Computational models of the cerebellum
Prof. Egidio D’Angelo
Università di Pavia
Brain Connectivity Unit, IRCCS Mondino - Pavia
Politecnico di Milano
25.S.1 Room (Building 25, Emilio Massa)
Via U.B. Secondo, 3
October 20th, 2023
1.15 pm
Contacts:
Alberto Antonietti
Research Line:
Technologies for diagnosis, therapy and rehabilitation
Università di Pavia
Brain Connectivity Unit, IRCCS Mondino - Pavia
Politecnico di Milano
25.S.1 Room (Building 25, Emilio Massa)
Via U.B. Secondo, 3
October 20th, 2023
1.15 pm
Contacts:
Alberto Antonietti
Research Line:
Technologies for diagnosis, therapy and rehabilitation
Sommario
On October 20th, 2023 at 1.15 pm Egidio D’Angelo, Professor at Università di Pavia, Director of the Brain Connectivity Unit at IRCCS Mondino, Pavia, will hold a seminar on "Computational models of the cerebellum" in 25.S.1 Room (Building 25) and on line by Webex.
The cerebellum is one of the most fascinating neural circuits of the brain. The cerebellum has been classically associated to the control of movement and its pathological counterpart, ataxia, but it has recently been related to cognitive processing and supposed to be involved in autism, dyslexia and Alzheimer disease just to mention some.
This talk will show a multiscale reconstruction of cerebellar functions making use of advanced data-driven modeling and robotic techniques and will open a perspective on how this multiscale approach could be applied to the analysis of integrated brain signals, like those deriving from structural and functional MRI, and used to assist the interpretation of brain function and pathology.
The cerebellum is one of the most fascinating neural circuits of the brain. The cerebellum has been classically associated to the control of movement and its pathological counterpart, ataxia, but it has recently been related to cognitive processing and supposed to be involved in autism, dyslexia and Alzheimer disease just to mention some.
This talk will show a multiscale reconstruction of cerebellar functions making use of advanced data-driven modeling and robotic techniques and will open a perspective on how this multiscale approach could be applied to the analysis of integrated brain signals, like those deriving from structural and functional MRI, and used to assist the interpretation of brain function and pathology.
