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Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity.

Ellen Jaspers1, Joshua H Balsters1, Pegah Kassraian Fard1

  • 1Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Switzerland.

Human Brain Mapping
|November 19, 2016
PubMed
Summary

Researchers developed a new method to map brain connectivity by clustering striatal subregions. This provides a baseline for detecting abnormal brain networks in neurological conditions.

Keywords:
corticostriatal connectivityhierarchical clusteringprobability mapsresting-state fMRI

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Area of Science:

  • Neuroscience
  • Brain Imaging
  • Connectomics

Background:

  • Structure-function relationships in the brain are increasingly viewed as network-based.
  • Corticostriatal circuits are crucial for sensorimotor, limbic, and cognitive functions.
  • Detecting abnormal connectivity at the individual level remains a challenge.

Purpose of the Study:

  • To develop a method for clustering brain structures into subregions with distinct functional connectivity.
  • To generate network probability maps for comparing individual cases against a baseline.
  • To identify reproducible striatal subregions and their connectivity patterns.

Main Methods:

  • Utilized resting-state functional magnetic resonance imaging (fMRI) data from 100 participants.
  • Applied hierarchical clustering methods to parcellate the striatum into functionally distinct clusters.
  • Validated findings in an independent replication dataset (N=100).

Main Results:

  • Identified three highly reproducible striatal subregions across both hemispheres.
  • The putamen showed sensorimotor and language network connectivity.
  • The ventromedial striatum exhibited limbic connectivity, and the caudate showed connectivity with thalamus, frontal, occipital, and cerebellar areas.
  • Generated corticostriatal probability maps consistent with existing data and showing high replication.

Conclusions:

  • The developed method effectively clusters the striatum into functionally distinct subregions.
  • The generated network probability maps serve as a valuable baseline for individual comparisons.
  • These maps can aid in investigating deviant connectivity in neurological patient populations.