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Topic: temporal difference learning

Seminar
1 seminar
ePoster
1 ePoster

In Computational Neuroscience and Mathematical Modeling

ePoster · Computational Neuroscience

Rapid approximation of successor representations with STDP and theta phase precession

Tom George,William de Cothi,Kimberly Stachenfeld,Caswell Barry · COSYNE 2022

Thu, Mar 17, 2022

The successor representation (SR) is a promising candidate principle for hippocampal function. Theory proposes that each place cell encodes the expected state occupancy of its target location in the near future. This framework has desirable consequences on the generalisability and efficiency of reinforcement learning algorithms operating over these representations and is supported by behavioural and electrophysiological evidence. However, it is unclear how the SR might be learnt in the brain. Temporal difference learning, commonly used to learn SRs in artificial agents, is not known to be impl

Seminar · Behavioral Neuroscience

Striatal circuits for reward learning and decision-making

Ilana Witten · Princeton University

Thu, Jun 11, 2020 · 16:30 UTC

How are actions linked with subsequent outcomes to guide choices? The nucleus accumbens (NAc), which is implicated in this process, receives glutamatergic inputs from the prelimbic cortex (PL) and midline regions of the thalamus (mTH). However, little is known about what is represented in PL or mTH neurons that project to NAc (PL-NAc and mTH-NAc). By comparing these inputs during a reinforcement learning task in mice, we discovered that i) PL-NAc preferentially represents actions and choices, ii) mTH-NAc preferentially represents cues, iii) choice-selective activity in PL-NAc is organized in s