Literature DB >> 18595740

Individual differences in reinforcement learning: behavioral, electrophysiological, and neuroimaging correlates.

Diane L Santesso1, Daniel G Dillon, Jeffrey L Birk, Avram J Holmes, Elena Goetz, Ryan Bogdan, Diego A Pizzagalli.   

Abstract

During reinforcement learning, phasic modulations of activity in midbrain dopamine neurons are conveyed to the dorsal anterior cingulate cortex (dACC) and basal ganglia (BG) and serve to guide adaptive responding. While the animal literature supports a role for the dACC in integrating reward history over time, most human electrophysiological studies of dACC function have focused on responses to single positive and negative outcomes. The present electrophysiological study investigated the role of the dACC in probabilistic reward learning in healthy subjects using a task that required integration of reinforcement history over time. We recorded the feedback-related negativity (FRN) to reward feedback in subjects who developed a response bias toward a more frequently rewarded ("rich") stimulus ("learners") versus subjects who did not ("non-learners"). Compared to non-learners, learners showed more positive (i.e., smaller) FRNs and greater dACC activation upon receiving reward for correct identification of the rich stimulus. In addition, dACC activation and a bias to select the rich stimulus were positively correlated. The same participants also completed a monetary incentive delay (MID) task administered during functional magnetic resonance imaging. Compared to non-learners, learners displayed stronger BG responses to reward in the MID task. These findings raise the possibility that learners in the probabilistic reinforcement task were characterized by stronger dACC and BG responses to rewarding outcomes. Furthermore, these results highlight the importance of the dACC to probabilistic reward learning in humans.

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Year:  2008        PMID: 18595740      PMCID: PMC2548326          DOI: 10.1016/j.neuroimage.2008.05.032

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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