Cognitive Affective & Behavioral NeuroscienceNeurosciencePeer-reviewed journal article
Towards a mechanistic understanding of the role of error monitoring and memory in social anxiety
Kianoosh HosseiniiD, Jeremy W. PettitiD, Fabián A. SotoiD, Aaron T. MattfeldiD, George Arthur BuzzelliD
Abstract
Cognitive models state social anxiety (SA) involves biased cognitive processing that impacts what is learned and remembered within social situations, leading to the maintenance of SA. Neuroscience work links SA to enhanced error monitoring, reflected in error-related neural responses arising from mediofrontal cortex (MFC). Yet, the role of error monitoring in SA remains unclear, as it is unknown whether error monitoring can drive changes in memory, biasing what is learned or remembered about social situations. Thus, we developed a novel paradigm to investigate the role of error-related MFC theta oscillations (associated with error monitoring) and memory biases in SA. EEG was collected while participants completed a novel Face-Flanker task, involving presentation of task-unrelated, trial-unique faces behind target/flanker arrows on each trial. A subsequent incidental memory assessment evaluated memory biases for error events. Severity of SA symptoms were associated with greater error-related theta synchrony over MFC, as well as between MFC and sensory cortex. SA was positively associated with memory biases for error events. Consistent with a mechanistic role in biased cognitive processing, greater error-related MFC-sensory theta synchrony during the Face-Flanker predicted subsequent memory biases for error events. Our findings suggest high SA individuals exhibit memory biases for error events, and that this behavioral phenomenon may be driven by error-related MFC-sensory theta synchrony associated with error monitoring. Moreover, results demonstrate the potential of a novel paradigm to elucidate mechanisms underlying relations between error monitoring and SA.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 2
- FWCI
- 0.82
- Field percentile
- top 24%
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