady	steady	ADJ
ma-100	114	7	-	-	PUNCT
ma-100	114	8	state	state	NOUN
ma-100	114	9	activation	activation	NOUN
ma-100	114	10	function	function	VERB
ma-100	114	11	m∞(v	m∞(v	PUNCT
ma-100	114	12	)	)	PUNCT
ma-100	114	13	and	and	CCONJ
ma-100	114	14	n∞(v	n∞(v	PROPN
ma-100	114	15	)	)	PUNCT
ma-100	114	16	,	,	PUNCT
ma-100	114	17	and	and	CCONJ
ma-100	114	18	the	the	DET
ma-100	114	19	time	time	NOUN
ma-100	114	20	constant	constant	ADJ
ma-100	114	21	τw	τw	NOUN
ma-100	114	22	(	(	PUNCT
ma-100	114	23	v	v	NOUN
ma-100	114	24	)	)	PUNCT
ma-100	114	25	can	can	AUX
ma-100	114	26	be	be	AUX
ma-100	114	27	measured	measure	VERB
ma-100	114	28	experimentally	experimentally	ADV
ma-100	114	29	.	.	PUNCT
ma-100	115	1	the	the	DET
ma-100	115	2	non	non	ADJ
ma-100	115	3	-	-	ADJ
ma-100	115	4	linear	linear	ADJ
ma-100	115	5	dynamics	dynamic	NOUN
ma-100	115	6	of	of	ADP
ma-100	115	7	the	the	DET
ma-100	115	8	original	original	ADJ
ma-100	115	9	morris	morris	ADJ
ma-100	115	10	-	-	PUNCT
ma-100	115	11	lecar	lecar	ADJ
ma-100	115	12	model	model	NOUN
ma-100	115	13	havebeen	havebeen	PROPN
ma-100	115	14	studied	study	VERB
ma-100	115	15	by	by	ADP
ma-100	115	16	different	different	ADJ
ma-100	115	17	researchers	researcher	NOUN
ma-100	115	18	during	during	ADP
ma-100	115	19	recent	recent	ADJ
ma-100	115	20	decades	decade	NOUN
ma-100	115	21	[	[	X
ma-100	115	22	18,37–43	18,37–43	NUM
ma-100	115	23	]	]	PUNCT
ma-100	115	24	.	.	PUNCT
ma-100	116	1	in	in	ADP
ma-100	116	2	the	the	DET
ma-100	116	3	next	next	ADJ
ma-100	116	4	section	section	NOUN
ma-100	116	5	we	we	PRON
ma-100	116	6	willlook	willlook	VERB
ma-100	116	7	at	at	ADP
ma-100	116	8	the	the	DET
ma-100	116	9	fractional	fractional	ADJ
ma-100	116	10	-	-	PUNCT
ma-100	116	11	order	order	NOUN
ma-100	116	12	morris	morris	ADJ
ma-100	116	13	-	-	PUNCT
ma-100	116	14	lecar	lecar	NOUN
ma-100	116	15	model	model	NOUN
ma-100	116	16	and	and	CCONJ
ma-100	116	17	its	its	PRON
ma-100	116	18	spiking	spike	VERB
ma-100	116	19	patterns	pattern	NOUN
ma-100	116	20	.	.	PUNCT
ma-100	117	1	3.1	3.1	NUM
ma-100	117	2	.	.	PUNCT
ma-100	117	3	fractional	fractional	ADJ
ma-100	117	4	morris	morris	PROPN
ma-100	117	5	-	-	PUNCT
ma-100	117	6	lecar	lecar	NOUN
ma-100	117	7	model	model	NOUN
ma-100	117	8	.	.	PUNCT
ma-100	118	1	now	now	ADV
ma-100	118	2	,	,	PUNCT
ma-100	118	3	we	we	PRON
ma-100	118	4	apply	apply	VERB
ma-100	118	5	the	the	DET
ma-100	118	6	basic	basic	ADJ
ma-100	118	7	theorems	theorem	NOUN
ma-100	118	8	of	of	ADP
ma-100	118	9	the	the	DET
ma-100	118	10	fractional	fractional	ADJ
ma-100	118	11	calculuson	calculuson	NOUN
ma-100	118	12	model	model	NOUN
ma-100	118	13	(	(	PUNCT
ma-100	118	14	6	6	NUM
ma-100	118	15	)	)	PUNCT
ma-100	118	16	.	.	PUNCT
ma-100	119	1	in	in	ADP
ma-100	119	2	morris	morris	PROPN
ma-100	119	3	-	-	PUNCT
ma-100	119	4	lecar	lecar	NOUN
ma-100	119	5	model	model	NOUN
ma-100	119	6	,	,	PUNCT
ma-100	119	7	we	we	PRON
ma-100	119	8	write	write	VERB
ma-100	119	9	the	the	DET
ma-100	119	10	total	total	ADJ
ma-100	119	11	membrane	membrane	NOUN
ma-100	119	12	current	current	NOUN
ma-100	119	13	to	to	ADP
ma-100	119	14	being	be	AUX
ma-100	119	15	the	the	DET
ma-100	119	16	sum	sum	NOUN
ma-100	119	17	of	of	ADP
ma-100	119	18	ioniccurrents	ioniccurrent	NOUN
ma-100	119	19	and	and	CCONJ
ma-100	119	20	the	the	DET
ma-100	119	21	capacitive	capacitive	ADJ
ma-100	119	22	current	current	NOUN
ma-100	119	23	:	:	PUNCT
ma-100	119	24	iapp	iapp	NUM
ma-100	119	25	=	=	NOUN
ma-100	119	26	iion	iion	NOUN
ma-100	119	27	+	+	CCONJ
ma-100	119	28	icm	icm	PROPN
ma-100	119	29	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	119	30	eur	eur	PROPN
ma-100	119	31	.	.	PUNCT
ma-100	120	1	j.	j.	PROPN
ma-100	120	2	math	math	PROPN
ma-100	120	3	.	.	PUNCT
ma-100	121	1	anal	anal	PROPN
ma-100	121	2	.	.	PUNCT
ma-100	122	1	10.28924	10.28924	NUM
ma-100	122	2	/	/	SYM
ma-100	122	3	ada	ada	PROPN
ma-100	122	4	/	/	SYM
ma-100	122	5	ma.3.2	ma.3.2	PROPN
ma-100	122	6	6for	6for	ADP
ma-100	122	7	the	the	DET
ma-100	122	8	fractional	fractional	ADJ
ma-100	122	9	-	-	PUNCT
ma-100	122	10	order	order	NOUN
ma-100	122	11	model	model	NOUN
ma-100	122	12	,	,	PUNCT
ma-100	122	13	we	we	PRON
ma-100	122	14	define	define	VERB
ma-100	122	15	:	:	PUNCT
ma-100	122	16	icm	icm	NOUN
ma-100	122	17	=	=	SYM
ma-100	122	18	cm	cm	NOUN
ma-100	122	19	dη	dη	NOUN
ma-100	122	20	v	v	ADP
ma-100	122	21	where	where	SCONJ
ma-100	122	22	,	,	PUNCT
ma-100	122	23	0	0	NUM
ma-100	122	24	<	<	X
ma-100	122	25	η	η	PROPN
ma-100	122	26	≤	≤	PROPN
ma-100	122	27	1	1	NUM
ma-100	122	28	and	and	CCONJ
ma-100	122	29	dη	dη	NOUN
ma-100	122	30	is	be	AUX
ma-100	122	31	defined	define	VERB
ma-100	122	32	in	in	ADP
ma-100	122	33	the	the	DET
ma-100	122	34	following	follow	VERB
ma-100	122	35	form	form	NOUN
ma-100	122	36	[	[	X
ma-100	122	37	44	44	NUM
ma-100	122	38	]	]	PUNCT
ma-100	122	39	:	:	PUNCT
ma-100	122	40	dη	dη	X
ma-100	122	41	v	v	X
ma-100	122	42	(	(	PUNCT
ma-100	122	43	t	t	NOUN
ma-100	122	44	)	)	PUNCT
ma-100	123	1	=	=	VERB
ma-100	123	2	lim	lim	PROPN
ma-100	123	3	h→0	h→0	PROPN
ma-100	123	4	h−η	h−η	PROPN
ma-100	124	1	[	[	X
ma-100	124	2	t	t	X
ma-100	124	3	]	]	PUNCT
ma-100	124	4	h∑	h∑	ADP
ma-100	124	5	i=0	i=0	PROPN
ma-100	124	6	(	(	PUNCT
ma-100	124	7	−1)i	−1)i	X
ma-100	124	8	(	(	PUNCT
ma-100	124	9	η	η	PROPN
ma-100	124	10	i	i	PROPN
ma-100	124	11	)	)	PUNCT
ma-100	124	12	v	v	PROPN
ma-100	124	13	(	(	PUNCT
ma-100	124	14	t	t	PROPN
ma-100	124	15	−	−	PROPN
ma-100	125	1	i	i	PRON
ma-100	125	2	h	h	NOUN
ma-100	125	3	)	)	PUNCT
ma-100	125	4	(	(	PUNCT
ma-100	125	5	11	11	NUM
ma-100	125	6	)	)	PUNCT
ma-100	125	7	we	we	PRON
ma-100	125	8	do	do	VERB
ma-100	125	9	the	the	DET
ma-100	125	10	same	same	ADJ
ma-100	125	11	for	for	ADP
ma-100	125	12	the	the	DET
ma-100	125	13	second	second	ADJ
ma-100	125	14	equation	equation	NOUN
ma-100	125	15	:	:	PUNCT
ma-100	125	16	dη	dη	NOUN
ma-100	125	17	w(t	w(t	PROPN
ma-100	125	18	)	)	PUNCT
ma-100	126	1	=	=	VERB
ma-100	126	2	lim	lim	PROPN
ma-100	126	3	h→0	h→0	PROPN
ma-100	126	4	h−η	h−η	PROPN
ma-100	127	1	[	[	X
ma-100	127	2	t	t	X
ma-100	127	3	]	]	PUNCT
ma-100	127	4	h∑	h∑	ADP
ma-100	127	5	i=0	i=0	PROPN
ma-100	127	6	(	(	PUNCT
ma-100	127	7	−1)i	−1)i	X
ma-100	127	8	(	(	PUNCT
ma-100	127	9	η	η	PROPN
ma-100	127	10	i	i	PROPN
ma-100	127	11	)	)	PUNCT
ma-100	128	1	w(t	w(t	PROPN
ma-100	128	2	−	−	PROPN
ma-100	129	1	i	i	PRON
ma-100	129	2	h	h	NOUN
ma-100	129	3	)	)	PUNCT
ma-100	129	4	(	(	PUNCT
ma-100	129	5	12	12	NUM
ma-100	129	6	)	)	PUNCT
ma-100	129	7	where	where	SCONJ
ma-100	129	8	[	[	X
ma-100	129	9	t	t	X
ma-100	129	10	]	]	PUNCT
ma-100	129	11	denotes	denote	VERB
ma-100	129	12	the	the	DET
ma-100	129	13	integer	integer	NOUN
ma-100	129	14	part	part	NOUN
ma-100	129	15	of	of	ADP
ma-100	129	16	t	t	PROPN
ma-100	129	17	and	and	CCONJ
ma-100	129	18	h	h	NOUN
ma-100	129	19	is	be	AUX
ma-100	129	20	the	the	DET
ma-100	129	21	step	step	NOUN
ma-100	129	22	size.after	size.aft	ADJ
ma-100	129	23	discretization	discretization	NOUN
ma-100	129	24	,	,	PUNCT
ma-100	129	25	(	(	PUNCT
ma-100	129	26	11	11	NUM
ma-100	129	27	)	)	PUNCT
ma-100	129	28	and	and	CCONJ
ma-100	129	29	(	(	PUNCT
ma-100	129	30	12	12	NUM
ma-100	129	31	)	)	PUNCT
ma-100	129	32	become:	become:	NOUN
ma-100	129	33	∑	∑	PUNCT
ma-100	130	1	[	[	X
ma-100	130	2	t	t	X
ma-100	130	3	]	]	X
ma-100	130	4	h	h	NOUN
ma-100	130	5	i=0	i=0	PROPN
ma-100	130	6	c	c	PROPN
ma-100	130	7	η	η	PROPN
ma-100	130	8	i	i	PRON
ma-100	130	9	v	v	PROPN
ma-100	130	10	(	(	PUNCT
ma-100	130	11	tk−i	tk−i	NOUN
ma-100	130	12	)	)	PUNCT
ma-100	130	13	=	=	SYM
ma-100	131	1	f	f	PROPN
ma-100	131	2	(	(	PUNCT
ma-100	131	3	tk	tk	PROPN
ma-100	131	4	,	,	PUNCT
ma-100	131	5	v	v	PROPN
ma-100	131	6	(	(	PUNCT
ma-100	131	7	tk	tk	PROPN
ma-100	131	8	)	)	PUNCT
ma-100	131	9	)	)	PUNCT
ma-100	131	10	,	,	PUNCT
ma-100	131	11	∑	∑	PROPN
ma-100	131	12	[	[	X
ma-100	131	13	t	t	X
ma-100	131	14	]	]	X
ma-100	131	15	h	h	NOUN
ma-100	131	16	i=0	i=0	PROPN
ma-100	131	17	c	c	PROPN
ma-100	131	18	η	η	PROPN
ma-100	131	19	i	i	PRON
ma-100	131	20	w(tk−i	w(tk−i	ADV
ma-100	131	21	)	)	PUNCT
ma-100	132	1	=	=	SYM
ma-100	132	2	g(tk	g(tk	NOUN
ma-100	132	3	,	,	PUNCT
ma-100	132	4	w(tk	w(tk	PROPN
ma-100	132	5	)	)	PUNCT
ma-100	132	6	)	)	PUNCT
ma-100	132	7	,	,	PUNCT
ma-100	132	8	where	where	SCONJ
ma-100	132	9	tk	tk	PROPN
ma-100	132	10	=	=	PROPN
ma-100	132	11	kh	kh	PROPN
ma-100	132	12	for	for	ADP
ma-100	132	13	k	k	PROPN
ma-100	132	14	=	=	SYM
ma-100	132	15	1	1	NUM
ma-100	132	16	,	,	PUNCT
ma-100	132	17	2	2	NUM
ma-100	132	18	,	,	PUNCT
ma-100	132	19	3	3	NUM
ma-100	132	20	,	,	PUNCT
ma-100	132	21	.	.	PUNCT
ma-100	132	22	.	.	PUNCT
ma-100	132	23	.	.	PUNCT
ma-100	133	1	and	and	CCONJ
ma-100	133	2	cηi	cηi	VERB
ma-100	133	3	are	be	AUX
ma-100	133	4	the	the	DET
ma-100	133	5	grunwald	grunwald	NOUN
ma-100	133	6	-	-	PUNCT
ma-100	133	7	letinkov	letinkov	NOUN
ma-100	133	8	coefficients	coefficient	NOUN
ma-100	133	9	as	as	ADP
ma-100	133	10	:	:	PUNCT
ma-100	133	11	cηi	cηi	X
ma-100	133	12	=	=	SYM
ma-100	133	13	(	(	PUNCT
ma-100	133	14	1−	1−	NUM
ma-100	133	15	1	1	NUM
ma-100	133	16	+	+	CCONJ
ma-100	133	17	η	η	PROPN
ma-100	133	18	i	i	PROPN
ma-100	133	19	)	)	PUNCT
ma-100	133	20	cηi−1	cηi−1	PROPN
ma-100	133	21	,	,	PUNCT
ma-100	133	22	cη0	cη0	NOUN
ma-100	134	1	=	=	PUNCT
ma-100	134	2	h−η	h−η	PROPN
ma-100	135	1	i	i	NOUN
ma-100	135	2	=	=	NOUN
ma-100	135	3	1	1	NUM
ma-100	135	4	,	,	PUNCT
ma-100	135	5	2	2	NUM
ma-100	135	6	,	,	PUNCT
ma-100	135	7	.	.	PUNCT
ma-100	135	8	.	.	PUNCT
ma-100	135	9	.	.	PUNCT
ma-100	136	1	then	then	ADV
ma-100	136	2	,	,	PUNCT
ma-100	136	3	we	we	PRON
ma-100	136	4	apply	apply	VERB
ma-100	136	5	the	the	DET
ma-100	136	6	non	non	ADJ
ma-100	136	7	-	-	ADJ
ma-100	136	8	standard	standard	ADJ
ma-100	136	9	finite	finite	ADJ
ma-100	136	10	difference	difference	NOUN
ma-100	136	11	(	(	PUNCT
ma-100	136	12	nsfd	nsfd	ADJ
ma-100	136	13	)	)	PUNCT
ma-100	136	14	schemes	scheme	NOUN
ma-100	136	15	proposed	propose	VERB
ma-100	136	16	by	by	ADP
ma-100	136	17	mickens	mickens	PROPN
ma-100	136	18	[	[	X
ma-100	136	19	31–33]and	31–33]and	NOUN
ma-100	136	20	replace	replace	VERB
ma-100	136	21	the	the	DET
ma-100	136	22	step	step	NOUN
ma-100	136	23	size	size	NOUN
ma-100	136	24	h	h	NOUN
ma-100	136	25	by	by	ADP
ma-100	136	26	a	a	DET
ma-100	136	27	function	function	NOUN
ma-100	136	28	ψ(h	ψ(h	NOUN
ma-100	136	29	)	)	PUNCT
ma-100	136	30	.	.	PUNCT
ma-100	137	1	next	next	ADV
ma-100	137	2	,	,	PUNCT
ma-100	137	3	we	we	PRON
ma-100	137	4	discretize	discretize	VERB
ma-100	137	5	the	the	DET
ma-100	137	6	equations	equation	NOUN
ma-100	137	7	(	(	PUNCT
ma-100	137	8	11	11	NUM
ma-100	137	9	)	)	PUNCT
ma-100	137	10	and	and	CCONJ
ma-100	137	11	(	(	PUNCT
ma-100	137	12	12)following	12)followe	VERB
ma-100	137	13	the	the	DET
ma-100	137	14	grunwald	grunwald	NOUN
ma-100	137	15	-	-	PUNCT
ma-100	137	16	letinkov	letinkov	NOUN
ma-100	137	17	discretization	discretization	NOUN
ma-100	137	18	,	,	PUNCT
ma-100	137	19	using	use	VERB
ma-100	137	20	v	v	NOUN
ma-100	137	21	(	(	PUNCT
ma-100	137	22	tk	tk	PROPN
ma-100	137	23	)	)	PUNCT
ma-100	137	24	=	=	SYM
ma-100	137	25	vk	vk	NOUN
ma-100	137	26	,	,	PUNCT
ma-100	137	27	w(tk	w(tk	PROPN
ma-100	137	28	)	)	PUNCT
ma-100	137	29	=	=	SYM
ma-100	138	1	wk	wk	INTJ
ma-100	138	2	,	,	PUNCT
ma-100	138	3	we	we	PRON
ma-100	138	4	have:	have:	PROPN
ma-100	138	5	cm	cm	PROPN
ma-100	138	6	∑k+1	∑k+1	PUNCT
ma-100	138	7	i=0	i=0	PROPN
ma-100	138	8	c	c	PROPN
ma-100	138	9	η	η	PROPN
ma-100	138	10	i	i	PROPN
ma-100	138	11	vk+1−i	vk+1−i	AUX
ma-100	138	12	=	=	PUNCT
ma-100	138	13	iapp	iapp	NOUN
ma-100	138	14	−	−	PROPN
ma-100	138	15	gl(vk	gl(vk	PROPN
ma-100	138	16	−	−	PROPN
ma-100	138	17	el)−	el)−	PROPN
ma-100	138	18	gkwk(vk	gkwk(vk	PROPN
ma-100	138	19	−	−	PROPN
ma-100	138	20	ek)−	ek)−	ADJ
ma-100	138	21	gcam∞(vk)(vk	gcam∞(vk)(vk	PROPN
ma-100	138	22	−	−	PROPN
ma-100	138	23	eca	eca	NOUN
ma-100	138	24	)	)	PUNCT
ma-100	139	1	,	,	PUNCT
ma-100	139	2	∑k+1	∑k+1	PROPN
ma-100	139	3	i=0	i=0	PROPN
ma-100	139	4	c	c	PROPN
ma-100	139	5	η	η	PROPN
ma-100	139	6	i	i	PRON
ma-100	139	7	wk+1−i	wk+1−i	VERB
ma-100	139	8	=	=	SYM
ma-100	139	9	φ(n∞(vk)−	φ(n∞(vk)−	PROPN
ma-100	139	10	wk)/τwk	wk)/τwk	PROPN
ma-100	139	11	(	(	PUNCT
ma-100	139	12	vk	vk	PROPN
ma-100	139	13	)	)	PUNCT
ma-100	139	14	,	,	PUNCT
ma-100	139	15	(	(	PUNCT
ma-100	139	16	13	13	NUM
ma-100	139	17	)	)	PUNCT
ma-100	139	18	where	where	SCONJ
ma-100	139	19	m∞(vk	m∞(vk	NOUN
ma-100	139	20	)	)	PUNCT
ma-100	139	21	=	=	SYM
ma-100	139	22	1	1	NUM
ma-100	139	23	2	2	NUM
ma-100	139	24	[	[	SYM
ma-100	139	25	1	1	NUM
ma-100	139	26	+	+	NUM
ma-100	139	27	tanh((vk	tanh((vk	PROPN
ma-100	139	28	−	−	PROPN
ma-100	139	29	v1)/v2	v1)/v2	NOUN
ma-100	139	30	)	)	PUNCT
ma-100	139	31	]	]	PUNCT
ma-100	139	32	,	,	PUNCT
ma-100	139	33	(	(	PUNCT
ma-100	139	34	14	14	NUM
ma-100	139	35	)	)	PUNCT
ma-100	139	36	τn(vk	τn(vk	PROPN
ma-100	139	37	)	)	PUNCT
ma-100	139	38	=	=	SYM
ma-100	140	1	1	1	X
ma-100	140	2	/	/	SYM
ma-100	140	3	cosh((vk	cosh((vk	PROPN
ma-100	140	4	−	−	PROPN
ma-100	140	5	v3)/(2v4	v3)/(2v4	NUM
ma-100	140	6	)	)	PUNCT
ma-100	140	7	)	)	PUNCT
ma-100	140	8	,	,	PUNCT
ma-100	140	9	(	(	PUNCT
ma-100	140	10	15	15	X
ma-100	140	11	)	)	PUNCT
ma-100	140	12	n∞(vk	n∞(vk	NOUN
ma-100	140	13	)	)	PUNCT
ma-100	141	1	=	=	PUNCT
ma-100	141	2	1	1	NUM
ma-100	141	3	2	2	NUM
ma-100	141	4	[	[	SYM
ma-100	141	5	1	1	NUM
ma-100	141	6	+	+	NUM
ma-100	141	7	tanh((vk	tanh((vk	PROPN
ma-100	141	8	−	−	PROPN
ma-100	141	9	v3)/v4	v3)/v4	PROPN
ma-100	141	10	)	)	PUNCT
ma-100	141	11	]	]	PUNCT
ma-100	141	12	.	.	PUNCT
ma-100	142	1	(	(	PUNCT
ma-100	142	2	16	16	NUM
ma-100	142	3	)	)	PUNCT
ma-100	142	4	and	and	CCONJ
ma-100	142	5	iion(vk	iion(vk	PROPN
ma-100	142	6	,	,	PUNCT
ma-100	142	7	wk	wk	PROPN
ma-100	142	8	)	)	PUNCT
ma-100	142	9	=	=	NOUN
ma-100	143	1	gl(vk	gl(vk	PROPN
ma-100	143	2	−	−	PROPN
ma-100	143	3	el	el	PROPN
ma-100	143	4	)	)	PUNCT
ma-100	144	1	+	+	CCONJ
ma-100	144	2	gkwk(vk	gkwk(vk	PROPN
ma-100	144	3	−	−	PROPN
ma-100	144	4	ek	ek	NOUN
ma-100	144	5	)	)	PUNCT
ma-100	144	6	+	+	CCONJ
ma-100	144	7	gcam∞(vk)(vk	gcam∞(vk)(vk	PROPN
ma-100	144	8	−	−	PROPN
ma-100	144	9	eca	eca	NOUN
ma-100	144	10	)	)	PUNCT
ma-100	144	11	(	(	PUNCT
ma-100	144	12	17	17	NUM
ma-100	144	13	)	)	PUNCT
ma-100	144	14	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	144	15	eur	eur	PROPN
ma-100	144	16	.	.	PUNCT
ma-100	145	1	j.	j.	PROPN
ma-100	145	2	math	math	PROPN
ma-100	145	3	.	.	PUNCT
ma-100	146	1	anal	anal	PROPN
ma-100	146	2	.	.	PUNCT
ma-100	147	1	10.28924	10.28924	NUM
ma-100	147	2	/	/	SYM
ma-100	147	3	ada	ada	PROPN
ma-100	147	4	/	/	SYM
ma-100	147	5	ma.3.2	ma.3.2	PROPN
ma-100	147	6	7	7	NUM
ma-100	147	7	table	table	NOUN
ma-100	147	8	1	1	NUM
ma-100	147	9	.	.	PUNCT
ma-100	148	1	parameter	parameter	NOUN
ma-100	148	2	values	value	NOUN
ma-100	148	3	for	for	ADP
ma-100	148	4	the	the	DET
ma-100	148	5	fractional	fractional	ADJ
ma-100	148	6	-	-	PUNCT
ma-100	148	7	order	order	NOUN
ma-100	148	8	morris	morris	ADJ
ma-100	148	9	-	-	PUNCT
ma-100	148	10	lecar	lecar	NOUN
ma-100	148	11	model	model	NOUN
ma-100	148	12	.	.	PUNCT
ma-100	149	1	after	after	SCONJ
ma-100	149	2	some	some	DET
ma-100	149	3	algebra,	algebra,	PROPN
ma-100	149	4	vk+1	vk+1	ADJ
ma-100	149	5	=	=	NOUN
ma-100	149	6	iapp	iapp	NOUN
ma-100	149	7	−	−	NOUN
ma-100	149	8	∑k+1	∑k+1	PUNCT
ma-100	149	9	i=1	i=1	PROPN
ma-100	149	10	c	c	PROPN
ma-100	149	11	η	η	PROPN
ma-100	149	12	i	i	PRON
ma-100	149	13	vk+1−i	vk+1−i	ADP
ma-100	149	14	−	−	PROPN
ma-100	150	1	gl(vk	gl(vk	PROPN
ma-100	150	2	−	−	PROPN
ma-100	150	3	el)−	el)−	PROPN
ma-100	150	4	gkwk(vk	gkwk(vk	PROPN
ma-100	150	5	−	−	PROPN
ma-100	150	6	ek)−	ek)−	ADJ
ma-100	150	7	gcam∞(vk)(vk	gcam∞(vk)(vk	PROPN
ma-100	150	8	−	−	PROPN
ma-100	150	9	eca	eca	NOUN
ma-100	150	10	)	)	PUNCT
ma-100	150	11	cm	cm	PROPN
ma-100	150	12	c	c	PROPN
ma-100	150	13	η	η	PROPN
ma-100	150	14	0	0	NUM
ma-100	150	15	wk+1	wk+1	X
ma-100	150	16	=	=	SYM
ma-100	150	17	φ(n∞(vk)−	φ(n∞(vk)−	ADJ
ma-100	150	18	wk)−	wk)−	ADJ
ma-100	150	19	τwk	τwk	PROPN
ma-100	150	20	(	(	PUNCT
ma-100	150	21	vk	vk	PROPN
ma-100	150	22	)	)	PUNCT
ma-100	150	23	∑k+1	∑k+1	PUNCT
ma-100	151	1	i=1	i=1	PROPN
ma-100	151	2	c	c	PROPN
ma-100	151	3	η	η	PROPN
ma-100	151	4	i	i	PRON
ma-100	151	5	wk+1−i	wk+1−i	AUX
ma-100	151	6	cη0	cη0	VERB
ma-100	151	7	τwk	τwk	PROPN
ma-100	151	8	(	(	PUNCT
ma-100	151	9	vk	vk	PROPN
ma-100	151	10	)	)	PUNCT
ma-100	151	11	(	(	PUNCT
ma-100	151	12	18	18	NUM
ma-100	151	13	)	)	PUNCT
ma-100	151	14	where	where	SCONJ
ma-100	151	15	cη0	cη0	NOUN
ma-100	151	16	=	=	SYM
ma-100	151	17	ψ(h)−η	ψ(h)−η	PROPN
ma-100	151	18	,	,	PUNCT
ma-100	151	19	ψ(h	ψ(h	PRON
ma-100	151	20	)	)	PUNCT
ma-100	151	21	=	=	SYM
ma-100	151	22	sin(h	sin(h	PROPN
ma-100	151	23	)	)	PUNCT
ma-100	151	24	the	the	DET
ma-100	151	25	fractional	fractional	ADJ
ma-100	151	26	-	-	PUNCT
ma-100	151	27	order	order	NOUN
ma-100	151	28	morris	morris	ADJ
ma-100	151	29	-	-	PUNCT
ma-100	151	30	lecar	lecar	ADJ
ma-100	151	31	model	model	NOUN
ma-100	151	32	displays	display	VERB
ma-100	151	33	different	different	ADJ
ma-100	151	34	ranges	range	NOUN
ma-100	151	35	of	of	ADP
ma-100	151	36	dynamics	dynamic	NOUN
ma-100	151	37	such	such	ADJ
ma-100	151	38	as	as	ADP
ma-100	151	39	hopfbifurcation	hopfbifurcation	NOUN
ma-100	151	40	,	,	PUNCT
ma-100	151	41	saddle	saddle	ADJ
ma-100	151	42	node	node	NOUN
ma-100	151	43	on	on	ADP
ma-100	151	44	invariant	invariant	ADJ
ma-100	151	45	limit	limit	NOUN
ma-100	151	46	cycles	cycle	NOUN
ma-100	151	47	(	(	PUNCT
ma-100	151	48	snlc	snlc	PROPN
ma-100	151	49	)	)	PUNCT
ma-100	151	50	and	and	CCONJ
ma-100	151	51	homoclinic	homoclinic	ADJ
ma-100	151	52	bifurcation	bifurcation	NOUN
ma-100	151	53	.	.	PUNCT
ma-100	152	1	we	we	PRON
ma-100	152	2	keepthe	keepthe	VERB
ma-100	152	3	same	same	ADJ
ma-100	152	4	biological	biological	ADJ
ma-100	152	5	parameters	parameter	NOUN
ma-100	152	6	as	as	ADP
ma-100	152	7	the	the	DET
ma-100	152	8	original	original	ADJ
ma-100	152	9	morris	morris	ADJ
ma-100	152	10	-	-	PUNCT
ma-100	152	11	lecar	lecar	NOUN
ma-100	152	12	model	model	NOUN
ma-100	152	13	.	.	PUNCT
ma-100	153	1	we	we	PRON
ma-100	153	2	have	have	AUX
ma-100	153	3	represented	represent	VERB
ma-100	153	4	theseparameters	theseparameter	NOUN
ma-100	153	5	for	for	ADP
ma-100	153	6	these	these	DET
ma-100	153	7	three	three	NUM
ma-100	153	8	different	different	ADJ
ma-100	153	9	dynamics	dynamic	NOUN
ma-100	153	10	in	in	ADP
ma-100	153	11	table	table	NOUN
ma-100	153	12	(	(	PUNCT
ma-100	153	13	1	1	NUM
ma-100	153	14	)	)	PUNCT
ma-100	154	1	[	[	X
ma-100	154	2	18	18	NUM
ma-100	154	3	]	]	PUNCT
ma-100	154	4	.	.	PUNCT
ma-100	155	1	we	we	PRON
ma-100	155	2	assume	assume	VERB
ma-100	155	3	iapp	iapp	NOUN
ma-100	155	4	as	as	ADP
ma-100	155	5	a	a	DET
ma-100	155	6	controlparameter	controlparameter	NOUN
ma-100	155	7	for	for	ADP
ma-100	155	8	numerical	numerical	ADJ
ma-100	155	9	simulations	simulation	NOUN
ma-100	155	10	.	.	PUNCT
ma-100	156	1	3.2	3.2	NUM
ma-100	156	2	.	.	PUNCT
