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Updated: Jan 27, 2026

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The spatial chronnectome reveals a dynamic interplay between functional segregation and integration.

Armin Iraji1, Thomas P Deramus1, Noah Lewis1

  • 1The Mind Research Network, Albuquerque, New Mexico.

Human Brain Mapping
|March 19, 2019
PubMed
Summary
This summary is machine-generated.

The novel spatial chronnectome reveals the brain

Keywords:
brain spatial dynamicsdynamic segregation and integrationlarge-scale networksresting state fMRI (rsfMRI)schizophreniaspatial chronnectomespatial couplingspatial statesspatiotemporal transition matrix

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Area of Science:

  • Neuroscience
  • Brain Imaging
  • Network Science

Background:

  • The brain exhibits dynamic activity across spatial and temporal scales.
  • Existing models often assume static brain networks, overlooking dynamic spatial variations.
  • The chronnectome models time-varying nodal activity and connectivity.

Purpose of the Study:

  • To introduce a novel approach for calculating a spatially fluid chronnectome.
  • To identify dynamic spatial features of brain network interactions at the voxel level.
  • To investigate transient network merging, separation, and anticorrelative connections.

Main Methods:

  • Developed a spatial chronnectome approach focusing on voxel-level network coupling variations.
  • Analyzed transient interactions, dynamic segregation, and integration of brain networks.
  • Utilized a multi-site dataset for preliminary assessments, including patients with schizophrenia.

Main Results:

  • Identified transient, spatially fluid interactions where brain networks merge and separate.
  • Revealed distinct spatial patterns in brain networks with unique temporal characteristics.
  • Observed transient anticorrelative connections and altered network coupling in schizophrenia patients.

Conclusions:

  • The spatial chronnectome enables the study of transient, voxel-level functional networks.
  • This approach uncovers mechanisms for spatial variability within and between subjects.
  • It offers new insights into brain dynamics and potential biomarkers for neurological conditions.