September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Examining spontaneous neural activity patterns in developmental prosopagnosia using resting state EEG
Author Affiliations & Notes
  • Maruti Mishra
    California State University Bakersfield, CA, USA
    VA Boston Healthcare/Harvard Medical School, Boston, MA
    University of Richmond, Virginia, USA
  • Erin Hugee
    Northwestern University, IL, USA
  • Patrick Sutphin
    University of Richmond, Virginia, USA
  • Kevin Spencer
    VA Boston Healthcare/Harvard Medical School, Boston, MA
  • Joseph DeGutis
    VA Boston Healthcare/Harvard Medical School, Boston, MA
  • Cindy Bukach
    University of Richmond, Virginia, USA
  • Footnotes
    Acknowledgements  NSF and James S. McDonnell Foundation Scholar Award to Cindy Bukach; R01EY032510-02 to Joe DeGutis
Journal of Vision September 2024, Vol.24, 1516. doi:https://doi.org/10.1167/jov.24.10.1516
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      Maruti Mishra, Erin Hugee, Patrick Sutphin, Kevin Spencer, Joseph DeGutis, Cindy Bukach; Examining spontaneous neural activity patterns in developmental prosopagnosia using resting state EEG. Journal of Vision 2024;24(10):1516. https://doi.org/10.1167/jov.24.10.1516.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Developmental prosopagnosia (DP) is characterized by a lifelong difficulty in learning and recognizing faces. While task-based studies have identified brain regions associated with face processing deficits in DPs, less is known about the spontaneous, intrinsic brain activity patterns in the absence of explicit tasks. To address this, resting-state electroencephalography (EEG) data were obtained from 32 DPs and 25 controls during five-minute open-eye recordings. The data were preprocessed at 0.5 to 100 Hz, ICA artifact corrected and average referenced to extract absolute spectral power values for delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (14-30 Hz), and gamma (30-80 Hz) bands for each electrode and then pooled into regional electrode clusters (frontal, central, parietal, temporal and occipital). A 3 way mixed ANOVA for the two groups, hemispheres, and regions revealed significant interactions for alpha and gamma bands, highlighting hemispheric differences. Individuals with DP displayed significantly lower alpha power in the left hemisphere compared to the right. This was driven by central and temporal electrode regions. In contrast, both groups exhibited significantly greater gamma power in the left hemisphere, with controls showing a larger hemispheric asymmetry. This asymmetry was driven by electrodes in the parietal, temporal, and occipital regions in controls, leading to significant DP vs control group differences. Alterations in alpha power have been associated with neuronal excitability and gamma in higher-level feature binding, both critical for face processing. Furthermore, both alpha and gamma have also been implicated in N170 ERP for face specific processing. Our findings provide evidence for the first time that there are cross-hemisphere differences in resting state alpha and gamma band power between DPs and controls.

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