ma-100	157	1	local	local	ADJ
ma-100	157	2	stability	stability	NOUN
ma-100	157	3	analysis	analysis	NOUN
ma-100	157	4	of	of	ADP
ma-100	157	5	fractional	fractional	ADJ
ma-100	157	6	order	order	NOUN
ma-100	157	7	morris	morris	ADJ
ma-100	157	8	-	-	PUNCT
ma-100	157	9	lecar	lecar	NOUN
ma-100	157	10	model	model	NOUN
ma-100	157	11	.	.	PUNCT
ma-100	158	1	in	in	ADP
ma-100	158	2	neuroscience	neuroscience	NOUN
ma-100	158	3	,	,	PUNCT
ma-100	158	4	it	it	PRON
ma-100	158	5	’s	’	VERB
ma-100	158	6	usuallyhard	usuallyhard	ADJ
ma-100	158	7	to	to	PART
ma-100	158	8	extract	extract	VERB
ma-100	158	9	analytically	analytically	ADV
ma-100	158	10	the	the	DET
ma-100	158	11	dynamics	dynamic	NOUN
ma-100	158	12	of	of	ADP
ma-100	158	13	the	the	DET
ma-100	158	14	neuronal	neuronal	ADJ
ma-100	158	15	systems	system	NOUN
ma-100	158	16	and	and	CCONJ
ma-100	158	17	we	we	PRON
ma-100	158	18	may	may	AUX
ma-100	158	19	need	need	VERB
ma-100	158	20	to	to	PART
ma-100	158	21	use	use	VERB
ma-100	158	22	somegeometrical	somegeometrical	ADJ
ma-100	158	23	and	and	CCONJ
ma-100	158	24	qualitative	qualitative	ADJ
ma-100	158	25	techniques	technique	NOUN
ma-100	158	26	such	such	ADJ
ma-100	158	27	as	as	ADP
ma-100	158	28	phase	phase	NOUN
ma-100	158	29	portrait	portrait	NOUN
ma-100	158	30	analysis	analysis	NOUN
ma-100	158	31	.	.	PUNCT
ma-100	159	1	phase	phase	NOUN
ma-100	159	2	portraits	portrait	VERB
ma-100	159	3	demonstratethe	demonstratethe	ADP
ma-100	159	4	evolution	evolution	NOUN
ma-100	159	5	of	of	ADP
ma-100	159	6	state	state	NOUN
ma-100	159	7	variables	variable	NOUN
ma-100	159	8	in	in	ADP
ma-100	159	9	time	time	NOUN
ma-100	159	10	with	with	ADP
ma-100	159	11	different	different	ADJ
ma-100	159	12	initial	initial	ADJ
ma-100	159	13	states	state	NOUN
ma-100	159	14	.	.	PUNCT
ma-100	160	1	by	by	ADP
ma-100	160	2	looking	look	VERB
ma-100	160	3	at	at	ADP
ma-100	160	4	the	the	DET
ma-100	160	5	phase	phase	NOUN
ma-100	160	6	portrait	portrait	NOUN
ma-100	160	7	,	,	PUNCT
ma-100	160	8	we	we	PRON
ma-100	160	9	can	can	AUX
ma-100	160	10	observe	observe	VERB
ma-100	160	11	the	the	DET
ma-100	160	12	qualitative	qualitative	ADJ
ma-100	160	13	behavior	behavior	NOUN
ma-100	160	14	of	of	ADP
ma-100	160	15	the	the	DET
ma-100	160	16	system	system	NOUN
ma-100	160	17	without	without	ADP
ma-100	160	18	knowing	know	VERB
ma-100	160	19	the	the	DET
ma-100	160	20	model	model	NOUN
ma-100	160	21	equations	equation	NOUN
ma-100	160	22	.	.	PUNCT
ma-100	161	1	toanalyze	toanalyze	VERB
ma-100	161	2	the	the	DET
ma-100	161	3	local	local	ADJ
ma-100	161	4	dynamics	dynamic	NOUN
ma-100	161	5	of	of	ADP
ma-100	161	6	fractional	fractional	ADJ
ma-100	161	7	order	order	NOUN
ma-100	161	8	morris	morris	ADJ
ma-100	161	9	-	-	PUNCT
ma-100	161	10	lecar	lecar	NOUN
ma-100	161	11	model	model	NOUN
ma-100	161	12	,	,	PUNCT
ma-100	161	13	we	we	PRON
ma-100	161	14	apply	apply	VERB
ma-100	161	15	a	a	DET
ma-100	161	16	useful	useful	ADJ
ma-100	161	17	theoremin	theoremin	ADJ
ma-100	161	18	dynamical	dynamical	ADJ
ma-100	161	19	systems	system	NOUN
ma-100	161	20	theory	theory	NOUN
ma-100	161	21	,	,	PUNCT
ma-100	161	22	called	call	VERB
ma-100	161	23	the	the	DET
ma-100	161	24	hartman	hartman	PROPN
ma-100	161	25	-	-	PUNCT
ma-100	161	26	grobman	grobman	NOUN
ma-100	161	27	theorem	theorem	VERB
ma-100	161	28	[	[	X
ma-100	161	29	45–47	45–47	NOUN
ma-100	161	30	]	]	PUNCT
ma-100	161	31	.	.	PUNCT
ma-100	162	1	according	accord	VERB
ma-100	162	2	to	to	ADP
ma-100	162	3	this	this	DET
ma-100	162	4	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	162	5	eur	eur	NOUN
ma-100	162	6	.	.	PUNCT
ma-100	163	1	j.	j.	PROPN
ma-100	163	2	math	math	PROPN
ma-100	163	3	.	.	PUNCT
ma-100	164	1	anal	anal	PROPN
ma-100	164	2	.	.	PUNCT
ma-100	165	1	10.28924	10.28924	NUM
ma-100	165	2	/	/	SYM
ma-100	165	3	ada	ada	PROPN
ma-100	165	4	/	/	SYM
ma-100	165	5	ma.3.2	ma.3.2	PROPN
ma-100	165	6	8theorem	8theorem	NUM
ma-100	165	7	non	non	ADJ
ma-100	165	8	-	-	ADJ
ma-100	165	9	linear	linear	ADJ
ma-100	165	10	fractional	fractional	ADJ
ma-100	165	11	order	order	NOUN
ma-100	165	12	morris	morris	ADJ
ma-100	165	13	-	-	PUNCT
ma-100	165	14	lecar	lecar	ADJ
ma-100	165	15	system	system	NOUN
ma-100	165	16	{	{	PUNCT
ma-100	165	17	vk+1	vk+1	PROPN
ma-100	165	18	=	=	SYM
ma-100	165	19	f	f	X
ma-100	165	20	(	(	PUNCT
ma-100	165	21	vk	vk	INTJ
ma-100	165	22	,	,	PUNCT
ma-100	165	23	wk	wk	NOUN
ma-100	165	24	)	)	PUNCT
ma-100	165	25	wk+1	wk+1	NOUN
ma-100	165	26	=	=	SYM
ma-100	165	27	g(vk	g(vk	PROPN
ma-100	165	28	,	,	PUNCT
ma-100	165	29	wk	wk	PROPN
ma-100	165	30	)	)	PUNCT
ma-100	165	31	(	(	PUNCT
ma-100	165	32	19	19	NUM
ma-100	165	33	)	)	PUNCT
ma-100	165	34	sufficiently	sufficiently	ADV
ma-100	165	35	near	near	ADP
ma-100	165	36	equilibrium	equilibrium	NOUN
ma-100	165	37	(	(	PUNCT
ma-100	165	38	v	v	NOUN
ma-100	165	39	,	,	PUNCT
ma-100	165	40	w	w	NOUN
ma-100	165	41	)	)	PUNCT
ma-100	165	42	=	=	SYM
ma-100	165	43	(	(	PUNCT
ma-100	165	44	v	v	NOUN
ma-100	165	45	∗	∗	NOUN
ma-100	165	46	,	,	PUNCT
ma-100	165	47	w∗	w∗	NOUN
ma-100	165	48	)	)	PUNCT
ma-100	165	49	is	be	AUX
ma-100	165	50	locally	locally	ADV
ma-100	165	51	topologically	topologically	ADV
ma-100	165	52	equivalent	equivalent	ADJ
ma-100	165	53	to	to	ADP
ma-100	165	54	the	the	DET
ma-100	165	55	linear	linear	ADJ
ma-100	165	56	partof	partof	VERB
ma-100	165	57	the	the	DET
ma-100	165	58	system	system	NOUN
ma-100	165	59	.	.	PUNCT
ma-100	166	1	first	first	ADV
ma-100	166	2	we	we	PRON
ma-100	166	3	transform	transform	VERB
ma-100	166	4	the	the	DET
ma-100	166	5	fixed	fix	VERB
ma-100	166	6	point	point	NOUN
ma-100	166	7	(	(	PUNCT
ma-100	166	8	v	v	NOUN
ma-100	166	9	∗	∗	NOUN
ma-100	166	10	,	,	PUNCT
ma-100	166	11	w∗	w∗	NOUN
ma-100	166	12	)	)	PUNCT
ma-100	166	13	of	of	ADP
ma-100	166	14	the	the	DET
ma-100	166	15	system	system	NOUN
ma-100	166	16	(	(	PUNCT
ma-100	166	17	19	19	NUM
ma-100	166	18	)	)	PUNCT
ma-100	166	19	to	to	ADP
ma-100	166	20	the	the	DET
ma-100	166	21	origin	origin	NOUN
ma-100	166	22	by	by	ADP
ma-100	166	23	thetranslation	thetranslation	NOUN
ma-100	166	24	v	v	ADP
ma-100	166	25	=	=	SYM
ma-100	166	26	v	v	ADP
ma-100	166	27	∗	∗	NOUN
ma-100	166	28	+	+	CCONJ
ma-100	167	1	v̄	v̄	NOUN
ma-100	168	1	and	and	CCONJ
ma-100	168	2	w	w	NOUN
ma-100	168	3	=	=	PROPN
ma-100	168	4	w∗	w∗	NOUN
ma-100	168	5	+	+	CCONJ
ma-100	168	6	w̄	w̄	NOUN
ma-100	168	7	.	.	PUNCT
ma-100	169	1	if	if	SCONJ
ma-100	169	2	we	we	PRON
ma-100	169	3	split	split	VERB
ma-100	169	4	off	off	ADP
ma-100	169	5	the	the	DET
ma-100	169	6	linear	linear	ADJ
ma-100	169	7	part	part	NOUN
ma-100	169	8	of	of	ADP
ma-100	169	9	the	the	DET
ma-100	169	10	system	system	NOUN
ma-100	169	11	from	from	ADP
ma-100	169	12	itsnon	itsnon	NOUN
ma-100	169	13	-	-	PUNCT
ma-100	169	14	linear	linear	NOUN
ma-100	169	15	part	part	NOUN
ma-100	169	16	,	,	PUNCT
ma-100	169	17	we	we	PRON
ma-100	169	18	have	have	VERB
ma-100	169	19	[	[	PUNCT
ma-100	169	20	v̄	v̄	ADJ
ma-100	169	21	w̄	w̄	NOUN
ma-100	169	22	]	]	PUNCT
ma-100	169	23	=	=	SYM
ma-100	169	24			ADJ
ma-100	170	1	∂f	∂f	PROPN
ma-100	170	2	(	(	PUNCT
ma-100	170	3	v̄	v̄	NOUN
ma-100	170	4	,	,	PUNCT
ma-100	170	5	w̄	w̄	NOUN
ma-100	170	6	)	)	PUNCT
ma-100	170	7	∂v̄	∂v̄	PROPN
ma-100	170	8	∂f	∂f	PROPN
ma-100	170	9	(	(	PUNCT
ma-100	170	10	v̄	v̄	PROPN
ma-100	170	11	,	,	PUNCT
ma-100	170	12	w̄	w̄	NOUN
ma-100	170	13	)	)	PUNCT
ma-100	171	1	∂w̄	∂w̄	PROPN
ma-100	171	2	∂g(v̄	∂g(v̄	PROPN
ma-100	171	3	,	,	PUNCT
ma-100	171	4	w̄	w̄	PROPN
ma-100	171	5	)	)	PUNCT
ma-100	171	6	∂v̄	∂v̄	PROPN
ma-100	171	7	∂g(v̄	∂g(v̄	PROPN
ma-100	171	8	,	,	PUNCT
ma-100	171	9	w̄	w̄	PROPN
ma-100	171	10	)	)	PUNCT
ma-100	172	1	∂w̄	∂w̄	PROPN
ma-100	172	2			NUM
ma-100	172	3	[	[	PUNCT
ma-100	172	4	v̄	v̄	NOUN
ma-100	172	5	w̄	w̄	NOUN
ma-100	172	6	]	]	PUNCT
ma-100	173	1	+	+	CCONJ
ma-100	173	2	f̃	f̃	PROPN
ma-100	173	3	(	(	PUNCT
ma-100	173	4	v̄	v̄	NOUN
ma-100	173	5	,	,	PUNCT
ma-100	173	6	w̄	w̄	NOUN
ma-100	173	7	)	)	PUNCT
ma-100	173	8	g̃(v̄	g̃(v̄	NOUN
ma-100	173	9	,	,	PUNCT
ma-100	173	10	w̄	w̄	NOUN
ma-100	173	11	)	)	PUNCT
ma-100	173	12			PROPN
ma-100	173	13	(	(	PUNCT
ma-100	173	14	20	20	NUM
ma-100	173	15	)	)	PUNCT
ma-100	173	16	where	where	SCONJ
ma-100	173	17	f̃	f̃	PROPN
ma-100	173	18	and	and	CCONJ
ma-100	173	19	g̃	g̃	PROPN
ma-100	173	20	represent	represent	VERB
ma-100	173	21	the	the	DET
ma-100	173	22	non	non	ADJ
ma-100	173	23	-	-	ADJ
ma-100	173	24	linear	linear	ADJ
ma-100	173	25	part	part	NOUN
ma-100	173	26	of	of	ADP
ma-100	173	27	the	the	DET
ma-100	173	28	system	system	NOUN
ma-100	173	29	(	(	PUNCT
ma-100	173	30	19	19	NUM
ma-100	173	31	)	)	PUNCT
ma-100	173	32	and	and	NOUN
ma-100	173	33	∂f	∂f	PROPN
ma-100	173	34	(	(	PUNCT
ma-100	173	35	v̄	v̄	NOUN
ma-100	173	36	,	,	PUNCT
ma-100	173	37	w̄	w̄	NOUN
ma-100	173	38	)	)	PUNCT
ma-100	173	39	∂v̄	∂v̄	PROPN
ma-100	173	40	=	=	PUNCT
ma-100	174	1	−	−	PROPN
ma-100	174	2	∑k+1	∑k+1	VERB
ma-100	174	3	i=1	i=1	PROPN
ma-100	174	4	c	c	PROPN
ma-100	174	5	η	η	PROPN
ma-100	174	6	i	i	PRON
ma-100	174	7	−	−	PROPN
ma-100	174	8	gl	gl	NOUN
ma-100	174	9	−	−	PROPN
ma-100	174	10	gkw̄	gkw̄	PROPN
ma-100	174	11	−	−	PROPN
ma-100	174	12	gcam∞(v̄	gcam∞(v̄	PROPN
ma-100	174	13	)	)	PUNCT
ma-100	174	14	cm	cm	PROPN
ma-100	174	15	c	c	PROPN
ma-100	174	16	η	η	PROPN
ma-100	174	17	0	0	NUM
ma-100	174	18	≡	≡	PROPN
ma-100	174	19	a	a	DET
ma-100	174	20	∂f	∂f	PROPN
ma-100	174	21	(	(	PUNCT
ma-100	174	22	v̄	v̄	NOUN
ma-100	174	23	,	,	PUNCT
ma-100	174	24	w̄	w̄	NOUN
ma-100	174	25	)	)	PUNCT
ma-100	174	26	∂w̄	∂w̄	PROPN
ma-100	175	1	=	=	PUNCT
ma-100	175	2	−gk	−gk	NOUN
ma-100	175	3	v̄	v̄	NOUN
ma-100	175	4	cm	cm	NOUN
ma-100	175	5	c	c	PROPN
ma-100	175	6	η	η	PROPN
ma-100	175	7	0	0	NUM
ma-100	175	8	≡	≡	PROPN
ma-100	175	9	b	b	PROPN
ma-100	176	1	∂g(v̄	∂g(v̄	PROPN
ma-100	176	2	,	,	PUNCT
ma-100	176	3	w̄	w̄	PROPN
ma-100	176	4	)	)	PUNCT
ma-100	176	5	∂v̄	∂v̄	PROPN
ma-100	176	6	=	=	PUNCT
ma-100	176	7	φn′∞(v̄	φn′∞(v̄	X
ma-100	176	8	)	)	PUNCT
ma-100	177	1	cη0	cη0	VERB
ma-100	177	2	τwk	τwk	PROPN
ma-100	178	1	(	(	PUNCT
ma-100	178	2	v̄	v̄	NOUN
ma-100	178	3	)	)	PUNCT
ma-100	178	4	≡	≡	PROPN
ma-100	178	5	c	c	PROPN
ma-100	179	1	∂g(v̄	∂g(v̄	PROPN
ma-100	179	2	,	,	PUNCT
ma-100	179	3	w̄	w̄	PROPN
ma-100	179	4	)	)	PUNCT
ma-100	180	1	∂w̄	∂w̄	PROPN
ma-100	180	2	=	=	PUNCT
ma-100	180	3	−φ−	−φ−	ADJ
ma-100	180	4	τwk	τwk	PROPN
ma-100	180	5	(	(	PUNCT
ma-100	180	6	v̄	v̄	NOUN
ma-100	180	7	)	)	PUNCT
ma-100	180	8	∑k+1	∑k+1	PUNCT
ma-100	181	1	i=1	i=1	PROPN
ma-100	181	2	c	c	PROPN
ma-100	181	3	η	η	PROPN
ma-100	181	4	i	i	PRON
ma-100	181	5	cη0	cη0	VERB
ma-100	181	6	τwk	τwk	PROPN
ma-100	182	1	(	(	PUNCT
ma-100	182	2	v̄	v̄	NOUN
ma-100	182	3	)	)	PUNCT
ma-100	182	4	≡	≡	PROPN
ma-100	182	5	d	d	X
ma-100	182	6	(	(	PUNCT
ma-100	182	7	21	21	NUM
ma-100	182	8	)	)	PUNCT
ma-100	182	9	to	to	PART
ma-100	182	10	find	find	VERB
ma-100	182	11	the	the	DET
ma-100	182	12	stability	stability	NOUN
ma-100	182	13	of	of	ADP
ma-100	182	14	the	the	DET
ma-100	182	15	interior	interior	ADJ
ma-100	182	16	equilibrium	equilibrium	NOUN
ma-100	182	17	point	point	NOUN
ma-100	182	18	of	of	ADP
ma-100	182	19	the	the	DET
ma-100	182	20	system	system	NOUN
ma-100	182	21	,	,	PUNCT
ma-100	182	22	we	we	PRON
ma-100	182	23	need	need	VERB
ma-100	182	24	to	to	PART
ma-100	182	25	look	look	VERB
ma-100	182	26	at	at	ADP
ma-100	182	27	the	the	DET
ma-100	182	28	linearpart	linearpart	NOUN
ma-100	182	29	of	of	ADP
ma-100	182	30	(	(	PUNCT
ma-100	182	31	20	20	NUM
ma-100	182	32	)	)	PUNCT
ma-100	182	33	which	which	PRON
ma-100	182	34	is	be	AUX
ma-100	182	35	given	give	VERB
ma-100	182	36	by	by	ADP
ma-100	182	37	(	(	PUNCT
ma-100	182	38	21	21	NUM
ma-100	182	39	)	)	PUNCT
ma-100	182	40	.	.	PUNCT
ma-100	183	1	at	at	ADP
ma-100	183	2	first	first	ADV
ma-100	183	3	,	,	PUNCT
ma-100	183	4	we	we	PRON
ma-100	183	5	assume	assume	VERB
ma-100	183	6	that	that	SCONJ
ma-100	183	7	for	for	ADP
ma-100	183	8	the	the	DET
ma-100	183	9	voltage	voltage	NOUN
ma-100	183	10	ek	ek	NOUN
ma-100	183	11	<	<	X
ma-100	183	12	v̄	v̄	X
ma-100	183	13	<	<	X
ma-100	183	14	eca	eca	PROPN
ma-100	183	15	.	.	PUNCT
ma-100	184	1	thenwe	thenwe	PROPN
ma-100	184	2	have	have	VERB
ma-100	184	3	b	b	NOUN
ma-100	184	4	<	<	X
ma-100	184	5	0	0	NUM
ma-100	184	6	,	,	PUNCT
ma-100	184	7	c	c	NOUN
ma-100	184	8	>	>	X
ma-100	184	9	0	0	NUM
ma-100	184	10	,	,	PUNCT
ma-100	184	11	and	and	CCONJ
ma-100	184	12	d	d	X
ma-100	184	13	<	<	X
ma-100	184	14	0	0	PUNCT
ma-100	184	15	and	and	CCONJ
ma-100	184	16	a	a	PRON
ma-100	184	17	can	can	AUX
ma-100	184	18	be	be	AUX
ma-100	184	19	either	either	CCONJ
ma-100	184	20	positive	positive	ADJ
ma-100	184	21	or	or	CCONJ
ma-100	184	22	negative	negative	ADJ
ma-100	184	23	.	.	PUNCT
ma-100	185	1	m∞(v̄	m∞(v̄	NOUN
ma-100	185	2	)	)	PUNCT
ma-100	185	3	which	which	PRON
ma-100	185	4	definesthe	definesthe	DET
ma-100	185	5	slope	slope	NOUN
ma-100	185	6	of	of	ADP
ma-100	185	7	the	the	DET
ma-100	185	8	calcium	calcium	NOUN
ma-100	185	9	activation	activation	NOUN
ma-100	185	10	function	function	NOUN
ma-100	185	11	can	can	AUX
ma-100	185	12	make	make	VERB
ma-100	185	13	a	a	DET
ma-100	185	14	>	>	X
ma-100	185	15	0	0	NUM
ma-100	185	16	.	.	PUNCT
ma-100	186	1	on	on	ADP
ma-100	186	2	the	the	DET
ma-100	186	3	other	other	ADJ
ma-100	186	4	hand	hand	NOUN
ma-100	186	5	,	,	PUNCT
ma-100	186	6	for	for	ADP
ma-100	186	7	a	a	DET
ma-100	186	8	<	<	X
ma-100	186	9	0	0	NUM
ma-100	186	10	,	,	PUNCT
ma-100	186	11	theequilibrium	theequilibrium	NOUN
ma-100	186	12	point	point	NOUN
ma-100	186	13	is	be	AUX
ma-100	186	14	asymptotically	asymptotically	ADV
ma-100	186	15	stable	stable	ADJ
ma-100	186	16	because	because	SCONJ
ma-100	186	17	a	a	PRON
ma-100	186	18	+	+	X
ma-100	186	19	d	d	X
ma-100	186	20	<	<	X
ma-100	186	21	0	0	NUM
ma-100	186	22	and	and	CCONJ
ma-100	186	23	ad	ad	NOUN
ma-100	186	24	−	−	PROPN
ma-100	186	25	bc	bc	PROPN
ma-100	186	26	>	>	X
ma-100	186	27	0	0	PROPN
ma-100	186	28	.	.	PUNCT
ma-100	187	1	moreover	moreover	ADV
ma-100	187	2	,	,	PUNCT
ma-100	187	3	for	for	ADP
ma-100	187	4	b	b	NOUN
ma-100	187	5	<	<	X
ma-100	187	6	0	0	PROPN
ma-100	187	7	the	the	DET
ma-100	187	8	equilibrium	equilibrium	NOUN
ma-100	187	9	point	point	NOUN
ma-100	187	10	is	be	AUX
ma-100	187	11	stable	stable	ADJ
ma-100	187	12	because	because	SCONJ
ma-100	187	13	the	the	DET
ma-100	187	14	negativity	negativity	NOUN
ma-100	187	15	of	of	ADP
ma-100	187	16	slope	slope	NOUN
ma-100	187	17	of	of	ADP
ma-100	187	18	v̄	v̄	ADJ
ma-100	187	19	-nullcline	-nullcline	NOUN
ma-100	187	20	,	,	PUNCT
ma-100	187	21	−ab	−ab	PRON
ma-100	187	22	<	<	X
ma-100	187	23	0.for	0.for	ADP
ma-100	187	24	the	the	DET
ma-100	187	25	case	case	NOUN
ma-100	187	26	that	that	SCONJ
ma-100	187	27	a	a	PRON
ma-100	187	28	>	>	X
ma-100	187	29	0	0	NUM
ma-100	188	1	the	the	DET
ma-100	188	2	equilibrium	equilibrium	NOUN
ma-100	188	3	point	point	NOUN
ma-100	188	4	is	be	AUX
ma-100	188	5	a	a	DET
ma-100	188	6	saddle	saddle	NOUN
ma-100	188	7	point	point	NOUN
ma-100	188	8	and	and	CCONJ
ma-100	188	9	unstable	unstable	ADJ
ma-100	188	10	because	because	SCONJ
ma-100	188	11	of	of	ADP
ma-100	188	12	thepositivity	thepositivity	NOUN
ma-100	188	13	of	of	ADP
ma-100	188	14	slope	slope	NOUN
ma-100	188	15	of	of	ADP
ma-100	188	16	the	the	DET
ma-100	188	17	w̄-nullcline	w̄-nullcline	PROPN
ma-100	188	18	−cd	−cd	NOUN
ma-100	188	19	>	>	X
ma-100	188	20	0.for	0.for	ADP
ma-100	188	21	−ab	−ab	PROPN
ma-100	188	22	>	>	X
ma-100	188	23	−c	−c	PROPN
ma-100	188	24	d	d	PROPN
ma-100	188	25	,	,	PUNCT
ma-100	188	26	the	the	DET
ma-100	188	27	equilibrium	equilibrium	NOUN
ma-100	188	28	point	point	NOUN
ma-100	188	29	is	be	AUX
ma-100	188	30	a	a	DET
ma-100	188	31	saddle	saddle	NOUN
ma-100	188	32	point	point	NOUN
ma-100	188	33	and	and	CCONJ
ma-100	188	34	unstable	unstable	ADJ
ma-100	188	35	because	because	SCONJ
ma-100	188	36	ad	ad	NOUN
ma-100	188	37	−	−	PROPN
ma-100	188	38	bc	bc	PROPN
ma-100	188	39	<	<	X
ma-100	188	40	0.however	0.however	PROPN
ma-100	188	41	,	,	PUNCT
ma-100	188	42	for	for	ADP
ma-100	188	43	−ab	−ab	PRON
ma-100	188	44	<	<	X
ma-100	188	45	−c	−c	PROPN
ma-100	188	46	d	d	PROPN
ma-100	188	47	and	and	CCONJ
ma-100	189	1	a	a	DET
ma-100	189	2	+	+	NOUN
ma-100	189	3	d	d	X
ma-100	189	4	<	<	X
ma-100	189	5	0	0	NUM
ma-100	189	6	,	,	PUNCT
ma-100	189	7	the	the	DET
ma-100	189	8	equilibrium	equilibrium	NOUN
ma-100	189	9	point	point	NOUN
ma-100	189	10	is	be	AUX
ma-100	189	11	stable	stable	ADJ
ma-100	189	12	and	and	CCONJ
ma-100	189	13	for	for	ADP
ma-100	189	14	−ab	−ab	PRON
ma-100	189	15	<	<	X
ma-100	189	16	−c	−c	PROPN
ma-100	189	17	d	d	PROPN
ma-100	189	18	and	and	CCONJ
ma-100	189	19	a+d	a+d	VERB
ma-100	189	20	>	>	X
ma-100	189	21	0	0	NUM
ma-100	189	22	,	,	PUNCT
ma-100	189	23	the	the	DET
ma-100	189	24	equilibrium	equilibrium	NOUN
ma-100	189	25	point	point	NOUN
ma-100	189	26	is	be	AUX
ma-100	189	27	unstable.finally	unstable.finally	PROPN
ma-100	189	28	,	,	PUNCT
ma-100	189	29	for	for	ADP
ma-100	189	30	the	the	DET
ma-100	189	31	case	case	NOUN
ma-100	189	32	that	that	SCONJ
ma-100	189	33	a	a	DET
ma-100	189	34	>	>	X
ma-100	189	35	0	0	PUNCT
ma-100	189	36	and	and	CCONJ
ma-100	189	37	the	the	DET
ma-100	189	38	speed	speed	NOUN
ma-100	189	39	of	of	ADP
ma-100	189	40	potassium	potassium	NOUN
ma-100	189	41	dynamics	dynamic	NOUN
ma-100	189	42	φ	φ	NOUN
ma-100	189	43	is	be	AUX
ma-100	189	44	small	small	ADJ
ma-100	189	45	,	,	PUNCT
ma-100	189	46	then	then	ADV
ma-100	189	47	the	the	DET
ma-100	189	48	equilibriumpoint	equilibriumpoint	NOUN
ma-100	189	49	is	be	AUX
ma-100	189	50	unstable	unstable	ADJ
ma-100	189	51	.	.	PUNCT
ma-100	190	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	190	2	eur	eur	PROPN
ma-100	190	3	.	.	PUNCT
ma-100	191	1	j.	j.	PROPN
ma-100	191	2	math	math	PROPN
ma-100	191	3	.	.	PUNCT
ma-100	192	1	anal	anal	PROPN
ma-100	192	2	.	.	PUNCT
ma-100	193	1	10.28924	10.28924	NUM
ma-100	193	2	/	/	SYM
ma-100	193	3	ada	ada	PROPN
ma-100	193	4	/	/	SYM
ma-100	193	5	ma.3.2	ma.3.2	PROPN
ma-100	193	6	94	94	NUM
ma-100	193	7	.	.	PUNCT
ma-100	194	1	numerical	numerical	ADJ
ma-100	194	2	results	result	NOUN
ma-100	194	3	in	in	ADP
ma-100	194	4	this	this	DET
ma-100	194	5	section	section	NOUN
ma-100	194	6	,	,	PUNCT
ma-100	194	7	we	we	PRON
ma-100	194	8	use	use	VERB
ma-100	194	9	some	some	DET
ma-100	194	10	numerical	numerical	ADJ
ma-100	194	11	simulations	simulation	NOUN
ma-100	194	12	to	to	PART
ma-100	194	13	study	study	VERB
ma-100	194	14	the	the	DET
ma-100	194	15	qualitative	qualitative	ADJ
ma-100	194	16	behavior	behavior	NOUN
ma-100	194	17	such	such	ADJ
ma-100	194	18	aslocal	aslocal	ADJ
ma-100	194	19	bifurcations	bifurcation	NOUN
ma-100	194	20	of	of	ADP
ma-100	194	21	the	the	DET
ma-100	194	22	fractional	fractional	ADJ
ma-100	194	23	order	order	NOUN
ma-100	194	24	morris	morris	ADJ
ma-100	194	25	-	-	PUNCT
ma-100	194	26	lecar	lecar	ADJ
ma-100	194	27	model	model	NOUN
ma-100	194	28	for	for	ADP
ma-100	194	29	different	different	ADJ
ma-100	194	30	fractional	fractional	ADJ
