TopicNeuroscience

classical conditioning

Content Overview
3Total items
2ePosters
1Seminar

Latest

SeminarNeuroscienceRecording

A role for dopamine in value-free learning

Luke Coddington
Dudman lab, HHMI Janelia
Jul 14, 2021

Recent success in training artificial agents and robots derives from a combination of direct learning of behavioral policies and indirect learning via value functions. Policy learning and value learning employ distinct algorithms that depend upon evaluation of errors in performance and reward prediction errors, respectively. In mammals, behavioral learning and the role of mesolimbic dopamine signaling have been extensively evaluated with respect to reward prediction errors; but there has been little consideration of how direct policy learning might inform our understanding. I’ll discuss our recent work on classical conditioning in naïve mice (https://www.biorxiv.org/content/10.1101/2021.05.31.446464v1) that provides multiple lines of evidence that phasic dopamine signaling regulates policy learning from performance errors in addition to its well-known roles in value learning. This work points towards new opportunities for unraveling the mechanisms of basal ganglia control over behavior under both adaptive and maladaptive learning conditions.

ePosterNeuroscience

MEDIAL PREFRONTAL CORTEX ACTIVITY PREDICTS BEHAVIOURAL SPECIFICITY AND TRANSFER IN VISUAL CLASSICAL CONDITIONING<S>​</S>

Haron Avgana, Andrew Peters

FENS Forum 2026

ePosterNeuroscience

Cortical-hippocampal information processing during classical conditioning

Rafael Pedrosa, Federico Stella, Francesco P. Battaglia

classical conditioning coverage

3 items

ePoster2
Seminar1

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