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Previous research has indicated potential structural and functional alterations in the default mode network (DMN) and reward-related regions in individuals exhibiting high levels of DT traits. However, these studies have often been limited by univariate analytical methods and small, unbalanced sample sizes. To address these gaps, we analyzed brain scans from a robust sample of 200 participants (mean age 32.43\u00a0years; 105 females) using group Independent Component Analysis (gICA), an unsupervised machine learning approach. This method allowed us to extract blood-oxygen-level-dependent (BOLD) low-frequency spectral power (fractional Amplitude of Low-Frequency Fluctuations; fALFF) associated with resting-state macro-networks without relying on predefined regions of interest. Our analysis identified 20 macro-networks, of which two were significantly predictive of DT traits: the Central Executive Network (CEN) and the posterior hub of the Default Mode Network (DMN). Notably, higher DT scores correlated with increased fALFF within the CEN and decreased fALFF within the DMN. The heightened activity in the CEN may reflect enhanced manipulative abilities and strategic planning commonly observed in individuals with high DT traits, which is supported by the association between the CEN and the Machiavellianism subscale. Conversely, reduced functionality in the DMN may correspond to diminished self-reflective and emotional capacities in these individuals. These findings contribute to a deeper understanding of the neurobiological basis of DT traits and hold implications for future research and interventions.<\/jats:p>","DOI":"10.3758\/s13415-025-01352-7","type":"journal-article","created":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T23:13:34Z","timestamp":1762298014000},"page":"139-154","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Neural fingerprint of the dark triad: Resting state BOLD power (fALFF) alterations in executive and default mode networks"],"prefix":"10.3758","volume":"26","author":[{"given":"Richard","family":"Bakiaj","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Clara Isabel Pantoja","family":"Mu\u00f1oz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Grecucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,4]]},"reference":[{"issue":"9","key":"1352_CR1","doi-asserted-by":"publisher","first-page":"1478","DOI":"10.1109\/JPROC.2015.2461624","volume":"103","author":"T Adali","year":"2015","unstructured":"Adali, T., Levin-Schwartz, Y., & Calhoun, V. 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