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TWINNING THE BRAIN WITH MACHINE 
LEARNING FOR NEURO-MUSCULAR EFFICIENCY 

(TwinBrain)

The project “TWINning the BRAIN with machine learning for neuro-muscular effi-
ciency (TwinBrain)1”, will be implemented between 1 November 2020 and 31 October 
2023. The project is a part of the call “Horizon 2020 Twinning widespread-05-2020”. 
The TwinBrain project was successfully designed and obtained within the Institute 
for Kinesiology Research, Science and Research Centre Koper (ZRS Koper), under 
the leadership of dr. Uroš Marušič. The project partners with prestigious universities 
from Germany (Technische Universität Berlin; TUB) and Switzerland (Université de 
Genève; UNIGE) and the Neurology Department of Cattinara Hospital (Università de-
gli Studi di Trieste; UNITS, Italy). The € 0.9M project, which will last for three years, 
aims to establish a research and diagnostic centre in the field of neuromuscular efficien-
cy and to understand the functioning and control of the central nervous system during 
movement. One specific goal of the TwinBrain project is to increase the scientific and 
technological capacities of related institutions with an emphasis on the institution of the 
applicant country - ZRS Koper.

The activities of the TwinBrain project are aimed at establishing and raising the 
quality of the research group in the country with a lower R&I index (ZRS Koper), with 
the help of partner institutions with a higher R&I index (TUB, UNIGE and UNITS). 
The ultimate goal of the project is to set up the SloMoBIL: Slovenian Mobile Brain/
Body Imaging Laboratory, which will be established through the transfer of knowledge 
and technology from BeMoBIL: Berlin Mobile Brain/Body Imaging Laboratory 2. In 
order to fully understand brain dynamics in actively moving people, we need to analyse 
brain dynamics in relation to coincident behaviour. This combination makes it possible 
to assess the complex interrelationships between brain and behavioural dynamics and is 
captured in the Mobile Brain/Body Imaging (MoBI) system. The MoBI system aligns 
real-time EEG signals with concurrent recordings of eye movements, body movements, 
and autonomic responses. The result is the simultaneous capture of large amounts of 
data that require advanced methods to process. To this end, the TwinBrain project plans 
to implement machine learning methods that can statistically “learn” nonlinear relati-
onships between brain dynamics and behaviour. A central aim of these analyses is to 
identify a limited number of functionally different large-brain networks that represents 
different aspects of the performed and recorded behavioural information. In that way, it 
would not only be possible to statically image brain activities related to the given task, 
but to characterise specific large-scale network dynamics and describe their time-resol-
ved properties in relation to behaviour. 

1 https://cordis.europa.eu/project/id/952401.
2 https://blogs.tu-berlin.de/bpn_bemobil/.

https://cordis.europa.eu/project/id/952401
https://blogs.tu-berlin.de/bpn_bemobil/


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ANNALES KINESIOLOGIAE • 11 • 2020 • 1

Finally, with successful coupling of brain dynamics, motion kinematics, advanced 
brain imaging techniques, and machine learning, this project aims at transferring tech-
nology and knowledge among the included partners and beyond. As a result, the con-
sortium will have enhanced scientific and technological capacity as well as networking 
activities. The institution from Slovenia (ZRS Koper) will raise its research profile and 
the research profile of its staff. Taking the broader perspective, through all proposed ac-
tivities, a new and dynamic network will be established, enabling the involved partners 
to continue their scientific and professional collaboration, including in the framework 
of new EU-funded research projects, with the view of addressing wider challenges 
related to demographics and health.

