Nitzan Shahar – Credit assignment to state-independent task representations

• Tuesday, November 26th 2019 at 16:00 - 17:00 UK (Other timezones)
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Natural environments are feature-rich and only a subset of these features are considered to predict action-outcome associations. To enable accurate action-outcome predictions a decision maker is faced with a challenge, namely that only a portion of the information in the environment is predictive of a desired outcome. Here, we highlight the tendency of individuals to assign credit to outcome-irrelevant task representations. We demonstrate that value is assigned to these representations in a model-free and state-independent manner. We further show the association between these low-level value associations and a more sophisticated model-based system, and propose how model-free representations might be regulated according to a model of the environment. Finally, we suggest that a deficit in the regulation of outcome-irrelevant model-free associations might lead to behavioral abnormalities such as compulsive behavior.