Contrasting effects of medial and lateral orbitofrontal cortex lesions on credit assignment and decision making in humans

The orbitofrontal cortex is critical for goal-directed behavior. Recent work in macaques has suggested the lateral orbitofrontal cortex (lOFC) is relatively more concerned with assignment of credit for rewards to particular choices during value-guided learning, whereas the medial orbitofrontal cortex (often referred to as ventromedial prefrontal cortex in humans; vmPFC/mOFC) is involved in constraining the decision to the relevant options. We examined whether people with damage restricted to subregions of prefrontal cortex showed the patterns of impairment observed in prior investigations of the effects of lesions to homologous regions in macaques. Groups of patients with either lOFC (predominantly right hemisphere), mOFC/vmPFC, or dorsomedial prefrontal (DMF), and a comparison group of healthy age- and education-matched controls performed a probabilistic 3-choice decision-making task. We report anatomically specific patterns of impairment. We found that credit assignment, as indexed by the normal influence of contingent relationships between choice and reward, is reduced in lOFC patients compared with Controls and mOFC/vmPFC patients. Moreover, the effects of reward contingency on choice were similar for patients with lesions in DMF or mOFC/vmPFC, compared with Controls. By contrast, mOFC/vmPFC-lesioned patients made more stochastic choices than Controls when the decision was framed by valuable distracting alternatives, suggesting that value comparisons were no longer independent of irrelevant options. Once again, there was evidence of regional specialization: patients with lOFC lesions were unimpaired relative to Controls. As in macaques, human lOFC and mOFC/vmPFC are necessary for contingent learning and value-guided decision-making, respectively

Frontopolar cortex represents complex features and decision value during choice between environments

Summary: Important decisions often involve choosing between complex environments that define future item encounters. Despite its importance for adaptive behavior and distinct computational challenges, decision-making research primarily focuses on item choice, ignoring environment choice altogether. Here we contrast previously studied item choice in ventromedial prefrontal cortex with lateral frontopolar cortex (FPl) linked to environment choice. Furthermore, we propose a mechanism for how FPl decomposes and represents complex environments during decision making. Specifically, we trained a choice-optimized, brain-naive convolutional neural network (CNN) and compared predicted CNN activation with actual FPl activity. We showed that the high-dimensional FPl activity decomposes environment features to represent the complexity of an environment to make such choice possible. Moreover, FPl functionally connects with posterior cingulate cortex for guiding environment choice. Further probing FPl’s computation revealed a parallel processing mechanism in extracting multiple environment features