Centralized and distributed cognitive task processing in the human connectome

A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). A systematic approach to measure pairwise functional distance at different brain states is lacking. This would provide a straightforward way to quantify dif...

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Main Authors: Enrico Amico, Alex Arenas, Joaquín Goñi
Format: Article
Language:English
Published: The MIT Press 2019-02-01
Series:Network Neuroscience
Subjects:
Online Access:https://www.mitpressjournals.org/doi/pdf/10.1162/netn_a_00072
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spelling doaj-5f037d9877cc4baab2fe8af5e3ffd0a42020-11-25T00:45:41ZengThe MIT PressNetwork Neuroscience2472-17512019-02-013245547410.1162/netn_a_00072netn_a_00072Centralized and distributed cognitive task processing in the human connectomeEnrico Amico0Alex Arenas1Joaquín Goñi2School of Industrial Engineering, Purdue University, West-Lafayette, IN, USADepartament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, SpainSchool of Industrial Engineering, Purdue University, West-Lafayette, IN, USAA key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). A systematic approach to measure pairwise functional distance at different brain states is lacking. This would provide a straightforward way to quantify differences in cognitive processing across tasks; also, it would help in relating these differences in task-based FCs to the underlying structural network. Here we propose a framework, based on the concept of Jensen-Shannon divergence, to map the task-rest connectivity distance between tasks and resting-state FC. We show how this information theoretical measure allows for quantifying connectivity changes in distributed and centralized processing in functional networks. We study resting state and seven tasks from the Human Connectome Project dataset to obtain the most distant links across tasks. We investigate how these changes are associated with different functional brain networks, and use the proposed measure to infer changes in the information-processing regimes. Furthermore, we show how the FC distance from resting state is shaped by structural connectivity, and to what extent this relationship depends on the task. This framework provides a well-grounded mathematical quantification of connectivity changes associated with cognitive processing in large-scale brain networks. A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). Here we propose a framework, based on Jensen-Shannon divergence, to define “connectivity distance” and to infer about brain network reconfiguration across different tasks with respect to resting state, and to explore changes in centralized and distributed processing in FCs. Three functional networks (dorsal attention, frontoparietal and DMN) showed major changes in distributed processing and minor changes in centralized processing. Changes in centralized processing depend on the underlying structural connectivity weights and structural path “hiddenness.” These findings suggest that the cognitive “switch” between resting state and task states is a complex interplay between maximally and minimally distant functional connections, and the underlying structure.https://www.mitpressjournals.org/doi/pdf/10.1162/netn_a_00072Brain connectomicsFunctional connectivityNetwork scienceInformation theoryCognitive task processing
collection DOAJ
language English
format Article
sources DOAJ
author Enrico Amico
Alex Arenas
Joaquín Goñi
spellingShingle Enrico Amico
Alex Arenas
Joaquín Goñi
Centralized and distributed cognitive task processing in the human connectome
Network Neuroscience
Brain connectomics
Functional connectivity
Network science
Information theory
Cognitive task processing
author_facet Enrico Amico
Alex Arenas
Joaquín Goñi
author_sort Enrico Amico
title Centralized and distributed cognitive task processing in the human connectome
title_short Centralized and distributed cognitive task processing in the human connectome
title_full Centralized and distributed cognitive task processing in the human connectome
title_fullStr Centralized and distributed cognitive task processing in the human connectome
title_full_unstemmed Centralized and distributed cognitive task processing in the human connectome
title_sort centralized and distributed cognitive task processing in the human connectome
publisher The MIT Press
series Network Neuroscience
issn 2472-1751
publishDate 2019-02-01
description A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). A systematic approach to measure pairwise functional distance at different brain states is lacking. This would provide a straightforward way to quantify differences in cognitive processing across tasks; also, it would help in relating these differences in task-based FCs to the underlying structural network. Here we propose a framework, based on the concept of Jensen-Shannon divergence, to map the task-rest connectivity distance between tasks and resting-state FC. We show how this information theoretical measure allows for quantifying connectivity changes in distributed and centralized processing in functional networks. We study resting state and seven tasks from the Human Connectome Project dataset to obtain the most distant links across tasks. We investigate how these changes are associated with different functional brain networks, and use the proposed measure to infer changes in the information-processing regimes. Furthermore, we show how the FC distance from resting state is shaped by structural connectivity, and to what extent this relationship depends on the task. This framework provides a well-grounded mathematical quantification of connectivity changes associated with cognitive processing in large-scale brain networks. A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). Here we propose a framework, based on Jensen-Shannon divergence, to define “connectivity distance” and to infer about brain network reconfiguration across different tasks with respect to resting state, and to explore changes in centralized and distributed processing in FCs. Three functional networks (dorsal attention, frontoparietal and DMN) showed major changes in distributed processing and minor changes in centralized processing. Changes in centralized processing depend on the underlying structural connectivity weights and structural path “hiddenness.” These findings suggest that the cognitive “switch” between resting state and task states is a complex interplay between maximally and minimally distant functional connections, and the underlying structure.
topic Brain connectomics
Functional connectivity
Network science
Information theory
Cognitive task processing
url https://www.mitpressjournals.org/doi/pdf/10.1162/netn_a_00072
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