ma-100	194	31	order	order	NOUN
ma-100	194	32	η	η	PROPN
ma-100	194	33	andapplied	andapplie	VERB
ma-100	194	34	current	current	ADJ
ma-100	194	35	iapp	iapp	NOUN
ma-100	194	36	.	.	PUNCT
ma-100	195	1	one	one	NUM
ma-100	195	2	of	of	ADP
ma-100	195	3	the	the	DET
ma-100	195	4	most	most	ADV
ma-100	195	5	common	common	ADJ
ma-100	195	6	types	type	NOUN
ma-100	195	7	of	of	ADP
ma-100	195	8	bifurcation	bifurcation	NOUN
ma-100	195	9	in	in	ADP
ma-100	195	10	neuroscience	neuroscience	NOUN
ma-100	195	11	is	be	AUX
ma-100	195	12	saddle	saddle	ADJ
ma-100	195	13	nodebifurcation	nodebifurcation	NOUN
ma-100	195	14	of	of	ADP
ma-100	195	15	limit	limit	NOUN
ma-100	195	16	cycle	cycle	NOUN
ma-100	195	17	or	or	CCONJ
ma-100	195	18	snlc	snlc	NOUN
ma-100	195	19	,	,	PUNCT
ma-100	195	20	and	and	CCONJ
ma-100	195	21	this	this	DET
ma-100	195	22	bifurcation	bifurcation	NOUN
ma-100	195	23	occurs	occur	VERB
ma-100	195	24	when	when	SCONJ
ma-100	195	25	with	with	ADP
ma-100	195	26	increasing	increase	VERB
ma-100	195	27	the	the	DET
ma-100	195	28	controlparameter	controlparameter	NOUN
ma-100	195	29	,	,	PUNCT
ma-100	195	30	here	here	ADV
ma-100	195	31	,	,	PUNCT
ma-100	195	32	applied	apply	VERB
ma-100	195	33	current	current	ADJ
ma-100	195	34	iapp	iapp	NOUN
ma-100	195	35	,	,	PUNCT
ma-100	195	36	two	two	NUM
ma-100	195	37	stable	stable	ADJ
ma-100	195	38	and	and	CCONJ
ma-100	195	39	unstable	unstable	ADJ
ma-100	195	40	limit	limit	NOUN
ma-100	195	41	cycles	cycle	NOUN
ma-100	195	42	which	which	PRON
ma-100	195	43	are	be	AUX
ma-100	195	44	associated	associate	VERB
ma-100	195	45	tothe	tothe	PRON
ma-100	195	46	stable	stable	ADJ
ma-100	195	47	node	node	NOUN
ma-100	195	48	and	and	CCONJ
ma-100	195	49	saddle	saddle	NOUN
ma-100	195	50	point	point	NOUN
ma-100	195	51	respectively	respectively	ADV
ma-100	195	52	,	,	PUNCT
ma-100	195	53	close	close	ADJ
ma-100	195	54	to	to	ADP
ma-100	195	55	each	each	DET
ma-100	195	56	other	other	ADJ
ma-100	195	57	,	,	PUNCT
ma-100	195	58	collide	collide	NOUN
ma-100	195	59	and	and	CCONJ
ma-100	195	60	at	at	ADP
ma-100	195	61	the	the	DET
ma-100	195	62	bifurcationtime	bifurcationtime	NOUN
ma-100	195	63	,	,	PUNCT
ma-100	195	64	a	a	DET
ma-100	195	65	limit	limit	NOUN
ma-100	195	66	cycle	cycle	NOUN
ma-100	195	67	appears	appear	VERB
ma-100	195	68	.	.	PUNCT
ma-100	196	1	with	with	ADP
ma-100	196	2	increasing	increase	VERB
ma-100	196	3	iapp	iapp	NOUN
ma-100	196	4	further	far	ADV
ma-100	196	5	,	,	PUNCT
ma-100	196	6	this	this	DET
ma-100	196	7	limit	limit	NOUN
ma-100	196	8	cycle	cycle	NOUN
ma-100	196	9	disappears	disappear	VERB
ma-100	196	10	.	.	PUNCT
ma-100	197	1	figures(1)-(4	figures(1)-(4	X
ma-100	197	2	)	)	PUNCT
ma-100	197	3	exhibit	exhibit	VERB
ma-100	197	4	different	different	ADJ
ma-100	197	5	spiking	spike	VERB
ma-100	197	6	behaviors	behavior	NOUN
ma-100	197	7	for	for	ADP
ma-100	197	8	fractional	fractional	ADJ
ma-100	197	9	morris	morris	ADJ
ma-100	197	10	-	-	PUNCT
ma-100	197	11	lecar	lecar	ADJ
ma-100	197	12	model	model	NOUN
ma-100	197	13	(	(	PUNCT
ma-100	197	14	13	13	NUM
ma-100	197	15	)	)	PUNCT
ma-100	197	16	,	,	PUNCT
ma-100	197	17	when	when	SCONJ
ma-100	197	18	we	we	PRON
ma-100	197	19	increase	increase	VERB
ma-100	197	20	iapp	iapp	NOUN
ma-100	197	21	=	=	SYM
ma-100	197	22	5	5	NUM
ma-100	197	23	,	,	PUNCT
ma-100	197	24	30	30	NUM
ma-100	197	25	,	,	PUNCT
ma-100	197	26	45	45	NUM
ma-100	197	27	,	,	PUNCT
ma-100	197	28	100	100	NUM
ma-100	197	29	using	use	VERB
ma-100	197	30	snlc	snlc	PROPN
ma-100	197	31	parameters	parameter	NOUN
ma-100	197	32	value	value	VERB
ma-100	197	33	in	in	ADP
ma-100	197	34	table	table	NOUN
ma-100	197	35	(	(	PUNCT
ma-100	197	36	1	1	NUM
ma-100	197	37	)	)	PUNCT
ma-100	197	38	.	.	PUNCT
ma-100	198	1	the	the	DET
ma-100	198	2	solution	solution	NOUN
ma-100	198	3	of	of	ADP
ma-100	198	4	the	the	DET
ma-100	198	5	integer	integer	NOUN
ma-100	198	6	ordermodel	ordermodel	NOUN
ma-100	198	7	(	(	PUNCT
ma-100	198	8	6	6	NUM
ma-100	198	9	)	)	PUNCT
ma-100	198	10	has	have	AUX
ma-100	198	11	been	be	AUX
ma-100	198	12	demonstrated	demonstrate	VERB
ma-100	198	13	in	in	ADP
ma-100	198	14	the	the	DET
ma-100	198	15	third	third	ADJ
ma-100	198	16	row	row	NOUN
ma-100	198	17	to	to	PART
ma-100	198	18	compare	compare	VERB
ma-100	198	19	with	with	ADP
ma-100	198	20	fractional	fractional	ADJ
ma-100	198	21	-	-	PUNCT
ma-100	198	22	order	order	NOUN
ma-100	198	23	morris	morris	NOUN
ma-100	198	24	-	-	PUNCT
ma-100	198	25	lecarmodel	lecarmodel	NOUN
ma-100	198	26	of	of	ADP
ma-100	198	27	different	different	ADJ
ma-100	198	28	order	order	NOUN
ma-100	198	29	.	.	PUNCT
ma-100	199	1	for	for	ADP
ma-100	199	2	the	the	DET
ma-100	199	3	case	case	NOUN
ma-100	199	4	of	of	ADP
ma-100	199	5	hopf	hopf	ADJ
ma-100	199	6	bifurcation	bifurcation	NOUN
ma-100	199	7	in	in	ADP
ma-100	199	8	figures	figure	NOUN
ma-100	199	9	(	(	PUNCT
ma-100	199	10	5)-(9	5)-(9	NOUN
ma-100	199	11	)	)	PUNCT
ma-100	199	12	,	,	PUNCT
ma-100	199	13	with	with	ADP
ma-100	199	14	increasing	increase	VERB
ma-100	199	15	the	the	DET
ma-100	199	16	applied	applied	ADJ
ma-100	199	17	current	current	ADJ
ma-100	199	18	iapp	iapp	NOUN
ma-100	199	19	,	,	PUNCT
ma-100	199	20	themodel	themodel	NOUN
ma-100	199	21	(	(	PUNCT
ma-100	199	22	13	13	NUM
ma-100	199	23	)	)	PUNCT
ma-100	199	24	displays	display	VERB
ma-100	199	25	the	the	DET
ma-100	199	26	occurrence	occurrence	NOUN
ma-100	199	27	of	of	ADP
ma-100	199	28	limit	limit	NOUN
ma-100	199	29	cycle	cycle	NOUN
ma-100	199	30	corresponding	correspond	VERB
ma-100	199	31	to	to	ADP
ma-100	199	32	hopf	hopf	ADJ
ma-100	199	33	bifurcation	bifurcation	NOUN
ma-100	199	34	like	like	ADP
ma-100	199	35	the	the	DET
ma-100	199	36	originalmodel	originalmodel	NOUN
ma-100	199	37	(	(	PUNCT
ma-100	199	38	6	6	NUM
ma-100	199	39	)	)	PUNCT
ma-100	199	40	but	but	CCONJ
ma-100	199	41	for	for	ADP
ma-100	199	42	orders	order	NOUN
ma-100	199	43	η	η	X
ma-100	199	44	=	=	PROPN
ma-100	199	45	0.3	0.3	NUM
ma-100	199	46	,	,	PUNCT
ma-100	199	47	.0.5	.0.5	NUM
ma-100	199	48	,	,	PUNCT
ma-100	199	49	0.7	0.7	NUM
ma-100	199	50	,	,	PUNCT
ma-100	199	51	0.9	0.9	NUM
ma-100	199	52	the	the	DET
ma-100	199	53	fractional	fractional	ADJ
ma-100	199	54	order	order	NOUN
ma-100	199	55	model	model	NOUN
ma-100	199	56	needs	need	VERB
ma-100	199	57	greater	great	ADJ
ma-100	199	58	value	value	NOUN
ma-100	199	59	forinput	forinput	NOUN
ma-100	199	60	current	current	ADJ
ma-100	199	61	to	to	PART
ma-100	199	62	start	start	VERB
ma-100	199	63	the	the	DET
ma-100	199	64	bifurcation.the	bifurcation.the	DET
ma-100	199	65	topological	topological	ADJ
ma-100	199	66	normal	normal	ADJ
ma-100	199	67	form	form	NOUN
ma-100	199	68	of	of	ADP
ma-100	199	69	the	the	DET
ma-100	199	70	model	model	NOUN
ma-100	199	71	(	(	PUNCT
ma-100	199	72	13	13	NUM
ma-100	199	73	)	)	PUNCT
ma-100	199	74	in	in	ADP
ma-100	199	75	polar	polar	ADJ
ma-100	199	76	coordinate	coordinate	NOUN
ma-100	199	77	for	for	ADP
ma-100	199	78	the	the	DET
ma-100	199	79	case	case	NOUN
ma-100	199	80	of	of	ADP
ma-100	199	81	hopf	hopf	X
ma-100	199	82	bifurcationhas	bifurcationha	VERB
ma-100	199	83	the	the	DET
ma-100	199	84	form	form	NOUN
ma-100	199	85	:	:	PUNCT
ma-100	200	1			PUNCT
ma-100	200	2	∑k+1	∑k+1	ADP
ma-100	200	3	i=0	i=0	PROPN
ma-100	200	4	c	c	PROPN
ma-100	200	5	η	η	PROPN
ma-100	200	6	i	i	PRON
ma-100	200	7	rk+1−i	rk+1−i	VERB
ma-100	200	8	=	=	SYM
ma-100	200	9	αr	αr	PROPN
ma-100	200	10	+	+	CCONJ
ma-100	200	11	a	a	DET
ma-100	200	12	r3	r3	NOUN
ma-100	200	13	∑k+1	∑k+1	PUNCT
ma-100	200	14	i=0	i=0	PROPN
ma-100	200	15	c	c	PROPN
ma-100	200	16	η	η	PROPN
ma-100	200	17	i	i	PRON
ma-100	200	18	θk+1−i	θk+1−i	VERB
ma-100	200	19	=	=	SYM
ma-100	200	20	ω0	ω0	PROPN
ma-100	200	21	+	+	CCONJ
ma-100	200	22	βr2	βr2	PROPN
ma-100	200	23	(	(	PUNCT
ma-100	200	24	22	22	NUM
ma-100	200	25	)	)	PUNCT
ma-100	200	26	after	after	ADP
ma-100	200	27	simplification	simplification	NOUN
ma-100	200	28	,	,	PUNCT
ma-100	200	29	the	the	DET
ma-100	200	30	fractional	fractional	ADJ
ma-100	200	31	-	-	PUNCT
ma-100	200	32	order	order	NOUN
ma-100	200	33	system	system	NOUN
ma-100	200	34	which	which	PRON
ma-100	200	35	is	be	AUX
ma-100	200	36	linear	linear	ADJ
ma-100	200	37	and	and	CCONJ
ma-100	200	38	time	time	NOUN
ma-100	200	39	-	-	PUNCT
ma-100	200	40	invariant	invariant	ADJ
ma-100	200	41	has	have	VERB
ma-100	200	42	the	the	DET
ma-100	200	43	followingform	followingform	NOUN
ma-100	200	44	:	:	PUNCT
ma-100	200	45			NUM
ma-100	200	46	rk+1	rk+1	X
ma-100	200	47	=	=	SYM
ma-100	200	48	αr	αr	PROPN
ma-100	200	49	+	+	NUM
ma-100	200	50	a	a	DET
ma-100	200	51	r3	r3	NOUN
ma-100	200	52	−	−	NUM
ma-100	200	53	∑k+1	∑k+1	PUNCT
ma-100	200	54	i=1	i=1	PROPN
ma-100	200	55	c	c	PROPN
ma-100	200	56	η	η	PROPN
ma-100	200	57	i	i	PRON
ma-100	200	58	rk+1−i	rk+1−i	VERB
ma-100	200	59	cη0	cη0	VERB
ma-100	200	60	θk+1	θk+1	NOUN
ma-100	200	61	=	=	PUNCT
ma-100	200	62	ω0	ω0	X
ma-100	200	63	+	+	CCONJ
ma-100	201	1	βr2	βr2	NOUN
ma-100	202	1	−	−	NOUN
ma-100	202	2	∑k+1	∑k+1	PUNCT
ma-100	202	3	i=1	i=1	PROPN
ma-100	202	4	c	c	PROPN
ma-100	202	5	η	η	PROPN
ma-100	203	1	i	i	PRON
ma-100	203	2	θk+1−i	θk+1−i	AUX
ma-100	203	3	cη0	cη0	VERB
ma-100	203	4	(	(	PUNCT
ma-100	203	5	23	23	NUM
ma-100	203	6	)	)	PUNCT
ma-100	203	7	where	where	SCONJ
ma-100	203	8	,	,	PUNCT
ma-100	203	9	α	α	PROPN
ma-100	203	10	and	and	CCONJ
ma-100	203	11	ω0	ω0	PROPN
ma-100	203	12	represent	represent	VERB
ma-100	203	13	the	the	DET
ma-100	203	14	real	real	ADJ
ma-100	203	15	part	part	NOUN
ma-100	203	16	and	and	CCONJ
ma-100	203	17	imaginary	imaginary	ADJ
ma-100	203	18	part	part	NOUN
ma-100	203	19	of	of	ADP
ma-100	203	20	the	the	DET
ma-100	203	21	eigenvalues	eigenvalue	NOUN
ma-100	203	22	of	of	ADP
ma-100	203	23	the	the	DET
ma-100	203	24	jacobian	jacobian	ADJ
ma-100	203	25	matrixfor	matrixfor	PROPN
ma-100	203	26	the	the	DET
ma-100	203	27	model	model	NOUN
ma-100	203	28	(	(	PUNCT
ma-100	203	29	13	13	NUM
ma-100	203	30	)	)	PUNCT
ma-100	203	31	around	around	ADP
ma-100	203	32	its	its	PRON
ma-100	203	33	equilibrium	equilibrium	NOUN
ma-100	203	34	point	point	NOUN
ma-100	203	35	respectively	respectively	ADV
ma-100	203	36	,	,	PUNCT
ma-100	203	37	a	a	PRON
ma-100	203	38	is	be	AUX
ma-100	203	39	called	call	VERB
ma-100	203	40	first	first	ADJ
ma-100	203	41	lyapunov	lyapunov	NOUN
ma-100	203	42	coefficient.for	coefficient.for	PUNCT
ma-100	203	43	a	a	DET
ma-100	203	44	>	>	X
ma-100	203	45	0	0	NUM
ma-100	204	1	there	there	PRON
ma-100	204	2	should	should	AUX
ma-100	204	3	exist	exist	VERB
ma-100	204	4	an	an	DET
ma-100	204	5	unstable	unstable	ADJ
ma-100	204	6	limit	limit	NOUN
ma-100	204	7	cycle	cycle	NOUN
ma-100	204	8	,	,	PUNCT
ma-100	204	9	bifurcating	bifurcate	VERB
ma-100	204	10	from	from	ADP
ma-100	204	11	the	the	DET
ma-100	204	12	equilibrium	equilibrium	NOUN
ma-100	204	13	and	and	CCONJ
ma-100	204	14	it	it	PRON
ma-100	204	15	indicatesthe	indicatesthe	DET
ma-100	204	16	appearance	appearance	NOUN
ma-100	204	17	of	of	ADP
ma-100	204	18	subcritical	subcritical	ADJ
ma-100	204	19	hopf	hopf	ADJ
ma-100	204	20	bifurcation	bifurcation	NOUN
ma-100	204	21	and	and	CCONJ
ma-100	204	22	for	for	ADP
ma-100	204	23	a	a	DET
ma-100	204	24	<	<	X
ma-100	204	25	0	0	NUM
ma-100	204	26	we	we	PRON
ma-100	204	27	have	have	VERB
ma-100	204	28	stable	stable	ADJ
ma-100	204	29	limit	limit	NOUN
ma-100	204	30	cycle	cycle	NOUN
ma-100	204	31	solutionand	solutionand	VERB
ma-100	204	32	supercritical	supercritical	ADJ
ma-100	204	33	hopf	hopf	ADJ
ma-100	204	34	bifurcates	bifurcate	NOUN
ma-100	204	35	from	from	ADP
ma-100	204	36	the	the	DET
ma-100	204	37	equilibrium	equilibrium	NOUN
ma-100	204	38	.	.	PUNCT
ma-100	205	1	here	here	ADV
ma-100	205	2	,	,	PUNCT
ma-100	205	3	β	β	PROPN
ma-100	205	4	does	do	AUX
ma-100	205	5	not	not	PART
ma-100	205	6	have	have	VERB
ma-100	205	7	any	any	DET
ma-100	205	8	dynamical	dynamical	ADJ
ma-100	205	9	effect	effect	NOUN
ma-100	205	10	.	.	PUNCT
ma-100	206	1	θ	θ	NOUN
ma-100	206	2	represents	represent	VERB
ma-100	206	3	the	the	DET
ma-100	206	4	angle	angle	NOUN
ma-100	206	5	of	of	ADP
ma-100	206	6	oscillations	oscillation	NOUN
ma-100	206	7	.	.	PUNCT
ma-100	207	1	if	if	SCONJ
ma-100	207	2	θ̇	θ̇	DET
ma-100	207	3	>	>	X
ma-100	207	4	0	0	NUM
ma-100	207	5	,	,	PUNCT
ma-100	207	6	it	it	PRON
ma-100	207	7	means	mean	VERB
ma-100	207	8	the	the	DET
ma-100	207	9	frequency	frequency	NOUN
ma-100	207	10	of	of	ADP
ma-100	207	11	damped	damped	NOUN
ma-100	207	12	or	or	CCONJ
ma-100	207	13	sustained	sustain	VERB
ma-100	207	14	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	207	15	eur	eur	NOUN
ma-100	207	16	.	.	PUNCT
ma-100	208	1	j.	j.	PROPN
ma-100	208	2	math	math	PROPN
ma-100	208	3	.	.	PUNCT
ma-100	209	1	anal	anal	PROPN
ma-100	209	2	.	.	PUNCT
ma-100	210	1	10.28924	10.28924	NUM
ma-100	210	2	/	/	SYM
ma-100	210	3	ada	ada	PROPN
ma-100	210	4	/	/	SYM
ma-100	210	5	ma.3.2	ma.3.2	PROPN
ma-100	210	6	10	10	NUM
ma-100	210	7	figure	figure	NOUN
ma-100	210	8	1	1	NUM
ma-100	210	9	.	.	PUNCT
ma-100	210	10	occurrence	occurrence	NOUN
ma-100	210	11	of	of	ADP
ma-100	210	12	saddle	saddle	ADJ
ma-100	210	13	node	node	ADJ
ma-100	210	14	bifurcation	bifurcation	NOUN
ma-100	210	15	of	of	ADP
ma-100	210	16	limit	limit	NOUN
ma-100	210	17	cycle	cycle	NOUN
ma-100	210	18	or	or	CCONJ
ma-100	210	19	snlc	snlc	PROPN
ma-100	210	20	in	in	ADP
ma-100	210	21	fractionalmorris	fractionalmorris	NOUN
ma-100	210	22	-	-	PUNCT
ma-100	210	23	lecar	lecar	NOUN
ma-100	210	24	model	model	NOUN
ma-100	210	25	(	(	PUNCT
ma-100	210	26	13	13	NUM
ma-100	210	27	)	)	PUNCT
ma-100	210	28	for	for	ADP
ma-100	210	29	iapp	iapp	NOUN
ma-100	210	30	=	=	SYM
ma-100	210	31	5	5	NUM
ma-100	210	32	,	,	PUNCT
ma-100	210	33	third	third	ADJ
ma-100	210	34	row	row	NOUN
ma-100	210	35	displays	display	VERB
ma-100	210	36	the	the	DET
ma-100	210	37	trajectory	trajectory	NOUN
ma-100	210	38	of	of	ADP
ma-100	210	39	the	the	DET
ma-100	210	40	originalmodel	originalmodel	NOUN
ma-100	210	41	(	(	PUNCT
ma-100	210	42	6	6	NUM
ma-100	210	43	)	)	PUNCT
ma-100	210	44	with	with	ADP
ma-100	210	45	the	the	DET
ma-100	210	46	same	same	ADJ
ma-100	210	47	applied	apply	VERB
ma-100	210	48	current	current	NOUN
ma-100	210	49	.	.	PUNCT
ma-100	211	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	211	2	eur	eur	PROPN
ma-100	211	3	.	.	PUNCT
ma-100	212	1	j.	j.	PROPN
ma-100	212	2	math	math	PROPN
ma-100	212	3	.	.	PUNCT
ma-100	213	1	anal	anal	PROPN
ma-100	213	2	.	.	PUNCT
ma-100	214	1	10.28924	10.28924	NUM
ma-100	214	2	/	/	SYM
ma-100	214	3	ada	ada	PROPN
ma-100	214	4	/	/	SYM
ma-100	214	5	ma.3.2	ma.3.2	PROPN
ma-100	214	6	11	11	NUM
ma-100	214	7	figure	figure	NOUN
ma-100	214	8	2	2	NUM
ma-100	214	9	.	.	PUNCT
ma-100	214	10	occurrence	occurrence	NOUN
ma-100	214	11	of	of	ADP
ma-100	214	12	saddle	saddle	ADJ
ma-100	214	13	node	node	ADJ
ma-100	214	14	bifurcation	bifurcation	NOUN
ma-100	214	15	of	of	ADP
ma-100	214	16	limit	limit	NOUN
ma-100	214	17	cycle	cycle	NOUN
ma-100	214	18	or	or	CCONJ
ma-100	214	19	snlc	snlc	PROPN
ma-100	214	20	in	in	ADP
ma-100	214	21	fractionalmorris	fractionalmorris	NOUN
ma-100	214	22	-	-	PUNCT
ma-100	214	23	lecar	lecar	NOUN
ma-100	214	24	model	model	NOUN
ma-100	214	25	(	(	PUNCT
ma-100	214	26	13	13	NUM
ma-100	214	27	)	)	PUNCT
ma-100	214	28	for	for	ADP
ma-100	214	29	iapp	iapp	NOUN
ma-100	214	30	=	=	SYM
ma-100	214	31	30	30	NUM
ma-100	214	32	,	,	PUNCT
ma-100	214	33	third	third	ADJ
ma-100	214	34	row	row	NOUN
ma-100	214	35	displays	display	VERB
ma-100	214	36	the	the	DET
ma-100	214	37	trajectory	trajectory	NOUN
ma-100	214	38	of	of	ADP
ma-100	214	39	theoriginal	theoriginal	ADJ
ma-100	214	40	model	model	NOUN
ma-100	214	41	(	(	PUNCT
ma-100	214	42	6	6	NUM
ma-100	214	43	)	)	PUNCT
ma-100	214	44	with	with	ADP
ma-100	214	45	the	the	DET
ma-100	214	46	same	same	ADJ
ma-100	214	47	applied	apply	VERB
ma-100	214	48	current	current	NOUN
ma-100	214	49	.	.	PUNCT
ma-100	215	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	215	2	eur	eur	PROPN
ma-100	215	3	.	.	PUNCT
ma-100	216	1	j.	j.	PROPN
ma-100	216	2	math	math	PROPN
ma-100	216	3	.	.	PUNCT
ma-100	217	1	anal	anal	PROPN
ma-100	217	2	.	.	PUNCT
ma-100	218	1	10.28924	10.28924	NUM
ma-100	218	2	/	/	SYM
ma-100	218	3	ada	ada	PROPN
ma-100	218	4	/	/	SYM
ma-100	218	5	ma.3.2	ma.3.2	PROPN
ma-100	218	6	12	12	NUM
ma-100	218	7	figure	figure	NOUN
ma-100	218	8	3	3	NUM
ma-100	218	9	.	.	PUNCT
ma-100	218	10	occurrence	occurrence	NOUN
ma-100	218	11	of	of	ADP
ma-100	218	12	saddle	saddle	ADJ
ma-100	218	13	node	node	ADJ
ma-100	218	14	bifurcation	bifurcation	NOUN
ma-100	218	15	of	of	ADP
ma-100	218	16	limit	limit	NOUN
ma-100	218	17	cycle	cycle	NOUN
ma-100	218	18	or	or	CCONJ
ma-100	218	19	snlc	snlc	PROPN
ma-100	218	20	in	in	ADP
ma-100	218	21	fractionalmorris	fractionalmorris	NOUN
ma-100	218	22	-	-	PUNCT
ma-100	218	23	lecar	lecar	NOUN
ma-100	218	24	model	model	NOUN
ma-100	218	25	(	(	PUNCT
ma-100	218	26	13	13	NUM
ma-100	218	27	)	)	PUNCT
ma-100	218	28	for	for	ADP
ma-100	218	29	iapp	iapp	NOUN
ma-100	218	30	=	=	SYM
ma-100	218	31	45	45	NUM
ma-100	218	32	,	,	PUNCT
ma-100	218	33	third	third	ADJ
ma-100	218	34	row	row	NOUN
ma-100	218	35	displays	display	VERB
ma-100	218	36	the	the	DET
ma-100	218	37	trajectory	trajectory	NOUN
ma-100	218	38	of	of	ADP
ma-100	218	39	theoriginal	theoriginal	ADJ
ma-100	218	40	model	model	NOUN
ma-100	218	41	(	(	PUNCT
ma-100	218	42	6	6	NUM
ma-100	218	43	)	)	PUNCT
ma-100	218	44	with	with	ADP
ma-100	218	45	the	the	DET
ma-100	218	46	same	same	ADJ
ma-100	218	47	applied	apply	VERB
ma-100	218	48	current	current	NOUN
ma-100	218	49	.	.	PUNCT
ma-100	219	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	219	2	eur	eur	PROPN
ma-100	219	3	.	.	PUNCT
ma-100	220	1	j.	j.	PROPN
ma-100	220	2	math	math	PROPN
ma-100	220	3	.	.	PUNCT
ma-100	221	1	anal	anal	PROPN
ma-100	221	2	.	.	PUNCT
ma-100	222	1	10.28924	10.28924	NUM
ma-100	222	2	/	/	SYM
ma-100	222	3	ada	ada	PROPN
ma-100	222	4	/	/	SYM
ma-100	222	5	ma.3.2	ma.3.2	PROPN
ma-100	222	6	13	13	NUM
ma-100	222	7	figure	figure	NOUN
ma-100	222	8	4	4	NUM
ma-100	222	9	.	.	PUNCT
ma-100	222	10	occurrence	occurrence	NOUN
ma-100	222	11	of	of	ADP
ma-100	222	12	saddle	saddle	ADJ
ma-100	222	13	node	node	ADJ
ma-100	222	14	bifurcation	bifurcation	NOUN
ma-100	222	15	of	of	ADP
ma-100	222	16	limit	limit	NOUN
ma-100	222	17	cycle	cycle	NOUN
ma-100	222	18	or	or	CCONJ
ma-100	222	19	snlc	snlc	PROPN
ma-100	222	20	in	in	ADP
ma-100	222	21	fractionalmorris	fractionalmorris	NOUN
ma-100	222	22	-	-	PUNCT
ma-100	222	23	lecar	lecar	NOUN
ma-100	222	24	model	model	NOUN
ma-100	222	25	(	(	PUNCT
ma-100	222	26	13	13	NUM
ma-100	222	27	)	)	PUNCT
ma-100	222	28	for	for	ADP
ma-100	222	29	iapp	iapp	NOUN
ma-100	222	30	=	=	SYM
ma-100	222	31	100	100	NUM
ma-100	222	32	,	,	PUNCT
ma-100	222	33	third	third	ADJ
ma-100	222	34	row	row	NOUN
ma-100	222	35	displays	display	VERB
ma-100	222	36	the	the	DET
ma-100	222	37	trajectory	trajectory	NOUN
