





















































Functioning of Declarative Memory: Intersection between Neuropsychology and Mathematics


Elementa
Intersections between Philosophy, Epistemology 
and Empirical Perspectives

1 
(2021) 

1-2

Pierpaolo Limone
Editorial 7

First Section

Slavoj Žižek
The Vagaries of the Superego 13

Ricardo Espinoza Lolas
Nature and Pandemic 33

Paolo Ponzio
Mask and Otherness between Recognition and Concealment: 47 
Notes on the Self and the You

Daniela Savino
“Liquid” Identity and Otherness in the Phenomenon 61 
of Religious Alienation: The Loss of Critical Thinking 
and the “Barter” of the Self in the System of Communion

Francesca R. Recchia Luciani
The Sexistential Vulnerability of Bodies in Contact 85 
in the Philosophy of Jean-Luc Nancy

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Elementa. Intersections between Philosophy, Epistemology and Empirical Perspectives

Second Section

Martina Rossi
Universal Design for Learning and Inclusive Teaching: 103 
Future Perspectives

Marco Ceccarelli
A Historical Account on Italian Mechanism Models 115

Giusi Antonia Toto - Alessia Scarinci
Cyberfeminism: A Relationship between Cyberspace, 135 
Technology, and the Internet

Luigi Traetta - Federica Doronzo
Super-Ego after Freud: A Lesson not to Be Forgotten 153

Federica Doronzo - Gianvito Calabrese
Functioning of Declarative Memory: Intersection 163 
between Neuropsychology and Mathematics

Giuliana Nardacchione - Guendalina Peconio
Peer Tutoring and Scaffolding Principle for Inclusive Teaching 181

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Functioning of Declarative Memory: 
Intersection between Neuropsychology 
and Mathematics 1

Federica Doronzo 
1 - Gianvito Calabrese 

2

1 Learning Science hub, Università degli Studi di Foggia (Italy)
2 Yield Engineer on Semiconductor

doi: https://dx.doi.org/10.7358/elem-2021-0102-doca
federica.doronzo@unifg.it
g.calabrese.296@gmail.com

Abstract

The understanding of memory has been a constant challenge for scientific research for 
centuries. The mnemonic processes, which determine the identity of the human being, 
have been investigated through multiple points of view, such as the psychological, neuro-
physiological and physical ones. The result is complex and multifaceted visions that 
should be integrated to provide a unitary and complete interpretation. A survey of the 
most recent scientific literature is carried out on the functioning of declarative memory, 
to analyse the relationship between real information coming from the outside world, the 
encoded event and the recovered memory. The aim of the essay is to investigate the neural 
correlates, which regulate the cognitive system in question, through a dual neuropsycho-
logical-mathematical interpretation. Neuropsychology sheds light on the anatomical, 
physiological and psychic mechanisms of memory while Mathematics associates the 
corresponding mathematical configurations to neural networks. The reunification process 
between the two disciplines is achieved through neuromorphic computational simulation 
that emulates mind uploading. The assembly of artificial neurons has the potential to 
clarify in detail the memory processes, the functioning of neural correlates and to carry out 
the mapping of the biological brain. We hope that the results obtained will provide new 
knowledge on mnestic mechanisms to contribute to the evolution of disciplines such as 
General Psychology, Forensic Neuroscience, Cognitive Rehabilitation and Awake Surgery. 

1 For the purposes of academic recognition, contributions are attributed as follows: 
introduction and paragraph 1 to Federica Doronzo; paragraph 2 to Gianvito Calabrese; and 
the conclusion is the result of a shared work. 

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Keywords: declarative memory; mathematical configurations; neuromorphic 
computation; neuropsychology.

Introduction

Memory is the cognitive domain that mediates a series of processes to 
acquire and store information over time, the aim is to guide behavior and 
plan future actions for survival. This function is fundamental for the human 
being as long-lasting memories form the basis of identity that is a self/
hetero perception of oneself and of the relationship between the self and 
the world. In particular, declarative memory is involved in the integration 
of individual experiences with the socio-cultural knowledge of the world. 

