Neurons in the macaque orbitofrontal cortex code relative preference of both rewarding and aversive outcomes

Hosokawa, Toru; Kato, Keichiro; Inoue, Masato; Mikami, Atsushi

doi:10.1016/j.neures.2006.12.003

Cited by 71 publications

(59 citation statements)

References 55 publications

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“…Although this region was implicated in a previous study of regret (Coricelli et al, 2005), it may actually be registering surprise, an interpretation that could not be made with the design of Coricelli et al (2005). This region has more commonly been associated with aversive outcomes and losses (Hosokawa et al, 2007;O'Doherty et al, 2001;Rolls, 2000;Ursu and Carter, 2005). Its activation with both regret and rejoice in our study may reflect a specialization for the processing of potentially aversive outcomes, whether realized or not.…”

Section: Discussioncontrasting

confidence: 60%

Neurobiological regret and rejoice functions for aversive outcomes

et al. 2008

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A decision maker may experience regret when a choice he makes results in a more adverse outcome than a different choice would have yielded. Analogously, he may experience rejoice when his choice resulted in better outcomes. We used fMRI to investigate the neural correlates of regret and rejoice where payoffs are in terms of a non-monetary medium. Incentives were created using painful outcomes in the form of mild electrical shocks to the foot and the possibility of avoiding them. We hypothesized that the neural response to a painful outcome resulting from an individual's choice would also reflect the degree of regret as measured by the likelihood that alternative choices would have yielded the same adverse outcome. Similarly, when an individual avoids a potential shock, he would experience a degree of rejoice that correlates with the probability he had of receiving the shock. For example, winning a bet when winning was unlikely, even if the outcome is the same, evokes more rejoice than winning when it was highly probable. Our results suggest that activation of a cortical network, consisting of the medial orbitofrontal cortex, left superior frontal cortex, right angular gyrus, and left thalamus, correlates with the degree of regret. A different network, including the rostral anterior cingulate, left hippocampus, left ventral striatum, and brainstem/midbrain correlated with rejoice. The right inferior orbitofrontal cortex, pre-supplementary motor area, anterior cingulate, and posterior cingulate showed similar patterns of activation with both regret and rejoice, suggesting that these regions may be associated with surprise from the realization of relatively unlikely events. Our results suggest that distinct, but overlapping networks are involved in the experiences of regret and rejoice.

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Section: Discussioncontrasting

confidence: 60%

Neurobiological regret and rejoice functions for aversive outcomes

et al. 2008

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“…An fMRI study with humans found similar results in the medial orbitofrontal cortex-a brain region involved in value coding [74]. Such neural patternsoutcomes activating orbitofrontal neurons only when they are comparatively better-are also exhibited with unpleasant stimuli [75].…”

Section: Box 2 Neurobiological Evidence In Support Of Comparison-basmentioning

confidence: 60%

Does the brain calculate value?

Vlaev

Chater

Stewart

et al. 2011

Trends in Cognitive Sciences

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Section: What Are the Components Of Value?mentioning

confidence: 99%

“…Human neuroimaging studies tend to indicate that rewards and losses/punishments are processed in distinct subregions of OFC, with lateral regions being more modulated by costs and medial regions by benefits [20,28,29]. However, the same neurons that respond to rewards can also signal aversive electrical shocks [30].A recent neuroimaging study [31] showed that part of OFC correlated with 'willingness to pay', a concept critical in economics that combines cost and benefit. By contrast, lesion studies in rodents failed to implicate the OFC in processing costs such as the effort of climbing a wall [32,33] or in instrumental behaviors in general [34].…”

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Neural representation of behavioral outcomes in the orbitofrontal cortex

Mainen

Kepecs

2009

Current Opinion in Neurobiology

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The orbitofrontal cortex (OFC) is important in processing rewards and other behavioral outcomes. Here, we review from a computational perspective recent progress in understanding this complex function. OFC neurons appear to represent abstract outcome values, which may facilitate the comparison of options, as well as concrete outcome attributes, such as flavor or location, which may enable predictive cues to access current outcome values in the face of dynamic modulation by internal state, context and learning. OFC can use reinforcement learning to generate outcome predictions; it can also generate outcome predictions using other mechanisms, including the evaluation of decision confidence or uncertainty. OFC neurons encode not only the mean expected outcome but also the variance, consistent with the idea that OFC uses a probabilistic population code to represent outcomes. We suggest that further attention to the nature of its representations and algorithms will be critical to further elucidating OFC function. IntroductionThe orbitofrontal cortex (OFC) was initially characterized as an area whose destruction profoundly impacted human personality, but, paradoxically, left no obvious deficits in standard cognitive tests (reviewed in [1]). Yet, through intensifying scrutiny over the last decade the function of the OFC has arisen from obscurity to take a central place in our understanding of learning and decision-making [2,3]. Today, through a remarkable convergence of studies conducted in species ranging from rats to humans, OFC is widely conceived as a place where the 'value' of things is represented in the brain.While the concept of 'value' may strike a hard-nosed neuroscientist as hopelessly fuzzy, this concept plays a central role in most behavioral theories of decisionmaking. In neuroeconomic theory, assignment of economic value allows qualitatively different goods to be compared in a single 'universal currency ' [4]. In animal learning theory, the similar concept of 'incentive value' measures the ability of outcomes to motivate behavior [5,6]. In machine learning theory, 'state values' and 'action values' are the principal targets of learning and action selection; by maximizing these values, agents learn optimal behavior [7]. By offering formal (i.e. quantitative) definitions of value and related concepts, these theoretical frameworks can help one to test and eventually to understand more precisely what the OFC does. That is because formal definitions can yield concrete predictions that are testable using traditional neurophysiological and behavioral measurements without resorting to semantic arguments about abstract terms [8].While theoretical perspectives are helpful, they also bring on more work. In the light of theory, questions about OFC function become not only more clear but also more detailed and nuanced, opening up and demanding further experimental tests. Moreover, different theoretical frameworks present partially overlapping, sometimes incongruent, views that must eventually be reconciled. Finally,...

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Neurons in the macaque orbitofrontal cortex code relative preference of both rewarding and aversive outcomes

Cited by 71 publications

References 55 publications

Neurobiological regret and rejoice functions for aversive outcomes

Neurobiological regret and rejoice functions for aversive outcomes

Does the brain calculate value?

Neural representation of behavioral outcomes in the orbitofrontal cortex

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