Decoding the Narcissistic Brain

There is a substantial knowledge gap in the narcissism literature: <1 % of the nearly 12,000 articles on narcissism have addressed its neural basis. To help fill this gap, we asked whether the multifacetedness of narcissism could be decoded from spontaneous neural oscillations. We attempted to do so by applying a machine learning approach (multivariate pattern analysis) to the resting-state EEG data of 162 participants who also completed a comprehensive battery of narcissism scales assessing agentic, admirative, rivalrous, communal, and vulnerable forms. Consistent with the agency-communion model of narcissism, agentic and communal forms of grandiose narcissism were reflected in distinct, non-overlapping patterns of spontaneous neural oscillations. Furthermore, consistent with a narcissistic admiration and rivalry concept model of narcissism, we observed largely non-overlapping patterns of spontaneous neural oscillations for admirative and rivalrous forms of narcissism. Vulnerable narcissism was negatively associated with power across fast and slow wave frequency bands. Taken together, the results suggest that the diverse forms of narcissism can be reliably predicted from spontaneous neural oscillations. The findings contribute to the burgeoning field of personality neuroscience.

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Publication Details

Journal
NeuroImage
Published
2025-05-20
DOI
https://doi.org/10.1016/j.neuroimage.2025.121284
Citations
2
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
4.61

Funders

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article

Decoding the Narcissistic Brain

Zhiwei Zhou, Chengli Huang, Nicholas J. Kelley, Douglas J. Angus et al.
2 citations
NeuroImage
Personality Traits and Psychology
4.61
article

Decoding the Narcissistic Brain

Zhiwei Zhou, Chengli Huang, Nicholas J. Kelley, Douglas J. Angus, Constantine Sedikides, Esther M. Robins
article en
2 citations

Abstract

There is a substantial knowledge gap in the narcissism literature: <1 % of the nearly 12,000 articles on narcissism have addressed its neural basis. To help fill this gap, we asked whether the multifacetedness of narcissism could be decoded from spontaneous neural oscillations. We attempted to do so by applying a machine learning approach (multivariate pattern analysis) to the resting-state EEG data of 162 participants who also completed a comprehensive battery of narcissism scales assessing agentic, admirative, rivalrous, communal, and vulnerable forms. Consistent with the agency-communion model of narcissism, agentic and communal forms of grandiose narcissism were reflected in distinct, non-overlapping patterns of spontaneous neural oscillations. Furthermore, consistent with a narcissistic admiration and rivalry concept model of narcissism, we observed largely non-overlapping patterns of spontaneous neural oscillations for admirative and rivalrous forms of narcissism. Vulnerable narcissism was negatively associated with power across fast and slow wave frequency bands. Taken together, the results suggest that the diverse forms of narcissism can be reliably predicted from spontaneous neural oscillations. The findings contribute to the burgeoning field of personality neuroscience.

NeuroImageVol. 315
Bond University (AU), Identity (US), University of Southampton (GB)
Economic and Social Research Council
Openalex Percentile: Top 6%
Personality Traits and Psychology
4.61
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Decoding the Narcissistic Brain — Zhiwei Zhou, Chengli Huang, et al. · NeuroImage (2025) | TGRS Research Map | TGRS