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research article

Homological Landscape of Human Brain Functional Sub-Circuits

Duong-Tran, Duy
•
Kaufmann, Ralph
•
Chen, Jiong
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February 1, 2024
Mathematics

Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., a set of functional sub-circuits induced by node or edge attributes) and non-local (e.g., higher-order functional coordination patterns) properties. Nonetheless, the non-local properties of topological strata induced by local/quasilocal functional sub-circuits have yet to be addressed. To that end, we proposed a homological formalism that enables the quantification of higher-order characteristics of human brain functional sub-circuits. Our results indicate that each homological order uniquely unravels diverse, complementary properties of human brain functional sub-circuits. Noticeably, the (Formula presented.) homological distance between rest and motor task was observed at both the whole-brain and sub-circuit consolidated levels, which suggested the self-similarity property of human brain functional connectivity unraveled by a homological kernel. Furthermore, at the whole-brain level, the rest–task differentiation was found to be most prominent between rest and different tasks at different homological orders: (i) Emotion task ((Formula presented.)), (ii) Motor task ((Formula presented.)), and (iii) Working memory task ((Formula presented.)). At the functional sub-circuit level, the rest–task functional dichotomy of the default mode network is found to be mostly prominent at the first and second homological scaffolds. Also at such scale, we found that the limbic network plays a significant role in homological reconfiguration across both the task and subject domains, which paves the way for subsequent investigations on the complex neuro-physiological role of such network. From a wider perspective, our formalism can be applied, beyond brain connectomics, to study the non-localized coordination patterns of localized structures stretching across complex network fibers.

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Type
research article
DOI
10.3390/math12030455
Scopus ID

2-s2.0-85184669465

Author(s)
Duong-Tran, Duy
•
Kaufmann, Ralph
•
Chen, Jiong
•
Wang, Xuan
•
Garai, Sumita
•
Xu, Frederick H.
•
Bao, Jingxuan
•
Amico, Enrico  
•
Kaplan, Alan D.
•
Petri, Giovanni
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Date Issued

2024-02-01

Published in
Mathematics
Volume

12

Issue

3

Article Number

455

Subjects

functional networks

•

functional sub-circuit

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homological kernel

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topological data analysis

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

FunderFunding(s)Grant NumberGrant URL

WU-Minn Consortium

1U54MH091657

National Science Foundation

IIS 1837964

NIH

R01 AG071470,RF1 AG068191,T32 AG076411,U01 AG068057

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Available on Infoscience
January 16, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/242875
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