CBMM Special Seminar: Next-generation recurrent network models for cognitive neuroscience

Photo of Guangyu Robert Yang, MIT June 15, 2021 - 2:00 pm to 3:30 pm

Abstract:  Recurrent Neural Networks (RNNs) trained with machine learning techniques on cognitive tasks have become a widely accepted tool for neuroscientists. In comparison to traditional computational models in neuroscience, RNNs can offer substantial advantages at explaining complex behavior and neural activity patterns. Their use allows rapid generation of mechanistic hypotheses for cognitive computations. RNNs further provide a natural way to flexibly combine bottom-up biological knowledge with top-down computational goals into network models. However, early works of this approach are faced with fundamental challenges. In this talk, I will discuss some of these challenges, and several recent steps that we took to partly address them and to build next-generation RNN models for cognitive neuroscience.​


June 15, 2021
2:00 pm to 3:30 pm
This seminar talk will be hosted remotely via Zoom.

Zoom link: https://mit.zoom.us/j/94734403753?pwd=YW5udzZJdndqVnc1NnkyQ0s3L0hVUT09

Passcode: 080128