Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience
Anna Letizia Allegra Mascaro
(1)
,
Egidio Falotico
(2)
,
Spase Petkoski
(3)
,
Maria Pasquini
(4)
,
Lorenzo Vannucci
(2)
,
Núria Tort-Colet
(5)
,
Emilia Conti
(6)
,
Francesco Resta
(6)
,
Cristina Spalletti
(7)
,
Shravan Tata Ramalingasetty
(8)
,
Axel von Arnim
(9)
,
Emanuele Formento
(10)
,
Emmanouil Angelidis
(9)
,
Camilla H Blixhavn
(11)
,
Trygve B Leergaard
(11)
,
Matteo Caleo
(12)
,
Alain Destexhe
(5)
,
Auke Ijspeert
(8)
,
Silvestro Micera
(10)
,
Cecilia Laschi
(4)
,
Viktor Jirsa
(3)
,
Marc-Oliver Gewaltig
(8)
,
Francesco S Pavone
(6)
1
LENS -
European Laboratory for Non-Linear Spectroscopy
2 The BioRobotics Institute
3 INS - Institut de Neurosciences des Systèmes
4 SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa]
5 NeuroPSI - Institut des Neurosciences Paris-Saclay
6 UniFI - Università degli Studi di Firenze = University of Florence = Université de Florence
7 CNR - Neuroscience Institute [Pisa, Italy]
8 EPFL - Ecole Polytechnique Fédérale de Lausanne
9 Fortiss GmbH
10 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
11 UiO - University of Oslo
12 AOUP - Azienda Ospedale Università di Padova = Hospital-University of Padua
2 The BioRobotics Institute
3 INS - Institut de Neurosciences des Systèmes
4 SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa]
5 NeuroPSI - Institut des Neurosciences Paris-Saclay
6 UniFI - Università degli Studi di Firenze = University of Florence = Université de Florence
7 CNR - Neuroscience Institute [Pisa, Italy]
8 EPFL - Ecole Polytechnique Fédérale de Lausanne
9 Fortiss GmbH
10 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
11 UiO - University of Oslo
12 AOUP - Azienda Ospedale Università di Padova = Hospital-University of Padua
Spase Petkoski
- Fonction : Auteur
- PersonId : 745614
- IdHAL : spase-petkoski
- ORCID : 0000-0003-4540-6293
Alain Destexhe
- Fonction : Auteur
- PersonId : 175973
- IdHAL : destexhe
- ORCID : 0000-0001-7405-0455
- IdRef : 061644528
Silvestro Micera
- Fonction : Auteur
- PersonId : 763071
- ORCID : 0000-0003-4396-8217
Viktor Jirsa
- Fonction : Auteur
- PersonId : 1053089
- IdHAL : viktor-jirsa
- ORCID : 0000-0002-8251-8860
- IdRef : 08197471X
Résumé
Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.
Domaines
Neurosciences [q-bio.NC]Format du dépôt | Fichier |
---|---|
Type de dépôt | Article dans une revue |
Résumé |
en
Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.
|
Titre |
en
Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience
|
Auteur(s) |
Anna Letizia Allegra Mascaro
1
, Egidio Falotico
2
, Spase Petkoski
3
, Maria Pasquini
4
, Lorenzo Vannucci
2
, Núria Tort-Colet
5
, Emilia Conti
6
, Francesco Resta
6
, Cristina Spalletti
7
, Shravan Tata Ramalingasetty
8
, Axel von Arnim
9
, Emanuele Formento
10
, Emmanouil Angelidis
9
, Camilla H Blixhavn
11
, Trygve B Leergaard
11
, Matteo Caleo
12
, Alain Destexhe
5
, Auke Ijspeert
8
, Silvestro Micera
10
, Cecilia Laschi
4
, Viktor Jirsa
3
, Marc-Oliver Gewaltig
8
, Francesco S Pavone
6
1
LENS -
European Laboratory for Non-Linear Spectroscopy
( 27535 )
- Via Nello Carrara 1, I-50019-Sesto-Fiorentino, Firenze
- Italie
2
The BioRobotics Institute
( 218937 )
- Viale Rinaldo Piaggio, 34, Pontedera (PI)
- Italie
3
INS -
Institut de Neurosciences des Systèmes
( 220661 )
- Faculté de Médecine - Secteur Timone - 27 boulevard Jean Moulin 13385 Marseille Cedex 05
- France
4
SSSUP -
Scuola Universitaria Superiore Sant'Anna [Pisa]
( 58000 )
- Piazza Martiri della Libertà 33 - 56127 Pisa
- Italie
5
NeuroPSI -
Institut des Neurosciences Paris-Saclay
( 1051126 )
- Centre National de la Recherche Scientifique, Unité Mixte de Recherche-9197 Université Paris-Saclay
Campus CEA Saclay, Bât. 151
151 route de la Rotonde
91400 Saclay
- France
6
UniFI -
Università degli Studi di Firenze = University of Florence = Université de Florence
( 148408 )
- Piazza di San Marco, 4, 50121 Firenze FI, Italie
- Italie
7
CNR -
Neuroscience Institute [Pisa, Italy]
( 1004042 )
- Italie
8
EPFL -
Ecole Polytechnique Fédérale de Lausanne
( 302851 )
- CH-1015 Lausanne, Switzerland
- Suisse
9
Fortiss GmbH
( 230806 )
- Munich
- Allemagne
10
ETH Zürich -
Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
( 180925 )
- Hauptgebäude, Rämistrasse 101, 8092 Zürich
- Suisse
11
UiO -
University of Oslo
( 50791 )
- P.O 1072 Blindern 0316 Oslo
- Norvège
12
AOUP -
Azienda Ospedale Università di Padova = Hospital-University of Padua
( 1067905 )
- Via Giustiniani, 2 - 35128 Padova
- Italie
|
Page/Identifiant |
31
|
Licence |
Paternité
|
Langue du document |
Anglais
|
Nom de la revue |
|
Vulgarisation |
Non
|
Comité de lecture |
Oui
|
Audience |
Internationale
|
Date de publication |
2020-07-07
|
Volume |
14
|
Projet(s) Européen(s) |
|
Domaine(s) |
|
Mots-clés |
en
motor control, stroke, rehabilitation, neural mass, spiking neuronal networks, brain network models, Kuramoto oscillators, closed-loop simulation
|
DOI | 10.3389/fnsys.2020.00031 |
Pubmed Id | 32733210 |
PubMed Central | PMC7359878 |
Origine :
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