Neural basis of transferable representations for efficient learning
Ai Phuong Tong,Vishnu Sreekumar,Mark Woolrich,Huiling Tan,Sara Inati,Kareem Zaghloul · COSYNE 2022
Thu, Mar 17, 2022
We learn different rules that can switch depending on context. When the rule depends on context, the context is important to learn to differentiate the rewarded choice in different contexts. While it has previously been shown that the reinstatement of context guides decisions for reward, it is less clear how or whether context-based reactivation guides the efficient learning of reward and context associations. We hypothesize that representations of the context are used to guide learning of associations between context and reward. We test whether this context is retrieved from memory circuits p