Computational Models

We use computational models to extract basic biological principles capturing the essence of complex interactions between the brain and the body, spanning from genomic data to social exchange. We aim for reproducible phenomena to advance the scientific methods and stimulate multi-disciplinary collaborations.

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Reaching to Grasp With a Multi-Jointed Arm (I) Computational Model  

Autism: The Micro-Movements Perspective 

Towards Precision Psychiatry: Statistical Platform for the Personalized Characterization of Natural Behaviors 

Neonatal Diagnostics: Towards Dynamic Growth Charts of Neuromotor Control 

A biomarker characterizing Neurodevelopment with applications to autism 

Optimal Time Lags from Causal Prediction Model Help Stratify and Forecast Nervous System Pathology 

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Psychiatric Disorders 

Rethinking Statistical Learning as a Dynamic Stochastic Process, from The Motor Systems Perspective