The four fundamental processes of memory are: coding, consoli-
dation, storage and retrieval. Coding is the processing of information 
(sensory analysis and attribution of meaning), the consolidation allows the 
generation of a representation, the storage consists in the recording of data 
in the storage-memory and the recovery phase is the recall mechanism of 
the memory. Recently Dudai (2012) confirmed the existence of another 
process, such as reconsolidation which is an extension of the phenomenon 
of memory consolidation. When a memory is recovered or reactivated it 
must be consolidated again, increasing the possibility that the reconsoli-
dated memory may include new information not present in the original 
version of the event. 

The multi-warehouse model, which evolved from James’ first theo-
rization in 1890, is the most accredited paradigm in the literature and 
provides for the subdivision of memory into hierarchically organized 
modules. A fundamental distinction concerns the component of temporal 
retention which determines the following subdivision: working memory, 
sensory memory and long-term memory. The latter can be classified into 
declarative (explicit), that is, conscious memory of events and facts, and 
non-declarative (implicit) which consists of memories expressed through 
the execution of actions regardless of awareness. 

The most recent model is the MNESIS model, i.e. Memory Neo-
Structural Inter-Systemic, in which the memory consists of interconnected 
sub-systems (Eustache, Viard, & Desgranges, 2016). The three modules of 
long-term representation (perceptual memory, semantic memory, episodic 
memory) interact with each other through the processes of consolidation 2 

 2 Phenomenon of reliving experiences: a still faint trace is converted into a perma-
nent or enhanced form. 

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and semantization 3; the episodic buffer 4 acts as an intermediary between 
working memory, procedural memory and long-term memory, and the 
latter two systems in turn have direct links. The structure demonstrates 
that memories have a dynamic and reconstructive nature and memory 
operates through a distributed set of brain areas that are, interconnected 
neural networks (Fig. 1). 

Figure 1. – MNESIS. Fonte: Eustache, Viard, & Desgranges, 2016, p. 100. 

Computational Science is contributing to the understanding of brain 
functioning by designing artificial brain networks. The modeling of the 
biological brain has the potential to photograph and reproduce the neural 
configurations during the different memory processes, distinguishing brain 
activity for coding, consolidation and information retrieval. 

The key issues of the reflection in question are:
• Are past events faithfully reproduced or does the memory function 

induce constructive activities by distorting the original information?
• Is neuromorphic computing  5 a feasible project? What repercussions 

would it have with respect to the understanding of the Central Nervous 
System?

 3 Passage from episodic memory to semantic memory due to the passage of time 
which induces the loss of episodic details of memories. 
 4 In 2000, Baddeley added episodic buffer to his short-term memory model. This 
third sub-component acts as an intermediary between systems having different codes, and 
combines them into unitary, meaningful and coherent representations.
 5 New paradigm that essentially consists in assembling artificial neurons so that they 
function according to the principles of the human brain. 

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The above themes are investigated with a dual point of view, neuropsy-
chological and mathematical, in order to integrate the results and increase 
knowledge with respect to the cognitive domain of memory. Understanding 
the psycho-physiological mechanisms associated with memory processes, 
mapping the human brain and mathematically representing neural config-
urations, would allow us to answer the aforementioned questions. 

These goals would generate innumerable implications: Forensic 
Neuroscience and Cognitive Rehabilitation would implement assessments 
and interventions calibrated on the specific functioning of the memory 
process and brain activity. Furthermore, a transdisciplinary understanding 
of the construct would enrich the theories and open questions of General 
Psychology (such as reconstruction and alteration of memories) and would 
help to ensure greater safety of Awake Surgery: the facilitation of intraop-
erative mapping would precisely determine the dedicated areas of the brain 
to fundamental neurological activities and their functioning. 

1. Neuropsychological perspective

Neuropsychology has provided a significant contribution to the knowledge 
on the functioning of declarative memory through the study of both the 
healthy subject and that affected by diseases of the Central Nervous System. 
The transdisciplinary nature provides it with an added value, this paragraph 
investigates the studies and empirical evidences that clarify the declarative 
mnestic mechanisms from a psychic and physiological point of view. 

