2024-05-17 : INT-CONECT seminar by Dan Goodman

“From neural mechanism to function.”

2024-05-17 512:00
  • When: Friday, May 17th 11:00 to 12:00
  • Where: salle Gastaut (TBC), Institut de Neurosciences de la Timone, Marseille, France.

During this INT-CONECT seminar, Dr Dan Goodman did present his recent work on theoretical modelling: From neural mechanism to function.

Abstract: What is the role of theoretical or computational work in neuroscience? In this talk, I will discuss how I think that techniques from machine learning can let us relate neural mechanisms to functions, illustrated with some examples from our recent research. In brief, theory lets us answer “what if” questions that would have been impossible to answer using experiments alone. Machine learning specifically gets us close to being able to answer “how well could the brain function if” questions that allow us to get at the computational role of particular neural mechanisms. Critically, this approach to theory is different to the ones that have often been suggested for computational neuroscience: fitting data, predicting data, letting us carry out “in silico” experiments. In summary, I will argue that if you want to understand what the functional role of a neural mechanism is, computational theory is essential, and that thinking of theory in this way lets us do it better. The research I will discuss includes: (1) How the heterogeneity of neurons allows the brain to solve sensory tasks with temporally rich structure. (2) How the structural modularity of the brain is not sufficient to guarantee functional modularity. (3) How neural nonlinearities are critical to extract temporally structured multimodal information.

Dan is a senior lecturer in the Intelligent Systems and Networks group in the Department of Electrical and Electronic Engineering at Imperial College London. The aim of his research is to uncover unifying principles underlying intelligent systems, including biological systems such as the brain, and artificial systems.
Laurent U Perrinet
Laurent U Perrinet
Researcher in Computational Neuroscience

My research interests include Machine Learning and computational neuroscience applied to Vision.

Antoine Grimaldi
Antoine Grimaldi
Phd candidate in Computational Neuroscience

During my PhD, I am focusing on pUltra-fast vision using Spiking Neural Networks.