Premotor cortex is hypoactive during sustained vowel production in individuals with Parkinson's disease and hypophonia.

Introduction: Hypophonia is a common feature of Parkinson's disease (PD); however, the contribution of motor cortical activity to reduced phonatory scaling in PD is still not clear. Methods: In this study, we employed a sustained vowel production task during functional magnetic resonance imaging to compare brain activity between individuals with PD and hypophonia and an older healthy control (OHC) group. Results: When comparing vowel production versus rest, the PD group showed fewer regions with significant BOLD activity compared to OHCs. Within the motor cortices, both OHC and PD groups showed bilateral activation of the laryngeal/phonatory area (LPA) of the primary motor cortex as well as activation of the supplementary motor area. The OHC group also recruited additional activity in the bilateral trunk motor area and right dorsal premotor cortex (PMd). A voxel-wise comparison of PD and HC groups showed that activity in right PMd was significantly lower in the PD group compared to OHC (p < 0.001, uncorrected). Right PMd activity was positively correlated with maximum phonation time in the PD group and negatively correlated with perceptual severity ratings of loudness and pitch. Discussion: Our findings suggest that hypoactivation of PMd may be associated with abnormal phonatory control in PD.

White matter microstructural integrity pre- and post-treatment in individuals with chronic post-stroke aphasia.

While previous studies have found that white matter damage relates to impairment severity in individuals with aphasia, further study is required to understand the relationship between white matter integrity and treatment response. In this study, 34 individuals with chronic post-stroke aphasia underwent behavioral testing and structural magnetic resonance imaging at two timepoints. Thirty participants within this sample completed typicality-based semantic feature treatment for anomia. Tractography of bi-hemispheric white matter tracts was completed via Automated Fiber Quantification. Associations between microstructural integrity metrics and behavioral measures were evaluated at the tract level and in nodes along the tract. Diffusion measures of the left inferior longitudinal, superior longitudinal, and arcuate fasciculi were related to aphasia severity and diffusion measures of the left inferior longitudinal fasciculus were related to naming and treatment response. This study also found preliminary evidence of left inferior longitudinal fasciculus microstructural changes following treatment.

Advanced diffusion imaging to track progression in Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy.

Advanced diffusion imaging which accounts for complex tissue properties, such as crossing fibers and extracellular fluid, may detect longitudinal changes in widespread pathology in atypical Parkinsonian syndromes. We implemented fixel-based analysis, Neurite Orientation and Density Imaging (NODDI), and free-water imaging in Parkinson's disease (PD), multiple system atrophy (MSAp), progressive supranuclear palsy (PSP), and controls longitudinally over one year. Further, we used these three advanced diffusion imaging techniques to investigate longitudinal progression-related effects in key white matter tracts and gray matter regions in PD and two common atypical Parkinsonian disorders. Fixel-based analysis and free-water imaging revealed longitudinal declines in a greater number of descending sensorimotor tracts in MSAp and PSP compared to PD. In contrast, only the primary motor descending sensorimotor tract had progressive decline over one year, measured by fiber density (FD), in PD compared to that in controls. PSP was characterized by longitudinal impairment in multiple transcallosal tracts (primary motor, dorsal and ventral premotor, pre-supplementary motor, and supplementary motor area) as measured by FD, whereas there were no transcallosal tracts with longitudinal FD impairment in MSAp and PD. In addition, free-water (FW) and FW-corrected fractional anisotropy (FAt) in gray matter regions showed longitudinal changes over one year in regions that have previously shown cross-sectional impairment in MSAp (putamen) and PSP (substantia nigra, putamen, subthalamic nucleus, red nucleus, and pedunculopontine nucleus). NODDI did not detect any longitudinal white matter tract progression effects and there were few effects in gray matter regions across Parkinsonian disorders. All three imaging methods were associated with change in clinical disease severity across all three Parkinsonian syndromes. These results identify novel extra-nigral and extra-striatal longitudinal progression effects in atypical Parkinsonian disorders through the application of multiple diffusion methods that are related to clinical disease progression. Moreover, the findings suggest that fixel-based analysis and free-water imaging are both particularly sensitive to these longitudinal changes in atypical Parkinsonian disorders.

Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia.

BACKGROUND: Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent and complementary prognostic role of different patient-related factors in predicting response to language rehabilitation after a stroke. METHODS: Fifty-five individuals with chronic poststroke aphasia underwent a battery of standardized assessments and structural and functional magnetic resonance imaging scans, and received 12 weeks of language treatment. Support vector machine and random forest models were constructed to predict responsiveness to treatment using pretreatment behavioral, demographic, and structural and functional neuroimaging data. RESULTS: The best prediction performance was achieved by a support vector machine model trained on aphasia severity, demographics, measures of anatomic integrity and resting-state functional connectivity (F1=0.94). This model resulted in a significantly superior prediction performance compared with support vector machine models trained on all feature sets (F1=0.82, P<0.001) or a single feature set (F1 range=0.68-0.84, P<0.001). Across random forest models, training on resting-state functional magnetic resonance imaging connectivity data yielded the best F1 score (F1=0.87). CONCLUSIONS: While behavioral, multimodal neuroimaging data and demographic information carry complementary information in predicting response to rehabilitation in chronic poststroke aphasia, functional connectivity of the brain at rest after stroke is a particularly important predictor of responsiveness to treatment, both alone and combined with other patient-related factors.

Increased Subthalamic Nucleus Deep Brain Stimulation Amplitude Impairs Inhibitory Control of Eye Movements in Parkinson's Disease.

