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Related Experiment Video

Updated: Apr 25, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Node persistence from topological data analysis reveals changes in brain functional connectivity.

Madhumita Mondal^1,2, Yasharth Yadav³, Jürgen Jost^4,5,6,7

¹The Institute of Mathematical Sciences (IMSc), Chennai, Tamil Nadu 600113, India.

Patterns (New York, N.Y.)

|April 24, 2026

Summary

This summary is machine-generated.

Persistent homology reveals brain region differences in healthy aging and autism spectrum disorder (ASD). This topological data analysis method identifies key brain areas affected by these conditions.

Keywords:

autism spectrum disorder functional connectivity healthy aging non-invasive brain stimulation persistent homology resting-state fMRI topological data analysis

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Last Updated: Apr 25, 2026

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Published on: May 7, 2014

Area of Science:

Neuroscience
Topological Data Analysis
Computational Biology

Background:

Large-scale brain functional connectivity analysis reveals neurological disruptions.
Healthy aging and autism spectrum disorder (ASD) involve altered brain activity and connectivity.

Purpose of the Study:

Investigate changes in resting-state functional connectivity using persistent homology (PH).
Analyze these changes across global, mesoscopic, and local brain scales.
Introduce and validate 'node persistence' for identifying clinically relevant brain regions.

Main Methods:

Applied persistent homology (PH) to resting-state functional connectivity data.
Examined brain changes at global (brain-wide), mesoscopic (network), and local (region) scales.
Developed and utilized node persistence, a PH-based metric for regional analysis.

Main Results:

Identified significant differences in functional connectivity at local scales in healthy aging and ASD.
Node persistence effectively detected brain regions with altered connectivity.
These identified regions align with those targeted for therapeutic interventions.

Conclusions:

Persistent homology, particularly node persistence, is a valuable tool for analyzing brain connectivity.
This approach can identify brain regions impacted by healthy aging and ASD.
Findings suggest clinical relevance for targeted brain stimulation and interventions.