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Whole-brain network dynamics underlying intolerance of uncertainty.

Wonyoung Kim1, Nayoung Kim2, Seohyeon Lee3

  • 1Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Victoria, Melbourne, Australia.

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|June 30, 2026
PubMed
Summary

Intolerance of uncertainty (IU) is linked to psychopathology. This study reveals a specific brain network sensitive to uncertainty, showing sustained activity and generalizing to clinical symptoms.

Keywords:
Functional connectivityInternalizing symptomsIntolerance of uncertaintyNetworkTemporal dynamics

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Cognitive Science

Background:

  • Intolerance of uncertainty (IU) is a significant risk factor for various psychopathologies.
  • The precise neural mechanisms underlying IU are not well understood.
  • Understanding these mechanisms is crucial for developing targeted interventions.

Purpose of the Study:

  • To investigate the neural underpinnings and network dynamics of intolerance of uncertainty (IU) using functional magnetic resonance imaging (fMRI).
  • To identify brain networks predictive of IU and examine their temporal characteristics.
  • To validate the generalizability of these findings in an independent dataset.

Main Methods:

  • Employed connectome-based predictive modeling (CPM) and edge time-series analysis on fMRI data during a task involving surprised faces.
  • Utilized a primary cohort (N=85) and a large independent dataset (N=878) for validation.
  • Examined network dynamics during task performance, post-task resting-state, and in relation to clinical symptoms during a gambling task.

Main Results:

  • CPM identified an IU-predictive network with specific visual-salience and subcortical-motor couplings.
  • IU was associated with both positive and negative network couplings, with inhibitory IU linked specifically to the negative network.
  • Sustained engagement of the IU-related network was observed during post-task resting-state in individuals with higher IU.
  • The identified network dynamics generalized to internalizing symptoms in an independent dataset during a gambling task.

Conclusions:

  • A distinct neural network sensitive to evoked uncertainty underlies intolerance of uncertainty.
  • This IU-related network exhibits sustained temporal dynamics that are generalizable across different tasks and populations.
  • These findings provide crucial insights into the neural basis of IU and its link to psychopathology.