Literature DB >> 16192338

Different neural correlates of reward expectation and reward expectation error in the putamen and caudate nucleus during stimulus-action-reward association learning.

Masahiko Haruno1, Mitsuo Kawato.   

Abstract

To select appropriate behaviors leading to rewards, the brain needs to learn associations among sensory stimuli, selected behaviors, and rewards. Recent imaging and neural-recording studies have revealed that the dorsal striatum plays an important role in learning such stimulus-action-reward associations. However, the putamen and caudate nucleus are embedded in distinct cortico-striatal loop circuits, predominantly connected to motor-related cerebral cortical areas and frontal association areas, respectively. This difference in their cortical connections suggests that the putamen and caudate nucleus are engaged in different functional aspects of stimulus-action-reward association learning. To determine whether this is the case, we conducted an event-related and computational model-based functional MRI (fMRI) study with a stochastic decision-making task in which a stimulus-action-reward association must be learned. A simple reinforcement learning model not only reproduced the subject's action selections reasonably well but also allowed us to quantitatively estimate each subject's temporal profiles of stimulus-action-reward association and reward-prediction error during learning trials. These two internal representations were used in the fMRI correlation analysis. The results revealed that neural correlates of the stimulus-action-reward association reside in the putamen, whereas a correlation with reward-prediction error was found largely in the caudate nucleus and ventral striatum. These nonuniform spatiotemporal distributions of neural correlates within the dorsal striatum were maintained consistently at various levels of task difficulty, suggesting a functional difference in the dorsal striatum between the putamen and caudate nucleus during stimulus-action-reward association learning.

Mesh:

Year:  2005        PMID: 16192338     DOI: 10.1152/jn.00382.2005

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


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