Unlocking the Reinforcement-Learning Circuits of the Orbitofrontal Cortex

Neuroimaging studies have consistently identified the orbitofrontal cortex (OFC) as being affected in individuals with neuropsychiatric disorders. OFC dysfunction has been proposed to be a key mechanism by which decision-making impairments emerge in diverse clinical populations, and recent studies employing computational approaches have revealed that distinct reinforcement-learning mechanisms of decision-making differ among diagnoses. In this perspective, we propose that these computational differences may be linked to select OFC circuits and present our recent work that has used a neurocomputational approach to understand the biobehavioral mechanisms of addiction pathology in rodent models. We describe how combining translationally analogous behavioral paradigms with reinforcement-learning algorithms and sophisticated neuroscience techniques in animals can provide critical insights into OFC pathology in biobehavioral disorders.

Automated summary

Neuroimaging studies consistently suggest the involvement of the orbitofrontal cortex (OFC) in neuropsychiatric disorders, with distinct reinforcement-learning mechanisms affecting decision-making in different clinical populations. By combining analogous behavioral paradigms, reinforcement-learning algorithms, and advanced neuroscience techniques in animals, critical insights into OFC pathology in biobehavioral disorders can be gained.