PT  - JOURNAL ARTICLE
AU  - Anna Letizia Allegra Mascaro
AU  - Egidio Falotico
AU  - Spase Petkoski
AU  - Maria Pasquini
AU  - Lorenzo Vannucci
AU  - Núria Tort-Colet
AU  - Emilia Conti
AU  - Francesco Resta
AU  - Cristina Spalletti
AU  - Shravan Tata Ramalingasetty
AU  - Axel von Arnim
AU  - Emanuele Formento
AU  - Emmanouil Angelidis
AU  - Camilla Hagen Blixhavn
AU  - Trygve Brauns Leergaard
AU  - Matteo Caleo
AU  - Alain Destexhe
AU  - Auke Ijspeert
AU  - Silvestro Micera
AU  - Cecilia Laschi
AU  - Viktor Jirsa
AU  - Marc-Oliver Gewaltig
AU  - Francesco S. Pavone
TI  - Experimental and computational study on motor control and recovery after stroke: towards a constructive loop between experimental and virtual embodied neuroscience
AID  - 10.1101/2020.04.22.019661
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.04.22.019661
4099  - http://biorxiv.org/content/early/2020/05/10/2020.04.22.019661.short
4100  - http://biorxiv.org/content/early/2020/05/10/2020.04.22.019661.full
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.