Parkinson's disease rigidity: relation to brain connectivity and motor performance

Objective: 1) To determine the brain connectivity pattern associated with clinical rigidity scores in Parkinson's disease (PD) and 2) to determine the relation between clinically-assessed rigidity and quantitative metrics of motor performance.Background: Rigidity, the resistance to passive m...

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Main Authors: Nazanin eBaradaran, Sun Nee eTan, Aiping eLiu, Ahmad eAshoori, Samantha J Palmer, Z. Jane eWang, Meeko M. K. Oishi, Martin J. McKeown
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-06-01
Series:Frontiers in Neurology
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fneur.2013.00067/full
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spelling doaj-e66dbf7c8d2e4f8fb7c746942c2ead3c2020-11-24T22:36:22ZengFrontiers Media S.A.Frontiers in Neurology1664-22952013-06-01410.3389/fneur.2013.0006748859Parkinson's disease rigidity: relation to brain connectivity and motor performanceNazanin eBaradaran0Sun Nee eTan1Aiping eLiu2Ahmad eAshoori3Samantha J Palmer4Z. Jane eWang5Meeko M. K. Oishi6Martin J. McKeown7Martin J. McKeown8Martin J. McKeown9University of British ColumbiaUniversity of British ColumbiaUniversity of British ColumbiaUniversity of British ColumbiaUniversity of British ColumbiaUniversity of British ColumbiaUniversity of New MexicoUniversity of British ColumbiaUniversity of British ColumbiaUniversity of British ColumbiaObjective: 1) To determine the brain connectivity pattern associated with clinical rigidity scores in Parkinson's disease (PD) and 2) to determine the relation between clinically-assessed rigidity and quantitative metrics of motor performance.Background: Rigidity, the resistance to passive movement, is exacerbated in PD by asking the subject to move the contralateral limb, implying that rigidity involves a distributed brain network. Rigidity mainly affects subjects when they attempt to move; yet the relation between clinical rigidity scores and quantitative aspects of motor performance are unknown.Methods: Ten clinically diagnosed PD patients (off medication) and ten controls were recruited to perform an fMRI squeeze-bulb tracking task that included both visually guided and internally guided features. The direct functional connectivity between anatomically defined regions of interest was assessed with Dynamic Bayesian Networks (DBNs). Tracking performance was assessed by fitting Linear Dynamical System (LDS) models to the motor performance, and was compared to the clinical rigidity scores. A cross-validated Least Absolute Shrinkage and Selection Operator (LASSO) regression method was used to determine the brain connectivity network that best predicted clinical rigidity scores.Results: The damping ratio of the LDS models significantly correlated with clinical rigidity scores (p < 10-4). An fMRI connectivity network in subcortical and primary and premotor cortical regions accurately predicted clinical rigidity scores (p < 10-5). Conclusions: A widely distributed cortical/subcortical network is associated with rigidity observed in PD patients, which reinforces the importance of altered functional connectivity in the pathophysiology of PD. PD subjects with higher rigidity scores tend to have less overshoot in their tracking performance, and damping ratio may represent a robust, quantitative marker of the motoric effects of increasing rigidity.http://journal.frontiersin.org/Journal/10.3389/fneur.2013.00067/fullfMRIParkinson’s diseaserigidityfMRI. Damping ratioLinear dynamical systemLASSO regression
collection DOAJ
language English
format Article
sources DOAJ
author Nazanin eBaradaran
Sun Nee eTan
Aiping eLiu
Ahmad eAshoori
Samantha J Palmer
Z. Jane eWang
Meeko M. K. Oishi
Martin J. McKeown
Martin J. McKeown
Martin J. McKeown
spellingShingle Nazanin eBaradaran
Sun Nee eTan
Aiping eLiu
Ahmad eAshoori
Samantha J Palmer
Z. Jane eWang
Meeko M. K. Oishi
Martin J. McKeown
Martin J. McKeown
Martin J. McKeown
Parkinson's disease rigidity: relation to brain connectivity and motor performance
Frontiers in Neurology
fMRI
Parkinson’s disease
rigidity
fMRI. Damping ratio
Linear dynamical system
LASSO regression
author_facet Nazanin eBaradaran
Sun Nee eTan
Aiping eLiu
Ahmad eAshoori
Samantha J Palmer
Z. Jane eWang
Meeko M. K. Oishi
Martin J. McKeown
Martin J. McKeown
Martin J. McKeown
author_sort Nazanin eBaradaran
title Parkinson's disease rigidity: relation to brain connectivity and motor performance
title_short Parkinson's disease rigidity: relation to brain connectivity and motor performance
title_full Parkinson's disease rigidity: relation to brain connectivity and motor performance
title_fullStr Parkinson's disease rigidity: relation to brain connectivity and motor performance
title_full_unstemmed Parkinson's disease rigidity: relation to brain connectivity and motor performance
title_sort parkinson's disease rigidity: relation to brain connectivity and motor performance
publisher Frontiers Media S.A.
series Frontiers in Neurology
issn 1664-2295
publishDate 2013-06-01
description Objective: 1) To determine the brain connectivity pattern associated with clinical rigidity scores in Parkinson's disease (PD) and 2) to determine the relation between clinically-assessed rigidity and quantitative metrics of motor performance.Background: Rigidity, the resistance to passive movement, is exacerbated in PD by asking the subject to move the contralateral limb, implying that rigidity involves a distributed brain network. Rigidity mainly affects subjects when they attempt to move; yet the relation between clinical rigidity scores and quantitative aspects of motor performance are unknown.Methods: Ten clinically diagnosed PD patients (off medication) and ten controls were recruited to perform an fMRI squeeze-bulb tracking task that included both visually guided and internally guided features. The direct functional connectivity between anatomically defined regions of interest was assessed with Dynamic Bayesian Networks (DBNs). Tracking performance was assessed by fitting Linear Dynamical System (LDS) models to the motor performance, and was compared to the clinical rigidity scores. A cross-validated Least Absolute Shrinkage and Selection Operator (LASSO) regression method was used to determine the brain connectivity network that best predicted clinical rigidity scores.Results: The damping ratio of the LDS models significantly correlated with clinical rigidity scores (p < 10-4). An fMRI connectivity network in subcortical and primary and premotor cortical regions accurately predicted clinical rigidity scores (p < 10-5). Conclusions: A widely distributed cortical/subcortical network is associated with rigidity observed in PD patients, which reinforces the importance of altered functional connectivity in the pathophysiology of PD. PD subjects with higher rigidity scores tend to have less overshoot in their tracking performance, and damping ratio may represent a robust, quantitative marker of the motoric effects of increasing rigidity.
topic fMRI
Parkinson’s disease
rigidity
fMRI. Damping ratio
Linear dynamical system
LASSO regression
url http://journal.frontiersin.org/Journal/10.3389/fneur.2013.00067/full
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