The primate orbitofrontal cortex (OFC) is involved in reward processing, learning, and decision making. Research in monkeys has shown that this region is densely connected with higher sensory, limbic, and subcortical regions. Moreover, a parcellation of the monkey OFC into two subdivisions has been suggested based on its intrinsic anatomical connections. However, in humans, little is known about any functional subdivisions of the OFC except for a rather coarse medial/lateral distinction. Here, we used resting-state fMRI in combination with unsupervised clustering techniques to investigate whether OFC subdivisions can be revealed based on their functional connectivity profiles with other brain regions. Examination of different cluster solutions provided support for a parcellation into two parts as observed in monkeys, but it also highlighted a much finer hierarchical clustering of the orbital surface. Specifically, we identified (1) a medial, (2) a posterior-central, (3) a central, and (4–6) three lateral clusters spanning the anterior–posterior gradient. Consistent with animal tracing studies, these OFC clusters were connected to other cortical regions such as prefrontal, temporal, and parietal cortices but also subcortical areas in the striatum and the midbrain. These connectivity patterns provide important implications for identifying specific functional roles of OFC subdivisions for reward processing, learning, and decision making. Moreover, this parcellation schema can provide guidance to report results in future studies.

An optimal choice among alternative behavioral options requires precise anticipatory representations of their possible outcomes. A fundamental question is how such anticipated outcomes are represented in the brain. Reward coding at the level of single cells in the orbitofrontal cortex (OFC) follows a more heterogeneous coding scheme than suggested by studies using functional MRI (fMRI) in humans. Using a combination of multivariate pattern classification and fMRI we show that the reward value of sensory cues can be decoded from distributed fMRI patterns in the OFC. This distributed representation is compatible with previous reports from animal electrophysiology that show that reward is encoded by different neural populations with opposing coding schemes. Importantly, the fMRI patterns representing specific values during anticipation are similar to those that emerge during the receipt of reward. Furthermore, we show that the degree of this coding similarity is related to subjects’ ability to use value information to guide behavior. These findings narrow the gap between reward coding in humans and animals and corroborate the notion that value representations in OFC are independent of whether reward is anticipated or actually received.

Patients suffering from addiction persist in consuming substances of abuse, despite negative consequences or absence of positive consequences. One potential explanation is that these patients are impaired at flexibly adapting their behavior to changes in reward contingencies. A key aspect of adaptive decision-making involves updating the value of behavioral options. This is thought to be mediated via a teaching signal expressed as a reward prediction error (PE) in the striatum. However, to exert control over adaptive behavior, value signals need to be broadcast to higher executive regions, such as prefrontal cortex. Here we used functional MRI and a reinforcement learning task to investigate the neural mechanisms underlying maladaptive behavior in human male alcohol-dependent patients. We show that in alcohol-dependent patients the expression of striatal PEs is intact. However, abnormal functional connectivity between striatum and dorsolateral prefrontal cortex (dlPFC) predicted impairments in learning and the magnitude of alcohol craving. These results are in line with reports of dlPFC structural abnormalities in substance dependence and highlight the importance of frontostriatal connectivity in addiction, and its pivotal role in adaptive updating of action values and behavioral regulation. Furthermore, they extend the scope of neurobiological deficits underlying addiction beyond the focus on the striatum.

Significance: The value and salience of predictive cues are important signals for regulating approach–avoidance behavior and attentional processing, respectively. However, the two signals often are confounded in studies of decision-making. Indeed, recent results suggest that neural signals in the primate posterior parietal cortex (PPC) which previously were thought to encode value actually reflect salience. This finding has created considerable uncertainty about previously identified value signals. Here we experimentally dissociate value and salience and use pattern-based functional MRI to demonstrate distinct encoding of both signals in the PPC, thereby reinforcing the earlier reports of value in the PPC. Moreover, we show that the orbitofrontal cortex encodes the predicted value of appetitive and aversive outcomes on a common neural scale.

Receiving social feedback such as praise or blame for one's character traits is a key component of everyday human interactions. It has been proposed that humans are positively biased when integrating social feedback into their self-concept. However, a mechanistic description of how humans process self-relevant feedback is lacking. Here, participants received feedback from peers after a real-life interaction. Participants processed feedback in a positively biased way, i.e., they changed their self-evaluations more toward desirable than toward undesirable feedback. Using functional magnetic resonance imaging we investigated two feedback components. First, the reward-related component correlated with activity in ventral striatum and in anterior cingulate cortex/medial prefrontal cortex (ACC/MPFC). Second, the comparison-related component correlated with activity in the mentalizing network, including the MPFC, the temporoparietal junction, the superior temporal sulcus, the temporal pole, and the inferior frontal gyrus. This comparison-related activity within the mentalizing system has a parsimonious interpretation, i.e., activity correlated with the differences between participants' own evaluation and feedback. Importantly, activity within the MPFC that integrated reward-related and comparison-related components predicted the self-related positive updating bias across participants offering a mechanistic account of positively biased feedback processing. Thus, theories on both reward and mentalizing are important for a better understanding of how social information is integrated into the human self-concept.