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

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

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

Main effect of ‘Modeling approach’: percent signal change in anatomical ROI (left, right precentral gyrus) as <i>F</i>-statistics obtained by comparing particular modeling approaches in levodopa OFF and levodopa ON conditions.

<p>AI^‡ - amplitude invariant.</p

Main effect of ‘Modeling approach’: percent signal change in anatomical ROI (left and right pallidum) as <i>F</i>-statistics obtained by comparing particular modeling approaches in levodopa ON condition.

<p>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 session-specific predictors of standard and kinematic approaches in individual-level modeling.

<p>(left, blue: standard approach, generated using experimental timing information and no movement assumptions; right, orange: kinematic, mean amplitude-sensitive approach, constructed using average of recorded kinematics from all sensors). Dashed lines indicate the most pronounced movement deviations in a measurement session of a particular patient. Standard modeling is not able to capture this variability and reflects it in the error term in GLM, likely resulting in biased statistics.</p

Group-level response (ON-OFF) of PD patients to levodopa treatment.

<p>Uncorrected threshold of <i>p</i><0.001 was adopted and maps were overlaid on coronal and axial slices (left, blue: group maps obtained by standard first-level modeling without further assumptions on motor performance; right, orange: improvement of group-level maps obtained using various kinematic modeling techniques taking movement performance into account). AI^‡ - amplitude invariant.</p

Variability of movement on behavioral level.

<p>Each bar represents average variance of movement performance calculated from a collection of measurement sessions separated for each level of experimental factors ‘Hand’ and ‘Levodopa medication’; displayed as mean+standard error. A: Average variances of global movement pattern representing the most coherent parts of glove recordings – finger tapping itself. Main effect of ‘Levodopa medication’ is significant (<i>p</i><0.001) and an interaction between ‘Levodopa medication’ and ‘Hand’ is significant (<i>p</i><0.05). B: Average variances of residual movement pattern representing stochastic, variable quantity of participants' motor behavior. Main effect of ‘Levodopa medication’ is significant (<i>p</i><0.001). a.u. - arbitrary unit.</p