Dataset Information

Functional connectivity between resting-state networks reflects decline in executive function in Parkinson's disease: A longitudinal fMRI study.

ABSTRACT: Deficits in cognitive functioning are a common yet poorly understood symptom in Parkinson's disease (PD). Recent studies have highlighted the importance of (dynamic) interactions between resting-state networks for cognition, which remains understudied in PD. We investigated how altered (dynamic) functional interactions between brain networks relate to cognitive dysfunction in PD patients. In this fMRI study, 50 PD patients (mean age 65.5 years ± 6.27) on dopaminergic medication were studied cross-sectionally, and of this cohort 31 PD patients were studied longitudinally. MRI imaging and neuropsychological testing was performed at two time points, with a follow-up duration of approximately three years. Functional connectivity within and between seven resting-state networks was calculated (both statically and dynamically) and correlated with four neuropsychological test scores; a combined score of (four) executive tasks, a motor perseveration, memory, and category fluency task. Cognitive dysfunction was determined based on a longitudinal sample of age-matched healthy controls (n = 13). PD patients showed dysfunction on six out of seven cognitive tasks when compared to healthy controls. Severity of executive dysfunction was correlated with higher static and lower dynamic functional connectivity between deep gray matter regions and the frontoparietal network (DGM-FPN). Over time, declining executive function was related to increasing static DGM-FPN connectivity, together with changes of connectivity involving the dorsal attention network (amongst others with the ventral attention network). Static functional connectivity between the ventral and dorsal attention network correlated with motor perseveration. Our findings demonstrate that in PD patients, dysfunctional communication between (i) subcortical, fronto-parietal and attention networks mostly underlies worsening of executive functioning, (ii) attention networks are involved in motor perseveration.

SUBMITTER: Boon LI

PROVIDER: S-EPMC7581965 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Functional connectivity between resting-state networks reflects decline in executive function in Parkinson's disease: A longitudinal fMRI study.

Boon Lennard I LI Hepp Dagmar H DH Douw Linda L van Geenen Noëlle N Broeders Tommy A A TAA Geurts Jeroen J G JJG Berendse Henk W HW Schoonheim Menno M MM

NeuroImage. Clinical 20201015

Deficits in cognitive functioning are a common yet poorly understood symptom in Parkinson's disease (PD). Recent studies have highlighted the importance of (dynamic) interactions between resting-state networks for cognition, which remains understudied in PD. We investigated how altered (dynamic) functional interactions between brain networks relate to cognitive dysfunction in PD patients. In this fMRI study, 50 PD patients (mean age 65.5 years ± 6.27) on dopaminergic medication were studied cros ...[more]

PMID: 33383608

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Project description:The human brain at rest exhibits intrinsic dynamics transitioning among the multiple metastable states of the inter-regional functional connectivity. Accordingly, the demand for exploring the state-specific functional connectivity increases for a deeper understanding of mental diseases. Functional connectivity, however, lacks information about the directed causal influences among the brain regions, called effective connectivity. This study presents the dynamic causal modeling (DCM) framework to explore the state-dependent effective connectivity using spectral DCM for the resting-state functional MRI (rsfMRI). We established the sequence of brain states using the hidden Markov model with the multivariate autoregressive coefficients of rsfMRI, summarizing the functional connectivity. We decomposed the state-dependent effective connectivity using a parametric empirical Bayes scheme that models the effective connectivity of consecutive windows with the time course of the discrete states as regressors. We showed the plausibility of the state-dependent effective connectivity analysis in a simulation setting. To test the clinical applicability, we applied the proposed method to characterize the state- and subtype-dependent effective connectivity of the default mode network in children with combined-type attention deficit hyperactivity disorder (ADHD-C) compared with age-matched, typically developed children (TDC). All 88 children were subtyped according to the occupation times (i.e., dwell times) of the three dominant functional connectivity states, independently of clinical diagnosis. The state-dependent effective connectivity differences between ADHD-C and TDC according to the subtypes and those between the subtypes of ADHD-C were expressed mainly in self-inhibition, magnifying the importance of excitation inhibition balance in the subtyping. These findings provide a clear motivation for decomposing the state-dependent dynamic effective connectivity and state-dependent analysis of the directed coupling in exploring mental diseases.

Dataset Information

Functional connectivity between resting-state networks reflects decline in executive function in Parkinson's disease: A longitudinal fMRI study.

Publications

Functional connectivity between resting-state networks reflects decline in executive function in Parkinson's disease: A longitudinal fMRI study.

Similar Datasets

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