In this study, we aimed to determine if …
- Individuals high in SA exhibit greater recognition memory performance of error-related information
- Greater recognition memory performance of error-related information will be associated with greater error monitoring at the time of encoding.
Stronger error monitoring is linked to social anxiety (SA). However, it is not understood why this is the case. One hypothesis is that stronger error monitoring could strengthen encoding of errors or their context (e.g., social cues in the environment). As encoding of errors or incidental social cues cannot be studied by traditional error monitoring tasks, we developed a novel paradigm to test these ideas. While EEG data was being collected, 54 participants completed a novel Face-Flanker task, involving presentation of task-unrelated, trial-unique faces behind target/flanker arrows on each trial. Following the task, a surprise memory test was used to evaluate incidental learning on error trials. During the subsequent surprise memory test, higher SA was associated with better recognition memory for faces originally appearing on error (vs. correct) trials (p < 0.01). During the flanker, individuals higher in SA showed greater error-related theta synchrony over MFC (p = .05), as well as between MFC and sensory (visual) cortex (p = .02). Crucially, greater error-related theta synchrony between MFC and sensory (visual) cortex during the flanker was correlated with subsequent increases in recognition memory for faces from error (vs. correct) trials (p = .03). Our findings not only suggest higher SA individuals exhibit better incidental encoding of social stimuli on error (vs. correct) trials, but this behavioral phenomenon may be driven by error-related dynamics within the theta band. Results demonstrate the potential of a novel paradigm to elucidate mechanisms underlying the link between error monitoring and SA.
Release 1: anticipated Q2 2023
Here is the link to the MS PPT file of the talk given by Kianoosh Hosseini at ACBM 2023 conference at NIH.
This main branch contains completed releases for this project. For all work-in-progress, please switch over to the dev branches.
| Name | Role |
|---|---|
| Kianoosh Hosseini | Project lead |
| George Buzzell | Guidance |
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