Evidence map›Paper›PMID 37293668›Full record

ArticleFrontiers in aging neuroscience2023

Discrete Ricci curvatures capture age-related changes in human brain functional connectivity networks.

Yasharth Yadav, Pavithra Elumalai, Nitin Williams, Jürgen Jost, Areejit Samal

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Article in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yasharth YadavThe Institute of Mathematical Sciences (IMSc), Chennai, India.
Pavithra ElumalaiThe Institute of Mathematical Sciences (IMSc), Chennai, India.
Nitin WilliamsDepartment of Computer Science, Helsinki Institute of Information Technology, Aalto University, Espoo, Finland.
Jürgen JostMax Planck Institute for Mathematics in the Sciences, Leipzig, Germany.
Areejit SamalThe Institute of Mathematical Sciences (IMSc), Chennai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Geometry-inspired notions of discrete Ricci curvature have been successfully used as markers of disrupted brain connectivity in neuropsychiatric disorders, but their ability to characterize age-related changes in functional connectivity is unexplored. Methods: We apply Forman-Ricci curvature and Ollivier-Ricci curvature to compare functional connectivity networks of healthy young and older subjects from the Max Planck Institute Leipzig Study for Mind-Body-Emotion Interactions (MPI-LEMON) dataset ( Results: We found that both Forman-Ricci curvature and Ollivier-Ricci curvature can capture whole-brain and region-level age-related differences in functional connectivity. Meta-analysis decoding demonstrated that those brain regions with age-related curvature differences were associated with cognitive domains known to manifest age-related changes-movement, affective processing, and somatosensory processing. Moreover, the curvature values of some brain regions showing age-related differences exhibited correlations with behavioral scores of affective processing. Finally, we found an overlap between brain regions showing age-related curvature differences and those brain regions whose non-invasive stimulation resulted in improved movement performance in older adults. Discussion: Our results suggest that both Forman-Ricci curvature and Ollivier-Ricci curvature correctly identify brain regions that are known to be functionally or clinically relevant. Our results add to a growing body of evidence demonstrating the sensitivity of discrete Ricci curvature measures to changes in the organization of functional connectivity networks, both in health and disease.

Indexed as

Forman-Ricci curvaturefunctional connectivity networkshealthy agingmotor performanceMPI-LEMONnon-invasive brain stimulationOllivier-Ricci curvatureresting-state fMRI

Identifiers

PMID37293668
PMCPMC10244515

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