Personalizing functional Magnetic Resonance Protocols for Studying Neural Substrates of Motor Deficits in Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder characterized by a large number of motor and non-motor deficits, which significantly contribute to reduced quality of life. Despite the definition of the broad spectrum of clinical characteristics, mechanisms triggering illness, the nature of its progression and a character of therapeutic effects still remain unknown. The enormous advances in magnetic resonance imaging (MRI) in the last decades have significantly affected the research attempts to uncover the functional and structural abnormalities in PD and have helped to develop and monitor various treatment strategies, of which dopamine replacement strategies, mainly in form of levodopa, has been the gold standard since the late seventies and eighties. Motor, task-related functional MRI (fMRI) has been extensively used to assess the pathological state of the motor circuitry in PD. Several studies employed motor paradigms and fMRI to review the functional brain responses of participants to levodopa treatment. Interestingly, they provided conflicting results. Wide spectrum of symptoms, variability and asymmetry of the disease presentation, several treatment approaches and their divergent outcomes make PD enormously heterogeneous. In this work we hypothesized that not considering the disease heterogeneity might have been an adequate cause for the discrepant results in aforementioned studies. We show that not accounting for the disease variability might indeed compromise the results and invalidate the consequent interpretations. Accordingly, we propose and formalize a statistical approach to account for the intra and inter subject variability. This might help to minimize this bias in future motor fMRI studies revealing the functional brain dysfunction and contribute to the understanding of still unknown pathophysiological mechanisms underlying PD

Personalizing functional Magnetic Resonance Protocols for Studying Neural Substrates of Motor Deficits in Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder characterized by a large number of motor and non-motor deficits, which significantly contribute to reduced quality of life. Despite the definition of the broad spectrum of clinical characteristics, mechanisms triggering illness, the nature of its progression and a character of therapeutic effects still remain unknown. The enormous advances in magnetic resonance imaging (MRI) in the last decades have significantly affected the research attempts to uncover the functional and structural abnormalities in PD and have helped to develop and monitor various treatment strategies, of which dopamine replacement strategies, mainly in form of levodopa, has been the gold standard since the late seventies and eighties. Motor, task-related functional MRI (fMRI) has been extensively used to assess the pathological state of the motor circuitry in PD. Several studies employed motor paradigms and fMRI to review the functional brain responses of participants to levodopa treatment. Interestingly, they provided conflicting results. Wide spectrum of symptoms, variability and asymmetry of the disease presentation, several treatment approaches and their divergent outcomes make PD enormously heterogeneous. In this work we hypothesized that not considering the disease heterogeneity might have been an adequate cause for the discrepant results in aforementioned studies. We show that not accounting for the disease variability might indeed compromise the results and invalidate the consequent interpretations. Accordingly, we propose and formalize a statistical approach to account for the intra and inter subject variability. This might help to minimize this bias in future motor fMRI studies revealing the functional brain dysfunction and contribute to the understanding of still unknown pathophysiological mechanisms underlying PD

Personalizing functional Magnetic Resonance Protocols for Studying Neural Substrates of Motor Deficits in Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder characterized by a large number of motor and non-motor deficits, which significantly contribute to reduced quality of life. Despite the definition of the broad spectrum of clinical characteristics, mechanisms triggering illness, the nature of its progression and a character of therapeutic effects still remain unknown. The enormous advances in magnetic resonance imaging (MRI) in the last decades have significantly affected the research attempts to uncover the functional and structural abnormalities in PD and have helped to develop and monitor various treatment strategies, of which dopamine replacement strategies, mainly in form of levodopa, has been the gold standard since the late seventies and eighties. Motor, task-related functional MRI (fMRI) has been extensively used to assess the pathological state of the motor circuitry in PD. Several studies employed motor paradigms and fMRI to review the functional brain responses of participants to levodopa treatment. Interestingly, they provided conflicting results. Wide spectrum of symptoms, variability and asymmetry of the disease presentation, several treatment approaches and their divergent outcomes make PD enormously heterogeneous. In this work we hypothesized that not considering the disease heterogeneity might have been an adequate cause for the discrepant results in aforementioned studies. We show that not accounting for the disease variability might indeed compromise the results and invalidate the consequent interpretations. Accordingly, we propose and formalize a statistical approach to account for the intra and inter subject variability. This might help to minimize this bias in future motor fMRI studies revealing the functional brain dysfunction and contribute to the understanding of still unknown pathophysiological mechanisms underlying PD

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a “microlesion effect” (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis

List of performance measures revealed by all modeling approaches.

<p>Showed items include <i>p</i>-values of clusters, numbers of activated voxels and peak <i>t</i>-values. Cluster <i>p</i>-value is FWE (Family Wise Error) corrected for multiple comparisons at <i>p</i><0.05. Number of activated voxels are at the threshold of <i>p</i><0.001 (uncorrected). AI^‡ - amplitude invariant.</p

Demographic and clinical summary of studied patients (N = 12).

<p>UPDRS* - Unified Parkinson's Disease Rating Scale. MMSE^† - Mini Mental State Examination.</p

Comparison of modeling approaches as average effect size in anatomical ROI (contralateral precentral gyrus).

<p>Each bar represents the average value from ROI for the ‘group-level mean’ PSC image, and each error bar the average of the ‘group-level standard error’ PSC image. A: Percent signal change for the Levodopa OFF condition and all modeling approaches. B: Percent signal change for the Levodopa ON condition and all modeling approaches. AI^‡ - amplitude invariant.</p

Accounting for Movement Increases Sensitivity in Detecting Brain Activity in Parkinson's Disease

<div><p>Parkinson's disease (PD) is manifested by motor impairment, which may impede the ability to accurately perform motor tasks during functional magnetic resonance imaging (fMRI). Both temporal and amplitude deviations of movement performance affect the blood oxygenation level-dependent (BOLD) response. We present a general approach for assessing PD patients' movement control employing simultaneously recorded fMRI time series and behavioral data of the patients' kinematics using MR-compatible gloves. Twelve male patients with advanced PD were examined with fMRI at 1.5T during epoch-based visually paced finger tapping. MR-compatible gloves were utilized online to quantify motor outcome in two conditions with or without dopaminergic medication. Modeling of individual-level brain activity included <em>(i)</em> a predictor consisting of a condition-specific, constant-amplitude boxcar function convolved with the canonical hemodynamic response function (HRF) as commonly used in fMRI statistics (standard model), or <em>(ii)</em> a custom-made predictor computed from glove time series convolved with the HRF (kinematic model). Factorial statistics yielded a parametric map for each modeling technique, showing the medication effect on the group level. Patients showed bilateral response to levodopa in putamen and globus pallidus during the motor experiment. Interestingly, kinematic modeling produced significantly higher activation in terms of both the extent and amplitude of activity. Our results appear to account for movement performance in fMRI motor experiments with PD and increase sensitivity in detecting brain response to levodopa. We strongly advocate quantitatively controlling for motor performance to reach more reliable and robust analyses in fMRI with PD patients.</p> </div

Comparison of modeling approaches as average effect size in anatomical ROI (left and right pallidum).

<p>Each bar represents the average value from ROI for the ‘group-level mean’ PSC image, and each error bar the average of the ‘group-level standard error’ PSC image. A: Percent signal change for the Levodopa OFF condition and all modeling approaches. In contrast to the ON condition, in the OFF condition, the basal ganglia were not activated so the data corresponds to noise. B: Percent signal change for the Levodopa ON condition and all modeling approaches. AI^‡ - amplitude invariant.</p