| Popis: |
Computational models of decision making have identified a relationship between obsessive-compulsive symptomatology and impairments in perceptual evidence accumulation. Past studies have suggested that these impairments in perceptual processing give rise to clusters of OCD symptoms (for example, not effectively “perceiving” that a door is locked or that one’s hands are clean gives rise to compulsive checking or washing). That interpretation has implications for our understanding of the disorder and warrants further testing; one way to investigate that is to determine whether such impairments correlate better with state-level symptoms (i.e., obsessions and compulsions during task performance) or trait-level symptoms (i.e., in general/past week). Using hierarchical drift-diffusion modeling, the current study examines this question in consideration of the alternate possibility that these decision impairments are simply a reflection of off-task processing of active obsessions and compulsions. We also examine whether working memory may mitigate such impairments, in light of prior studies that have associated larger working memory spans with better suppression of distractors and with faster perceptual evidence accumulation. 161 adults completed the random dot-motion task, OSPAN working memory task, and OCD symptom questionnaires online. Participants who reported greater obsessive-compulsive symptoms demonstrated slower evidence accumulation (“drift rate”) in the dot-motion task. These drift rate reductions were better explained by state-level symptom severity than trait-level severity. Working memory span showed a significant negative interaction with state-level symptom score on drift rate, however only for the easiest trials. While the current study does not negate a role of perceptual evidence accumulation deficits in the pathogenesis of OCD, these findings support the possibility that such deficits may also be brought about by active symptoms during task execution. We discuss using impairments in drift rate to approximate attentional bias for off-task symptoms, as this provides a novel computational framework in closer alignment with existing clinical models of OCD. |
