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<p>Characterizing individual variation in brain network organization is essential for developing fMRI-based biomarkers in precision psychiatry. We show that arousal, assessed by systemic low-frequency oscillation (sLFO) amplitude in the fMRI signal, is strongly associated with interindividual variability in functional brain network properties (e.g., R = 0.70 for default mode network (DMN)–dorsal attention network (DAN) connectivity; R = −0.63 for DMN dynamics), with replication across independent sessions and samples. These relationships persist after regressing the sLFO out of the BOLD signal and are replicated using established physiological arousal indices, indicating that arousal-related physiology significantly contributes to variability in brain network measures. Pharmacological manipulation shows that increased arousal under catecholaminergic agonism is associated with enhanced network differentiation, whereas antagonism produces the opposite effect. These findings highlight arousal-related physiological processes as a major contributor to individual differences in functional brain network properties as estimated with fMRI and indicate that catecholaminergic modulation is associated with these effects via arousal-related processes.</p>

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Physiological arousal as a predominant source of individual differences in functional brain networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月10日

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  • Justine A. Hill,
  • Tianye Zhai,
  • Cole Korponay,
  • Julia C. Welsh,
  • Betty Jo Salmeron,
  • Thomas J. Ross,
  • Yihong Yang,
  • Blaise deB. Frederick,
  • Amy C. Janes

摘要

Characterizing individual variation in brain network organization is essential for developing fMRI-based biomarkers in precision psychiatry. We show that arousal, assessed by systemic low-frequency oscillation (sLFO) amplitude in the fMRI signal, is strongly associated with interindividual variability in functional brain network properties (e.g., R = 0.70 for default mode network (DMN)–dorsal attention network (DAN) connectivity; R = −0.63 for DMN dynamics), with replication across independent sessions and samples. These relationships persist after regressing the sLFO out of the BOLD signal and are replicated using established physiological arousal indices, indicating that arousal-related physiology significantly contributes to variability in brain network measures. Pharmacological manipulation shows that increased arousal under catecholaminergic agonism is associated with enhanced network differentiation, whereas antagonism produces the opposite effect. These findings highlight arousal-related physiological processes as a major contributor to individual differences in functional brain network properties as estimated with fMRI and indicate that catecholaminergic modulation is associated with these effects via arousal-related processes.