Dataset Information

Altered monetary loss processing and reinforcement-based learning in individuals with obesity.

ABSTRACT: Individuals with obesity are often characterized by alterations in reward processing. This may affect how new information is used to update stimulus values during reinforcement-based learning. Here, we investigated obesity-related changes in non-food reinforcement processing, their impact on learning performance as well as the neural underpinnings of reinforcement-based learning in obesity. Nineteen individuals with obesity (BMI?>?=?30 kg/m2, 10 female) and 23 lean control participants (BMI 18.5-24.9 kg/m2, 11 female) performed a probabilistic learning task during functional magnetic resonance imaging (fMRI), in which they learned to choose between advantageous and disadvantageous choice options in separate monetary gain, loss, and neutral conditions. During learning individuals with obesity made a significantly lower number of correct choices and accumulated a significantly lower overall monetary outcome than lean control participants. FMRI analyses revealed aberrant medial prefrontal cortex responses to monetary losses in individuals with obesity. There were no significant group differences in the regional representation of prediction errors. However, we found evidence for increased functional connectivity between the ventral striatum and insula in individuals with obesity. The present results suggest that obesity is associated with aberrant value representations for monetary losses, alterations in functional connectivity during the processing of learning outcomes, as well as a decresased reinforcement-based learning performance. This may affect how new information is incorporated to adjust dysfunctional behavior and could be a factor contributing to the maintenance of dysfunctional eating behavior in obesity.

SUBMITTER: Kube J

PROVIDER: S-EPMC6290732 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Altered monetary loss processing and reinforcement-based learning in individuals with obesity.

Kube Jana J Mathar David D Horstmann Annette A Kotz Sonja A SA Villringer Arno A Neumann Jane J

Brain imaging and behavior 20181001 5

Individuals with obesity are often characterized by alterations in reward processing. This may affect how new information is used to update stimulus values during reinforcement-based learning. Here, we investigated obesity-related changes in non-food reinforcement processing, their impact on learning performance as well as the neural underpinnings of reinforcement-based learning in obesity. Nineteen individuals with obesity (BMI > = 30 kg/m<sup>2</sup>, 10 female) and 23 lean control participant ...[more]

PMID: 29285721

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Project description:Recent research has shown that perceptual processing of stimuli previously associated with high-value rewards is automatically prioritized even when rewards are no longer available. It has been hypothesized that such reward-related modulation of stimulus salience is conceptually similar to an "attentional habit." Recording event-related potentials in humans during a reinforcement learning task, we show strong evidence in favor of this hypothesis. Resistance to outcome devaluation (the defining feature of a habit) was shown by the stimulus-locked P1 component, reflecting activity in the extrastriate visual cortex. Analysis at longer latencies revealed a positive component (corresponding to the P3b, from 550-700 ms) sensitive to outcome devaluation. Therefore, distinct spatiotemporal patterns of brain activity were observed corresponding to habitual and goal-directed processes. These results demonstrate that reinforcement learning engages both attentional habits and goal-directed processes in parallel. Consequences for brain and computational models of reinforcement learning are discussed.SIGNIFICANCE STATEMENT The human attentional network adapts to detect stimuli that predict important rewards. A recent hypothesis suggests that the visual cortex automatically prioritizes reward-related stimuli, driven by cached representations of reward value; that is, stimulus-response habits. Alternatively, the neural system may track the current value of the predicted outcome. Our results demonstrate for the first time that visual cortex activity is increased for reward-related stimuli even when the rewarding event is temporarily devalued. In contrast, longer-latency brain activity was specifically sensitive to transient changes in reward value. Therefore, we show that both habit-like attention and goal-directed processes occur in the same learning episode at different latencies. This result has important consequences for computational models of reinforcement learning.

Dataset Information

Altered monetary loss processing and reinforcement-based learning in individuals with obesity.

Publications

Altered monetary loss processing and reinforcement-based learning in individuals with obesity.

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