Thalamic Contribution to Detecting and Learning from Unexpected Events

Project 2

To learn effectively, the brain must identify when events differ from expectations and determine which information is important to update existing knowledge. Detecting unexpected or behaviorally relevant events is therefore a fundamental first step in learning, allowing neural circuits to revise internal models of the environment. Although prediction error and deviance detection have been extensively studied in cortical circuits, the contribution of thalamic networks to these processes remains poorly understood. 

Our laboratory investigates how thalamic circuits detect unexpected events and contribute to learning. We are particularly interested in how thalamic neurons integrate sensory information and cortical feedback to identify deviations from expected patterns, and how these signals influence downstream circuits involved in perception and memory.

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