ma-100	222	38	of	of	ADP
ma-100	222	39	theoriginal	theoriginal	ADJ
ma-100	222	40	model	model	NOUN
ma-100	222	41	(	(	PUNCT
ma-100	222	42	6	6	NUM
ma-100	222	43	)	)	PUNCT
ma-100	222	44	with	with	ADP
ma-100	222	45	the	the	DET
ma-100	222	46	same	same	ADJ
ma-100	222	47	applied	apply	VERB
ma-100	222	48	current	current	NOUN
ma-100	222	49	.	.	PUNCT
ma-100	223	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	223	2	eur	eur	PROPN
ma-100	223	3	.	.	PUNCT
ma-100	224	1	j.	j.	PROPN
ma-100	224	2	math	math	PROPN
ma-100	224	3	.	.	PUNCT
ma-100	225	1	anal	anal	PROPN
ma-100	225	2	.	.	PUNCT
ma-100	226	1	10.28924	10.28924	NUM
ma-100	226	2	/	/	SYM
ma-100	226	3	ada	ada	PROPN
ma-100	226	4	/	/	SYM
ma-100	226	5	ma.3.2	ma.3.2	PROPN
ma-100	226	6	14	14	NUM
ma-100	226	7	figure	figure	NOUN
ma-100	226	8	5	5	NUM
ma-100	226	9	.	.	PUNCT
ma-100	226	10	occurrence	occurrence	NOUN
ma-100	226	11	of	of	ADP
ma-100	226	12	hopf	hopf	ADJ
ma-100	226	13	bifurcation	bifurcation	NOUN
ma-100	226	14	in	in	ADP
ma-100	226	15	fractional	fractional	ADJ
ma-100	226	16	morris	morris	PROPN
ma-100	226	17	-	-	PUNCT
ma-100	226	18	lecar	lecar	ADJ
ma-100	226	19	model	model	NOUN
ma-100	226	20	(	(	PUNCT
ma-100	226	21	13	13	NUM
ma-100	226	22	)	)	PUNCT
ma-100	226	23	for	for	ADP
ma-100	226	24	iapp	iapp	NOUN
ma-100	226	25	=	=	SYM
ma-100	226	26	20	20	NUM
ma-100	226	27	,	,	PUNCT
ma-100	226	28	third	third	ADJ
ma-100	226	29	row	row	NOUN
ma-100	226	30	displays	display	VERB
ma-100	226	31	the	the	DET
ma-100	226	32	trajectory	trajectory	NOUN
ma-100	226	33	of	of	ADP
ma-100	226	34	the	the	DET
ma-100	226	35	original	original	ADJ
ma-100	226	36	model	model	NOUN
ma-100	226	37	(	(	PUNCT
ma-100	226	38	6	6	NUM
ma-100	226	39	)	)	PUNCT
ma-100	226	40	with	with	ADP
ma-100	226	41	the	the	DET
ma-100	226	42	sameapplied	sameapplied	ADJ
ma-100	226	43	current	current	NOUN
ma-100	226	44	.	.	PUNCT
ma-100	227	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	227	2	eur	eur	PROPN
ma-100	227	3	.	.	PUNCT
ma-100	228	1	j.	j.	PROPN
ma-100	228	2	math	math	PROPN
ma-100	228	3	.	.	PUNCT
ma-100	229	1	anal	anal	PROPN
ma-100	229	2	.	.	PUNCT
ma-100	230	1	10.28924	10.28924	NUM
ma-100	230	2	/	/	SYM
ma-100	230	3	ada	ada	PROPN
ma-100	230	4	/	/	SYM
ma-100	230	5	ma.3.2	ma.3.2	PROPN
ma-100	230	6	15	15	NUM
ma-100	230	7	figure	figure	NOUN
ma-100	230	8	6	6	NUM
ma-100	230	9	.	.	PUNCT
ma-100	231	1	occurrence	occurrence	NOUN
ma-100	231	2	of	of	ADP
ma-100	231	3	hopf	hopf	ADJ
ma-100	231	4	bifurcation	bifurcation	NOUN
ma-100	231	5	in	in	ADP
ma-100	231	6	fractional	fractional	ADJ
ma-100	231	7	morris	morris	PROPN
ma-100	231	8	-	-	PUNCT
ma-100	231	9	lecar	lecar	ADJ
ma-100	231	10	model	model	NOUN
ma-100	231	11	(	(	PUNCT
ma-100	231	12	13	13	NUM
ma-100	231	13	)	)	PUNCT
ma-100	231	14	for	for	ADP
ma-100	231	15	iapp	iapp	NOUN
ma-100	231	16	=	=	SYM
ma-100	231	17	88	88	NUM
ma-100	231	18	,	,	PUNCT
ma-100	231	19	third	third	ADJ
ma-100	231	20	row	row	NOUN
ma-100	231	21	displays	display	VERB
ma-100	231	22	the	the	DET
ma-100	231	23	trajectory	trajectory	NOUN
ma-100	231	24	of	of	ADP
ma-100	231	25	the	the	DET
ma-100	231	26	original	original	ADJ
ma-100	231	27	model	model	NOUN
ma-100	231	28	(	(	PUNCT
ma-100	231	29	6	6	NUM
ma-100	231	30	)	)	PUNCT
ma-100	231	31	with	with	ADP
ma-100	231	32	the	the	DET
ma-100	231	33	sameapplied	sameapplied	ADJ
ma-100	231	34	current	current	NOUN
ma-100	231	35	.	.	PUNCT
ma-100	232	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	232	2	eur	eur	PROPN
ma-100	232	3	.	.	PUNCT
ma-100	233	1	j.	j.	PROPN
ma-100	233	2	math	math	PROPN
ma-100	233	3	.	.	PUNCT
ma-100	234	1	anal	anal	PROPN
ma-100	234	2	.	.	PUNCT
ma-100	235	1	10.28924	10.28924	NUM
ma-100	235	2	/	/	SYM
ma-100	235	3	ada	ada	PROPN
ma-100	235	4	/	/	SYM
ma-100	235	5	ma.3.2	ma.3.2	PROPN
ma-100	235	6	16	16	NUM
ma-100	235	7	figure	figure	NOUN
ma-100	235	8	7	7	NUM
ma-100	235	9	.	.	PUNCT
ma-100	235	10	occurrence	occurrence	NOUN
ma-100	235	11	of	of	ADP
ma-100	235	12	hopf	hopf	ADJ
ma-100	235	13	bifurcation	bifurcation	NOUN
ma-100	235	14	in	in	ADP
ma-100	235	15	fractional	fractional	ADJ
ma-100	235	16	morris	morris	PROPN
ma-100	235	17	-	-	PUNCT
ma-100	235	18	lecar	lecar	ADJ
ma-100	235	19	model	model	NOUN
ma-100	235	20	(	(	PUNCT
ma-100	235	21	13	13	NUM
ma-100	235	22	)	)	PUNCT
ma-100	235	23	for	for	ADP
ma-100	235	24	iapp	iapp	NOUN
ma-100	235	25	=	=	SYM
ma-100	235	26	90	90	NUM
ma-100	235	27	,	,	PUNCT
ma-100	235	28	third	third	ADJ
ma-100	235	29	row	row	NOUN
ma-100	235	30	displays	display	VERB
ma-100	235	31	the	the	DET
ma-100	235	32	trajectory	trajectory	NOUN
ma-100	235	33	of	of	ADP
ma-100	235	34	the	the	DET
ma-100	235	35	original	original	ADJ
ma-100	235	36	model	model	NOUN
ma-100	235	37	(	(	PUNCT
ma-100	235	38	6	6	NUM
ma-100	235	39	)	)	PUNCT
ma-100	235	40	with	with	ADP
ma-100	235	41	the	the	DET
ma-100	235	42	sameapplied	sameapplied	ADJ
ma-100	235	43	current	current	NOUN
ma-100	235	44	.	.	PUNCT
ma-100	236	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	236	2	eur	eur	PROPN
ma-100	236	3	.	.	PUNCT
ma-100	237	1	j.	j.	PROPN
ma-100	237	2	math	math	PROPN
ma-100	237	3	.	.	PUNCT
ma-100	238	1	anal	anal	PROPN
ma-100	238	2	.	.	PUNCT
ma-100	239	1	10.28924	10.28924	NUM
ma-100	239	2	/	/	SYM
ma-100	239	3	ada	ada	PROPN
ma-100	239	4	/	/	SYM
ma-100	239	5	ma.3.2	ma.3.2	PROPN
ma-100	239	6	17	17	NUM
ma-100	239	7	figure	figure	NOUN
ma-100	239	8	8	8	NUM
ma-100	239	9	.	.	PUNCT
ma-100	239	10	occurrence	occurrence	NOUN
ma-100	239	11	of	of	ADP
ma-100	239	12	hopf	hopf	ADJ
ma-100	239	13	bifurcation	bifurcation	NOUN
ma-100	239	14	in	in	ADP
ma-100	239	15	fractional	fractional	ADJ
ma-100	239	16	morris	morris	PROPN
ma-100	239	17	-	-	PUNCT
ma-100	239	18	lecar	lecar	ADJ
ma-100	239	19	model	model	NOUN
ma-100	239	20	(	(	PUNCT
ma-100	239	21	13	13	NUM
ma-100	239	22	)	)	PUNCT
ma-100	239	23	for	for	ADP
ma-100	239	24	iapp	iapp	NOUN
ma-100	239	25	=	=	SYM
ma-100	239	26	95	95	NUM
ma-100	239	27	,	,	PUNCT
ma-100	239	28	third	third	ADJ
ma-100	239	29	row	row	NOUN
ma-100	239	30	displays	display	VERB
ma-100	239	31	the	the	DET
ma-100	239	32	trajectory	trajectory	NOUN
ma-100	239	33	of	of	ADP
ma-100	239	34	the	the	DET
ma-100	239	35	original	original	ADJ
ma-100	239	36	model	model	NOUN
ma-100	239	37	(	(	PUNCT
ma-100	239	38	6	6	NUM
ma-100	239	39	)	)	PUNCT
ma-100	239	40	with	with	ADP
ma-100	239	41	the	the	DET
ma-100	239	42	sameapplied	sameapplied	ADJ
ma-100	239	43	current	current	NOUN
ma-100	239	44	.	.	PUNCT
ma-100	240	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	240	2	eur	eur	PROPN
ma-100	240	3	.	.	PUNCT
ma-100	241	1	j.	j.	PROPN
ma-100	241	2	math	math	PROPN
ma-100	241	3	.	.	PUNCT
ma-100	242	1	anal	anal	PROPN
ma-100	242	2	.	.	PUNCT
ma-100	243	1	10.28924	10.28924	NUM
ma-100	243	2	/	/	SYM
ma-100	243	3	ada	ada	PROPN
ma-100	243	4	/	/	SYM
ma-100	243	5	ma.3.2	ma.3.2	PROPN
ma-100	243	6	18	18	NUM
ma-100	243	7	figure	figure	NOUN
ma-100	243	8	9	9	NUM
ma-100	243	9	.	.	PUNCT
ma-100	243	10	occurrence	occurrence	NOUN
ma-100	243	11	of	of	ADP
ma-100	243	12	hopf	hopf	ADJ
ma-100	243	13	bifurcation	bifurcation	NOUN
ma-100	243	14	in	in	ADP
ma-100	243	15	fractional	fractional	ADJ
ma-100	243	16	morris	morris	PROPN
ma-100	243	17	-	-	PUNCT
ma-100	243	18	lecar	lecar	ADJ
ma-100	243	19	model	model	NOUN
ma-100	243	20	(	(	PUNCT
ma-100	243	21	13	13	NUM
ma-100	243	22	)	)	PUNCT
ma-100	243	23	for	for	ADP
ma-100	243	24	iapp	iapp	NOUN
ma-100	243	25	=	=	SYM
ma-100	243	26	220	220	NUM
ma-100	243	27	,	,	PUNCT
ma-100	243	28	third	third	ADJ
ma-100	243	29	row	row	NOUN
ma-100	243	30	displays	display	VERB
ma-100	243	31	the	the	DET
ma-100	243	32	trajectory	trajectory	NOUN
ma-100	243	33	of	of	ADP
ma-100	243	34	the	the	DET
ma-100	243	35	original	original	ADJ
ma-100	243	36	model	model	NOUN
ma-100	243	37	(	(	PUNCT
ma-100	243	38	6	6	NUM
ma-100	243	39	)	)	PUNCT
ma-100	243	40	with	with	ADP
ma-100	243	41	the	the	DET
ma-100	243	42	sameapplied	sameapplied	ADJ
ma-100	243	43	current	current	NOUN
ma-100	243	44	.	.	PUNCT
ma-100	244	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	244	2	eur	eur	PROPN
ma-100	244	3	.	.	PUNCT
ma-100	245	1	j.	j.	PROPN
ma-100	245	2	math	math	PROPN
ma-100	245	3	.	.	PUNCT
ma-100	246	1	anal	anal	PROPN
ma-100	246	2	.	.	PUNCT
ma-100	247	1	10.28924	10.28924	NUM
ma-100	247	2	/	/	SYM
ma-100	247	3	ada	ada	PROPN
ma-100	247	4	/	/	SYM
ma-100	247	5	ma.3.2	ma.3.2	PROPN
ma-100	247	6	19oscillations	19oscillation	NOUN
ma-100	247	7	around	around	ADP
ma-100	247	8	ω0	ω0	PROPN
ma-100	247	9	is	be	AUX
ma-100	247	10	increasing	increase	VERB
ma-100	247	11	.	.	PUNCT
ma-100	248	1	on	on	ADP
ma-100	248	2	the	the	DET
ma-100	248	3	other	other	ADJ
ma-100	248	4	hand	hand	NOUN
ma-100	248	5	,	,	PUNCT
ma-100	248	6	for	for	ADP
ma-100	248	7	θ̇	θ̇	PRON
ma-100	248	8	<	<	X
ma-100	248	9	0	0	PUNCT
ma-100	248	10	the	the	DET
ma-100	248	11	frequency	frequency	NOUN
ma-100	248	12	of	of	ADP
ma-100	248	13	damped	damped	ADJ
ma-100	248	14	orsustained	orsustaine	VERB
ma-100	248	15	oscillations	oscillation	NOUN
ma-100	248	16	around	around	ADP
ma-100	248	17	ω0	ω0	PROPN
ma-100	248	18	is	be	AUX
ma-100	248	19	decreasing.in	decreasing.in	PROPN
ma-100	248	20	neuroscience	neuroscience	NOUN
ma-100	248	21	point	point	NOUN
ma-100	248	22	of	of	ADP
ma-100	248	23	view	view	NOUN
ma-100	248	24	,	,	PUNCT
ma-100	248	25	the	the	DET
ma-100	248	26	hopf	hopf	ADJ
ma-100	248	27	bifurcation	bifurcation	NOUN
ma-100	248	28	happens	happen	VERB
ma-100	248	29	when	when	SCONJ
ma-100	248	30	the	the	DET
ma-100	248	31	behaviors	behavior	NOUN
ma-100	248	32	of	of	ADP
ma-100	248	33	neuron	neuron	PROPN
ma-100	248	34	changefrom	changefrom	PROPN
ma-100	248	35	resting	rest	VERB
ma-100	248	36	to	to	ADP
ma-100	248	37	spiking	spike	VERB
ma-100	248	38	(	(	PUNCT
ma-100	248	39	the	the	DET
ma-100	248	40	stable	stable	ADJ
ma-100	248	41	constant	constant	ADJ
ma-100	248	42	solutions	solution	NOUN
ma-100	248	43	are	be	AUX
ma-100	248	44	corresponding	correspond	VERB
ma-100	248	45	to	to	ADP
ma-100	248	46	the	the	DET
ma-100	248	47	resting	rest	VERB
ma-100	248	48	state	state	NOUN
ma-100	248	49	andspiking	andspike	VERB
ma-100	248	50	state	state	NOUN
ma-100	248	51	shows	show	VERB
ma-100	248	52	the	the	DET
ma-100	248	53	existence	existence	NOUN
ma-100	248	54	of	of	ADP
ma-100	248	55	periodic	periodic	ADJ
ma-100	248	56	solutions).the	solutions).the	DET
ma-100	248	57	other	other	ADJ
ma-100	248	58	common	common	ADJ
ma-100	248	59	type	type	NOUN
ma-100	248	60	of	of	ADP
ma-100	248	61	dynamical	dynamical	ADJ
ma-100	248	62	behavior	behavior	NOUN
ma-100	248	63	for	for	ADP
ma-100	248	64	a	a	DET
ma-100	248	65	neuron	neuron	NOUN
ma-100	248	66	cell	cell	NOUN
ma-100	248	67	occurs	occur	VERB
ma-100	248	68	when	when	SCONJ
ma-100	248	69	with	with	ADP
ma-100	248	70	increasing	increase	VERB
ma-100	248	71	thecontrol	thecontrol	NOUN
ma-100	248	72	parameter	parameter	NOUN
ma-100	248	73	,	,	PUNCT
ma-100	248	74	a	a	DET
ma-100	248	75	saddle	saddle	NOUN
ma-100	248	76	point	point	NOUN
ma-100	248	77	and	and	CCONJ
ma-100	248	78	a	a	DET
ma-100	248	79	limit	limit	NOUN
ma-100	248	80	cycle	cycle	NOUN
ma-100	248	81	collide	collide	NOUN
ma-100	248	82	,	,	PUNCT
ma-100	248	83	this	this	DET
ma-100	248	84	bifurcation	bifurcation	NOUN
ma-100	248	85	called	call	VERB
ma-100	248	86	saddle	saddle	NOUN
ma-100	248	87	-	-	PUNCT
ma-100	248	88	homoclinicbifurcation	homoclinicbifurcation	NOUN
ma-100	248	89	.	.	PUNCT
ma-100	249	1	the	the	DET
ma-100	249	2	period	period	NOUN
ma-100	249	3	of	of	ADP
ma-100	249	4	the	the	DET
ma-100	249	5	periodic	periodic	ADJ
ma-100	249	6	orbit	orbit	NOUN
ma-100	249	7	that	that	PRON
ma-100	249	8	appears	appear	VERB
ma-100	249	9	at	at	ADP
ma-100	249	10	the	the	DET
ma-100	249	11	moment	moment	NOUN
ma-100	249	12	of	of	ADP
ma-100	249	13	bifurcation	bifurcation	NOUN
ma-100	249	14	goes	go	VERB
ma-100	249	15	to	to	ADP
ma-100	249	16	infinityand	infinityand	NOUN
ma-100	249	17	with	with	ADP
ma-100	249	18	further	further	ADJ
ma-100	249	19	increasing	increase	VERB
ma-100	249	20	of	of	ADP
ma-100	249	21	control	control	NOUN
ma-100	249	22	parameter	parameter	NOUN
ma-100	249	23	this	this	DET
ma-100	249	24	periodic	periodic	ADJ
ma-100	249	25	orbit	orbit	NOUN
ma-100	249	26	disappears	disappear	VERB
ma-100	249	27	.	.	PUNCT
ma-100	250	1	figures	figure	NOUN
ma-100	250	2	(	(	PUNCT
ma-100	250	3	10)-(14),demonstrate	10)-(14),demonstrate	NUM
ma-100	250	4	the	the	DET
ma-100	250	5	appearance	appearance	NOUN
ma-100	250	6	and	and	CCONJ
ma-100	250	7	disappearance	disappearance	NOUN
ma-100	250	8	of	of	ADP
ma-100	250	9	saddle	saddle	NOUN
ma-100	250	10	-	-	PUNCT
ma-100	250	11	homoclinic	homoclinic	NOUN
ma-100	250	12	bifurcation	bifurcation	NOUN
ma-100	250	13	in	in	ADP
ma-100	250	14	the	the	DET
ma-100	250	15	model	model	NOUN
ma-100	250	16	(	(	PUNCT
ma-100	250	17	13)with	13)with	NUM
ma-100	250	18	increasing	increase	VERB
ma-100	250	19	the	the	DET
ma-100	250	20	applied	applied	ADJ
ma-100	250	21	current	current	ADJ
ma-100	250	22	iapp	iapp	NOUN
ma-100	250	23	=	=	SYM
ma-100	250	24	23	23	NUM
ma-100	250	25	,	,	PUNCT
ma-100	250	26	40	40	NUM
ma-100	250	27	,	,	PUNCT
ma-100	250	28	50	50	NUM
ma-100	250	29	,	,	PUNCT
ma-100	250	30	60	60	NUM
ma-100	250	31	,	,	PUNCT
ma-100	250	32	70	70	NUM
ma-100	250	33	like	like	ADP
ma-100	250	34	the	the	DET
ma-100	250	35	original	original	ADJ
ma-100	250	36	model	model	NOUN
ma-100	250	37	(	(	PUNCT
ma-100	250	38	6	6	NUM
ma-100	250	39	)	)	PUNCT
ma-100	250	40	but	but	CCONJ
ma-100	250	41	liketwo	liketwo	NOUN
ma-100	250	42	previous	previous	ADJ
ma-100	250	43	bifurcations	bifurcation	NOUN
ma-100	250	44	,	,	PUNCT
ma-100	250	45	for	for	ADP
ma-100	250	46	fractional	fractional	ADJ
ma-100	250	47	order	order	NOUN
ma-100	250	48	model	model	NOUN
ma-100	250	49	of	of	ADP
ma-100	250	50	orders	order	NOUN
ma-100	250	51	η	η	PROPN
ma-100	250	52	=	=	PROPN
ma-100	250	53	0.3	0.3	NUM
ma-100	250	54	,	,	PUNCT
ma-100	250	55	.0.5	.0.5	NUM
ma-100	250	56	,	,	PUNCT
ma-100	250	57	0.7	0.7	NUM
ma-100	250	58	,	,	PUNCT
ma-100	250	59	0.9	0.9	NUM
ma-100	250	60	the	the	DET
ma-100	250	61	neuronneeds	neuronneed	NOUN
ma-100	250	62	higher	high	ADJ
ma-100	250	63	input	input	NOUN
ma-100	250	64	current	current	ADJ
ma-100	250	65	iapp	iapp	NOUN
ma-100	250	66	to	to	PART
ma-100	250	67	bifurcate.in	bifurcate.in	VERB
ma-100	250	68	neuroscience	neuroscience	NOUN
ma-100	250	69	point	point	NOUN
ma-100	250	70	of	of	ADP
ma-100	250	71	view	view	NOUN
ma-100	250	72	,	,	PUNCT
ma-100	250	73	when	when	SCONJ
ma-100	250	74	saddle	saddle	ADJ
ma-100	250	75	homoclinic	homoclinic	ADJ
ma-100	250	76	bifurcation	bifurcation	NOUN
ma-100	250	77	happens	happen	VERB
ma-100	250	78	,	,	PUNCT
ma-100	250	79	we	we	PRON
ma-100	250	80	expect	expect	VERB
ma-100	250	81	theappearance	theappearance	NOUN
ma-100	250	82	or	or	CCONJ
ma-100	250	83	disappearance	disappearance	NOUN
ma-100	250	84	of	of	ADP
ma-100	250	85	spiking	spike	VERB
ma-100	250	86	behavior	behavior	NOUN
ma-100	250	87	.	.	PUNCT
ma-100	251	1	5	5	X
ma-100	251	2	.	.	X
ma-100	251	3	discussion	discussion	NOUN
ma-100	251	4	fractional	fractional	ADJ
ma-100	251	5	-	-	PUNCT
ma-100	251	6	order	order	NOUN
ma-100	251	7	excitable	excitable	ADJ
ma-100	251	8	systems	system	NOUN
ma-100	251	9	can	can	AUX
ma-100	251	10	be	be	AUX
ma-100	251	11	physically	physically	ADV
ma-100	251	12	considered	consider	VERB
ma-100	251	13	as	as	ADP
ma-100	251	14	a	a	DET
ma-100	251	15	memory	memory	NOUN
ma-100	251	16	dependent	dependent	ADJ
ma-100	251	17	phe	phe	NOUN
ma-100	251	18	-	-	PUNCT
ma-100	251	19	nomenon	nomenon	NOUN
ma-100	251	20	which	which	PRON
ma-100	251	21	display	display	VERB
ma-100	251	22	oscillatory	oscillatory	ADJ
ma-100	251	23	behaviors	behavior	NOUN
ma-100	251	24	for	for	ADP
ma-100	251	25	certain	certain	ADJ
ma-100	251	26	types	type	NOUN
ma-100	251	27	of	of	ADP
ma-100	251	28	neuron	neuron	NOUN
ma-100	251	29	models	model	NOUN
ma-100	251	30	.	.	PUNCT
ma-100	252	1	in	in	ADP
ma-100	252	2	this	this	DET
ma-100	252	3	research	research	NOUN
ma-100	252	4	,	,	PUNCT
ma-100	252	5	we	we	PRON
ma-100	252	6	have	have	AUX
ma-100	252	7	studied	study	VERB
ma-100	252	8	the	the	DET
ma-100	252	9	neuronal	neuronal	ADJ
ma-100	252	10	spiking	spike	VERB
ma-100	252	11	patterns	pattern	NOUN
ma-100	252	12	of	of	ADP
ma-100	252	13	fractional	fractional	ADJ
ma-100	252	14	morris	morris	PROPN
ma-100	252	15	-	-	PUNCT
ma-100	252	16	lecal	lecal	ADJ
ma-100	252	17	neuron	neuron	NOUN
ma-100	252	18	model	model	NOUN
ma-100	252	19	where	where	SCONJ
ma-100	252	20	thefractional	thefractional	ADJ
ma-100	252	21	-	-	PUNCT
ma-100	252	22	orders	order	NOUN
ma-100	252	23	could	could	AUX
ma-100	252	24	change	change	VERB
ma-100	252	25	the	the	DET
ma-100	252	26	responses	response	NOUN
ma-100	252	27	of	of	ADP
ma-100	252	28	the	the	DET
ma-100	252	29	model	model	NOUN
ma-100	252	30	from	from	ADP
ma-100	252	31	periodic	periodic	NOUN
ma-100	252	32	to	to	ADP
ma-100	252	33	non	non	ADJ
ma-100	252	34	-	-	NOUN
ma-100	252	35	periodic	periodic	ADJ
ma-100	252	36	,	,	PUNCT
ma-100	252	37	and	and	CCONJ
ma-100	252	38	wehave	wehave	NOUN
ma-100	252	39	compared	compare	VERB
ma-100	252	40	its	its	PRON
ma-100	252	41	dynamics	dynamic	NOUN
ma-100	252	42	to	to	ADP
ma-100	252	43	the	the	DET
ma-100	252	44	original	original	ADJ
ma-100	252	45	morris	morris	ADJ
ma-100	252	46	-	-	PUNCT
ma-100	252	47	lecar	lecar	NOUN
ma-100	252	48	model	model	NOUN
ma-100	252	49	.	.	PUNCT
ma-100	253	1	the	the	DET
ma-100	253	2	original	original	ADJ
ma-100	253	3	morris	morris	PROPN
ma-100	253	4	-	-	PUNCT
ma-100	253	5	lecal	lecal	ADJ
ma-100	253	6	neuronmodel	neuronmodel	NOUN
ma-100	253	7	which	which	PRON
ma-100	253	8	is	be	AUX
ma-100	253	9	a	a	DET
ma-100	253	10	reduction	reduction	NOUN
ma-100	253	11	version	version	NOUN
ma-100	253	12	of	of	ADP
ma-100	253	13	hodgkin	hodgkin	PROPN
ma-100	253	14	-	-	PUNCT
ma-100	253	15	huxley	huxley	PROPN
ma-100	253	16	model	model	NOUN
ma-100	253	17	includes	include	VERB
ma-100	253	18	two	two	NUM
ma-100	253	19	equations	equation	NOUN
ma-100	253	20	with	with	ADP
ma-100	253	21	integerorder	integerorder	NOUN
ma-100	253	22	derivatives	derivative	NOUN
ma-100	253	23	and	and	CCONJ
ma-100	253	24	three	three	NUM
ma-100	253	25	ionic	ionic	ADJ
ma-100	253	26	channels	channel	NOUN
ma-100	253	27	,	,	PUNCT
ma-100	253	28	a	a	DET
ma-100	253	29	potassium	potassium	NOUN
ma-100	253	30	channel	channel	NOUN
ma-100	253	31	,	,	PUNCT
ma-100	253	32	a	a	DET
ma-100	253	33	leak	leak	NOUN
ma-100	253	34	and	and	CCONJ
ma-100	253	35	a	a	DET
ma-100	253	36	calcium	calcium	NOUN
ma-100	253	37	channel.we	channel.we	PRON
ma-100	253	38	have	have	AUX
ma-100	253	39	preserved	preserve	VERB
ma-100	253	40	the	the	DET
ma-100	253	41	same	same	ADJ
ma-100	253	42	ionic	ionic	ADJ
ma-100	253	43	channels	channel	NOUN
ma-100	253	44	and	and	CCONJ
ma-100	253	45	to	to	PART
