Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

M. Hassan; L. Chaton; P. Benquet; A. Delval; C. Leroy; L. Plomhause; A. J. H. Moonen; A. A. Duits; A. F. G. Leentjens; V. van Kranen-Mastenbroek; L. Defebvre; P. Derambure; F. Wendling; K. Dujardin

doi:10.1016/j.nicl.2017.03.002

Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

M. Hassan^*, L. Chaton, P. Benquet, A. Delval, C. Leroy, L. Plomhause, A. J. H. Moonen, A. A. Duits, A. F. G. Leentjens, V. van Kranen-Mastenbroek, L. Defebvre, P. Derambure, F. Wendling, K. Dujardin

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand.

This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a clense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level. Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p <0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (p = 0.49, p <0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact.

These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease. 2017 The Authors. Published by Elsevier Inc This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Original language	English
Pages (from-to)	591-601
Number of pages	11
Journal	NeuroImage: Clinical
Volume	14
DOIs	https://doi.org/10.1016/j.nicl.2017.03.002
Publication status	Published - 2017

Keywords

Parkinson's disease
Cognitive deficits
Dense electroencephalography
Brain connectivity
Network measures
GRAPH-THEORETICAL ANALYSIS
ALZHEIMERS-DISEASE
BRAIN NETWORKS
QUANTITATIVE EEG
RATING-SCALE
SMALL-WORLD
FRONTOTEMPORAL DEMENTIA
CORTICAL NETWORKS
LEWY BODIES
MEG

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Hassan, M., Chaton, L., Benquet, P., Delval, A., Leroy, C., Plomhause, L., Moonen, A. J. H., Duits, A. A., Leentjens, A. F. G., van Kranen-Mastenbroek, V., Defebvre, L., Derambure, P., Wendling, F., & Dujardin, K. (2017). Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease. NeuroImage: Clinical, 14, 591-601. https://doi.org/10.1016/j.nicl.2017.03.002

@article{ee978ae1c50248b2aa2cf62bb78131a2,

title = "Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease",

abstract = "Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand.This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a clense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level. Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p <0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (p = 0.49, p <0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact.These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease. 2017 The Authors. Published by Elsevier Inc This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).",

keywords = "Parkinson's disease, Cognitive deficits, Dense electroencephalography, Brain connectivity, Network measures, GRAPH-THEORETICAL ANALYSIS, ALZHEIMERS-DISEASE, BRAIN NETWORKS, QUANTITATIVE EEG, RATING-SCALE, SMALL-WORLD, FRONTOTEMPORAL DEMENTIA, CORTICAL NETWORKS, LEWY BODIES, MEG",

author = "M. Hassan and L. Chaton and P. Benquet and A. Delval and C. Leroy and L. Plomhause and Moonen, {A. J. H.} and Duits, {A. A.} and Leentjens, {A. F. G.} and {van Kranen-Mastenbroek}, V. and L. Defebvre and P. Derambure and F. Wendling and K. Dujardin",

year = "2017",

doi = "10.1016/j.nicl.2017.03.002",

language = "English",

volume = "14",

pages = "591--601",

journal = "NeuroImage: Clinical",

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Hassan, M, Chaton, L, Benquet, P, Delval, A, Leroy, C, Plomhause, L, Moonen, AJH, Duits, AA , Leentjens, AFG , van Kranen-Mastenbroek, V, Defebvre, L, Derambure, P, Wendling, F & Dujardin, K 2017, 'Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease', NeuroImage: Clinical, vol. 14, pp. 591-601. https://doi.org/10.1016/j.nicl.2017.03.002

TY - JOUR

T1 - Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

AU - Hassan, M.

AU - Chaton, L.

AU - Benquet, P.

AU - Delval, A.

AU - Leroy, C.

AU - Plomhause, L.

AU - Moonen, A. J. H.

AU - Duits, A. A.

AU - Leentjens, A. F. G.

AU - van Kranen-Mastenbroek, V.

AU - Defebvre, L.

AU - Derambure, P.

AU - Wendling, F.

AU - Dujardin, K.

PY - 2017

Y1 - 2017

N2 - Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand.This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a clense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level. Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p <0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (p = 0.49, p <0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact.These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease. 2017 The Authors. Published by Elsevier Inc This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

AB - Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand.This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a clense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level. Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p <0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (p = 0.49, p <0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact.These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease. 2017 The Authors. Published by Elsevier Inc This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

KW - Parkinson's disease

KW - Cognitive deficits

KW - Dense electroencephalography

KW - Brain connectivity

KW - Network measures

KW - GRAPH-THEORETICAL ANALYSIS

KW - ALZHEIMERS-DISEASE

KW - BRAIN NETWORKS

KW - QUANTITATIVE EEG

KW - RATING-SCALE

KW - SMALL-WORLD

KW - FRONTOTEMPORAL DEMENTIA

KW - CORTICAL NETWORKS

KW - LEWY BODIES

KW - MEG

U2 - 10.1016/j.nicl.2017.03.002

DO - 10.1016/j.nicl.2017.03.002

M3 - Article

SN - 2213-1582

VL - 14

SP - 591

EP - 601

JO - NeuroImage: Clinical

JF - NeuroImage: Clinical

ER -