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Xiao-Jing Wang is a Distinguished Global Professor of Neuroscience at NYU

Xiao-Jing was born and grew up in China, spent 8 years in Belgium studying theoretical physics like nonlinear dynamical systems and deterministic chaos. And as he says it, he arrived from Brussels to California as a postdoc, and in one day switched from French to English, from European to American culture, and physics to neuroscience. I know Xiao-Jing as a legend in non-human primate neurophysiology and modeling, paving the way for the rest of us to study brain activity related cognitive functions like working memory and decision-making.

He has just released his new textbook, Theoretical Neuroscience: Understanding Cognition, which covers the history and current research on modeling cognitive functions from the very simple to the very cognitive. The book is also somewhat philosophical, arguing that we need to update our approach to explaining how brains function, to go beyond Marr's levels and enter a cross-level mechanistic explanatory pursuit, which we discuss. I just learned he even cites my own PhD research, studying metacognition in nonhuman primates - so you know it's a great book. Learn more about Xiao-Jing and the book in the show notes. It was fun having one of my heroes on the podcast, and I hope you enjoy our discussion.

0:00 - Intro 3:08 - Why the book now? 11:00 - Modularity in neuro vs AI 14:01 - Working memory and modularity 22:37 - Canonical cortical microcircuits 25:53 - Gradient of inhibitory neurons 27:47 - Comp neuro then and now 45:35 - Cross-level mechanistic understanding 1:13:38 - Bifurcation 1:24:51 - Bifurcation and degeneracy 1:34:02 - Control theory 1:35:41 - Psychiatric disorders 1:39:14 - Beyond dynamical systems 1:43:447 - Mouse as a model 1:48:11 - AI needs a PFC

Theoretical Neuroscience

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