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Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain

Jin Liu1,2,3, Xuhong Liao1,2,3, Mingrui Xia1,2,3

  • 1National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.

Human Brain Mapping
|November 17, 2017
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Summary

The brain's dynamic connectivity patterns, or chronnectome, show unique individual fingerprints. These brain network dynamics can identify individuals and predict cognitive abilities like fluid intelligence.

Keywords:
R-fMRIconnectomicsfunctional dynamicsindividual differencessliding window

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Area of Science:

  • Neuroscience
  • Network Science
  • Cognitive Neuroscience

Background:

  • The human brain functions as a dynamic network with time-varying connectivity, known as the chronnectome.
  • Individual uniqueness in chronnectome dynamics remains largely unexplored.
  • Understanding brain network variability is crucial for characterizing individual differences.

Purpose of the Study:

  • To investigate if dynamic properties of the chronnectome can serve as an individual "fingerprint."
  • To examine the relationship between chronnectome dynamics and higher cognitive performance.
  • To explore the potential of chronnectome for individualized health and disease characterization.

Main Methods:

  • Utilized multiband resting-state functional magnetic resonance imaging (rs-fMRI) data from the Human Connectome Project (N=105).
  • Applied a sliding time-window dynamic network analysis to assess time-varying brain connectivity.
  • Analyzed individual variability in connectivity strength, stability, and variability.

Main Results:

  • Identified stable and significant individual variability in dynamic brain connectivity characteristics.
  • Found this variability concentrated in higher-order cognitive systems (default mode, dorsal attention, fronto-parietal) and primary systems (visual, sensorimotor).
  • Demonstrated that spatial patterns of dynamic connectivity accurately identify individuals and predict cognitive performance (fluid intelligence, executive function).

Conclusions:

  • The chronnectome captures inherent, individualized functional dynamics of brain networks.
  • Dynamic connectivity patterns offer a unique neural signature for individual identification.
  • Findings have implications for personalized medicine and understanding neurological health and disease.