Pathology in neural circuits that control the expression of goal-directed and habitual behaviors is hypothesized to be a major contributing factor to addiction. In this study, we investigate cortico-striatal circuitry involved in learning and how cortical interactions with specific striatal subregions are involved in the emergence of inflexible behaviors such as compulsive drinking. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal directed and stimulus-response learning. The model accomplishes learning by distinguishing between the dorsomedial striatum (DMS)-where dopamine release encodes reward prediction error-and the dorsolateral striatum (DLS)-where dopamine release encodes motivation or salience. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC), which represented outcomes and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and punishment learning. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the loss of executive control, which was implemented as poor outcome representation in the PFC. Following this manipulation, no detectable of reward devaluation was observed, however, the efficacy of goal-directed learning was reduced, and stimulus response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model provides a mechanism that describes how the loss of executive control could contribute to the emergence of inflexible behavior.
Medial prefrontal cortex (mPFC) activity is fundamental for working memory (WM), attention, and behavioral inhibition; however, a comprehensive understanding of the neural computations underlying these processes is still forthcoming. Towards this goal, neural recordings were obtained from the mPFC of awake, behaving rats performing an odor span task of WM capacity. Neural populations were observed to encode distinct task epochs and the transitions between epochs were accompanied by abrupt shifts in neural activity patterns. Putative pyramidal neuron activity increased significantly earlier in the delay for sessions where rats achieved higher spans. Furthermore, increased putative interneuron activity was only observed at the termination of the delay thus indicating that local processing in inhibitory networks was a unique feature to initiate foraging. During foraging, changes in neural activity patterns associated with the approach to a novel odor, but not familiar odors, were robust. Collectively, these data suggest that distinct mPFC activity states underlie the delay, foraging, and reward epochs of the odor span task. Transitions between these states enable successful performance in dynamic environments placing strong demands on the substrates of working memory.
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