1.1. Construction and reconstruction of declarative memories

To understand how memory works, it starts by examining its character-
izing process: learning. This process, which mediates the consolidation of 
the traces, is determined by changes involving the synapses for both short-
term memory (greater neurotransmitter release) and long-term memory 
(formation of new synapses). Any experience that results in remembering 
produces physical changes in the Central Nervous System (CNS). The 
brain circuits that support the formation, storage and retrieval of declara-
tive memory converge in a hippocampus-dependent system  6. In 1937 

 6 Eichenbaum (2000) demonstrated that rats with hippocampal and parahip-
pocampal lesions lose the ability to retrieve previously acquired memories (specifically 
spatial ones). 

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Papez was among the first to identify the circuit involved in the forma-
tion of long-term memories, known as the Papez circuit, consisting of the 
projections from the hippocampal formation to the mammillary bodies 
and from the mammillary bodies to the anterior thalamus. Squire (2015) 
most recently identified the main areas of the circuit: medial temporal 
lobe, hippocampus and primary, secondary and associative cortex. The 
hippocampus and the diencephalic structures are of crucial importance 
for the formation and consolidation of memories which are subsequently 
stored throughout the brain. 

Here are four theories that differently describe how episodic memory 
works. 

Squire, in 2004, developed the Standard consolidation theory according 
to which the hippocampus acts as an “index” of access to recent memories 
for their spatial localization, for example visual elements are stored in the 
visual cortices, the sounds of words in language areas, etc. Subsequently, 
the consolidation period allows direct connection to the cortical traces of 
memories, and the hippocampus is no longer essential for the retrieval of 
information. 

Nadel and Moscovitch (1997) with the Multiple trace theory argue 
that episodic memories, more or less consolidated, are always dependent 
on the hippocampus. The temporal gradient is not associated with 
the transfer to the cortex but with the number of traces stored in the 
hippocampus: every time a memory is reactivated, a new memory trace 
is stored in the hippocampus. As a result, remote memories are encoded 
by multiple tracks and become more resistant to hippocampal damage. 
The recall can therefore alter the memory as a photograph of what really 
happened is not constructed, but rather a reconstruction of what is remem-
bered the last time one thought about the memory takes place. In 2013 
Maguire and Mullally advanced the Scene construction theory, according to 
which the hippocampus is able to reconstruct the past experience in the 
absence of the original trace. During the re-enactment of a recent event, 
the hippocampus constructs a series of coherent scenes with event through 
neocortical-hippocampal interactions. These scenes quickly fade from the 
hippocampus as the representations consolidate into adjacent cortical areas. 

Schacter and Addis (2007), with the Episodic simulation of future 
events, argue that the memory of the past and the imagination of the future 
draw on similar information stored in episodic memory, which therefore 
also supports the construction of future events by extracting and recom-
bining the information stored in a simulation of a new event. 

Bartlett provides another element in support of the distorted nature 
of memory by proposing a constructive vision of memory as early as the 

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first half of the 1900s. Cognition would not allow a duplicative process 
of reality as it is impossible to separate memory from other higher func-
tions such as thought and imagination. Memory therefore plays a role of 
active transformation of memories by integrating perception and subjec-
tive experience. This phenomenon is due to the presence of patterns, e.g. 
knowledge that everyone has about objects or events, which guide the 
memory processes. 

From these theories it emerges that declarative memory is still the 
subject of controversial studies and appears to be the result of complex 
constructive and reconstructive mechanisms dependent on extended brain 
circuits. 

The doubt about the reliability of memories arises from the first 
mnestic process of information processing. Constructivism argues that 
knowledge is necessarily dependent on the knowing subject as an active 
construction process. Objectivity is therefore an illusion: the subject intro-
duces his own order and meaning to what he experiences. The same event is 
meaning and remembered differently on the basis of one’s psycho-physical 
state (depending on the moment in which it is known), past experiences 
(which build the representations, defined by the Bowlby theory IWM 7), 
and the common sense 8 determined by the place of belonging and the inter-
actions subsequent to the occurrence of the event. Below we present some 
theories that analyze the processes that affect the reliability of memories. 

The emotion-memory interactions occur in several phases from the 
construction to recovery of the memory trace by modifying the original 
data. The amygdala modulates, according to emotions, both the encoding 
and the memorization of memories dependent on the hippocampus, 
this in turn generates episodic representations of the emotional meaning 
and interpretation of events, influencing the response of the amyg-
dala when stimuli are encountered emotional. Although the amygdala 
and hippocampus are independent, they act in concert (Phelps, 2004): 
emotions regulate memory and vice versa. The association between mood 
disorders and memory impairment is due to the fact that dysfunctional 
emotional alterations reduce the amount of cognitive resources available 
for the memory domain (Dalgleish & Power, 2004). 

