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The self-awareness brain network: Construction, characterization, and alterations in schizophrenia and major
Xiaoluan Xia1, Fei Gao2, Shiyang Xu3
1Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, 19000, China; Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 519000, China; Zhuhai UM Science and Technology Research Institute, University of Macau, Zhuhai, 519000, China.
Abstract:
Self-awareness (SA) research is crucial for understanding cognition, social behavior, mental health, and education, but SA's underlying network architecture, particularly connectivity patterns, remains largely uncharted. We integrated meta-analytic findings with connectivity-behavior correlation analyses to systematically identify SA-related regions and connections in healthy adults. Edge-weighted networks capturing public, private, and composite SA dimensions were established, where weights represented correlation strengths between tractography-derived structural connectivities and SA levels quantified through behavioral assessments. Then, multilevel SA networks were extracted across a spectrum of correlation thresholds. Robust full-threshold analyses revealed their hierarchical continuum encompassing distinct lateralization patterns, topological transitions, and characteristic hourglass-like architectures. Pathological analysis demonstrated SA connectivity disruptions in schizophrenia (SZ) and major depressive disorder (MDD): approximately 40 % of SA-related connectivities were altered in SZ and 20 % in MDD, with 90 % of MDD alterations overlapping with SZ. While disease-specific and shared alterations were also observed in network-level topological properties, the core SA connectivity framework remained preserved in both disorders. Collectively, these findings significantly advanced our understanding of SA's neurobiological substrates and their pathological deviations.
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