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bioRxiv · 10.64898/2026.10.21.760530

Dissociating Resting-State Networks of Pedohebephilic Preference and Child Sexual Offending Using Network-Based Prediction

Abstract

Background: Pedohebephilia (P+), the sexual preference for prepubescent and early pubertal minors, regularly causes distress in those affected. While associated with child sexual offending (CSO), P+ is not a prerequisite for CSO. Limited neuroimaging studies have identified alterations associated with P+, while these may primarily reflect offending history. The correlates of P+ independent of CSO therefore remain unclear. We examined this distinction using intrinsic functional networks within a multivariate predictive framework. Methods: Using resting-state functional connectivity (rsFC) and network-based prediction (NBS-Predict), we performed pairwise classifications among non-offending pedohebephilic men (P+CSO-, n=35), pedohebephilic men with CSO (P+CSO+, n=38), and non-pedohebephilic controls without CSO (P-CSO-, n=63). Classification-relevant subnetwork nodal strength was associated post hoc with trait impulsivity within P+ groups. Results: P+CSO- were significantly distinguished from P-CSO- (balanced accuracy [BAC]=0.621, pFDR=.041), and showed reductions between default-mode hubs and temporoparietal somatomotor and ventral attention regions. P+CSO+ were also significantly distinguished from P+CSO- (BAC=0.645, pFDR=.032) and yielded a smaller subnetwork centered on the substantia nigra. Against P-CSO-, P+CSO+ showed widespread reductions, particularly across subcortical, default mode, visual, limbic, and somatomotor regions (BAC=0.640, pFDR=0.032). Right precentral gyrus nodal strength correlated with impulsivity in P+CSO+ only (r=0.57, pFDR=0.024). Conclusions: Whole-brain rsFC contains information distinguishing pedohebephilic preference in the absence of known CSO, while P+CSO+ show additional and more widespread network alterations involving systems implicated in action selection and behavioral regulation. These findings open new avenues for integrating pedohebephilia into broader neurobiological research frameworks.

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Serin, E., Khan, K. R., Krueger, T., Sinke, C., Beier, K. M., Walter, M., Schiffer, B., Amelung, T., Walter, H.. 2026-10-26. Dissociating Resting-State Networks of Pedohebephilic Preference and Child Sexual Offending Using Network-Based Prediction. https://doi.org/10.64898/2026.10.21.760530

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