Uroš Marušič



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TWINNING THE BRAIN WITH MACHINE 
LEARNING FOR NEURO-MUSCULAR EFFICIENCY 

(TwinBrain)

Med 1. novembrom 2020 in 31. oktobrom 2023 bodo potekale dejavnosti pro-
jekta »TWINning the BRAIN with machine learning for neuro-muscular efficiency 
(TwinBrain)3«, ki je bil pridobljen na razpisu »Horizont 2020 Twinning widespre-
ad-05-2020«. Projekt TwinBrain je bil v okviru Inštituta za kineziološke raziskave Znan-
stveno-raziskovalnega središča Koper (ZRS Koper) uspešno zasnovan in prijavljen pod 
vodstvom dr. Uroša Marušiča. Ob ZRS Koper sodelujejo v projektu kot partnerji presti-
žni univerzi iz Nemčije (Technische Universität Berlin; TUB) in Švice (Université de 
Genève; UNIGE) ter nevrološki oddelek bolnišnice Cattinara (Università degli Studi 
di Trieste; UNITS, Italija). Projekt v vrednosti 0,9 milijona evrov, ki bo trajal tri leta, 
si za cilj postavlja vzpostavitev raziskovalno-diagnostičnega centra na področju živč-
no-mišične učinkovitosti ter razumevanja delovanja in nadzora centralnega živčnega 
sistema med gibanjem. Poseben cilj projekta TwinBrain je tudi povečanje znanstvene in 
tehnološke zmogljivosti povezanih inštitucij, pri čemer je poudarek na inštituciji države 
prijaviteljice ZRS Koper. 

Dejavnosti projekta TwinBrain so usmerjene v vzpostavitev in dvig kakovosti 
raziskovalne skupine v državi z nižjim kazalnikom raziskav in inovacij (R&I; ZRS 
Koper) s pomočjo partnerskih inštitucij z višjim kazalnikom R&I (TUB, UNIGE in 
UNITS). Končni cilj projekta je postavitev laboratorija SloMoBIL: Slovenian Mobile 
Brain/Body Imaging Laboratory, ki bo vzpostavljen prek prenosa znanj in tehnologije 
iz BeMoBIL: Berlin Mobile Brain/Body Imaging Laboratory4. Da bi lahko v celoti 
razumeli možgansko dinamiko pri aktivno premikajočih se ljudeh, moramo analizirati 
možgansko dinamiko v povezavi s sočasnim vedenjem. Ta kombinacija omogoča oce-
no zapletenih medsebojnih odnosov med možgansko in vedenjsko dinamiko in je zajeta 
v sistemu Mobile Brain/Body Imaging (MoBI). Ta sistem v realnem času usklajuje 
EEGsignale s hkratnimi posnetki gibov oči, gibov telesa in avtonomnih odzivov. Posle-
dično gre za hkratno zajemanje velike količine podatkov, ki zahtevajo napredne metode 
obdelave. V ta namen v projektu TwinBrain načrtujemo uporabo metod strojnega uče-
nja, ki se lahko statistično »naučijo« nelinearnih razmerij med možgansko dinamiko in 
vedenjem. Osrednji cilj teh analiz je prepoznati omejeno število funkcionalno različnih 
obsežnih možganskih omrežij, ki predstavljajo različne vidike izvedenih in zabeleženih 
vedenjskih informacij. Tako ne bi bilo mogoče le statično prikazati možganskih dejav-
nosti, povezanih z dano nalogo, temveč tudi opredeliti specifično dinamiko obsežnega 
možganskega omrežja in opisati njihove časovne lastnosti glede na vedenje.

Nazadnje je cilj tega projekta ob uspešnem povezovanju možganske dinamike, ki-
nematike gibanja, naprednih tehnik slikanja možganov in strojnega učenja prenesti teh-

3  https://cordis.europa.eu/project/id/952401.
4  https://blogs.tu-berlin.de/bpn_bemobil/.



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nologije in znanja med vključene partnerje in širše. Rezultat tega bodo okrepljene znan-
stvene in tehnološke zmogljivosti in dejavnosti mreženja konzorcija. Vodilni partner 
projekta iz Slovenije (ZRS Koper) bo povečal svoj raziskovalni profil in raziskovalni 
profil svojega osebja. Na podlagi širše perspektive se bo z vsemi predlaganimi dejav-
nostmi vzpostavila nova dinamična mreža, ki bo vključenim partnerjem omogočila na-
daljevanje znanstvenega in strokovnega sodelovanja tudi v okviru novih raziskovalnih 
projektov, ki jih financira EU, s pogledom na obravnavanje širših izzivov, povezanih z 
demografijo in zdravjem.

Uroš Marušič


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