ma-100	253	46	find	find	VERB
ma-100	253	47	the	the	DET
ma-100	253	48	fractional	fractional	ADJ
ma-100	253	49	order	order	NOUN
ma-100	253	50	morris	morris	ADJ
ma-100	253	51	-	-	PUNCT
ma-100	253	52	lecar	lecar	NOUN
ma-100	253	53	model	model	NOUN
ma-100	253	54	,	,	PUNCT
ma-100	253	55	we	we	PRON
ma-100	253	56	have	have	AUX
ma-100	253	57	applied	apply	VERB
ma-100	253	58	the	the	DET
ma-100	253	59	non	non	ADJ
ma-100	253	60	-	-	ADJ
ma-100	253	61	standard	standard	ADJ
ma-100	253	62	finite	finite	ADJ
ma-100	253	63	difference	difference	NOUN
ma-100	253	64	(	(	PUNCT
ma-100	253	65	nsfd	nsfd	ADJ
ma-100	253	66	)	)	PUNCT
ma-100	253	67	schemes	scheme	NOUN
ma-100	253	68	on	on	ADP
ma-100	253	69	this	this	DET
ma-100	253	70	system	system	NOUN
ma-100	253	71	of	of	ADP
ma-100	253	72	equationssince	equationssince	NOUN
ma-100	253	73	they	they	PRON
ma-100	253	74	have	have	VERB
ma-100	253	75	a	a	DET
ma-100	253	76	better	well	ADJ
ma-100	253	77	performance	performance	NOUN
ma-100	253	78	than	than	ADP
ma-100	253	79	standard	standard	ADJ
ma-100	253	80	finite	finite	ADJ
ma-100	253	81	difference	difference	NOUN
ma-100	253	82	methods	method	NOUN
ma-100	253	83	.	.	PUNCT
ma-100	254	1	then	then	ADV
ma-100	254	2	we	we	PRON
ma-100	254	3	have	have	VERB
ma-100	254	4	dis	dis	PROPN
ma-100	254	5	-	-	PUNCT
ma-100	254	6	cretized	cretize	VERB
ma-100	254	7	the	the	DET
ma-100	254	8	model	model	NOUN
ma-100	254	9	using	use	VERB
ma-100	254	10	the	the	DET
ma-100	254	11	grunwald	grunwald	NOUN
ma-100	254	12	-	-	PUNCT
ma-100	254	13	letinkov	letinkov	NOUN
ma-100	254	14	discretization	discretization	NOUN
ma-100	254	15	.	.	PUNCT
ma-100	255	1	we	we	PRON
ma-100	255	2	use	use	VERB
ma-100	255	3	effective	effective	ADJ
ma-100	255	4	numerical	numerical	ADJ
ma-100	255	5	methodsto	methodsto	PROPN
ma-100	255	6	display	display	VERB
ma-100	255	7	the	the	DET
ma-100	255	8	solution	solution	NOUN
ma-100	255	9	of	of	ADP
ma-100	255	10	fractional	fractional	ADJ
ma-100	255	11	order	order	NOUN
ma-100	255	12	morris	morris	ADJ
ma-100	255	13	-	-	PUNCT
ma-100	255	14	lecar	lecar	NOUN
ma-100	255	15	model	model	NOUN
ma-100	255	16	.	.	PUNCT
ma-100	256	1	to	to	PART
ma-100	256	2	explore	explore	VERB
ma-100	256	3	the	the	DET
ma-100	256	4	exciting	exciting	ADJ
ma-100	256	5	behaviorsof	behaviorsof	ADJ
ma-100	256	6	fractional	fractional	ADJ
ma-100	256	7	morris	morris	PROPN
ma-100	256	8	-	-	PUNCT
ma-100	256	9	lecar	lecar	NOUN
ma-100	256	10	model	model	NOUN
ma-100	256	11	,	,	PUNCT
ma-100	256	12	we	we	PRON
ma-100	256	13	have	have	AUX
ma-100	256	14	conducted	conduct	VERB
ma-100	256	15	different	different	ADJ
ma-100	256	16	numerical	numerical	ADJ
ma-100	256	17	simulations	simulation	NOUN
ma-100	256	18	with	with	ADP
ma-100	256	19	changinginput	changinginput	NOUN
ma-100	256	20	currents	current	NOUN
ma-100	256	21	.	.	PUNCT
ma-100	257	1	it	it	PRON
ma-100	257	2	was	be	AUX
ma-100	257	3	obvious	obvious	ADJ
ma-100	257	4	that	that	SCONJ
ma-100	257	5	the	the	DET
ma-100	257	6	solutions	solution	NOUN
ma-100	257	7	depends	depend	VERB
ma-100	257	8	on	on	ADP
ma-100	257	9	the	the	DET
ma-100	257	10	fractional	fractional	ADJ
ma-100	257	11	-	-	PUNCT
ma-100	257	12	order	order	NOUN
ma-100	257	13	parameters	parameter	NOUN
ma-100	257	14	.	.	PUNCT
ma-100	258	1	wehave	wehave	PROPN
ma-100	258	2	shown	show	VERB
ma-100	258	3	that	that	SCONJ
ma-100	258	4	the	the	DET
ma-100	258	5	fractional	fractional	ADJ
ma-100	258	6	morris	morris	ADJ
ma-100	258	7	-	-	PUNCT
ma-100	258	8	lecar	lecar	ADJ
ma-100	258	9	model	model	NOUN
ma-100	258	10	with	with	ADP
ma-100	258	11	the	the	DET
ma-100	258	12	same	same	ADJ
ma-100	258	13	biological	biological	ADJ
ma-100	258	14	parameters	parameter	NOUN
ma-100	258	15	values	value	VERB
ma-100	258	16	asthe	asthe	DET
ma-100	258	17	original	original	ADJ
ma-100	258	18	model	model	NOUN
ma-100	258	19	,	,	PUNCT
ma-100	258	20	displays	display	VERB
ma-100	258	21	the	the	DET
ma-100	258	22	same	same	ADJ
ma-100	258	23	firing	firing	NOUN
ma-100	258	24	patterns	pattern	NOUN
ma-100	258	25	such	such	ADJ
ma-100	258	26	as	as	ADP
ma-100	258	27	quiescent	quiescent	ADJ
ma-100	258	28	and	and	CCONJ
ma-100	258	29	spiking	spike	VERB
ma-100	258	30	behaviors	behavior	NOUN
ma-100	258	31	butfor	butfor	ADP
ma-100	258	32	different	different	ADJ
ma-100	258	33	values	value	NOUN
ma-100	258	34	of	of	ADP
ma-100	258	35	input	input	NOUN
ma-100	258	36	currents	current	NOUN
ma-100	258	37	.	.	PUNCT
ma-100	259	1	we	we	PRON
ma-100	259	2	have	have	AUX
ma-100	259	3	noticed	notice	VERB
ma-100	259	4	that	that	SCONJ
ma-100	259	5	in	in	ADP
ma-100	259	6	this	this	DET
ma-100	259	7	case	case	NOUN
ma-100	259	8	,	,	PUNCT
ma-100	259	9	the	the	DET
ma-100	259	10	saddle	saddle	ADJ
ma-100	259	11	node	node	PROPN
ma-100	259	12	bifurcationof	bifurcationof	NOUN
ma-100	259	13	limit	limit	NOUN
ma-100	259	14	cycle	cycle	NOUN
ma-100	259	15	(	(	PUNCT
ma-100	259	16	snlc	snlc	PROPN
ma-100	259	17	)	)	PUNCT
ma-100	259	18	,	,	PUNCT
ma-100	259	19	hopf	hopf	ADJ
ma-100	259	20	bifurcation	bifurcation	NOUN
ma-100	259	21	and	and	CCONJ
ma-100	259	22	saddle	saddle	NOUN
ma-100	259	23	-	-	PUNCT
ma-100	259	24	homoclinic	homoclinic	NOUN
ma-100	259	25	bifurcation	bifurcation	NOUN
ma-100	259	26	happen	happen	VERB
ma-100	259	27	at	at	ADP
ma-100	259	28	larger	large	ADJ
ma-100	259	29	values	value	NOUN
ma-100	259	30	forinjected	forinjecte	VERB
ma-100	259	31	current	current	ADJ
ma-100	259	32	compare	compare	NOUN
ma-100	259	33	to	to	ADP
ma-100	259	34	the	the	DET
ma-100	259	35	original	original	ADJ
ma-100	259	36	model	model	NOUN
ma-100	259	37	and	and	CCONJ
ma-100	259	38	we	we	PRON
ma-100	259	39	have	have	AUX
ma-100	259	40	derived	derive	VERB
ma-100	259	41	these	these	DET
ma-100	259	42	bifurcations	bifurcation	NOUN
ma-100	259	43	analyticallyusing	analyticallyuse	VERB
ma-100	259	44	rigorous	rigorous	ADJ
ma-100	259	45	normal	normal	ADJ
ma-100	259	46	form	form	NOUN
ma-100	259	47	theory	theory	NOUN
ma-100	259	48	.	.	PUNCT
ma-100	260	1	similar	similar	ADJ
ma-100	260	2	to	to	ADP
ma-100	260	3	the	the	DET
ma-100	260	4	original	original	ADJ
ma-100	260	5	morris	morris	ADJ
ma-100	260	6	-	-	PUNCT
ma-100	260	7	lecar	lecar	NOUN
ma-100	260	8	model	model	NOUN
ma-100	260	9	,	,	PUNCT
ma-100	260	10	its	its	PRON
ma-100	260	11	fractional	fractional	ADJ
ma-100	260	12	-	-	PUNCT
ma-100	260	13	order	order	NOUN
ma-100	260	14	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	260	15	eur	eur	PROPN
ma-100	260	16	.	.	PUNCT
ma-100	261	1	j.	j.	PROPN
ma-100	261	2	math	math	PROPN
ma-100	261	3	.	.	PUNCT
ma-100	262	1	anal	anal	PROPN
ma-100	262	2	.	.	PUNCT
ma-100	263	1	10.28924	10.28924	NUM
ma-100	263	2	/	/	SYM
ma-100	263	3	ada	ada	PROPN
ma-100	263	4	/	/	SYM
ma-100	263	5	ma.3.2	ma.3.2	PROPN
ma-100	263	6	20	20	NUM
ma-100	263	7	figure	figure	NOUN
ma-100	263	8	10	10	NUM
ma-100	263	9	.	.	PUNCT
ma-100	264	1	occurrence	occurrence	NOUN
ma-100	264	2	of	of	ADP
ma-100	264	3	saddle	saddle	NOUN
ma-100	264	4	-	-	PUNCT
ma-100	264	5	homoclinic	homoclinic	NOUN
ma-100	264	6	bifurcation	bifurcation	NOUN
ma-100	264	7	in	in	ADP
ma-100	264	8	fractional	fractional	ADJ
ma-100	264	9	morris	morris	PROPN
ma-100	264	10	-	-	PUNCT
ma-100	264	11	lecarmodel	lecarmodel	PROPN
ma-100	264	12	(	(	PUNCT
ma-100	264	13	13	13	NUM
ma-100	264	14	)	)	PUNCT
ma-100	264	15	for	for	ADP
ma-100	264	16	iapp	iapp	NOUN
ma-100	264	17	=	=	SYM
ma-100	264	18	23	23	NUM
ma-100	264	19	,	,	PUNCT
ma-100	264	20	third	third	ADJ
ma-100	264	21	row	row	NOUN
ma-100	264	22	displays	display	VERB
ma-100	264	23	the	the	DET
ma-100	264	24	trajectory	trajectory	NOUN
ma-100	264	25	of	of	ADP
ma-100	264	26	the	the	DET
ma-100	264	27	original	original	ADJ
ma-100	264	28	model	model	NOUN
ma-100	264	29	(	(	PUNCT
ma-100	264	30	6)with	6)with	NUM
ma-100	264	31	the	the	DET
ma-100	264	32	same	same	ADJ
ma-100	264	33	applied	apply	VERB
ma-100	264	34	current	current	NOUN
ma-100	264	35	.	.	PUNCT
ma-100	265	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	265	2	eur	eur	PROPN
ma-100	265	3	.	.	PUNCT
ma-100	266	1	j.	j.	PROPN
ma-100	266	2	math	math	PROPN
ma-100	266	3	.	.	PUNCT
ma-100	267	1	anal	anal	PROPN
ma-100	267	2	.	.	PUNCT
ma-100	268	1	10.28924	10.28924	NUM
ma-100	268	2	/	/	SYM
ma-100	268	3	ada	ada	PROPN
ma-100	268	4	/	/	SYM
ma-100	268	5	ma.3.2	ma.3.2	PROPN
ma-100	268	6	21	21	NUM
ma-100	268	7	figure	figure	NOUN
ma-100	268	8	11	11	NUM
ma-100	268	9	.	.	PUNCT
ma-100	269	1	occurrence	occurrence	NOUN
ma-100	269	2	of	of	ADP
ma-100	269	3	saddle	saddle	NOUN
ma-100	269	4	-	-	PUNCT
ma-100	269	5	homoclinic	homoclinic	NOUN
ma-100	269	6	bifurcation	bifurcation	NOUN
ma-100	269	7	in	in	ADP
ma-100	269	8	fractional	fractional	ADJ
ma-100	269	9	morris	morris	PROPN
ma-100	269	10	-	-	PUNCT
ma-100	269	11	lecarmodel	lecarmodel	PROPN
ma-100	269	12	(	(	PUNCT
ma-100	269	13	13	13	NUM
ma-100	269	14	)	)	PUNCT
ma-100	269	15	for	for	ADP
ma-100	269	16	iapp	iapp	NOUN
ma-100	269	17	=	=	SYM
ma-100	269	18	40	40	NUM
ma-100	269	19	,	,	PUNCT
ma-100	269	20	third	third	ADJ
ma-100	269	21	row	row	NOUN
ma-100	269	22	displays	display	VERB
ma-100	269	23	the	the	DET
ma-100	269	24	trajectory	trajectory	NOUN
ma-100	269	25	of	of	ADP
ma-100	269	26	the	the	DET
ma-100	269	27	original	original	ADJ
ma-100	269	28	model	model	NOUN
ma-100	269	29	(	(	PUNCT
ma-100	269	30	6)with	6)with	NUM
ma-100	269	31	the	the	DET
ma-100	269	32	same	same	ADJ
ma-100	269	33	applied	apply	VERB
ma-100	269	34	current	current	NOUN
ma-100	269	35	.	.	PUNCT
ma-100	270	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	270	2	eur	eur	PROPN
ma-100	270	3	.	.	PUNCT
ma-100	271	1	j.	j.	PROPN
ma-100	271	2	math	math	PROPN
ma-100	271	3	.	.	PUNCT
ma-100	272	1	anal	anal	PROPN
ma-100	272	2	.	.	PUNCT
ma-100	273	1	10.28924	10.28924	NUM
ma-100	273	2	/	/	SYM
ma-100	273	3	ada	ada	PROPN
ma-100	273	4	/	/	SYM
ma-100	273	5	ma.3.2	ma.3.2	PROPN
ma-100	273	6	22	22	NUM
ma-100	273	7	figure	figure	NOUN
ma-100	273	8	12	12	NUM
ma-100	273	9	.	.	PUNCT
ma-100	274	1	occurrence	occurrence	NOUN
ma-100	274	2	of	of	ADP
ma-100	274	3	saddle	saddle	NOUN
ma-100	274	4	-	-	PUNCT
ma-100	274	5	homoclinic	homoclinic	NOUN
ma-100	274	6	bifurcation	bifurcation	NOUN
ma-100	274	7	in	in	ADP
ma-100	274	8	fractional	fractional	ADJ
ma-100	274	9	morris	morris	PROPN
ma-100	274	10	-	-	PUNCT
ma-100	274	11	lecarmodel	lecarmodel	PROPN
ma-100	274	12	(	(	PUNCT
ma-100	274	13	13	13	NUM
ma-100	274	14	)	)	PUNCT
ma-100	274	15	for	for	ADP
ma-100	274	16	iapp	iapp	NOUN
ma-100	274	17	=	=	SYM
ma-100	274	18	50	50	NUM
ma-100	274	19	,	,	PUNCT
ma-100	274	20	third	third	ADJ
ma-100	274	21	row	row	NOUN
ma-100	274	22	displays	display	VERB
ma-100	274	23	the	the	DET
ma-100	274	24	trajectory	trajectory	NOUN
ma-100	274	25	of	of	ADP
ma-100	274	26	the	the	DET
ma-100	274	27	original	original	ADJ
ma-100	274	28	model	model	NOUN
ma-100	274	29	(	(	PUNCT
ma-100	274	30	6)with	6)with	NUM
ma-100	274	31	the	the	DET
ma-100	274	32	same	same	ADJ
ma-100	274	33	applied	apply	VERB
ma-100	274	34	current	current	NOUN
ma-100	274	35	.	.	PUNCT
ma-100	275	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	275	2	eur	eur	PROPN
ma-100	275	3	.	.	PUNCT
ma-100	276	1	j.	j.	PROPN
ma-100	276	2	math	math	PROPN
ma-100	276	3	.	.	PUNCT
ma-100	277	1	anal	anal	PROPN
ma-100	277	2	.	.	PUNCT
ma-100	278	1	10.28924	10.28924	NUM
ma-100	278	2	/	/	SYM
ma-100	278	3	ada	ada	PROPN
ma-100	278	4	/	/	SYM
ma-100	278	5	ma.3.2	ma.3.2	PROPN
ma-100	278	6	23	23	NUM
ma-100	278	7	figure	figure	NOUN
ma-100	278	8	13	13	NUM
ma-100	278	9	.	.	PUNCT
ma-100	279	1	occurrence	occurrence	NOUN
ma-100	279	2	of	of	ADP
ma-100	279	3	saddle	saddle	NOUN
ma-100	279	4	-	-	PUNCT
ma-100	279	5	homoclinic	homoclinic	NOUN
ma-100	279	6	bifurcation	bifurcation	NOUN
ma-100	279	7	in	in	ADP
ma-100	279	8	fractional	fractional	ADJ
ma-100	279	9	morris	morris	PROPN
ma-100	279	10	-	-	PUNCT
ma-100	279	11	lecarmodel	lecarmodel	PROPN
ma-100	279	12	(	(	PUNCT
ma-100	279	13	13	13	NUM
ma-100	279	14	)	)	PUNCT
ma-100	279	15	for	for	ADP
ma-100	279	16	iapp	iapp	NOUN
ma-100	279	17	=	=	SYM
ma-100	279	18	60	60	NUM
ma-100	279	19	,	,	PUNCT
ma-100	279	20	third	third	ADJ
ma-100	279	21	row	row	NOUN
ma-100	279	22	displays	display	VERB
ma-100	279	23	the	the	DET
ma-100	279	24	trajectory	trajectory	NOUN
ma-100	279	25	of	of	ADP
ma-100	279	26	the	the	DET
ma-100	279	27	original	original	ADJ
ma-100	279	28	model	model	NOUN
ma-100	279	29	(	(	PUNCT
ma-100	279	30	6)with	6)with	NUM
ma-100	279	31	the	the	DET
ma-100	279	32	same	same	ADJ
ma-100	279	33	applied	apply	VERB
ma-100	279	34	current	current	NOUN
ma-100	279	35	.	.	PUNCT
ma-100	280	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	280	2	eur	eur	PROPN
ma-100	280	3	.	.	PUNCT
ma-100	281	1	j.	j.	PROPN
ma-100	281	2	math	math	PROPN
ma-100	281	3	.	.	PUNCT
ma-100	282	1	anal	anal	PROPN
ma-100	282	2	.	.	PUNCT
ma-100	283	1	10.28924	10.28924	NUM
ma-100	283	2	/	/	SYM
ma-100	283	3	ada	ada	PROPN
ma-100	283	4	/	/	SYM
ma-100	283	5	ma.3.2	ma.3.2	PROPN
ma-100	283	6	24	24	NUM
ma-100	283	7	figure	figure	NOUN
ma-100	283	8	14	14	NUM
ma-100	283	9	.	.	PUNCT
ma-100	284	1	occurrence	occurrence	NOUN
ma-100	284	2	of	of	ADP
ma-100	284	3	saddle	saddle	NOUN
ma-100	284	4	-	-	PUNCT
ma-100	284	5	homoclinic	homoclinic	NOUN
ma-100	284	6	bifurcation	bifurcation	NOUN
ma-100	284	7	in	in	ADP
ma-100	284	8	fractional	fractional	ADJ
ma-100	284	9	morris	morris	PROPN
ma-100	284	10	-	-	PUNCT
ma-100	284	11	lecarmodel	lecarmodel	PROPN
ma-100	284	12	(	(	PUNCT
ma-100	284	13	13	13	NUM
ma-100	284	14	)	)	PUNCT
ma-100	284	15	for	for	ADP
ma-100	284	16	iapp	iapp	NOUN
ma-100	284	17	=	=	SYM
ma-100	284	18	70	70	NUM
ma-100	284	19	,	,	PUNCT
ma-100	284	20	third	third	ADJ
ma-100	284	21	row	row	NOUN
ma-100	284	22	displays	display	VERB
ma-100	284	23	the	the	DET
ma-100	284	24	trajectory	trajectory	NOUN
ma-100	284	25	of	of	ADP
ma-100	284	26	the	the	DET
ma-100	284	27	original	original	ADJ
ma-100	284	28	model	model	NOUN
ma-100	284	29	(	(	PUNCT
ma-100	284	30	6)with	6)with	NUM
ma-100	284	31	the	the	DET
ma-100	284	32	same	same	ADJ
ma-100	284	33	applied	apply	VERB
ma-100	284	34	current	current	NOUN
ma-100	284	35	.	.	PUNCT
ma-100	285	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	285	2	eur	eur	PROPN
ma-100	285	3	.	.	PUNCT
ma-100	286	1	j.	j.	PROPN
ma-100	286	2	math	math	PROPN
ma-100	286	3	.	.	PUNCT
ma-100	287	1	anal	anal	PROPN
ma-100	287	2	.	.	PUNCT
ma-100	288	1	10.28924	10.28924	NUM
ma-100	288	2	/	/	SYM
ma-100	288	3	ada	ada	PROPN
ma-100	288	4	/	/	SYM
ma-100	288	5	ma.3.2	ma.3.2	PROPN
ma-100	288	6	25model	25model	PROPN
ma-100	288	7	undergoes	undergo	VERB
ma-100	288	8	a	a	DET
ma-100	288	9	transition	transition	NOUN
ma-100	288	10	between	between	ADP
ma-100	288	11	integrator	integrator	NOUN
ma-100	288	12	and	and	CCONJ
ma-100	288	13	resonator	resonator	NOUN
ma-100	288	14	.	.	PUNCT
ma-100	289	1	when	when	SCONJ
ma-100	289	2	saddle	saddle	NOUN
ma-100	289	3	-	-	PUNCT
ma-100	289	4	node	node	NOUN
ma-100	289	5	bifurcationhappens	bifurcationhappen	NOUN
ma-100	289	6	,	,	PUNCT
ma-100	289	7	the	the	DET
ma-100	289	8	neuron	neuron	NOUN
ma-100	289	9	is	be	AUX
ma-100	289	10	called	call	VERB
ma-100	289	11	an	an	DET
ma-100	289	12	integrator	integrator	NOUN
ma-100	289	13	means	mean	VERB
ma-100	289	14	that	that	SCONJ
ma-100	289	15	there	there	PRON
ma-100	289	16	is	be	VERB
ma-100	289	17	no	no	DET
ma-100	289	18	damped	damped	NOUN
ma-100	289	19	subthreshold	subthreshold	ADJ
ma-100	289	20	oscilla	oscilla	NOUN
ma-100	289	21	-	-	PUNCT
ma-100	289	22	tions	tion	NOUN
ma-100	289	23	.	.	PUNCT
ma-100	290	1	on	on	ADP
ma-100	290	2	the	the	DET
ma-100	290	3	other	other	ADJ
ma-100	290	4	hand	hand	NOUN
ma-100	290	5	,	,	PUNCT
ma-100	290	6	when	when	SCONJ
ma-100	290	7	hopf	hopf	ADJ
ma-100	290	8	bifurcation	bifurcation	NOUN
ma-100	290	9	happens	happen	VERB
ma-100	290	10	the	the	DET
ma-100	290	11	neuron	neuron	NOUN
ma-100	290	12	is	be	AUX
ma-100	290	13	called	call	VERB
ma-100	290	14	a	a	DET
ma-100	290	15	resonator	resonator	NOUN
ma-100	290	16	withdamped	withdampe	VERB
ma-100	290	17	subthreshold	subthreshold	ADJ
ma-100	290	18	oscillations	oscillation	NOUN
ma-100	290	19	.	.	PUNCT
ma-100	291	1	using	use	VERB
ma-100	291	2	the	the	DET
ma-100	291	3	fractional	fractional	ADJ
ma-100	291	4	order	order	NOUN
ma-100	291	5	derivative	derivative	NOUN
ma-100	291	6	,	,	PUNCT
ma-100	291	7	we	we	PRON
ma-100	291	8	have	have	AUX
ma-100	291	9	added	add	VERB
ma-100	291	10	a	a	DET
ma-100	291	11	newparameter	newparameter	NOUN
ma-100	291	12	as	as	ADP
ma-100	291	13	the	the	DET
ma-100	291	14	order	order	NOUN
ma-100	291	15	of	of	ADP
ma-100	291	16	derivatives	derivative	NOUN
ma-100	291	17	that	that	PRON
ma-100	291	18	helped	help	VERB
ma-100	291	19	us	we	PRON
ma-100	291	20	to	to	PART
ma-100	291	21	control	control	VERB
ma-100	291	22	the	the	DET
ma-100	291	23	spiking	spike	VERB
ma-100	291	24	patterns	pattern	NOUN
ma-100	291	25	of	of	ADP
ma-100	291	26	the	the	DET
ma-100	291	27	neuroncell	neuroncell	NOUN
ma-100	291	28	.	.	PUNCT
ma-100	292	1	taking	take	VERB
ma-100	292	2	the	the	DET
ma-100	292	3	advantages	advantage	NOUN
ma-100	292	4	of	of	ADP
ma-100	292	5	this	this	DET
ma-100	292	6	type	type	NOUN
ma-100	292	7	modeling	modeling	NOUN
ma-100	292	8	,	,	PUNCT
ma-100	292	9	we	we	PRON
ma-100	292	10	investigated	investigate	VERB
ma-100	292	11	how	how	SCONJ
ma-100	292	12	the	the	DET
ma-100	292	13	classical	classical	ADJ
ma-100	292	14	order	order	NOUN
ma-100	292	15	systemschanges	systemschange	VERB
ma-100	292	16	its	its	PRON
ma-100	292	17	complex	complex	ADJ
ma-100	292	18	dynamics	dynamic	NOUN
ma-100	292	19	such	such	ADJ
ma-100	292	20	as	as	ADP
ma-100	292	21	firing	fire	VERB
ma-100	292	22	patterns	pattern	NOUN
ma-100	292	23	and	and	CCONJ
ma-100	292	24	also	also	ADV
ma-100	292	25	firing	fire	VERB
ma-100	292	26	frequency	frequency	NOUN
ma-100	292	27	,	,	PUNCT
ma-100	292	28	when	when	SCONJ
ma-100	292	29	they	they	PRON
ma-100	292	30	turn	turn	VERB
ma-100	292	31	tobe	tobe	VERB
ma-100	292	32	fractional	fractional	ADJ
ma-100	292	33	order	order	NOUN
ma-100	292	34	systems	system	NOUN
ma-100	292	35	.	.	PUNCT
ma-100	293	1	this	this	DET
ma-100	293	2	work	work	NOUN
ma-100	293	3	improved	improve	VERB
ma-100	293	4	the	the	DET
ma-100	293	5	preceding	precede	VERB
ma-100	293	6	ones	one	NOUN
ma-100	293	7	[	[	X
ma-100	293	8	37,38	37,38	NOUN
ma-100	293	9	]	]	PUNCT
ma-100	293	10	by	by	ADP
ma-100	293	11	discovering	discover	VERB
ma-100	293	12	differentattractors	differentattractor	NOUN
ma-100	293	13	of	of	ADP
ma-100	293	14	the	the	DET
ma-100	293	15	system	system	NOUN
ma-100	293	16	for	for	ADP
ma-100	293	17	different	different	ADJ
ma-100	293	18	fractional	fractional	ADJ
ma-100	293	19	orders	order	NOUN
ma-100	293	20	and	and	CCONJ
ma-100	293	21	keeping	keep	VERB
ma-100	293	22	the	the	DET
ma-100	293	23	same	same	ADJ
ma-100	293	24	biological	biological	ADJ
