Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder

Major depressive disorder (MDD) is associated with complex disruptions in brain function, yet the underlying neural mechanisms remain incompletely understood. Traditional approaches to studying functional brain networks have primarily focused on pairwise interactions between brain regions, offering...

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Main Authors: Semen A. Kurkin, Nikita M. Smirnov, Rositsa Paunova, Sevdalina Kandilarova, Drozdstoy Stoyanov, Larisa Mayorova, Alexander E. Hramov
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10811911/
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author Semen A. Kurkin
Nikita M. Smirnov
Rositsa Paunova
Sevdalina Kandilarova
Drozdstoy Stoyanov
Larisa Mayorova
Alexander E. Hramov
author_facet Semen A. Kurkin
Nikita M. Smirnov
Rositsa Paunova
Sevdalina Kandilarova
Drozdstoy Stoyanov
Larisa Mayorova
Alexander E. Hramov
author_sort Semen A. Kurkin
collection DOAJ
description Major depressive disorder (MDD) is associated with complex disruptions in brain function, yet the underlying neural mechanisms remain incompletely understood. Traditional approaches to studying functional brain networks have primarily focused on pairwise interactions between brain regions, offering valuable insights into basic connectivity. However, such methods often fail to capture the complexity of higher-order interactions that are critical for understanding integrative processes in the brain. This study aims to address this gap by applying Q-analysis, a mathematical framework that extends beyond pairwise interactions, to fMRI-derived brain networks to investigate higher-order interactions and structural organization in individuals with MDD compared to healthy controls (HCs). Our analysis revealed significant alterations in the topology of brain networks in MDD patients, characterized by a lower maximum topology level and an increased prevalence of isolated edges and chains at the pairwise interaction level. The substantia nigra area demonstrated a higher topological dimension in MDD, suggesting its greater integration into disrupted network structures, potentially reflecting dopaminergic dysfunction associated with the disorder. Additionally, the consensus networks at higher topology levels indicated distinct network configurations between MDD patients and HCs, with the former exhibiting a single q-connected component primarily involving limbic, cerebellar, and occipital-temporal regions. We identified significant disruptions in the higher-order organizational structures of the brain, characterized by reduced topological diversity and complexity, fewer and less connected cliques, and altered involvement of key brain regions in MDD: the increased engagement of the limbic structures such as the substantia nigra, parahippocampal gyrus, and hippocampus, and decreased involvement of the cerebellum, the occipital and temporal lobes. Our study introduces a novel approach to understanding MDD pathophysiology through the lens of higher-order network structures, offering potential avenues for more targeted diagnostic and therapeutic strategies.
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spelling doaj-art-7cda036e4b794fdba6e5448b38fae0c92024-12-31T00:00:47ZengIEEEIEEE Access2169-35362024-01-011219716819718610.1109/ACCESS.2024.352124910811911Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive DisorderSemen A. Kurkin0https://orcid.org/0000-0002-3438-5717Nikita M. Smirnov1https://orcid.org/0009-0002-7593-4345Rositsa Paunova2Sevdalina Kandilarova3Drozdstoy Stoyanov4https://orcid.org/0000-0002-9975-3680Larisa Mayorova5https://orcid.org/0000-0001-5112-7878Alexander E. Hramov6https://orcid.org/0000-0003-2787-2530Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, RussiaBaltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, RussiaDepartment of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Plovdiv, BulgariaDepartment of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Plovdiv, BulgariaDepartment of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Plovdiv, BulgariaFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Solnechnogorsk, RussiaBaltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, RussiaMajor depressive disorder (MDD) is associated with complex disruptions in brain function, yet the underlying neural mechanisms remain incompletely understood. Traditional approaches to studying functional brain networks have primarily focused on pairwise interactions between brain regions, offering valuable insights into basic connectivity. However, such methods often fail to capture the complexity of higher-order interactions that are critical for understanding integrative processes in the brain. This study aims to address this gap by applying Q-analysis, a mathematical framework that extends beyond pairwise interactions, to fMRI-derived brain networks to investigate higher-order interactions and structural organization in individuals with MDD compared to healthy controls (HCs). Our analysis revealed significant alterations in the topology of brain networks in MDD patients, characterized by a lower maximum topology level and an increased prevalence of isolated edges and chains at the pairwise interaction level. The substantia nigra area demonstrated a higher topological dimension in MDD, suggesting its greater integration into disrupted network structures, potentially reflecting dopaminergic dysfunction associated with the disorder. Additionally, the consensus networks at higher topology levels indicated distinct network configurations between MDD patients and HCs, with the former exhibiting a single q-connected component primarily involving limbic, cerebellar, and occipital-temporal regions. We identified significant disruptions in the higher-order organizational structures of the brain, characterized by reduced topological diversity and complexity, fewer and less connected cliques, and altered involvement of key brain regions in MDD: the increased engagement of the limbic structures such as the substantia nigra, parahippocampal gyrus, and hippocampus, and decreased involvement of the cerebellum, the occipital and temporal lobes. Our study introduces a novel approach to understanding MDD pathophysiology through the lens of higher-order network structures, offering potential avenues for more targeted diagnostic and therapeutic strategies.https://ieeexplore.ieee.org/document/10811911/Higher-order interactionsfMRImajor depressive disorderfunctional brain networkQ-analysisclique
spellingShingle Semen A. Kurkin
Nikita M. Smirnov
Rositsa Paunova
Sevdalina Kandilarova
Drozdstoy Stoyanov
Larisa Mayorova
Alexander E. Hramov
Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
IEEE Access
Higher-order interactions
fMRI
major depressive disorder
functional brain network
Q-analysis
clique
title Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
title_full Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
title_fullStr Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
title_full_unstemmed Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
title_short Beyond Pairwise Interactions: Higher-Order Q-Analysis of fMRI-Based Brain Functional Networks in Patients With Major Depressive Disorder
title_sort beyond pairwise interactions higher order q analysis of fmri based brain functional networks in patients with major depressive disorder
topic Higher-order interactions
fMRI
major depressive disorder
functional brain network
Q-analysis
clique
url https://ieeexplore.ieee.org/document/10811911/
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