 7 Individuals, through interaction with the environment and in particular with the 
caregiver, build Internal Working Models from childhood, that is, representations of them-
selves and the world. These mental structures regulate the perception and interpretation of 
events, allowing you to make predictions and create expectations about the events of your 
relational life. 
 8 Pre-conceptual sense, implicitly shared by the members of a cultural context, which 
allows people to be in tune with what is common (Stanghellini, 2008).

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The Self Memory System 9 (Conway & Pleydell-Pearce, 2000) intro-
duces another dynamic influencing memory such as the self-concept. This 
framework considers memory as a “motivated process” that is guided by 
the self-goals. Autobiographical knowledge limits what the self is, has been 
and can be, in turn the self modulates access to long-term knowledge: in 
the event of changes in the self, memory stores are radically reorganized 
(Conway, 2005). The self and memory can therefore operate indepen-
dently and influence each other. 

It is also necessary to consider that memories also interact with each 
other changing them self. This interrelation is called interference, and it is 
both the tendency of new memories to compromise the recovery of past 
memories (retroactive) and vice versa the tendency of pre-existing informa-
tion to influence new events (proactive). As a demonstration of this, it is 
observed that the mastery of a task can facilitate or hinder the learning or 
execution of a new task. 

At the end of this path, the contribution that Schacter, one of the 
most famous researcher of memory, has provided to the theme, is exhibited. 
The scientist argues that memory plays fundamental functions in everyday 
life, but that it is also vulnerable to error and delusion. He theorized the 
existence of seven sins (imperfections) by assigning to memory a construc-
tive and adaptive nature (functional to survival). Sins are divided into three 
types of phenomena: oblivion phenomena (transience, absent-mindedness, 
blocking), distortion phenomena (misattribution, suggestibility, bias) and 
pathological phenomena (persistence). Considering the evidence showing 
the pervasiveness of memory errors, Schather concludes that memory is a 
faulty process that has serious repercussions on the legal system, especially 
in the context of the accuracy of the testimony. In fact, research has shown 
that post-event suggestion can contaminate a person’s memory by inducing 
false memories. 

This discussion has presented the pitfalls to which the memory is 
exposed. What emerged has implications not only for police investiga-
tions and criminal judgments but also for other disciplinary sectors such 
as Psychotherapy which has long debated the veracity of memories. The 
novelty proposed is that Mathematics is trying to combine psychological 
phenomena with neural correlates explained in terms of mathematical 
models, to scientifically corroborate what has been observed at a behavioral 
level. 

 9 The SMS is a paradigm made up of two main components, the working self 
(complex set of active goals and associated self-images) and the knowledge of autobiograph-
ical memory. These components intertwine to form memories and self-representations. 

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1.2. The engram: from the biochemical perspective to the mathematical 
model

Neuropsychology clarifies the brain psychic and neurophysiological pro-
cesses regulating memory but does not precisely delineate the activation 
configurations of neurons in the various mnestic phases. The innovative 
connectionist model implements a computational approach of the mind: 
it attempts to simulate biological intelligence, reproducible on a computer, 
through artificial neural networks. 

Mathematical models can help provide a detailed representation of 
neural activity during the different memory processes to photograph the 
neural correlates of coding, consolidation, reconsolidation and recovery 
of memories. Emerging changing configurations in support of the 
constructive and reconstructive nature theorized by neuropsychological 
research. 

Below we describe the functioning of the learning process, at the 
basis of mathematical modelling, starting from the concept of engram. The 
engram is structured through a biochemical process by which neurons, 
which once functioned independently, begin to work together as a network. 
Daniel Hebb was the first, in 1949, to hypothesize that memories are 
stored in the brain in the form of networks of neurons. Hebb’s postulate 
states that axonic terminations, strengthened thanks to corelated activity, 
form new branches, while terminations weakened by unrelated activity lose 
their grip on the post-synaptic cell. 

