BI 097 Omri Barak and David Sussillo: Dynamics and Structure

February 08, 2021 01:23:57
BI 097 Omri Barak and David Sussillo: Dynamics and Structure
Brain Inspired
BI 097 Omri Barak and David Sussillo: Dynamics and Structure

Feb 08 2021 | 01:23:57

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Show Notes

Omri, David and I discuss using recurrent neural network models (RNNs) to understand brains and brain function. Omri and David both use dynamical systems theory (DST) to describe how RNNs solve tasks, and to compare the dynamical stucture/landscape/skeleton of RNNs with real neural population recordings. We talk about how their thoughts have evolved since their 2103 Opening the Black Box paper, which began these lines of research and thinking. Some of the other topics we discuss:

Timestamps:
0:00 – Intro
5:41 – Best scientific moment
9:37 – Why do you do what you do?
13:21 – Computation via dynamics
19:12 – Evolution of thinking about RNNs and brains
26:22 – RNNs vs. minds
31:43 – Classical computational modeling vs. machine learning modeling approach
35:46 – What are models good for?
43:08 – Ecological task validity with respect to using RNNs as models
46:27 – Optimization vs. learning
49:11 – Universality
1:00:47 – Solutions dictated by tasks
1:04:51 – Multiple solutions to the same task
1:11:43 – Direct fit (Uri Hasson)
1:19:09 – Thinking about the bigger picture

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