Abstract
Recently, the subthalamic nucleus (STN) has been shown to be critically involved in decision-making, action selection, and motor control. Here we investigate the effect of deep brain stimulation (DBS) of the STN on reward-based decision-learning in patients diagnosed with Parkinson's disease (PD). We determined computational measures of outcome evaluation and reward prediction from PD patients who performed a probabilistic reward-based decision-learning task. In previous work, these measures covaried with activation in the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that stimulation of the STN motor regions in PD patients served to improve reward-based decision-learning, probably through its effect on activity in frontostriatal motor loops (prominently involving the putamen and, hence, reward prediction). In a subset of relatively younger patients with relatively shorter disease duration, the effects of DBS appeared to spread to more cognitive regions of the STN, benefiting loops that connect the caudate to various prefrontal areas importantfor outcome evaluation. These results highlight positive effects of STN stimulation on cognitive functions that may benefit PD patients in daily-life association-learning situations.
Highlights
Making appropriate choices between distinct options in daily life is vital for optimal behavior and requires learning the causal relation between events, actions and their outcomes
While the above analysis showed no effect of subthalamic nucleus (STN) stimulation on reward-prediction errors (RPE) across the entire block of trials, we focused the second analysis on the first phase of learning within each block to link our study to previous findings and provide better clarification about the effects of STN stimulation on RPE values linked to caudate nucleus activity (Haruno and Kawato, 2006a)
The present study investigated the effect of STN stimulation on separate components of reward-based learning: outcome evaluation and reward www.frontiersin.org
Summary
Making appropriate choices between distinct options in daily life (for example friend or foe, food, or non-food) is vital for optimal behavior and requires learning the causal relation between events, actions and their outcomes. Expectations about the favorability of a decision’s outcome (i.e., leads to reward versus leads to punishment) are uncertain, and the associations between a situation, a response to it, and the outcome of that decision must be learned on the basis of trial and error. Several brain areas have been linked to key aspects of reward-based decision-learning, including prefrontal regions (e.g., the dorsolateral and orbito-frontal cortices) and the basal ganglia. Among the latter structures, the subthalamic nucleus (STN) has been implicated recently as a key structure in decision-making processes (Frank et al, 2007). The purpose of the present investigation was to determine how STN modulation affects reward-based learning in patients with Parkinson’s disease (PD) who have been treated with STN deep brain stimulation (DBS)
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