ma-100	293	25	parameters.as	parameters.as	NOUN
ma-100	293	26	a	a	DET
ma-100	293	27	result	result	NOUN
ma-100	293	28	,	,	PUNCT
ma-100	293	29	fractional	fractional	ADJ
ma-100	293	30	order	order	NOUN
ma-100	293	31	plays	play	VERB
ma-100	293	32	a	a	DET
ma-100	293	33	key	key	ADJ
ma-100	293	34	role	role	NOUN
ma-100	293	35	in	in	ADP
ma-100	293	36	describing	describe	VERB
ma-100	293	37	the	the	DET
ma-100	293	38	firing	firing	NOUN
ma-100	293	39	patterns	pattern	NOUN
ma-100	293	40	and	and	CCONJ
ma-100	293	41	characterizing	characterize	VERB
ma-100	293	42	thememory	thememory	NOUN
ma-100	293	43	effect	effect	NOUN
ma-100	293	44	of	of	ADP
ma-100	293	45	neurons	neuron	NOUN
ma-100	293	46	which	which	PRON
ma-100	293	47	helps	help	VERB
ma-100	293	48	to	to	PART
ma-100	293	49	control	control	VERB
ma-100	293	50	the	the	DET
ma-100	293	51	long	long	ADJ
ma-100	293	52	term	term	NOUN
ma-100	293	53	dependency	dependency	NOUN
ma-100	293	54	of	of	ADP
ma-100	293	55	the	the	DET
ma-100	293	56	neuron	neuron	NOUN
ma-100	293	57	responsesby	responsesby	VERB
ma-100	293	58	adding	add	VERB
ma-100	293	59	extra	extra	ADJ
ma-100	293	60	freedom	freedom	NOUN
ma-100	293	61	to	to	ADP
ma-100	293	62	the	the	DET
ma-100	293	63	system	system	NOUN
ma-100	293	64	.	.	PUNCT
ma-100	294	1	moreover	moreover	ADV
ma-100	294	2	,	,	PUNCT
ma-100	294	3	using	use	VERB
ma-100	294	4	this	this	DET
ma-100	294	5	fractional	fractional	ADJ
ma-100	294	6	operator	operator	NOUN
ma-100	294	7	could	could	AUX
ma-100	294	8	display	display	VERB
ma-100	294	9	morenon	morenon	ADJ
ma-100	294	10	-	-	ADJ
ma-100	294	11	local	local	ADJ
ma-100	294	12	natural	natural	ADJ
ma-100	294	13	dynamics	dynamic	NOUN
ma-100	294	14	as	as	ADP
ma-100	294	15	a	a	DET
ma-100	294	16	sign	sign	NOUN
ma-100	294	17	of	of	ADP
ma-100	294	18	fractal	fractal	ADJ
ma-100	294	19	behaviors	behavior	NOUN
ma-100	294	20	compared	compare	VERB
ma-100	294	21	to	to	ADP
ma-100	294	22	the	the	DET
ma-100	294	23	integer	integer	NOUN
ma-100	294	24	order	order	NOUN
ma-100	294	25	model	model	NOUN
ma-100	294	26	.	.	PUNCT
ma-100	295	1	thisdifferentiation	thisdifferentiation	NOUN
ma-100	295	2	operator	operator	NOUN
ma-100	295	3	which	which	PRON
ma-100	295	4	is	be	AUX
ma-100	295	5	a	a	DET
ma-100	295	6	combination	combination	NOUN
ma-100	295	7	of	of	ADP
ma-100	295	8	fractal	fractal	ADJ
ma-100	295	9	and	and	CCONJ
ma-100	295	10	fractional	fractional	ADJ
ma-100	295	11	differentiation	differentiation	NOUN
ma-100	295	12	indicated	indicate	VERB
ma-100	295	13	theimportance	theimportance	NOUN
ma-100	295	14	of	of	ADP
ma-100	295	15	using	use	VERB
ma-100	295	16	fractal	fractal	ADJ
ma-100	295	17	geometry	geometry	NOUN
ma-100	295	18	to	to	PART
ma-100	295	19	study	study	VERB
ma-100	295	20	the	the	DET
ma-100	295	21	neural	neural	ADJ
ma-100	295	22	dynamic	dynamic	ADJ
ma-100	295	23	systems	system	NOUN
ma-100	295	24	.	.	PUNCT
ma-100	296	1	references	reference	NOUN
ma-100	296	2	[	[	X
ma-100	296	3	1	1	NUM
ma-100	296	4	]	]	PUNCT
ma-100	296	5	r.	r.	NOUN
ma-100	296	6	hilfer	hilfer	PROPN
ma-100	296	7	,	,	PUNCT
ma-100	296	8	applications	application	NOUN
ma-100	296	9	of	of	ADP
ma-100	296	10	fractional	fractional	ADJ
ma-100	296	11	calculus	calculus	NOUN
ma-100	296	12	in	in	ADP
ma-100	296	13	physics	physics	PROPN
ma-100	296	14	,	,	PUNCT
ma-100	296	15	world	world	NOUN
ma-100	296	16	scientific	scientific	PROPN
ma-100	296	17	,	,	PUNCT
ma-100	296	18	singapore	singapore	PROPN
ma-100	296	19	,	,	PUNCT
ma-100	296	20	2000	2000	NUM
ma-100	296	21	.	.	PUNCT
ma-100	297	1	https://doi.org/10	https://doi.org/10	PROPN
ma-100	297	2	.	.	PUNCT
ma-100	298	1	1142/3779.[2	1142/3779.[2	NUM
ma-100	298	2	]	]	X
ma-100	298	3	f.a	f.a	PROPN
ma-100	298	4	.	.	PROPN
ma-100	298	5	rihan	rihan	PROPN
ma-100	298	6	,	,	PUNCT
ma-100	298	7	d.	d.	PROPN
ma-100	298	8	baleanu	baleanu	PROPN
ma-100	298	9	,	,	PUNCT
ma-100	298	10	s.	s.	PROPN
ma-100	298	11	lakshmanan	lakshmanan	PROPN
ma-100	298	12	,	,	PUNCT
ma-100	298	13	r.	r.	PROPN
ma-100	298	14	rakkiyappan	rakkiyappan	PROPN
ma-100	298	15	,	,	PUNCT
ma-100	298	16	on	on	ADP
ma-100	298	17	fractional	fractional	PROPN
ma-100	298	18	sirc	sirc	PROPN
ma-100	298	19	model	model	NOUN
ma-100	298	20	with	with	ADP
ma-100	298	21	salmonella	salmonella	NOUN
ma-100	298	22	bacterial	bacterial	ADJ
ma-100	298	23	infection,2014	infection,2014	NOUN
ma-100	298	24	(	(	PUNCT
ma-100	298	25	2014	2014	NUM
ma-100	298	26	)	)	PUNCT
ma-100	298	27	136263	136263	NUM
ma-100	298	28	.	.	PUNCT
ma-100	299	1	https://doi.org/10.1155/2014/136263.[3	https://doi.org/10.1155/2014/136263.[3	NOUN
ma-100	299	2	]	]	PUNCT
ma-100	299	3	f.a	f.a	PROPN
ma-100	299	4	.	.	PROPN
ma-100	299	5	rihan	rihan	PROPN
ma-100	299	6	,	,	PUNCT
ma-100	299	7	s.	s.	PROPN
ma-100	299	8	lakshmanan	lakshmanan	PROPN
ma-100	299	9	,	,	PUNCT
ma-100	299	10	a.h	a.h	PROPN
ma-100	299	11	.	.	PROPN
ma-100	299	12	hashish	hashish	PROPN
ma-100	299	13	,	,	PUNCT
ma-100	299	14	r.	r.	PROPN
ma-100	299	15	rakkiyappan	rakkiyappan	PROPN
ma-100	299	16	,	,	PUNCT
ma-100	299	17	e.	e.	PROPN
ma-100	299	18	ahmed	ahmed	PROPN
ma-100	299	19	,	,	PUNCT
ma-100	299	20	fractional	fractional	ADJ
ma-100	299	21	-	-	PUNCT
ma-100	299	22	order	order	NOUN
ma-100	299	23	delayed	delay	VERB
ma-100	299	24	predator	predator	NOUN
ma-100	299	25	–	–	PUNCT
ma-100	299	26	prey	prey	PROPN
ma-100	299	27	sys	sy	NOUN
ma-100	299	28	-	-	NOUN
ma-100	299	29	tems	tem	NOUN
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ma-100	299	31	holling	holle	VERB
ma-100	299	32	type	type	NOUN
ma-100	299	33	-	-	PUNCT
ma-100	299	34	ii	ii	NOUN
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ma-100	299	36	response	response	NOUN
ma-100	299	37	,	,	PUNCT
ma-100	299	38	nonlinear	nonlinear	ADJ
ma-100	299	39	dyn	dyn	NOUN
ma-100	299	40	.	.	PUNCT
ma-100	300	1	80	80	NUM
ma-100	300	2	(	(	PUNCT
ma-100	300	3	2015	2015	NUM
ma-100	300	4	)	)	PUNCT
ma-100	301	1	777–789	777–789	NUM
ma-100	301	2	.	.	PUNCT
ma-100	302	1	https://doi.org/10.1007/	https://doi.org/10.1007/	PROPN
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ma-100	302	3	-	-	PUNCT
ma-100	302	4	015	015	NUM
ma-100	302	5	-	-	PUNCT
ma-100	302	6	1905	1905	NUM
ma-100	302	7	-	-	SYM
ma-100	302	8	8.[4	8.[4	NUM
ma-100	302	9	]	]	X
ma-100	302	10	f.a	f.a	PROPN
ma-100	302	11	.	.	PROPN
ma-100	302	12	rihan	rihan	PROPN
ma-100	302	13	,	,	PUNCT
ma-100	302	14	a.	a.	NOUN
ma-100	302	15	hashish	hashish	PROPN
ma-100	302	16	,	,	PUNCT
ma-100	302	17	f.	f.	PROPN
ma-100	302	18	al	al	PROPN
ma-100	302	19	-	-	PUNCT
ma-100	302	20	maskari	maskari	PROPN
ma-100	302	21	,	,	PUNCT
ma-100	302	22	et	et	PROPN
ma-100	302	23	al	al	PROPN
ma-100	302	24	.	.	PUNCT
ma-100	303	1	dynamics	dynamic	NOUN
ma-100	303	2	of	of	ADP
ma-100	303	3	tumor	tumor	NOUN
ma-100	303	4	-	-	PUNCT
ma-100	303	5	immune	immune	ADJ
ma-100	303	6	system	system	NOUN
ma-100	303	7	with	with	ADP
ma-100	303	8	fractional	fractional	ADJ
ma-100	303	9	-	-	PUNCT
ma-100	303	10	order	order	NOUN
ma-100	303	11	,	,	PUNCT
ma-100	303	12	j.	j.	PROPN
ma-100	303	13	tumor	tumor	PROPN
ma-100	303	14	res.2	res.2	PROPN
ma-100	303	15	(	(	PUNCT
ma-100	303	16	2016	2016	NUM
ma-100	303	17	)	)	PUNCT
ma-100	304	1	109.[5	109.[5	NUM
ma-100	304	2	]	]	X
ma-100	304	3	j.	j.	PROPN
ma-100	304	4	gómez	gómez	PROPN
ma-100	304	5	-	-	PUNCT
ma-100	304	6	aguilar	aguilar	PROPN
ma-100	304	7	,	,	PUNCT
ma-100	304	8	m.	m.	NOUN
ma-100	304	9	lópez	lópez	NOUN
ma-100	304	10	-	-	PUNCT
ma-100	304	11	lópez	lópez	PROPN
ma-100	304	12	,	,	PUNCT
ma-100	304	13	v.	v.	ADP
ma-100	304	14	alvarado	alvarado	PROPN
ma-100	304	15	-	-	PUNCT
ma-100	304	16	martínez	martínez	PROPN
ma-100	304	17	,	,	PUNCT
ma-100	304	18	d.	d.	PROPN
ma-100	304	19	baleanu	baleanu	PROPN
ma-100	304	20	,	,	PUNCT
ma-100	304	21	h.	h.	PROPN
ma-100	304	22	khan	khan	PROPN
ma-100	304	23	,	,	PUNCT
ma-100	304	24	chaos	chaos	NOUN
ma-100	304	25	in	in	ADP
ma-100	304	26	a	a	DET
ma-100	304	27	cancer	cancer	NOUN
ma-100	304	28	model	model	NOUN
ma-100	304	29	via	via	ADP
ma-100	304	30	fractionalderivatives	fractionalderivative	NOUN
ma-100	304	31	with	with	ADP
ma-100	304	32	exponential	exponential	ADJ
ma-100	304	33	decay	decay	NOUN
ma-100	304	34	and	and	CCONJ
ma-100	304	35	mittag	mittag	ADJ
ma-100	304	36	-	-	PUNCT
ma-100	304	37	leffler	leffler	NOUN
ma-100	304	38	law	law	NOUN
ma-100	304	39	,	,	PUNCT
ma-100	304	40	entropy	entropy	PROPN
ma-100	304	41	.	.	PROPN
ma-100	305	1	19	19	NUM
ma-100	305	2	(	(	PUNCT
ma-100	305	3	2017	2017	NUM
ma-100	305	4	)	)	PUNCT
ma-100	305	5	681	681	NUM
ma-100	305	6	.	.	PUNCT
ma-100	306	1	https://doi.org/10.3390/	https://doi.org/10.3390/	PROPN
ma-100	306	2	e19120681.[6	e19120681.[6	NUM
ma-100	306	3	]	]	X
ma-100	306	4	m.	m.	NOUN
ma-100	306	5	zeinadini	zeinadini	PROPN
ma-100	306	6	,	,	PUNCT
ma-100	306	7	m.	m.	NOUN
ma-100	306	8	namjoo	namjoo	NOUN
ma-100	306	9	,	,	PUNCT
ma-100	306	10	approximation	approximation	NOUN
ma-100	306	11	of	of	ADP
ma-100	306	12	fractional	fractional	ADJ
ma-100	306	13	-	-	PUNCT
ma-100	306	14	order	order	NOUN
ma-100	306	15	chemostat	chemostat	NOUN
ma-100	306	16	model	model	NOUN
ma-100	306	17	with	with	ADP
ma-100	306	18	nonstandard	nonstandard	ADJ
ma-100	306	19	finite	finite	ADJ
ma-100	306	20	differencescheme	differencescheme	NOUN
ma-100	306	21	,	,	PUNCT
ma-100	306	22	hacettepe	hacettepe	PROPN
ma-100	306	23	j.	j.	PROPN
ma-100	306	24	math	math	PROPN
ma-100	306	25	.	.	PUNCT
ma-100	307	1	stat	stat	PROPN
ma-100	307	2	.	.	PUNCT
ma-100	308	1	46	46	NUM
ma-100	308	2	(	(	PUNCT
ma-100	308	3	2017	2017	NUM
ma-100	308	4	)	)	PUNCT
ma-100	308	5	469	469	NUM
ma-100	308	6	-	-	SYM
ma-100	308	7	482.[7	482.[7	NUM
ma-100	308	8	]	]	X
ma-100	308	9	d.	d.	PROPN
ma-100	308	10	matignon	matignon	PROPN
ma-100	308	11	,	,	PUNCT
ma-100	308	12	stability	stability	NOUN
ma-100	308	13	results	result	VERB
ma-100	308	14	for	for	ADP
ma-100	308	15	fractional	fractional	ADJ
ma-100	308	16	differential	differential	ADJ
ma-100	308	17	equations	equation	NOUN
ma-100	308	18	with	with	ADP
ma-100	308	19	applications	application	NOUN
ma-100	308	20	to	to	PART
ma-100	308	21	control	control	VERB
ma-100	308	22	processing	processing	NOUN
ma-100	308	23	,	,	PUNCT
ma-100	308	24	comput.eng	comput.eng	X
ma-100	308	25	.	.	PUNCT
ma-100	309	1	syst	syst	PROPN
ma-100	309	2	.	.	PUNCT
ma-100	310	1	appl	appl	PROPN
ma-100	310	2	.	.	PROPN
ma-100	310	3	2	2	NUM
ma-100	310	4	(	(	PUNCT
ma-100	310	5	1996	1996	NUM
ma-100	310	6	)	)	PUNCT
ma-100	310	7	963	963	NUM
ma-100	310	8	-	-	SYM
ma-100	310	9	968.[8	968.[8	NUM
ma-100	310	10	]	]	X
ma-100	310	11	e.	e.	PROPN
ma-100	310	12	ahmed	ahmed	PROPN
ma-100	310	13	,	,	PUNCT
ma-100	310	14	a.m.a	a.m.a	PROPN
ma-100	310	15	.	.	PUNCT
ma-100	311	1	el	el	PROPN
ma-100	311	2	-	-	PUNCT
ma-100	311	3	sayed	say	VERB
ma-100	311	4	,	,	PUNCT
ma-100	311	5	h.a.a	h.a.a	PROPN
ma-100	311	6	.	.	PUNCT
ma-100	312	1	el	el	PROPN
ma-100	312	2	-	-	PUNCT
ma-100	312	3	saka	saka	PROPN
ma-100	312	4	,	,	PUNCT
ma-100	312	5	on	on	ADP
ma-100	312	6	some	some	DET
ma-100	312	7	routh	routh	PROPN
ma-100	312	8	–	–	PUNCT
ma-100	312	9	hurwitz	hurwitz	PROPN
ma-100	312	10	conditions	condition	NOUN
ma-100	312	11	for	for	ADP
ma-100	312	12	fractional	fractional	ADJ
ma-100	312	13	order	order	NOUN
ma-100	312	14	differentialequations	differentialequation	NOUN
ma-100	312	15	and	and	CCONJ
ma-100	312	16	their	their	PRON
ma-100	312	17	applications	application	NOUN
ma-100	312	18	in	in	ADP
ma-100	312	19	lorenz	lorenz	PROPN
ma-100	312	20	,	,	PUNCT
ma-100	312	21	rössler	rössler	NOUN
ma-100	312	22	,	,	PUNCT
ma-100	312	23	chua	chua	PROPN
ma-100	312	24	and	and	CCONJ
ma-100	312	25	chen	chen	PROPN
ma-100	312	26	systems	systems	PROPN
ma-100	312	27	,	,	PUNCT
ma-100	312	28	phys	phy	NOUN
ma-100	312	29	.	.	PUNCT
ma-100	313	1	lett	lett	PROPN
ma-100	313	2	.	.	PUNCT
ma-100	314	1	a.	a.	PROPN
ma-100	314	2	358	358	NUM
ma-100	314	3	(	(	PUNCT
ma-100	314	4	2006	2006	NUM
ma-100	314	5	)	)	PUNCT
ma-100	314	6	1–4	1–4	PROPN
ma-100	314	7	.	.	PUNCT
ma-100	314	8	https	https	PROPN
ma-100	314	9	:	:	PUNCT
ma-100	314	10	//doi.org/10.1016	//doi.org/10.1016	PROPN
ma-100	314	11	/	/	SYM
ma-100	314	12	j.physleta.2006.04.087.[9	j.physleta.2006.04.087.[9	PROPN
ma-100	314	13	]	]	X
ma-100	314	14	e.m	e.m	PROPN
ma-100	314	15	.	.	PROPN
ma-100	315	1	izhikevich	izhikevich	PROPN
ma-100	315	2	,	,	PUNCT
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ma-100	315	4	systems	system	NOUN
ma-100	315	5	in	in	ADP
ma-100	315	6	neuroscience	neuroscience	NOUN
ma-100	315	7	,	,	PUNCT
ma-100	315	8	mit	mit	NOUN
ma-100	315	9	press	press	NOUN
ma-100	315	10	,	,	PUNCT
ma-100	315	11	2007.[10	2007.[10	NUM
ma-100	315	12	]	]	X
ma-100	316	1	e.m	e.m	PROPN
ma-100	316	2	.	.	PROPN
ma-100	316	3	izhikevich	izhikevich	PROPN
ma-100	316	4	,	,	PUNCT
ma-100	316	5	simple	simple	ADJ
ma-100	316	6	model	model	NOUN
ma-100	316	7	of	of	ADP
ma-100	316	8	spiking	spike	VERB
ma-100	316	9	neurons	neuron	NOUN
ma-100	316	10	,	,	PUNCT
ma-100	316	11	ieee	ieee	NOUN
ma-100	316	12	trans	trans	PROPN
ma-100	316	13	.	.	PUNCT
ma-100	317	1	neural	neural	ADJ
ma-100	317	2	netw	netw	NOUN
ma-100	317	3	.	.	PUNCT
ma-100	318	1	14	14	NUM
ma-100	318	2	(	(	PUNCT
ma-100	318	3	2003	2003	NUM
ma-100	318	4	)	)	PUNCT
ma-100	318	5	1569–1572	1569–1572	NUM
ma-100	318	6	.	.	PUNCT
ma-100	319	1	https://doi	https://doi	PROPN
ma-100	320	1	.	.	PUNCT
ma-100	320	2	org/10.1109	org/10.1109	PROPN
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ma-100	320	6	e.m	e.m	PROPN
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ma-100	320	12	to	to	PART
ma-100	320	13	use	use	VERB
ma-100	320	14	for	for	ADP
ma-100	320	15	cortical	cortical	ADJ
ma-100	320	16	spiking	spike	VERB
ma-100	320	17	neurons	neuron	NOUN
ma-100	320	18	?	?	PUNCT
ma-100	320	19	,	,	PUNCT
ma-100	320	20	ieee	ieee	PROPN
ma-100	320	21	trans	trans	PROPN
ma-100	320	22	.	.	PUNCT
ma-100	321	1	neural	neural	ADJ
ma-100	321	2	netw	netw	NOUN
ma-100	321	3	.	.	PUNCT
ma-100	322	1	15	15	NUM
ma-100	322	2	(	(	PUNCT
ma-100	322	3	2004	2004	NUM
ma-100	322	4	)	)	PUNCT
ma-100	322	5	1063–1070	1063–1070	NUM
ma-100	322	6	.	.	PUNCT
ma-100	323	1	https://doi.org/10.1109/tnn.2004.832719	https://doi.org/10.1109/tnn.2004.832719	NOUN
ma-100	323	2	.	.	PUNCT
ma-100	324	1	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
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ma-100	324	8	https://doi.org/10.3390/e19120681	https://doi.org/10.3390/e19120681	PUNCT
ma-100	325	1	https://doi.org/10.1016/j.physleta.2006.04.087	https://doi.org/10.1016/j.physleta.2006.04.087	ADV
ma-100	325	2	https://doi.org/10.1016/j.physleta.2006.04.087	https://doi.org/10.1016/j.physleta.2006.04.087	ADV
ma-100	325	3	https://doi.org/10.1109/tnn.2003.820440	https://doi.org/10.1109/tnn.2003.820440	ADJ
ma-100	325	4	https://doi.org/10.1109/tnn.2003.820440	https://doi.org/10.1109/tnn.2003.820440	PROPN
ma-100	325	5	https://doi.org/10.1109/tnn.2004.832719	https://doi.org/10.1109/tnn.2004.832719	PROPN
ma-100	325	6	eur	eur	PROPN
ma-100	325	7	.	.	PUNCT
ma-100	326	1	j.	j.	PROPN
ma-100	326	2	math	math	PROPN
ma-100	326	3	.	.	PUNCT
ma-100	327	1	anal	anal	PROPN
ma-100	327	2	.	.	PUNCT
ma-100	328	1	10.28924	10.28924	NUM
ma-100	328	2	/	/	SYM
ma-100	328	3	ada	ada	PROPN
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ma-100	328	5	ma.3.2	ma.3.2	PROPN
ma-100	328	6	26	26	NUM
ma-100	329	1	[	[	X
ma-100	329	2	12	12	NUM
ma-100	329	3	]	]	X
ma-100	329	4	e.m	e.m	PROPN
ma-100	329	5	.	.	PROPN
ma-100	329	6	izhikevich	izhikevich	PROPN
ma-100	329	7	,	,	PUNCT
ma-100	329	8	neural	neural	ADJ
ma-100	329	9	excitability	excitability	NOUN
ma-100	329	10	,	,	PUNCT
ma-100	329	11	spiking	spike	VERB
ma-100	329	12	and	and	CCONJ
ma-100	329	13	bursting	bursting	NOUN
ma-100	329	14	,	,	PUNCT
ma-100	329	15	int	int	NOUN
ma-100	329	16	.	.	PUNCT
ma-100	330	1	j.	j.	PROPN
ma-100	330	2	bifurcation	bifurcation	NOUN
ma-100	330	3	chaos	chaos	NOUN
ma-100	330	4	.	.	PUNCT
ma-100	331	1	10	10	NUM
ma-100	331	2	(	(	PUNCT
ma-100	331	3	2000	2000	NUM
ma-100	331	4	)	)	PUNCT
ma-100	331	5	1171–1266	1171–1266	NUM
ma-100	331	6	.	.	PUNCT
ma-100	332	1	https	https	NOUN
ma-100	332	2	:	:	PUNCT
ma-100	332	3	//doi.org/10.1142	//doi.org/10.1142	X
ma-100	332	4	/	/	SYM
ma-100	332	5	s0218127400000840.[13	s0218127400000840.[13	PROPN
ma-100	332	6	]	]	X
ma-100	332	7	f.c	f.c	PROPN
ma-100	332	8	.	.	PROPN
ma-100	332	9	hoppensteadt	hoppensteadt	PROPN
ma-100	332	10	,	,	PUNCT
ma-100	332	11	e.m	e.m	PROPN
ma-100	332	12	.	.	PROPN
ma-100	333	1	izhikevich	izhikevich	PROPN
ma-100	333	2	,	,	PUNCT
ma-100	333	3	weakly	weakly	ADJ
ma-100	333	4	connected	connected	ADJ
ma-100	333	5	neural	neural	ADJ
ma-100	333	6	networks	network	NOUN
ma-100	333	7	,	,	PUNCT
ma-100	333	8	springer	springer	NOUN
ma-100	333	9	new	new	PROPN
ma-100	333	10	york	york	PROPN
ma-100	333	11	,	,	PUNCT
ma-100	333	12	2012	2012	NUM
ma-100	333	13	.	.	PUNCT
ma-100	334	1	https://doi	https://doi	PROPN
ma-100	334	2	.	.	PUNCT
ma-100	334	3	org/10.1007/978	org/10.1007/978	PROPN
ma-100	334	4	-	-	PUNCT
ma-100	334	5	1	1	NUM
ma-100	334	6	-	-	PUNCT
ma-100	334	7	4612	4612	NUM
ma-100	334	8	-	-	PUNCT
ma-100	334	9	1828	1828	NUM
ma-100	334	10	-	-	PUNCT
ma-100	334	11	9.[14	9.[14	PROPN
ma-100	334	12	]	]	X
ma-100	334	13	a.l	a.l	PROPN
ma-100	334	14	.	.	PROPN
ma-100	334	15	hodgkin	hodgkin	PROPN
ma-100	334	16	,	,	PUNCT
ma-100	334	17	the	the	DET
ma-100	334	18	local	local	ADJ
ma-100	334	19	electric	electric	ADJ
ma-100	334	20	changes	change	NOUN
ma-100	334	21	associated	associate	VERB
ma-100	334	22	with	with	ADP
ma-100	334	23	repetitive	repetitive	ADJ
ma-100	334	24	action	action	NOUN
ma-100	334	25	in	in	ADP
ma-100	334	26	a	a	DET
ma-100	334	27	non	non	ADJ
ma-100	334	28	-	-	ADJ
ma-100	334	29	medullated	medullated	ADJ
ma-100	334	30	axon	axon	NOUN
ma-100	334	31	,	,	PUNCT
ma-100	334	32	j.	j.	PROPN
ma-100	334	33	physiol	physiol	PROPN
ma-100	334	34	.	.	PUNCT
ma-100	335	1	107(1948	107(1948	NUM
ma-100	335	2	)	)	PUNCT
ma-100	336	1	165–181	165–181	NUM
ma-100	336	2	.	.	PUNCT
ma-100	337	1	https://doi.org/10.1113/jphysiol.1948.sp004260.[15	https://doi.org/10.1113/jphysiol.1948.sp004260.[15	VERB
ma-100	337	2	]	]	X
ma-100	337	3	a.l	a.l	PROPN
ma-100	337	4	.	.	PROPN
ma-100	337	5	hodgkin	hodgkin	PROPN
ma-100	337	6	,	,	PUNCT
ma-100	337	7	a.f	a.f	PROPN
ma-100	337	8	.	.	PROPN
ma-100	337	9	huxley	huxley	PROPN
ma-100	337	10	,	,	PUNCT
ma-100	337	11	a	a	DET
ma-100	337	12	quantitative	quantitative	ADJ
ma-100	337	13	description	description	NOUN
ma-100	337	14	of	of	ADP
ma-100	337	15	membrane	membrane	NOUN
ma-100	337	16	current	current	NOUN
ma-100	337	17	and	and	CCONJ
ma-100	337	18	its	its	PRON
ma-100	337	19	application	application	NOUN
ma-100	337	20	to	to	ADP
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ma-100	337	26	j.	j.	PROPN
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ma-100	338	1	117	117	NUM
ma-100	338	2	(	(	PUNCT
