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Comparison of different group-level templates in gradient-based multimodal connectivity analysis.

Sunghun Kim1,2,3, Seulki Yoo4, Ke Xie5

  • 1Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea.

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Summary

Researchers compared brain connectivity template strategies for autism spectrum disorder (ASD). Aligning a combined ASD and control template from ABIDE onto the HCP template best identified ASD-related brain regions, improving gradient analysis.

Keywords:
Connectome gradientsGradient alignmentGroup-level templateMultimodal connectivity analysis

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Area of Science:

  • Neuroscience
  • Brain Connectivity
  • Computational Psychiatry

Background:

  • Unsupervised gradient analysis is emerging for studying large-scale brain connectivity and interindividual variations.
  • A key challenge is selecting an appropriate group-level template for aligning individual brain connectivity gradients.
  • Autism spectrum disorder (ASD) research can benefit from refined methods for analyzing brain connectivity differences.

Purpose of the Study:

  • To compare various group-level template construction strategies for gradient analysis of brain connectivity.
  • To identify the optimal strategy for detecting between-group differences in functional and structural connectomes, particularly in individuals with ASD.
  • To assess the generalizability of the chosen strategy across different datasets and neurological conditions.

Main Methods:

  • Utilized multimodal magnetic resonance imaging data from the Autism Brain Imaging Data Exchange (ABIDE) Initiative II and the Human Connectome Project (HCP).
  • Designed six template construction strategies, varying inclusion of control subjects and dataset mapping.
  • Aligned individual functional and structural gradients to different group-level templates and evaluated effect sizes for identifying ASD-related differences.

Main Results:

  • Aligning a combined template of ASD and control subjects from ABIDE onto the HCP template yielded the most significant effect size.
  • This strategy robustly identified brain regions associated with ASD in both functional and structural gradients.
  • The approach demonstrated generalizability through successful replication in studies of focal epilepsy.

Conclusions:

  • The optimal template construction strategy involves combining ASD and control data from one dataset (ABIDE) and aligning it to a template from another (HCP).
  • This method enhances the sensitivity of gradient analysis for detecting neurobiological differences in ASD.
  • The findings provide a refined methodology for gradient-based brain connectivity research, applicable across various neurological conditions.