Bills and Lomo, in 1973, discovered that by administering a train 
of high frequency electrical stimuli (at the hippocampus) the action 
potentials produced by subsequent stimuli were increased but only in that 
neural path (the electric current strengthened the synaptic connections 
along that away for hours or weeks). This is the long-term potentiation 
(LTP): a persistent increase in synaptic efficacy that mediates the forma-
tion of memory. This phenomenon occurs only in the presence of a close 
temporal correspondence between the paired activities of pre-synaptic and 
post-synaptic cells. 

The neural activity model gradually changes with training to become 
consistent: the synchrony index of the triggered neurons is low at the 
beginning but increases with training cycles (Zhou et al., 2020). The 
change in the dynamics of neurons from irregularity to synchronization 
coincides with the appearance of learned behaviors (e.g., mouse freezing 
for fear conditioning). Synaptic plasticity is the generative mechanism of 
memorization, the LTP with the formation of new synapses regulates the 
consolidation of memories. 

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The neuronal dynamics, which determine the memorization, can be 
described through mathematical models based on measurements of the 
voltage and time dependence of the currents that cross the membrane. 
The memorization process is interpreted as a return of the brain to the 
neuronal configuration equal to the one it had at the time of the stimulus; 
and the brain network is studied as a mathematical system having dynamic 
configurations (Luccioli, 2005). 

The neuronal network can be represented as a system of N units 
(neurons) that interact with each other at instant t. At each instant the 
network is characterized by a configuration determined by the values of 
the electrical potentials assumed by the neurons. The information is then 
represented by specific configurations where the first neuron is active 
and the second quiescent and so on. The potential that the i-th neuron 
receives from the others is defined by the sum of the potentials that the 
neurons send to the i-th neuron. A neuron will be active if the sum of 
the electrical potentials, it receives from the other neurons, exceeds its 
threshold value in analogy to what happens biologically. On the basis 
of the mathematically defined configuration it is possible to identify the 
recognition of a stimulus and compare the configurations at different 
instants, differentiating the processes of coding and retrieving informa-
tion (Doria, 1994). 

What has been discovered, biologically and mathematically, coded 
potentially makes it possible to carefully evaluate the admissibility limits 
of testimonial evidence, the memory impairments in the medical field and 
the mapping of neural networks as a function of neurosurgical interven-
tions. 

2. Mathematical perspective

The difference in scale between the biological phenomena (neural activi-
ties) and the behavioral expressions (mnestic processes) creates room for 
multiple discipline to be hosted in and, in this scenario, mathematics has 
taken its role as special guest. The mathematical modelling allows to simu-
late the association between specific neural configurations and the various 
cognitive operations laying the foundation for the data neuromorphic 
processing. 

In the current paragraph the most important milestones, success (and 
perplexities) along the artifical neural networks conceptualization roadpath 
are presented. 

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2.1. The technological keys of the mind

The difficulties involing a neuromorphic processor realization are multiple. 
In the classical computational system based on the von Neumann archi-
tecture (hardware architecture for programmable digital machines which 
shares the instructions and the data in the same memory area) the control 
processing units (CPUs) are physically separetad from the memory block, 
instead in the neural networks, processing and memorization co-exist 
inside the same synaptic structure. The increase of the completed opera-
tions by time unit (i.e. increasing clock frequency), could affect the micro-
electronic fabrication process. Considering that forcing the boundaries of 
the solid state physics is not always a chance some strategitcal workaround 
and smart tricks are needed to support the continuos improvement of the 
computer performance. First of all the multi core parallel computing and 
the hierarical organization of cache memory. For the special case of paral-
lelism, Amdahl law state that if F is the fraction of a processing which can 
be done in parallel, and (1 − F ) is the part which has to be done in serial, 
then the best achievable speedup 10 (S) using a N core machine is:

S = 
1

(1 − F ) + F
 N

(2.1)

Looking at the future of computation virtually means to reimage it: the 
brain organization is one of the most promising and ispiring technolog-
ical architecture in the roadmap of the computer evolution. The field of 
application of the neuromorphic computing are wide, as it is extensive the 
number of solution proposed to reach the final accomplishment. 

