Neural Estimates of Imagined Outcomes in the Orbitofrontal Cortex Drive Behavior and Learning

Takahashi, Yuji K.; Chang, Chun Yun; Lucantonio, Federica; Haney, Richard Z.; Berg, B.A.M. van den; Yau, Hau Jie; Bonci, Antonello; Schoenbaum, Geoffrey

doi:10.1016/j.neuron.2013.08.008

Cited by 81 publications

(97 citation statements)

References 52 publications

(56 reference statements)

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“…We found that the firing of OFC neurons did not appear to correlate with errors in reward prediction and instead seemed to provide a complementary signal, anticipating expected rewards. This finding is consistent with several prior studies that have looked for and failed to see error signals in single units recorded in OFC (Kennerley, Behrens, & Wallis, 2011; McDannald et al, 2014; Takahashi et al, 2013, 2009). This study extends those prior reports by testing whether activity in OFC reflects errors in the prediction of the sensory features of the rewards, independent of value.…”

Section: Discussionsupporting

confidence: 93%

Orbitofrontal neurons signal reward predictions, not reward prediction errors

Stalnaker

Liu

Takahashi

et al. 2018

Neurobiology of Learning and Memory

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Neurons in the orbitofrontal cortex (OFC) fire in anticipation of and during rewards. Such firing has been suggested to encode reward predictions and to account in some way for the role of this area in adaptive behavior and learning. However, it has also been reported that neural activity in OFC reflects reward prediction errors, which might drive learning directly. Here we tested this question by analyzing the firing of OFC neurons recorded in an odor discrimination task in which rats were trained to sample odor cues and respond left or right on each trial for reward. Neurons were recorded across blocks of trials in which we switched either the number or the flavor of the reward delivered in each well. Previously we have described how neurons in this dataset fired to the predictive cues (Stalnaker et al., 2014); here we focused on the firing in anticipation of and just after delivery of each drop of reward, looking specifically for differences in firing based on whether the reward number or flavor was unexpected or expected. Unlike dopamine neurons recorded in this setting, which exhibited phasic error-like responses after surprising changes in either reward number or reward flavor (Takahashi et al., 2017), OFC neurons showed no such error correlates and instead fired in a way that reflected reward predictions.

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Section: Discussionsupporting

confidence: 93%

Orbitofrontal neurons signal reward predictions, not reward prediction errors

Stalnaker

Liu

Takahashi

et al. 2018

Neurobiology of Learning and Memory

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“…In accordance with the aforementioned results, BOLD-activation associated with PEs incorporating inference on alternative options was reduced in the vmPFC of BED patients. In healthy individuals, concurrent tracking of multiple decision possibilities and their potential consequences contributes to flexible goal-directed behavior in dynamic environments (Abe and Lee, 2011;BrombergMartin et al, 2010;Glascher et al, 2009;Hampton et al, 2006;Lohrenz et al, 2007;Takahashi et al, 2013). In the present study, vmPFC PE signatures incorporating inference on alternative options were indeed positively associated with successful choices and negatively associated with switching behavior.…”

Section: Reduced Incorporation Of Inference On Alternative Options Insupporting

confidence: 55%

Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging

Reiter

Heinze

Schlagenhauf

et al. 2016

Neuropsychopharmacol

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Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, binge eating disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n = 22) and matched healthy individuals (n = 22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, although so-called model-free reward prediction errors remained intact, representation of ventro-medial prefrontal learning signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. On the basis of a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED.

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“…Previous rodent studies indicate that OFC neurons start representing the relative value of potential outcomes from the time a decision is made (Sul et al 2010;Takahashi et al 2013). Indeed, we now have preliminary evidence that neuronal activity in the OFC of rats performing the same task carried value signals at possible choice areas of the T-maze (e.g., the start arm and the junction of the 3 arms) and these signals persisted until the end of delay periods ( Jo and Mizumori, unpublished data).…”

Section: Ofc Contribution To Generating Expected Reward Valuementioning

confidence: 99%

“…The literature suggests that the PFC can flexibly adjust outcome values in response to motivational or environmental changes even before experiencing the outcome (Corbit and Balleine 2003;Izquierdo et al 2004;Ostlund and Balleine 2005;Jones et al 2012;Takahashi et al 2013). Due to this characteristic of updating values independent of reward prediction errors, little attention has been paid to the possibility that the PFC may directly influence computations of DAergic error signals.…”

Section: Introductionmentioning

confidence: 99%

Prefrontal Regulation of Neuronal Activity in the Ventral Tegmental Area

Mizumori

2015

Cereb. Cortex

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Growing evidence indicates that midbrain dopamine (DA) cells integrate reward expectancy-related information from the prefrontal cortex to properly compute errors in reward prediction. Here we investigated how 2 major prefrontal subregions, the orbitofrontal cortex (OFC) and the medial prefrontal cortex (mPFC), contributed to DAergic prediction errors while rats performed a delay discounting task on a T-maze. Most putative DA cells in the task showed phasic responses to salient cues that predicted delayed rewards, but not to the actual rewards. After temporary inactivation of the OFC, putative DA cells exhibited strikingly reduced phasic responses to reward-predicting cues but increased responses to rewards. In contrast, mPFC inactivation significantly elevated DA responses to both predictive cues and rewards. In addition, OFC, but not mPFC, inactivation disrupted the activity of putative non-DA cells that encoded expected reward values during waiting periods. These results suggest that the 2 prefrontal subregions differentially regulate DAergic prediction errors and the OFC conveys value signals to midbrain dopamine systems.

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Neural Estimates of Imagined Outcomes in the Orbitofrontal Cortex Drive Behavior and Learning

Cited by 81 publications

References 52 publications

Orbitofrontal neurons signal reward predictions, not reward prediction errors

Orbitofrontal neurons signal reward predictions, not reward prediction errors

Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging

Prefrontal Regulation of Neuronal Activity in the Ventral Tegmental Area

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