Dataset Information

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.

ABSTRACT: 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.

SUBMITTER: Allegra Mascaro AL

PROVIDER: S-EPMC7359878 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.

Allegra Mascaro Anna Letizia AL Falotico Egidio E Petkoski Spase S Pasquini Maria M Vannucci Lorenzo L Tort-Colet Núria N Conti Emilia E Resta Francesco F Spalletti Cristina C Ramalingasetty Shravan Tata ST von Arnim Axel A Formento Emanuele E Angelidis Emmanouil E Blixhavn Camilla H CH Leergaard Trygve B TB Caleo Matteo M Destexhe Alain A Ijspeert Auke A Micera Silvestro S Laschi Cecilia C Jirsa Viktor V Gewaltig Marc-Oliver MO Pavone Francesco S FS

Frontiers in systems neuroscience 20200707

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 aft ...[more]

PMID: 32733210

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Dataset Information

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.

Publications

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.

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