The new neuromorphic technological platform could be the most 
natural interface between human body and cybernetic prostheses. This can 
open a new window on the way to approach the nervous system diseas, 
as quadriplegia and also more complex clinical picture (Collinger et al., 
2013). For the moment this looks like more the (happy) ending of the story. 
The input processing capacity a biological system can accept (104) and 
the fan-in 11, nominal or effective, of the computation machines are order 
of magnitude different (102). Beyond the scale issue it’s the spike-timing 
design to be a deep conceptual difference in the information treatment 

 10 Computational acceleration of partially divisible algorithm due to the insertion of 
N processors in parallel. 
 11 Number of acceptable input from a circuit logic operator. 

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when comparent to the current standard. The SpiNNaker project (Spiking 
Neural Network Architecture) try to jump over the fence by a multi-core 
architecture based on the paradigm of the brain functioning (Mead, 1990). 
Its billions of computation units are able to reinforce their interconnection 
thanks to the STDP mechanism constituing an high parallel degree artifi-
cial platform. If compared to the biological systems it is not more than the 
1% of the human brain, of if it sounds more encouraging, it is equivalent 
to ten times a mouse brain (Fig. 2). 

The basic block of the SpiNNaker is the SpiNNaker multicore System-
on-Chip. The chip is a Globally Asynchronous Locally Synchronous (GALS) 
system 12 whee the nodes are represented by 18 ARM968 processors working 
in synchronized regime, grafted in a circuital infrastracture based on the 
Address-Event-Representation (AER)  13 communication protocol, which 
allows large fan-in and fan-out. The AER protocol is optimized for the real 
time housing of a great number of mini-packets able to emulate the neural 
spikes (Mead, 1990). The strong legacy of the standard management of the 
computational resources introuduced by the classic ARM processors seems 
to have been further exceeded by the TrueNorth project by IBM. The struc-
ture is made by 4096 cores which fulfil the role on neural network in turn 
integrated on a single motherboard. Each one of the core raccoglie 256 
simil-neural electronic units (approximately the size of a caterpillar’s brain) 
that allows to program 256 × 256 binary synaptic connections (Indiveri, 
2011). 

The True North is the IBM second largest chip ever made and 
only consumes 73 mW (a thousand time less than a typical commercial 
CPU) proving, as expected, a natural inclination toward the challenges 
coming from the domain of the cognitive responses or, from a more 
computer science point of view, the target themes of the machine learning 
alghorithms (Indiveri & Liu, 2015). A quantitative metric of what just 
discussed can be better defined looking at the image recognition capacity. 
The TrueNorth is able to categorize 6000 images per watt with respect to 
a canonical GPU, altought excellent, as the NVIDIA Tesla p4 GPU which 
can perform the identification of just 160 immagini for the same power 
unit. This approach seems to be most successful than SpiNNaker in terms 
of memory distribution grade (Fig. 3). 

 12 Computational architecture based on secure and robust communication between 
synchronous islands in a system of independent clock domains. 
 13 Address Event Representation (AER) is an emerging protocol dedicated to the 
communication of neuromorphic networks that aims to create a massive interconnection 
between neural units with a strong real-time focus.

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Figure 2. – Schematic representation of the GALS architecture flanked by an image 
of the SpiNNaker matrix, with the 18 cores (synchronous islands). 

Source: http://apt.cs.manchester.ac.uk.

Figure 3. – The Neurogrid Layout (to the left) is characterized by a 64 × 64 “neurosynaptic cores”. 
Each core (to the right) owns 256 neurons and 65,536 synapsis. 

Surce: IBM Research, CC BY.

 

174

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One of the main issues is the large size di questo dispositivo, 4.3 cm2, 
which makes questionable is industrial sustinability in term of die yield. 
Also assuming to miniaturize the chip consistently with the mass produc-
tion CPU size, the processor shows up a lack of plasticity/learning capacity 
which represent, instead, a choice taken during the development face in 
order to semplify design and operation. 

As last study case it is proposed the NeuroGrid which is based on an 
unusual array of neurons and synapses made by analog electronic circuits 
assisted by a digital router. This MixedSignal machine is the apotheosis 
of the real-time concept thought to handle the data on the fly and avoid 
any kind of machine state storage (Douglas, Mahowald, & Mead, 1995). 
It appears to be what is closest to the formlization of coincidence of data 
retainment with the dynamic dialogue of the circuital components. The 
network pretends to interact realistically with biological systems and is, 
therefore, calibrated on time constants of tens of milliseconds. It’s a very 
long time scale if the reference is the digital system performance but for 
sure, for an analogic VLSI 14 is a very challenging result to reach. 