ma-100	338	3	1952	1952	NUM
ma-100	338	4	)	)	PUNCT
ma-100	338	5	,	,	PUNCT
ma-100	338	6	500–544	500–544	NUM
ma-100	338	7	.	.	PUNCT
ma-100	338	8	https://doi.org/10.1113/jphysiol.1952.sp004764.[16	https://doi.org/10.1113/jphysiol.1952.sp004764.[16	PROPN
ma-100	338	9	]	]	PUNCT
ma-100	338	10	j.	j.	PROPN
ma-100	338	11	rinzel	rinzel	PROPN
ma-100	338	12	,	,	PUNCT
ma-100	338	13	g.b	g.b	PROPN
ma-100	338	14	.	.	PROPN
ma-100	338	15	ermentrout	ermentrout	PROPN
ma-100	338	16	,	,	PUNCT
ma-100	338	17	analysis	analysis	NOUN
ma-100	338	18	of	of	ADP
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ma-100	338	20	excitability	excitability	NOUN
ma-100	338	21	and	and	CCONJ
ma-100	338	22	oscillations	oscillation	NOUN
ma-100	338	23	,	,	PUNCT
ma-100	338	24	mit	mit	PROPN
ma-100	338	25	press	press	NOUN
ma-100	338	26	,	,	PUNCT
ma-100	338	27	cambridge	cambridge	PROPN
ma-100	338	28	,	,	PUNCT
ma-100	338	29	ma	ma	PROPN
ma-100	338	30	,	,	PUNCT
ma-100	338	31	1989.[17	1989.[17	PROPN
ma-100	338	32	]	]	X
ma-100	338	33	j.	j.	PROPN
ma-100	338	34	rinzel	rinzel	PROPN
ma-100	338	35	,	,	PUNCT
ma-100	338	36	g.b	g.b	PROPN
ma-100	338	37	.	.	PROPN
ma-100	338	38	ermentrout	ermentrout	PROPN
ma-100	338	39	,	,	PUNCT
ma-100	338	40	analysis	analysis	NOUN
ma-100	338	41	of	of	ADP
ma-100	338	42	neural	neural	ADJ
ma-100	338	43	excitability	excitability	NOUN
ma-100	338	44	and	and	CCONJ
ma-100	338	45	oscillations	oscillation	NOUN
ma-100	338	46	,	,	PUNCT
ma-100	338	47	methods	method	NOUN
ma-100	338	48	in	in	ADP
ma-100	338	49	neuronal	neuronal	ADJ
ma-100	338	50	modeling	modeling	NOUN
ma-100	338	51	,	,	PUNCT
ma-100	338	52	mitpress	mitpress	PROPN
ma-100	338	53	cambridge	cambridge	PROPN
ma-100	338	54	,	,	PUNCT
ma-100	338	55	ma	ma	PROPN
ma-100	338	56	,	,	PUNCT
ma-100	338	57	1998.[18	1998.[18	NUM
ma-100	338	58	]	]	X
ma-100	338	59	g.b	g.b	PROPN
ma-100	338	60	.	.	PROPN
ma-100	338	61	ermentrout	ermentrout	PROPN
ma-100	338	62	,	,	PUNCT
ma-100	338	63	d.h	d.h	PROPN
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ma-100	338	65	terman	terman	PROPN
ma-100	338	66	,	,	PUNCT
ma-100	338	67	mathematical	mathematical	ADJ
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ma-100	338	69	of	of	ADP
ma-100	338	70	neuroscience	neuroscience	NOUN
ma-100	338	71	,	,	PUNCT
ma-100	338	72	springer	springer	NOUN
ma-100	338	73	new	new	PROPN
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ma-100	338	75	,	,	PUNCT
ma-100	338	76	2010	2010	NUM
ma-100	338	77	.	.	PUNCT
ma-100	339	1	https	https	NOUN
ma-100	339	2	:	:	PUNCT
ma-100	339	3	//doi.org/10.1007/978	//doi.org/10.1007/978	NUM
ma-100	339	4	-	-	SYM
ma-100	339	5	0	0	NUM
ma-100	339	6	-	-	PUNCT
ma-100	339	7	387	387	NUM
ma-100	339	8	-	-	PUNCT
ma-100	339	9	87708	87708	NUM
ma-100	339	10	-	-	PUNCT
ma-100	339	11	2.[19	2.[19	NUM
ma-100	339	12	]	]	PUNCT
ma-100	339	13	b.	b.	PROPN
ma-100	339	14	ermentrout	ermentrout	PROPN
ma-100	339	15	,	,	PUNCT
ma-100	339	16	type	type	NOUN
ma-100	339	17	i	i	PRON
ma-100	339	18	membranes	membrane	NOUN
ma-100	339	19	,	,	PUNCT
ma-100	339	20	phase	phase	NOUN
ma-100	339	21	resetting	reset	VERB
ma-100	339	22	curves	curve	NOUN
ma-100	339	23	,	,	PUNCT
ma-100	339	24	and	and	CCONJ
ma-100	339	25	synchrony	synchrony	NOUN
ma-100	339	26	,	,	PUNCT
ma-100	339	27	neural	neural	ADJ
ma-100	339	28	comput	comput	NOUN
ma-100	339	29	.	.	PUNCT
ma-100	340	1	8	8	NUM
ma-100	340	2	(	(	PUNCT
ma-100	340	3	1996	1996	NUM
ma-100	340	4	)	)	PUNCT
ma-100	340	5	979–1001	979–1001	X
ma-100	340	6	.	.	PUNCT
ma-100	341	1	https://doi.org/10.1162/neco.1996.8.5.979.[20	https://doi.org/10.1162/neco.1996.8.5.979.[20	PROPN
ma-100	341	2	]	]	X
ma-100	341	3	k.	k.	PROPN
ma-100	341	4	moaddy	moaddy	PROPN
ma-100	341	5	,	,	PUNCT
ma-100	341	6	a.g	a.g	PROPN
ma-100	341	7	.	.	PROPN
ma-100	341	8	radwan	radwan	PROPN
ma-100	341	9	,	,	PUNCT
ma-100	341	10	k.n	k.n	PROPN
ma-100	341	11	.	.	PROPN
ma-100	341	12	salama	salama	PROPN
ma-100	341	13	,	,	PUNCT
ma-100	341	14	s.	s.	PROPN
ma-100	341	15	momani	momani	PROPN
ma-100	341	16	,	,	PUNCT
ma-100	341	17	i.	i.	PROPN
ma-100	341	18	hashim	hashim	PROPN
ma-100	341	19	,	,	PUNCT
ma-100	341	20	the	the	DET
ma-100	341	21	fractional	fractional	ADJ
ma-100	341	22	-	-	PUNCT
ma-100	341	23	order	order	NOUN
ma-100	341	24	modeling	modeling	NOUN
ma-100	341	25	and	and	CCONJ
ma-100	341	26	synchronizationof	synchronizationof	PROPN
ma-100	341	27	electrically	electrically	ADV
ma-100	341	28	coupled	couple	VERB
ma-100	341	29	neuron	neuron	PROPN
ma-100	341	30	systems	system	NOUN
ma-100	341	31	,	,	PUNCT
ma-100	341	32	computers	computer	NOUN
ma-100	341	33	math	math	NOUN
ma-100	341	34	.	.	PUNCT
ma-100	342	1	appl	appl	PROPN
ma-100	342	2	.	.	PUNCT
ma-100	343	1	64	64	NUM
ma-100	343	2	(	(	PUNCT
ma-100	343	3	2012	2012	NUM
ma-100	343	4	)	)	PUNCT
ma-100	344	1	3329–3339	3329–3339	NUM
ma-100	344	2	.	.	PUNCT
ma-100	345	1	https://doi.org/10.1016/	https://doi.org/10.1016/	PROPN
ma-100	345	2	j.camwa.2012.01.005.[21	j.camwa.2012.01.005.[21	PROPN
ma-100	345	3	]	]	X
ma-100	345	4	b.n	b.n	PROPN
ma-100	345	5	.	.	PROPN
ma-100	345	6	lundstrom	lundstrom	PROPN
ma-100	345	7	,	,	PUNCT
ma-100	345	8	m.h	m.h	PROPN
ma-100	345	9	.	.	PROPN
ma-100	345	10	higgs	higgs	PROPN
ma-100	345	11	,	,	PUNCT
ma-100	345	12	w.j	w.j	PROPN
ma-100	345	13	.	.	PROPN
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ma-100	345	15	,	,	PUNCT
ma-100	345	16	a.l	a.l	PROPN
ma-100	345	17	.	.	PROPN
ma-100	345	18	fairhall	fairhall	PROPN
ma-100	345	19	,	,	PUNCT
ma-100	345	20	fractional	fractional	ADJ
ma-100	345	21	differentiation	differentiation	NOUN
ma-100	345	22	by	by	ADP
ma-100	345	23	neocortical	neocortical	ADJ
ma-100	345	24	pyramidal	pyramidal	ADJ
ma-100	345	25	neurons	neuron	NOUN
ma-100	345	26	,	,	PUNCT
ma-100	345	27	nat	nat	PROPN
ma-100	345	28	.	.	PUNCT
ma-100	346	1	neurosci	neurosci	PROPN
ma-100	346	2	.	.	PUNCT
ma-100	347	1	11	11	NUM
ma-100	347	2	(	(	PUNCT
ma-100	347	3	2008	2008	NUM
ma-100	347	4	)	)	PUNCT
ma-100	347	5	1335–1342	1335–1342	NUM
ma-100	347	6	.	.	PUNCT
ma-100	348	1	https://doi.org/10.1038/nn.2212.[22	https://doi.org/10.1038/nn.2212.[22	PROPN
ma-100	348	2	]	]	PUNCT
ma-100	348	3	s.a	s.a	PROPN
ma-100	348	4	.	.	PROPN
ma-100	348	5	malik	malik	PROPN
ma-100	348	6	,	,	PUNCT
ma-100	348	7	a.h	a.h	PROPN
ma-100	348	8	.	.	PROPN
ma-100	348	9	mir	mir	PROPN
ma-100	348	10	,	,	PUNCT
ma-100	348	11	fpga	fpga	PROPN
ma-100	348	12	realization	realization	NOUN
ma-100	348	13	of	of	ADP
ma-100	348	14	fractional	fractional	ADJ
ma-100	348	15	order	order	NOUN
ma-100	348	16	neuron	neuron	NOUN
ma-100	348	17	,	,	PUNCT
ma-100	348	18	appl	appl	PROPN
ma-100	348	19	.	.	PROPN
ma-100	348	20	math	math	PROPN
ma-100	348	21	.	.	PUNCT
ma-100	349	1	model	model	NOUN
ma-100	349	2	.	.	PUNCT
ma-100	350	1	81	81	NUM
ma-100	350	2	(	(	PUNCT
ma-100	350	3	2020	2020	NUM
ma-100	350	4	)	)	PUNCT
ma-100	351	1	372–385	372–385	NUM
ma-100	351	2	.	.	PUNCT
ma-100	352	1	https	https	NOUN
ma-100	352	2	:	:	PUNCT
ma-100	352	3	//doi.org/10.1016	//doi.org/10.1016	PROPN
ma-100	352	4	/	/	SYM
ma-100	352	5	j.apm.2019.12.008.[23	j.apm.2019.12.008.[23	NOUN
ma-100	352	6	]	]	PUNCT
ma-100	352	7	m.	m.	PROPN
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ma-100	352	9	,	,	PUNCT
ma-100	352	10	z.	z.	PROPN
ma-100	352	11	wang	wang	PROPN
ma-100	352	12	,	,	PUNCT
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ma-100	352	14	bursting	bursting	NOUN
ma-100	352	15	patterns	pattern	NOUN
ma-100	352	16	of	of	ADP
ma-100	352	17	a	a	DET
ma-100	352	18	fractional	fractional	ADJ
ma-100	352	19	-	-	PUNCT
ma-100	352	20	order	order	NOUN
ma-100	352	21	morris	morris	PROPN
ma-100	352	22	–	–	PUNCT
ma-100	352	23	lecar	lecar	ADJ
ma-100	352	24	neuron	neuron	PROPN
ma-100	352	25	model	model	PROPN
ma-100	352	26	,	,	PUNCT
ma-100	352	27	commun	commun	PROPN
ma-100	352	28	.	.	PUNCT
ma-100	353	1	nonlinearsci	nonlinearsci	PROPN
ma-100	353	2	.	.	PUNCT
ma-100	354	1	numer	numer	PROPN
ma-100	354	2	.	.	PUNCT
ma-100	355	1	simul	simul	PROPN
ma-100	355	2	.	.	PROPN
ma-100	356	1	19	19	NUM
ma-100	356	2	(	(	PUNCT
ma-100	356	3	2014	2014	NUM
ma-100	356	4	)	)	PUNCT
ma-100	356	5	1956–1969	1956–1969	NUM
ma-100	356	6	.	.	PUNCT
ma-100	357	1	https://doi.org/10.1016/j.cnsns.2013.10.032.[24	https://doi.org/10.1016/j.cnsns.2013.10.032.[24	PROPN
ma-100	357	2	]	]	PUNCT
ma-100	357	3	d.	d.	PROPN
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ma-100	357	5	,	,	PUNCT
ma-100	357	6	z.	z.	PROPN
ma-100	357	7	guang	guang	PROPN
ma-100	357	8	-	-	PUNCT
ma-100	357	9	jun	jun	PROPN
ma-100	357	10	,	,	PUNCT
ma-100	357	11	x.	x.	PROPN
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ma-100	357	13	,	,	PUNCT
ma-100	357	14	y.	y.	PROPN
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ma-100	357	16	,	,	PUNCT
ma-100	357	17	w.	w.	PROPN
ma-100	357	18	jue	jue	PROPN
ma-100	357	19	,	,	PUNCT
ma-100	357	20	dynamic	dynamic	ADJ
ma-100	357	21	behavior	behavior	NOUN
ma-100	357	22	analysis	analysis	NOUN
ma-100	357	23	of	of	ADP
ma-100	357	24	fractional	fractional	ADJ
ma-100	357	25	-	-	PUNCT
ma-100	357	26	order	order	NOUN
ma-100	357	27	hindmarsh	hindmarsh	NOUN
ma-100	357	28	–	–	PUNCT
ma-100	357	29	roseneuronal	roseneuronal	ADJ
ma-100	357	30	model	model	NOUN
ma-100	357	31	,	,	PUNCT
ma-100	357	32	cogn	cogn	ADJ
ma-100	357	33	.	.	PUNCT
ma-100	358	1	neurodyn	neurodyn	NOUN
ma-100	358	2	.	.	PUNCT
ma-100	359	1	8	8	NUM
ma-100	359	2	(	(	PUNCT
ma-100	359	3	2013	2013	NUM
ma-100	359	4	)	)	PUNCT
ma-100	359	5	167–175	167–175	NUM
ma-100	359	6	.	.	PUNCT
ma-100	360	1	https://doi.org/10.1007/s11571-013-9273-x.[25	https://doi.org/10.1007/s11571-013-9273-x.[25	PRON
ma-100	360	2	]	]	X
ma-100	360	3	z.	z.	PROPN
ma-100	360	4	wang	wang	PROPN
ma-100	360	5	,	,	PUNCT
ma-100	360	6	x.	x.	PROPN
ma-100	360	7	wang	wang	PROPN
ma-100	360	8	,	,	PUNCT
ma-100	360	9	y.	y.	PROPN
ma-100	360	10	li	li	PROPN
ma-100	360	11	,	,	PUNCT
ma-100	360	12	x.	x.	PROPN
ma-100	360	13	huang	huang	PROPN
ma-100	360	14	,	,	PUNCT
ma-100	360	15	stability	stability	NOUN
ma-100	360	16	and	and	CCONJ
ma-100	360	17	hopf	hopf	ADJ
ma-100	360	18	bifurcation	bifurcation	NOUN
ma-100	360	19	of	of	ADP
ma-100	360	20	fractional	fractional	ADJ
ma-100	360	21	-	-	PUNCT
ma-100	360	22	order	order	NOUN
ma-100	360	23	complex	complex	NOUN
ma-100	360	24	-	-	PUNCT
ma-100	360	25	valued	value	VERB
ma-100	360	26	sin	sin	NOUN
ma-100	360	27	-	-	PUNCT
ma-100	360	28	gle	gle	NOUN
ma-100	360	29	neuron	neuron	NOUN
ma-100	360	30	model	model	NOUN
ma-100	360	31	with	with	ADP
ma-100	360	32	time	time	NOUN
ma-100	360	33	delay	delay	NOUN
ma-100	360	34	,	,	PUNCT
ma-100	360	35	int	int	NOUN
ma-100	360	36	.	.	PUNCT
ma-100	361	1	j.	j.	PROPN
ma-100	361	2	bifurcation	bifurcation	NOUN
ma-100	361	3	chaos	chaos	NOUN
ma-100	361	4	.	.	PUNCT
ma-100	362	1	27	27	NUM
ma-100	362	2	(	(	PUNCT
ma-100	362	3	2017	2017	NUM
ma-100	362	4	)	)	PUNCT
ma-100	362	5	1750209	1750209	NUM
ma-100	362	6	.	.	PUNCT
ma-100	363	1	https://doi.org/10.1142/	https://doi.org/10.1142/	PROPN
ma-100	363	2	s0218127417502091.[26	s0218127417502091.[26	PROPN
ma-100	363	3	]	]	X
ma-100	363	4	b.i	b.i	PROPN
ma-100	363	5	.	.	PROPN
ma-100	363	6	henry	henry	PROPN
ma-100	363	7	,	,	PUNCT
ma-100	363	8	t.a.m	t.a.m	PROPN
ma-100	363	9	.	.	PROPN
ma-100	363	10	langlands	langlands	PROPN
ma-100	363	11	,	,	PUNCT
ma-100	363	12	s.l	s.l	PROPN
ma-100	363	13	.	.	PROPN
ma-100	363	14	wearne	wearne	ADJ
ma-100	363	15	,	,	PUNCT
ma-100	363	16	fractional	fractional	ADJ
ma-100	363	17	cable	cable	NOUN
ma-100	363	18	models	model	NOUN
ma-100	363	19	for	for	ADP
ma-100	363	20	spiny	spiny	ADJ
ma-100	363	21	neuronal	neuronal	ADJ
ma-100	363	22	dendrites	dendrite	NOUN
ma-100	363	23	,	,	PUNCT
ma-100	363	24	phys	phy	NOUN
ma-100	363	25	.	.	PUNCT
ma-100	364	1	rev	rev	PROPN
ma-100	364	2	.	.	PROPN
ma-100	365	1	lett.100	lett.100	PROPN
ma-100	365	2	(	(	PUNCT
ma-100	365	3	2008	2008	NUM
ma-100	365	4	)	)	PUNCT
ma-100	365	5	128103	128103	NUM
ma-100	365	6	.	.	PUNCT
ma-100	366	1	https://doi.org/10.1103/physrevlett.100.128103.[27	https://doi.org/10.1103/physrevlett.100.128103.[27	PROPN
ma-100	366	2	]	]	X
ma-100	366	3	m.f	m.f	PROPN
ma-100	366	4	.	.	PUNCT
ma-100	366	5	tolba	tolba	PROPN
ma-100	366	6	,	,	PUNCT
ma-100	366	7	a.h	a.h	PROPN
ma-100	366	8	.	.	PROPN
ma-100	366	9	elsafty	elsafty	PROPN
ma-100	366	10	,	,	PUNCT
ma-100	366	11	m.	m.	NOUN
ma-100	366	12	armanyos	armanyos	PROPN
ma-100	366	13	,	,	PUNCT
ma-100	366	14	l.a	l.a	PROPN
ma-100	366	15	.	.	PROPN
ma-100	366	16	said	say	VERB
ma-100	366	17	,	,	PUNCT
ma-100	366	18	a.h	a.h	PROPN
ma-100	366	19	.	.	PROPN
ma-100	366	20	madian	madian	PROPN
ma-100	366	21	,	,	PUNCT
ma-100	366	22	a.g	a.g	PROPN
ma-100	366	23	.	.	PROPN
ma-100	366	24	radwan	radwan	PROPN
ma-100	366	25	,	,	PUNCT
ma-100	366	26	synchronization	synchronization	NOUN
ma-100	366	27	and	and	CCONJ
ma-100	366	28	fpga	fpga	PROPN
ma-100	366	29	realizationof	realizationof	NOUN
ma-100	366	30	fractional	fractional	ADJ
ma-100	366	31	-	-	PUNCT
ma-100	366	32	order	order	NOUN
ma-100	366	33	izhikevich	izhikevich	PROPN
ma-100	366	34	neuron	neuron	PROPN
ma-100	366	35	model	model	PROPN
ma-100	366	36	,	,	PUNCT
ma-100	366	37	microelectronics	microelectronic	NOUN
ma-100	366	38	j.	j.	PROPN
ma-100	366	39	89	89	NUM
ma-100	366	40	(	(	PUNCT
ma-100	366	41	2019	2019	NUM
ma-100	366	42	)	)	PUNCT
ma-100	366	43	56–69	56–69	NUM
ma-100	366	44	.	.	PUNCT
ma-100	367	1	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
ma-100	367	2	.	.	PUNCT
ma-100	368	1	mejo.2019.05.003.[28	mejo.2019.05.003.[28	PROPN
ma-100	368	2	]	]	X
ma-100	368	3	a.	a.	NOUN
ma-100	368	4	mondal	mondal	PROPN
ma-100	368	5	,	,	PUNCT
ma-100	368	6	s.k	s.k	PROPN
ma-100	368	7	.	.	PROPN
ma-100	368	8	sharma	sharma	PROPN
ma-100	368	9	,	,	PUNCT
ma-100	368	10	r.k	r.k	PROPN
ma-100	368	11	.	.	PROPN
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ma-100	368	22	-	-	PUNCT
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ma-100	368	25	-	-	PUNCT
ma-100	368	26	rinzelbursting	rinzelburste	VERB
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ma-100	368	28	model	model	NOUN
ma-100	368	29	and	and	CCONJ
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ma-100	368	31	coupled	couple	VERB
ma-100	368	32	dynamics	dynamic	NOUN
ma-100	368	33	,	,	PUNCT
ma-100	368	34	sci	sci	PROPN
ma-100	368	35	.	.	PROPN
ma-100	368	36	rep	rep	PROPN
ma-100	368	37	.	.	PROPN
ma-100	368	38	9	9	NUM
ma-100	368	39	(	(	PUNCT
ma-100	368	40	2019	2019	NUM
ma-100	368	41	)	)	PUNCT
ma-100	368	42	15721	15721	NUM
ma-100	368	43	.	.	PUNCT
ma-100	369	1	https://doi.org/10.1038/	https://doi.org/10.1038/	PROPN
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ma-100	369	3	-	-	PUNCT
ma-100	369	4	019	019	NUM
ma-100	369	5	-	-	PUNCT
ma-100	369	6	52061	52061	NUM
ma-100	369	7	-	-	SYM
ma-100	369	8	4.[29	4.[29	X
ma-100	369	9	]	]	X
ma-100	369	10	k.s	k.s	PROPN
ma-100	369	11	.	.	PROPN
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ma-100	369	13	,	,	PUNCT
ma-100	369	14	b.	b.	PROPN
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ma-100	369	16	,	,	PUNCT
ma-100	369	17	an	an	DET
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ma-100	369	19	to	to	ADP
ma-100	369	20	the	the	DET
ma-100	369	21	fractional	fractional	ADJ
ma-100	369	22	calculus	calculus	NOUN
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ma-100	369	24	fractional	fractional	ADJ
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ma-100	369	26	equations	equation	NOUN
ma-100	369	27	,	,	PUNCT
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ma-100	369	31	]	]	X
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ma-100	369	34	,	,	PUNCT
ma-100	369	35	fractional	fractional	ADJ
ma-100	369	36	differential	differential	ADJ
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ma-100	369	38	:	:	PUNCT
ma-100	369	39	an	an	DET
ma-100	369	40	introduction	introduction	NOUN
ma-100	369	41	to	to	ADP
ma-100	369	42	fractional	fractional	ADJ
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ma-100	369	44	,	,	PUNCT
ma-100	369	45	fractional	fractional	ADJ
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ma-100	369	48	-	-	PUNCT
ma-100	369	49	tions	tion	NOUN
ma-100	369	50	,	,	PUNCT
ma-100	369	51	to	to	ADP
ma-100	369	52	methods	method	NOUN
ma-100	369	53	of	of	ADP
ma-100	369	54	their	their	PRON
ma-100	369	55	solution	solution	NOUN
ma-100	369	56	and	and	CCONJ
ma-100	369	57	some	some	PRON
ma-100	369	58	of	of	ADP
ma-100	369	59	their	their	PRON
ma-100	369	60	applications	application	NOUN
ma-100	369	61	,	,	PUNCT
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ma-100	369	65	]	]	X
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ma-100	369	73	models	model	NOUN
ma-100	369	74	of	of	ADP
ma-100	369	75	differential	differential	ADJ
ma-100	369	76	equations	equation	NOUN
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ma-100	369	81	1994.[32	1994.[32	PROPN
ma-100	369	82	]	]	X
ma-100	369	83	r.e	r.e	PROPN
ma-100	369	84	.	.	PROPN
ma-100	369	85	mickens	mickens	PROPN
ma-100	369	86	,	,	PUNCT
ma-100	369	87	nonstandard	nonstandard	ADJ
ma-100	369	88	finite	finite	ADJ
ma-100	369	89	difference	difference	NOUN
ma-100	369	90	schemes	scheme	NOUN
ma-100	369	91	for	for	ADP
ma-100	369	92	reaction	reaction	NOUN
ma-100	369	93	-	-	PUNCT
ma-100	369	94	diffusion	diffusion	NOUN
ma-100	369	95	equations	equation	NOUN
ma-100	369	96	,	,	PUNCT
ma-100	369	97	numer	numer	NOUN
ma-100	369	98	.	.	PUNCT
ma-100	369	99	meth	meth	PROPN
ma-100	369	100	.	.	PUNCT
ma-100	370	1	part	part	NOUN
ma-100	370	2	.	.	PUNCT
ma-100	371	1	differ	differ	VERB
ma-100	371	2	.	.	PUNCT
ma-100	372	1	equ.15	equ.15	NOUN
ma-100	372	2	(	(	PUNCT
ma-100	372	3	1999	1999	NUM
ma-100	372	4	)	)	PUNCT
ma-100	373	1	201–214	201–214	NUM
ma-100	373	2	.	.	PUNCT
ma-100	374	1	https://doi.org/10.1002/(sici)1098-2426(199903)15:2<201::aid-num5>3.0.co;2-h	https://doi.org/10.1002/(sici)1098-2426(199903)15:2<201::aid-num5>3.0.co;2-h	PROPN
ma-100	374	2	.	.	PROPN
ma-100	374	3	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	375	1	https://doi.org/10.1142/s0218127400000840	https://doi.org/10.1142/s0218127400000840	NOUN
ma-100	375	2	https://doi.org/10.1142/s0218127400000840	https://doi.org/10.1142/s0218127400000840	NOUN
ma-100	375	3	https://doi.org/10.1007/978-1-4612-1828-9	https://doi.org/10.1007/978-1-4612-1828-9	PROPN
ma-100	376	1	https://doi.org/10.1007/978-1-4612-1828-9	https://doi.org/10.1007/978-1-4612-1828-9	PROPN
ma-100	376	2	https://doi.org/10.1113/jphysiol.1948.sp004260	https://doi.org/10.1113/jphysiol.1948.sp004260	PROPN
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ma-100	376	5	https://doi.org/10.1007/978-0-387-87708-2	https://doi.org/10.1007/978-0-387-87708-2	ADJ
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ma-100	376	8	https://doi.org/10.1016/j.camwa.2012.01.005	https://doi.org/10.1016/j.camwa.2012.01.005	PRON
