Abstract
ABSTRACTEveryday decision-making commonly involves assigning values to complex objects with multiple value-relevant attributes. Drawing on object recognition theories, we hypothesized two routes to multi-attribute evaluation: assessing the value of the whole object based on holistic attribute configuration or summing individual attribute-values. In two samples of healthy human participants undergoing eye-tracking and fMRI while evaluating novel pseudo-objects, we found evidence for both forms of evaluation. Fixations to, and transitions between attributes differed systematically when value of pseudo-objects was associated with individual attributes or attribute configurations. Ventromedial prefrontal cortex (vmPFC) and perirhinal cortex were engaged when configural processing was required. These results converge with our recent findings that individuals with vmPFC lesions were impaired in decisions requiring configural evaluation, but not when evaluating “the sum of the parts”. This suggests that multi-attribute decision-making engages distinct evaluation mechanisms relying on partially dissociable neural substrates, depending on the relationship between attributes and value.SIGNIFICANCE STATEMENTDecision neuroscience has only recently begun to address how multiple choice-relevant attributes are brought together during evaluation and choice among complex options. Object recognition research makes a crucial distinction between individual attribute and holistic/configural object processing, but how the brain evaluates attributes and whole objects remains unclear. Using fMRI and eye-tracking, we found that the vmPFC and the perirhinal cortex contribute to value estimation specifically when it emerged from the whole objects i.e. predicted by the unique configuration of attributes, and not when value was predicted by the sum of individual attributes. This novel perspective on the interactions between subjective value and object processing mechanisms bridges an important gap between the fields of object recognition and reward-guided decision-making.
Publisher
Cold Spring Harbor Laboratory
Cited by
3 articles.
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