Conclusions

The studies on memories evolve constantly and the underlying compre-
hension is gradually becaming more complex and detailed. In particular 
all the learning about the memories generation and recall mechanism have 
quicly expanded. An important item in the field is the trustability of the 
recalled information. The brain is not a passive storage node instead it 
covers an adaptive function which can cause the memories alteration. This 
kind of error introduction serves for survival purpose. The memory builds 
patterns to expedite and facilitate the world understanding, although these 
processes cause the distortion of remembered events. 

The Neuropsychology is helping to clarify the anatomical, physi-
ological and psychic correlates of memory in order to understand its 
functioning. The Neuropsychological studies show that mental activity 
is distributed through the brain and not categorized into independent 
modules: the modularization paradigm has been discarded in favor of the 
connectionist one, proving the existence of interconnected neural networks. 

 14 Very large scale integration (in acronym VLSI) is a denomination that indicates a 
high integration of transistors within a single chip. Generally it refers to the devices with the 
highest level of integration based on the technologies of the time. 

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Mathematics fits into this context by representing complex neural configu-
rations through the mathematical models. All the disciplines offer their 
contribution in the same direction of establishing the neuromorphic 
computing theory and design the perfect machine for its interpretation. 
The development of new IT architectures is slowly becoming a reality. In 
the 2020 the neural chips market counted 1.952 billion dollars, and it is 
expected to grow to exceed 7 billion ollars by the 2026 with a particular 
traction from the automotive market (Mordor Intelligence, 2021). 

The integration of psychological, neuro-physiological knowledge 
with the mathematical one implies making an improvement for different 
disciplines and for the quality of life of the human being. The General 
Psychology will be able to answer unresolved questions about the unreli-
ability of memories and their reconstructive nature. The Forensic Neuro-
science will have a valid mathematical model that illustrates brain activity 
during the memorization making the detectives able to easily filter out 
fake information. Thanks to the Neuroimaging the cerebral images could 
be directly associated with some computational configuration to support 
the diagnosis and and the follow-up in in the neurological and psychiatric 
fields. The Awake Surgery will increase the safety and effectiveness of the 
interventions throught the systematic mapping by the cerebral network. At 
the end the Neuropsychological rehabilitation could arrange very precise 
intervention plan to fix the specific mnestic impairment and better moni-
toring the further progresses by the support of the prediction and behav-
iour suggested by the mathematical modelling. 

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Riassunto

La comprensione della memoria si configura, da secoli, come una sfida costante per la ri-
cerca scientifica. I processi mnestici, determinanti l’identità dell’essere umano, sono stati 
indagati attraverso molteplici punti di vista, come quello psicologico, neurofisiologico e 
fisico. Ne risultano visioni complesse e sfaccettate che andrebbero integrate per fornire 
un’interpretazione unitaria e completa. Si effettua una ricognizione della letteratura 
scientifica più recente, sul funzionamento della memoria dichiarativa, per analizzare 
la relazione tra l’informazione reale proveniente dal mondo esterno, l’evento codificato 
e il ricordo recuperato. L’obiettivo del saggio è indagare i correlati neurali, che regolano 
il sistema cognitivo in oggetto, mediante una duplice interpretazione neuropsicologico-
matematica. La Neuropsicologia fa luce sui meccanismi anatomici, fisiologici e psichici 
della memoria mentre la Matematica associa alle reti neurali le corrispondenti configu-
razioni matematiche. Il percorso di ricongiungimento, tra le due discipline, si realizza 
attraverso la simulazione computazionale neuromorfica che emula il “mind uploading”. 

Copyright (©) 2021 Federica Doronzo, Gianvito Calabrese 
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How to cite this paper:
Doronzo, F., & Calabrese, G. (2021). Functioning of declarative memory: Intersection 
between neuropsychology and mathematics. Elementa. Intersections between Philosophy, 
Epistemology and Empirical Perspectives, 1(1-2), 163-179. doi: https://dx.doi.org/10.7358/
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	Elementa_1-2021-1-2_00b_Sommario.pdf
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	Mask and Otherness
between Recognition and Concealment: Notes on the Self and the You

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