MINDS / CIS Seminar Series – Mathematical Institute for Data Science

Ida Momennejad – Multi-scale Predictive Representations

Nov 3 @ 12:00 pm – 1:00 pm

Abstract: Memory and planning rely on learning the relational structure of experience. A century after ‘latent learning’ experiments summarized by Tolman, the larger puzzle of cognitive maps remains elusive: how does the brain learn compact representations of relational structures to guide flexible behavior? I use reinforcement learning (RL) to study how humans learn predictive representations in memory and planning. I show behavioral, fMRI, and electrophysiology evidence that hippocampal and prefrontal hierarchies learn multi-scale predictive representations updated via offline replay. This approach advances the century old notion of cognitive maps and can inform biologically inspired artificial agents as well as computational psychiatry.

Bio: Ida Momennejad is a senior researcher in reinforcement learning at Microsoft Research NYC. Ida builds and tests neurally plausible algorithms for learning the structure of the environment such that it serves memory, exploration, & planning. Her approach combines reinforcement learning with behavioral experiments, fMRI, & electrophysiology. Ida got her BSc in software engineering (Tehran, Iran), MSc in Philosophy of Science (Utrecht, Netherlands), PhD in psychology/computational neuroscience (Berlin, Germany). She was a postdoc at Princeton and an associate research scientist at Columbia BME.

Nov

Tue

SueYeon Chung

Tickets

Nov 10 @ 12:00 pm – 1:00 pm

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Nov

Tue

Kimia Ghobadi

Tickets

Nov 17 @ 12:00 pm – 1:00 pm

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