RT Journal Article
SR Electronic
T1 Experimental and computational study on motor control and recovery after stroke: towards a constructive loop between experimental and virtual embodied neuroscience
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.04.22.019661
DO 10.1101/2020.04.22.019661
A1 Anna Letizia Allegra Mascaro
A1 Egidio Falotico
A1 Spase Petkoski
A1 Maria Pasquini
A1 Lorenzo Vannucci
A1 Núria Tort-Colet
A1 Emilia Conti
A1 Francesco Resta
A1 Cristina Spalletti
A1 Shravan Tata Ramalingasetty
A1 Axel von Arnim
A1 Emanuele Formento
A1 Emmanouil Angelidis
A1 Camilla Hagen Blixhavn
A1 Trygve Brauns Leergaard
A1 Matteo Caleo
A1 Alain Destexhe
A1 Auke Ijspeert
A1 Silvestro Micera
A1 Cecilia Laschi
A1 Viktor Jirsa
A1 Marc-Oliver Gewaltig
A1 Francesco S. Pavone
YR 2020
UL http://biorxiv.org/content/early/2020/05/10/2020.04.22.019661.abstract
AB 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.Competing Interest StatementThe authors have declared no competing interest.