The seminar will focus on how experimental data can be used to build bottom-up mathematical models of neural activity. Three use-cases will be presented and investigated: a bio-inspired cerebellar controller for neurorobotic applications, a clinically driven modeling study to investigate the basal ganglia and cerebellum interplay in Parkinson’s disease and, finally, a data-driven reconstruction of the motor thalamus. The design choices underlying each use-case will be analyzed, to provide concrete examples on how experimental and in silico neuroscience can be combined to tackle different research questions.

Lugar: Sala de Seminarios, Laboratorio de Anatomía Aplicada del Departamento de Anatomía, Histología y Neurociencia. Fecha y Hora: lunes 3 de octubre, 16.00h.

Francesco Jamal Sheiban received his B.Sc. degree in Biomedical Engineering at Politecnico di Milano (Italy), in 2018 and M.Sc. in Information Bioengineering at Politecnico di Milano (Italy), in 2020. He spent one year as a research fellow at the neuro-engineering and medical robotics lab (NearLab, Politecnico di Milano), before enrolling in the Italian National PhD in Artificial Intelligence in 2021. His research interests include data-driven brain modelling, artificial intelligence and neuro-ethics.