ma-100	376	9	https://doi.org/10.1038/nn.2212	https://doi.org/10.1038/nn.2212	NOUN
ma-100	376	10	https://doi.org/10.1016/j.apm.2019.12.008	https://doi.org/10.1016/j.apm.2019.12.008	NOUN
ma-100	376	11	https://doi.org/10.1016/j.apm.2019.12.008	https://doi.org/10.1016/j.apm.2019.12.008	NOUN
ma-100	376	12	https://doi.org/10.1016/j.cnsns.2013.10.032	https://doi.org/10.1016/j.cnsns.2013.10.032	PROPN
ma-100	376	13	https://doi.org/10.1007/s11571-013-9273-x	https://doi.org/10.1007/s11571-013-9273-x	NOUN
ma-100	376	14	https://doi.org/10.1142/s0218127417502091	https://doi.org/10.1142/s0218127417502091	PROPN
ma-100	376	15	https://doi.org/10.1142/s0218127417502091	https://doi.org/10.1142/s0218127417502091	NUM
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ma-100	376	17	https://doi.org/10.1016/j.mejo.2019.05.003	https://doi.org/10.1016/j.mejo.2019.05.003	PROPN
ma-100	376	18	https://doi.org/10.1016/j.mejo.2019.05.003	https://doi.org/10.1016/j.mejo.2019.05.003	PROPN
ma-100	376	19	https://doi.org/10.1038/s41598-019-52061-4	https://doi.org/10.1038/s41598-019-52061-4	NUM
ma-100	376	20	https://doi.org/10.1038/s41598-019-52061-4	https://doi.org/10.1038/s41598-019-52061-4	NUM
ma-100	376	21	https://doi.org/10.1002/(sici)1098-2426(199903)15:2<201::aid-num5>3.0.co;2-h	https://doi.org/10.1002/(sici)1098-2426(199903)15:2<201::aid-num5>3.0.co;2-h	PROPN
ma-100	376	22	eur	eur	PROPN
ma-100	376	23	.	.	PUNCT
ma-100	377	1	j.	j.	PROPN
ma-100	377	2	math	math	PROPN
ma-100	377	3	.	.	PUNCT
ma-100	378	1	anal	anal	PROPN
ma-100	378	2	.	.	PUNCT
ma-100	379	1	10.28924	10.28924	NUM
ma-100	379	2	/	/	SYM
ma-100	379	3	ada	ada	PROPN
ma-100	379	4	/	/	SYM
ma-100	379	5	ma.3.2	ma.3.2	PROPN
ma-100	379	6	27	27	NUM
ma-100	379	7	[	[	SYM
ma-100	379	8	33	33	NUM
ma-100	379	9	]	]	X
ma-100	379	10	r.e	r.e	PROPN
ma-100	379	11	.	.	PROPN
ma-100	379	12	mickens	mickens	PROPN
ma-100	379	13	,	,	PUNCT
ma-100	379	14	a	a	DET
ma-100	379	15	nonstandard	nonstandard	ADJ
ma-100	379	16	finite	finite	ADJ
ma-100	379	17	difference	difference	NOUN
ma-100	379	18	scheme	scheme	NOUN
ma-100	379	19	for	for	ADP
ma-100	379	20	a	a	DET
ma-100	379	21	fisher	fisher	PROPN
ma-100	379	22	pde	pde	PROPN
ma-100	379	23	having	have	VERB
ma-100	379	24	nonlinear	nonlinear	ADJ
ma-100	379	25	diffusion	diffusion	NOUN
ma-100	379	26	,	,	PUNCT
ma-100	379	27	computers	computer	NOUN
ma-100	379	28	math.appl	math.appl	NOUN
ma-100	379	29	.	.	PUNCT
ma-100	380	1	45	45	NUM
ma-100	380	2	(	(	PUNCT
ma-100	380	3	2003	2003	NUM
ma-100	380	4	)	)	PUNCT
ma-100	381	1	429–436	429–436	NUM
ma-100	381	2	.	.	PUNCT
ma-100	382	1	https://doi.org/10.1016/s0898-1221(03)80028-7.[34	https://doi.org/10.1016/s0898-1221(03)80028-7.[34	NOUN
ma-100	382	2	]	]	X
ma-100	382	3	r.	r.	PROPN
ma-100	382	4	anguelov	anguelov	PROPN
ma-100	382	5	,	,	PUNCT
ma-100	382	6	j.m.s	j.m.s	PROPN
ma-100	382	7	.	.	PUNCT
ma-100	383	1	lubuma	lubuma	PROPN
ma-100	383	2	,	,	PUNCT
ma-100	383	3	contributions	contribution	NOUN
ma-100	383	4	to	to	ADP
ma-100	383	5	the	the	DET
ma-100	383	6	mathematics	mathematic	NOUN
ma-100	383	7	of	of	ADP
ma-100	383	8	the	the	DET
ma-100	383	9	nonstandard	nonstandard	ADJ
ma-100	383	10	finite	finite	ADJ
ma-100	383	11	difference	difference	NOUN
ma-100	383	12	method	method	NOUN
ma-100	383	13	andapplications	andapplication	NOUN
ma-100	383	14	,	,	PUNCT
ma-100	383	15	numer	numer	NOUN
ma-100	383	16	.	.	PUNCT
ma-100	383	17	meth	meth	PROPN
ma-100	383	18	.	.	PUNCT
ma-100	384	1	part	part	NOUN
ma-100	384	2	.	.	PUNCT
ma-100	385	1	differ	differ	VERB
ma-100	385	2	.	.	PUNCT
ma-100	386	1	equ	equ	PROPN
ma-100	386	2	.	.	PROPN
ma-100	386	3	17	17	NUM
ma-100	386	4	(	(	PUNCT
ma-100	386	5	2001	2001	NUM
ma-100	386	6	)	)	PUNCT
ma-100	387	1	518–543	518–543	NUM
ma-100	387	2	.	.	PUNCT
ma-100	388	1	https://doi.org/10.1002/num.1025.[35	https://doi.org/10.1002/num.1025.[35	PROPN
ma-100	388	2	]	]	X
ma-100	388	3	c.	c.	PROPN
ma-100	388	4	morris	morris	PROPN
ma-100	388	5	,	,	PUNCT
ma-100	388	6	h.	h.	PROPN
ma-100	388	7	lecar	lecar	PROPN
ma-100	388	8	,	,	PUNCT
ma-100	388	9	voltage	voltage	NOUN
ma-100	388	10	oscillations	oscillation	NOUN
ma-100	388	11	in	in	ADP
ma-100	388	12	the	the	DET
ma-100	388	13	barnacle	barnacle	NOUN
ma-100	388	14	giant	giant	ADJ
ma-100	388	15	muscle	muscle	NOUN
ma-100	388	16	fiber	fiber	NOUN
ma-100	388	17	,	,	PUNCT
ma-100	388	18	biophys	biophy	NOUN
ma-100	388	19	.	.	PUNCT
ma-100	389	1	j.	j.	PROPN
ma-100	389	2	35	35	NUM
ma-100	389	3	(	(	PUNCT
ma-100	389	4	1981	1981	NUM
ma-100	389	5	)	)	PUNCT
ma-100	389	6	193–213	193–213	NUM
ma-100	389	7	.	.	PUNCT
ma-100	389	8	https	https	NOUN
ma-100	389	9	:	:	PUNCT
ma-100	389	10	//doi.org/10.1016	//doi.org/10.1016	PROPN
ma-100	389	11	/	/	SYM
ma-100	389	12	s0006	s0006	NOUN
ma-100	389	13	-	-	PUNCT
ma-100	389	14	3495(81)84782	3495(81)84782	NUM
ma-100	389	15	-	-	PUNCT
ma-100	389	16	0.[36	0.[36	NOUN
ma-100	389	17	]	]	X
ma-100	389	18	r.	r.	PROPN
ma-100	389	19	fitzhugh	fitzhugh	PROPN
ma-100	389	20	,	,	PUNCT
ma-100	389	21	impulses	impulse	NOUN
ma-100	389	22	and	and	CCONJ
ma-100	389	23	physiological	physiological	ADJ
ma-100	389	24	states	state	NOUN
ma-100	389	25	in	in	ADP
ma-100	389	26	theoretical	theoretical	ADJ
ma-100	389	27	models	model	NOUN
ma-100	389	28	of	of	ADP
ma-100	389	29	nerve	nerve	NOUN
ma-100	389	30	membrane	membrane	NOUN
ma-100	389	31	,	,	PUNCT
ma-100	389	32	biophys	biophy	NOUN
ma-100	389	33	.	.	PUNCT
ma-100	390	1	j.	j.	PROPN
ma-100	390	2	1	1	NUM
ma-100	390	3	(	(	PUNCT
ma-100	390	4	1961)445–466	1961)445–466	NUM
ma-100	390	5	.	.	PUNCT
ma-100	391	1	https://doi.org/10.1016/s0006-3495(61)86902-6.[37	https://doi.org/10.1016/s0006-3495(61)86902-6.[37	PROPN
ma-100	391	2	]	]	X
ma-100	391	3	t.	t.	PROPN
ma-100	391	4	azizi	azizi	PROPN
ma-100	391	5	,	,	PUNCT
ma-100	391	6	r.	r.	PROPN
ma-100	391	7	mugabi	mugabi	PROPN
ma-100	391	8	,	,	PUNCT
ma-100	391	9	the	the	DET
ma-100	391	10	phenomenon	phenomenon	NOUN
ma-100	391	11	of	of	ADP
ma-100	391	12	neural	neural	ADJ
ma-100	391	13	bursting	bursting	NOUN
ma-100	391	14	and	and	CCONJ
ma-100	391	15	spiking	spike	VERB
ma-100	391	16	in	in	ADP
ma-100	391	17	neurons	neuron	NOUN
ma-100	391	18	:	:	PUNCT
ma-100	391	19	morris	morris	ADJ
ma-100	391	20	-	-	PUNCT
ma-100	391	21	lecar	lecar	ADJ
ma-100	391	22	model	model	NOUN
ma-100	391	23	,	,	PUNCT
ma-100	391	24	appl	appl	PROPN
ma-100	391	25	.	.	PUNCT
ma-100	392	1	math.11	math.11	PROPN
ma-100	392	2	(	(	PUNCT
ma-100	392	3	2020	2020	NUM
ma-100	392	4	)	)	PUNCT
ma-100	392	5	203–226	203–226	NUM
ma-100	392	6	.	.	PUNCT
ma-100	393	1	https://doi.org/10.4236/am.2020.113017.[38	https://doi.org/10.4236/am.2020.113017.[38	PRON
ma-100	393	2	]	]	PUNCT
ma-100	393	3	t.	t.	PROPN
ma-100	393	4	azizi	azizi	PROPN
ma-100	393	5	,	,	PUNCT
ma-100	393	6	b.	b.	PROPN
ma-100	393	7	alali	alali	PROPN
ma-100	393	8	,	,	PUNCT
ma-100	393	9	impact	impact	NOUN
ma-100	393	10	of	of	ADP
ma-100	393	11	chloride	chloride	ADJ
ma-100	393	12	channel	channel	NOUN
ma-100	393	13	on	on	ADP
ma-100	393	14	spiking	spike	VERB
ma-100	393	15	patterns	pattern	NOUN
ma-100	393	16	of	of	ADP
ma-100	393	17	morris	morris	PROPN
ma-100	393	18	-	-	PUNCT
ma-100	393	19	lecar	lecar	NOUN
ma-100	393	20	model	model	NOUN
ma-100	393	21	,	,	PUNCT
ma-100	393	22	appl	appl	PROPN
ma-100	393	23	.	.	PROPN
ma-100	393	24	math	math	NOUN
ma-100	393	25	.	.	PUNCT
ma-100	394	1	11	11	NUM
ma-100	394	2	(	(	PUNCT
ma-100	394	3	2020)650–669	2020)650–669	NUM
ma-100	394	4	.	.	PUNCT
ma-100	395	1	https://doi.org/10.4236/am.2020.117044.[39	https://doi.org/10.4236/am.2020.117044.[39	X
ma-100	395	2	]	]	X
ma-100	395	3	t.	t.	PROPN
ma-100	395	4	azizi	azizi	PROPN
ma-100	395	5	,	,	PUNCT
ma-100	395	6	mathematical	mathematical	ADJ
ma-100	395	7	modeling	modeling	NOUN
ma-100	395	8	with	with	ADP
ma-100	395	9	applications	application	NOUN
ma-100	395	10	in	in	ADP
ma-100	395	11	biological	biological	ADJ
ma-100	395	12	systems	system	NOUN
ma-100	395	13	,	,	PUNCT
ma-100	395	14	physiology	physiology	NOUN
ma-100	395	15	,	,	PUNCT
ma-100	395	16	and	and	CCONJ
ma-100	395	17	neuroscience	neuroscience	NOUN
ma-100	395	18	,	,	PUNCT
ma-100	395	19	kansasstate	kansasstate	PROPN
ma-100	395	20	university	university	PROPN
ma-100	395	21	,	,	PUNCT
ma-100	395	22	2021.[40	2021.[40	NUM
ma-100	395	23	]	]	X
ma-100	395	24	t.	t.	PROPN
ma-100	395	25	azizi	azizi	PROPN
ma-100	395	26	,	,	PUNCT
ma-100	395	27	b.	b.	PROPN
ma-100	395	28	alali	alali	PROPN
ma-100	395	29	,	,	PUNCT
ma-100	395	30	g.	g.	PROPN
ma-100	395	31	kerr	kerr	PROPN
ma-100	395	32	,	,	PUNCT
ma-100	395	33	mathematical	mathematical	ADJ
ma-100	395	34	modeling	modeling	NOUN
ma-100	395	35	:	:	PUNCT
ma-100	395	36	with	with	ADP
ma-100	395	37	applications	application	NOUN
ma-100	395	38	in	in	ADP
ma-100	395	39	physics	physics	NOUN
ma-100	395	40	,	,	PUNCT
ma-100	395	41	biology	biology	NOUN
ma-100	395	42	,	,	PUNCT
ma-100	395	43	chemistry	chemistry	NOUN
ma-100	395	44	,	,	PUNCT
ma-100	395	45	and	and	CCONJ
ma-100	395	46	engineering	engineering	NOUN
ma-100	395	47	,	,	PUNCT
ma-100	395	48	edition-2	edition-2	PROPN
ma-100	395	49	,	,	PUNCT
ma-100	395	50	(	(	PUNCT
ma-100	395	51	2021	2021	NUM
ma-100	395	52	)	)	PUNCT
ma-100	395	53	1–117	1–117	NUM
ma-100	395	54	.	.	PUNCT
ma-100	396	1	https://doi.org/10.9734/bpi/mono/978-93-91312-16-9.[41	https://doi.org/10.9734/bpi/mono/978-93-91312-16-9.[41	PROPN
ma-100	396	2	]	]	X
ma-100	396	3	r.k	r.k	PROPN
ma-100	396	4	.	.	PROPN
ma-100	396	5	upadhyay	upadhyay	PROPN
ma-100	396	6	,	,	PUNCT
ma-100	396	7	a.	a.	NOUN
ma-100	396	8	mondal	mondal	PROPN
ma-100	396	9	,	,	PUNCT
ma-100	396	10	dynamics	dynamic	NOUN
ma-100	396	11	of	of	ADP
ma-100	396	12	fractional	fractional	ADJ
ma-100	396	13	order	order	NOUN
ma-100	396	14	modified	modify	VERB
ma-100	396	15	morris	morris	ADJ
ma-100	396	16	-	-	PUNCT
ma-100	396	17	lecar	lecar	ADJ
ma-100	396	18	neural	neural	ADJ
ma-100	396	19	model	model	NOUN
ma-100	396	20	,	,	PUNCT
ma-100	396	21	netw	netw	NOUN
ma-100	396	22	.	.	PUNCT
ma-100	397	1	biol	biol	PROPN
ma-100	397	2	.	.	PUNCT
ma-100	398	1	5	5	NUM
ma-100	398	2	(	(	PUNCT
ma-100	398	3	2015)113	2015)113	PROPN
ma-100	398	4	-	-	PUNCT
ma-100	398	5	136.[42	136.[42	PROPN
ma-100	398	6	]	]	X
ma-100	398	7	g.	g.	PROPN
ma-100	398	8	qi	qi	PROPN
ma-100	398	9	,	,	PUNCT
ma-100	398	10	y.	y.	PROPN
ma-100	398	11	wu	wu	PROPN
ma-100	398	12	,	,	PUNCT
ma-100	398	13	j.	j.	PROPN
ma-100	398	14	hu	hu	PROPN
ma-100	398	15	,	,	PUNCT
ma-100	398	16	abundant	abundant	ADJ
ma-100	398	17	firing	firing	NOUN
ma-100	398	18	patterns	pattern	NOUN
ma-100	398	19	in	in	ADP
ma-100	398	20	a	a	DET
ma-100	398	21	memristive	memristive	ADJ
ma-100	398	22	morris	morris	PROPN
ma-100	398	23	–	–	PUNCT
ma-100	398	24	lecar	lecar	ADJ
ma-100	398	25	neuron	neuron	PROPN
ma-100	398	26	model	model	PROPN
ma-100	398	27	,	,	PUNCT
ma-100	398	28	int	int	PROPN
ma-100	398	29	.	.	PUNCT
ma-100	399	1	j.	j.	PROPN
ma-100	399	2	bifurcation	bifurcation	PROPN
ma-100	399	3	chaos.31	chaos.31	PROPN
ma-100	399	4	(	(	PUNCT
ma-100	399	5	2021	2021	NUM
ma-100	399	6	)	)	PUNCT
ma-100	399	7	2150170	2150170	NUM
ma-100	399	8	.	.	PUNCT
ma-100	400	1	https://doi.org/10.1142/s0218127421501704.[43	https://doi.org/10.1142/s0218127421501704.[43	CCONJ
ma-100	400	2	]	]	X
ma-100	400	3	m.	m.	NOUN
ma-100	400	4	xing	xing	PROPN
ma-100	400	5	,	,	PUNCT
ma-100	400	6	x.	x.	NOUN
ma-100	400	7	song	song	PROPN
ma-100	400	8	,	,	PUNCT
ma-100	400	9	h.	h.	PROPN
ma-100	400	10	wang	wang	PROPN
ma-100	400	11	,	,	PUNCT
ma-100	400	12	z.	z.	PROPN
ma-100	400	13	yang	yang	PROPN
ma-100	400	14	,	,	PUNCT
ma-100	400	15	y.	y.	PROPN
ma-100	400	16	chen	chen	PROPN
ma-100	400	17	,	,	PUNCT
ma-100	400	18	frequency	frequency	NOUN
ma-100	400	19	synchronization	synchronization	NOUN
ma-100	400	20	and	and	CCONJ
ma-100	400	21	excitabilities	excitability	NOUN
ma-100	400	22	of	of	ADP
ma-100	400	23	two	two	NUM
ma-100	400	24	coupled	couple	VERB
ma-100	400	25	hetero	hetero	NOUN
ma-100	400	26	-	-	PUNCT
ma-100	400	27	geneous	geneous	ADJ
ma-100	400	28	morris	morris	NOUN
ma-100	400	29	-	-	PUNCT
ma-100	400	30	lecar	lecar	ADJ
ma-100	400	31	neurons	neuron	NOUN
ma-100	400	32	,	,	PUNCT
ma-100	400	33	chaos	chaos	NOUN
ma-100	400	34	solitons	soliton	NOUN
ma-100	400	35	fractals	fractal	NOUN
ma-100	400	36	.	.	PUNCT
ma-100	401	1	157	157	NUM
ma-100	401	2	(	(	PUNCT
ma-100	401	3	2022	2022	NUM
ma-100	401	4	)	)	PUNCT
ma-100	401	5	111959	111959	NUM
ma-100	401	6	.	.	PUNCT
ma-100	402	1	https://doi.org/10.1016/j.chaos	https://doi.org/10.1016/j.chaos	NOUN
ma-100	402	2	.	.	PUNCT
ma-100	403	1	2022.111959.[44	2022.111959.[44	NOUN
ma-100	403	2	]	]	PUNCT
ma-100	403	3	m.m	m.m	PROPN
ma-100	403	4	.	.	PROPN
ma-100	403	5	meerschaert	meerschaert	PROPN
ma-100	403	6	,	,	PUNCT
ma-100	403	7	c.	c.	PROPN
ma-100	403	8	tadjeran	tadjeran	NOUN
ma-100	403	9	,	,	PUNCT
ma-100	403	10	finite	finite	ADJ
ma-100	403	11	difference	difference	NOUN
ma-100	403	12	approximations	approximation	NOUN
ma-100	403	13	for	for	ADP
ma-100	403	14	fractional	fractional	ADJ
ma-100	403	15	advection	advection	NOUN
ma-100	403	16	–	–	PUNCT
ma-100	403	17	dispersion	dispersion	NOUN
ma-100	403	18	flow	flow	NOUN
ma-100	403	19	equations	equation	NOUN
ma-100	403	20	,	,	PUNCT
ma-100	403	21	j.	j.	PROPN
ma-100	403	22	comput	comput	PROPN
ma-100	403	23	.	.	PUNCT
ma-100	404	1	appl	appl	PROPN
ma-100	404	2	.	.	PROPN
ma-100	404	3	math	math	NOUN
ma-100	404	4	.	.	PUNCT
ma-100	405	1	172	172	NUM
ma-100	405	2	(	(	PUNCT
ma-100	405	3	2004	2004	NUM
ma-100	405	4	)	)	PUNCT
ma-100	405	5	65–77	65–77	NUM
ma-100	405	6	.	.	PUNCT
ma-100	406	1	https://doi.org/10.1016/j.cam.2004.01.033.[45	https://doi.org/10.1016/j.cam.2004.01.033.[45	PROPN
ma-100	406	2	]	]	PUNCT
ma-100	406	3	d.m	d.m	PROPN
ma-100	406	4	.	.	PROPN
ma-100	406	5	grobman	grobman	PROPN
ma-100	406	6	,	,	PUNCT
ma-100	406	7	homeomorphism	homeomorphism	NOUN
ma-100	406	8	of	of	ADP
ma-100	406	9	systems	system	NOUN
ma-100	406	10	of	of	ADP
ma-100	406	11	differential	differential	ADJ
ma-100	406	12	equations	equation	NOUN
ma-100	406	13	,	,	PUNCT
ma-100	406	14	dokl	dokl	NOUN
ma-100	406	15	.	.	PUNCT
ma-100	407	1	akad	akad	PROPN
ma-100	407	2	.	.	PUNCT
ma-100	408	1	nauk	nauk	PROPN
ma-100	408	2	sssr	sssr	NOUN
ma-100	408	3	128	128	NUM
ma-100	408	4	(	(	PUNCT
ma-100	408	5	1959	1959	NUM
ma-100	408	6	)	)	PUNCT
ma-100	409	1	880–881[46	880–881[46	PROPN
ma-100	409	2	]	]	PUNCT
ma-100	410	1	p.	p.	PROPN
ma-100	410	2	hartman	hartman	PROPN
ma-100	410	3	,	,	PUNCT
ma-100	410	4	on	on	ADP
ma-100	410	5	local	local	ADJ
ma-100	410	6	homeomorphisms	homeomorphism	NOUN
ma-100	410	7	of	of	ADP
ma-100	410	8	euclidean	euclidean	ADJ
ma-100	410	9	spaces	space	NOUN
ma-100	410	10	,	,	PUNCT
ma-100	410	11	bol	bol	NOUN
ma-100	410	12	.	.	PUNCT
ma-100	411	1	soc	soc	PROPN
ma-100	411	2	.	.	PUNCT
ma-100	412	1	mat	mat	PROPN
ma-100	412	2	.	.	PUNCT
ma-100	413	1	mexicana	mexicana	PROPN
ma-100	413	2	,	,	PUNCT
ma-100	413	3	5	5	NUM
ma-100	413	4	(	(	PUNCT
ma-100	413	5	1960	1960	NUM
ma-100	413	6	)	)	PUNCT
ma-100	413	7	,	,	PUNCT
ma-100	413	8	220	220	NUM
ma-100	413	9	-	-	SYM
ma-100	413	10	241.[47	241.[47	NUM
ma-100	413	11	]	]	PUNCT
ma-100	413	12	p.	p.	PROPN
ma-100	413	13	hartman	hartman	PROPN
ma-100	413	14	,	,	PUNCT
ma-100	413	15	a	a	DET
ma-100	413	16	lemma	lemma	PROPN
ma-100	413	17	in	in	ADP
ma-100	413	18	the	the	DET
ma-100	413	19	theory	theory	NOUN
ma-100	413	20	of	of	ADP
ma-100	413	21	structural	structural	ADJ
ma-100	413	22	stability	stability	NOUN
ma-100	413	23	of	of	ADP
ma-100	413	24	differential	differential	ADJ
ma-100	413	25	equations	equation	NOUN
ma-100	413	26	,	,	PUNCT
ma-100	413	27	proc	proc	NOUN
ma-100	413	28	.	.	PUNCT
ma-100	414	1	amer	amer	PROPN
ma-100	414	2	.	.	PUNCT
ma-100	414	3	math	math	PROPN
ma-100	414	4	.	.	PUNCT
ma-100	415	1	soc	soc	PROPN
ma-100	415	2	.	.	PUNCT
ma-100	416	1	11	11	NUM
ma-100	416	2	(	(	PUNCT
ma-100	416	3	1960)610–620	1960)610–620	NUM
ma-100	416	4	.	.	PUNCT
ma-100	417	1	https://doi.org/10.1090/s0002-9939-1960-0121542-7	https://doi.org/10.1090/s0002-9939-1960-0121542-7	PROPN
ma-100	417	2	.	.	PUNCT
ma-100	417	3	https://doi.org/10.28924/ada/ma.3.2	https://doi.org/10.28924/ada/ma.3.2	PROPN
ma-100	417	4	https://doi.org/10.1016/s0898-1221(03)80028-7	https://doi.org/10.1016/s0898-1221(03)80028-7	PROPN
ma-100	417	5	https://doi.org/10.1002/num.1025	https://doi.org/10.1002/num.1025	NOUN
ma-100	417	6	https://doi.org/10.1016/s0006-3495(81)84782-0	https://doi.org/10.1016/s0006-3495(81)84782-0	PROPN
ma-100	417	7	https://doi.org/10.1016/s0006-3495(81)84782-0	https://doi.org/10.1016/s0006-3495(81)84782-0	NOUN
ma-100	417	8	https://doi.org/10.1016/s0006-3495(61)86902-6	https://doi.org/10.1016/s0006-3495(61)86902-6	ADJ
ma-100	417	9	https://doi.org/10.4236/am.2020.113017	https://doi.org/10.4236/am.2020.113017	NOUN
ma-100	417	10	https://doi.org/10.4236/am.2020.117044	https://doi.org/10.4236/am.2020.117044	PROPN
ma-100	417	11	https://doi.org/10.9734/bpi/mono/978-93-91312-16-9	https://doi.org/10.9734/bpi/mono/978-93-91312-16-9	PROPN
ma-100	417	12	https://doi.org/10.1142/s0218127421501704	https://doi.org/10.1142/s0218127421501704	NUM
ma-100	417	13	https://doi.org/10.1016/j.chaos.2022.111959	https://doi.org/10.1016/j.chaos.2022.111959	PROPN
ma-100	417	14	https://doi.org/10.1016/j.chaos.2022.111959	https://doi.org/10.1016/j.chaos.2022.111959	PROPN
ma-100	417	15	https://doi.org/10.1016/j.cam.2004.01.033	https://doi.org/10.1016/j.cam.2004.01.033	PROPN
ma-100	417	16	https://doi.org/10.1090/s0002-9939-1960-0121542-7	https://doi.org/10.1090/s0002-9939-1960-0121542-7	PROPN
ma-100	417	17	1	1	NUM
ma-100	417	18	.	.	PUNCT
ma-100	418	1	introduction	introduction	NOUN
ma-100	418	2	2	2	NUM
ma-100	418	3	.	.	PUNCT
ma-100	418	4	grünwald	grünwald	NOUN
ma-100	418	5	-	-	PUNCT
ma-100	418	6	letinkov	letinkov	NOUN
ma-100	418	7	approximation	approximation	NOUN
ma-100	418	8	3	3	NUM
ma-100	418	9	.	.	PUNCT
ma-100	418	10	description	description	NOUN
ma-100	418	11	of	of	ADP
ma-100	418	12	model	model	NOUN
ma-100	418	13	equations	equation	NOUN
ma-100	418	14	3.1	3.1	NUM
ma-100	418	15	.	.	PUNCT
ma-100	418	16	fractional	fractional	ADJ
ma-100	418	17	morris	morris	PROPN
ma-100	418	18	-	-	PUNCT
ma-100	418	19	lecar	lecar	ADJ
ma-100	418	20	model	model	NOUN
ma-100	418	21	3.2	3.2	NUM
ma-100	418	22	.	.	PUNCT
ma-100	419	1	local	local	ADJ
ma-100	419	2	stability	stability	NOUN
ma-100	419	3	analysis	analysis	NOUN
ma-100	419	4	of	of	ADP
ma-100	419	5	fractional	fractional	ADJ
ma-100	419	6	order	order	NOUN
ma-100	419	7	morris	morris	ADJ
ma-100	419	8	-	-	PUNCT
ma-100	419	9	lecar	lecar	ADJ
ma-100	419	10	model	model	NOUN
ma-100	419	11	4	4	NUM
ma-100	419	12	.	.	PUNCT
ma-100	419	13	numerical	numerical	ADJ
ma-100	419	14	results	result	NOUN
ma-100	419	15	5	5	NUM
ma-100	419	16	.	.	PUNCT
ma-100	420	1	discussion	discussion	NOUN
ma-100	420	2	references	reference	NOUN