BACKGROUND AND OBJECTIVES: Bilateral subthalamic nucleus deep brain stimulation (STN DBS) in Parkinson's disease (PD) can have detrimental effects on eye movement inhibitory control. To investigate this detrimental effect of bilateral STN DBS, we examined the effects of manipulating STN DBS amplitude on inhibitory control during the antisaccade task. The prosaccade error rate during the antisaccade task, that is, directional errors, was indicative of impaired inhibitory control. We hypothesized that as stimulation amplitude increased, the prosaccade error rate would increase. MATERIALS AND METHODS: Ten participants with bilateral STN DBS completed the antisaccade task on six different stimulation amplitudes (including zero amplitude) after a 12-hour overnight withdrawal from antiparkinsonian medication. RESULTS: We found that the prosaccade error rate increased as stimulation amplitude increased (p < 0.01). Additionally, prosaccade error rate increased as the modeled volume of tissue activated (VTA) and STN overlap decreased, but this relationship depended on stimulation amplitude (p = 0.04). CONCLUSIONS: Our findings suggest that higher stimulation amplitude settings can be modulatory for inhibitory control. Some individual variability in the effect of stimulation amplitude can be explained by active contact location and VTA-STN overlap. Higher stimulation amplitudes are more deleterious if the active contacts fall outside of the STN resulting in a smaller VTA-STN overlap. This is clinically significant as it can inform clinical optimization of STN DBS parameters. Further studies are needed to determine stimulation amplitude effects on other aspects of cognition and whether inhibitory control deficits on the antisaccade task result in a meaningful impact on the quality of life.

Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism.

Neurite orientation dispersion and density imaging (NODDI) uses a three-compartment model to probe brain tissue microstructure, whereas free-water (FW) imaging models two-compartments. It is unknown if NODDI detects more disease-specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi- and single-shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi-shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single-shell; FW; free-water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.

Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.

BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approach. METHODS: We did an international study at 17 MRI centres in Austria, Germany, and the USA. We used diffusion-weighted MRI from 1002 patients and the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute space between Parkinson's disease and atypical parkinsonism (multiple system atrophy and progressive supranuclear palsy) and between multiple system atrophy and progressive supranuclear palsy. For each comparison, models were developed on a training and validation cohort and evaluated in an independent test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic curves. The primary outcomes were free water and free-water-corrected fractional anisotropy across 60 different template regions. FINDINGS: In the test cohort for disease-specific comparisons, the diffusion-weighted MRI plus MDS-UPDRS III model (Parkinson's disease vs atypical parkinsonism had an AUC 0·962; multiple system atrophy vs progressive supranuclear palsy AUC 0·897) and diffusion-weighted MRI only model had high AUCs (Parkinson's disease vs atypical parkinsonism AUC 0·955; multiple system atrophy vs progressive supranuclear palsy AUC 0·926), whereas the MDS-UPDRS III only models had significantly lower AUCs (Parkinson's disease vs atypical parkinsonism 0·775; multiple system atrophy vs progressive supranuclear palsy 0·582). These results indicate that a non-invasive imaging approach is capable of differentiating forms of parkinsonism comparable to current gold standard methods. INTERPRETATIONS: This study provides an objective, validated, and generalisable imaging approach to distinguish different forms of parkinsonian syndromes using multisite diffusion-weighted MRI cohorts. The diffusion-weighted MRI method does not involve radioactive tracers, is completely automated, and can be collected in less than 12 min across 3T scanners worldwide. The use of this test could positively affect the clinical care of patients with Parkinson's disease and parkinsonism and reduce the number of misdiagnosed cases in clinical trials. FUNDING: National Institutes of Health and Parkinson's Foundation.

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.

Background: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes. Methods: We used dMRI from 1002 subjects, along with the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute (MNI) space between Parkinson's disease (PD) and Atypical Parkinsonism (multiple system atrophy - MSA, progressive supranuclear palsy - PSP), as well as between MSA and PSP. For each comparison, models were developed on a training/validation cohort and evaluated in a test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic (ROC) curves. Findings: In the test cohort for both disease-specific comparisons, AUCs were high in the dMRI + MDS-UPDRS (PD vs. Atypical Parkinsonism: 0·962; MSA vs. PSP: 0·897) and dMRI Only (PD vs. Atypical Parkinsonism: 0·955; MSA vs. PSP: 0·926) models, whereas the MDS-UPDRS III Only models had significantly lower AUCs (PD vs. Atypical Parkinsonism: 0·775; MSA vs. PSP: 0·582). Interpretations: This study provides an objective, validated, and generalizable imaging approach to distinguish different forms of Parkinsonian syndromes using multi-site dMRI cohorts. The dMRI method does not involve radioactive tracers, is completely automated, and can be collected in less than 12 minutes across 3T scanners worldwide. The use of this test could thus positively impact the clinical care of patients with Parkinson's disease and Parkinsonism as well as reduce the number of misdiagnosed cases in clinical trials.

Altered resting-state functional connectivity of the putamen and internal globus pallidus is related to speech impairment in Parkinson's disease.

INTRODUCTION: Speech impairment in Parkinson's disease (PD) is pervasive, with life-impacting consequences. Yet, little is known about how functional connections between the basal ganglia and cortex relate to PD speech impairment (PDSI). Whole-brain resting-state connectivity analyses of basal ganglia nuclei can expand the understanding of PDSI pathophysiology. METHODS: Resting-state data from 89 right-handed subjects were downloaded from the Parkinson's Progression Markers Initiative database. Subjects included 12 older healthy controls ("OHC"), 42 PD patients without speech impairment ("PDN"), and 35 PD subjects with speech impairment ("PDSI"). Subjects were assigned to PDN and PDSI groups based on the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III speech item scores ("0" vs. "1-4"). Whole-brain functional connectivity was calculated for four basal ganglia seeds in each hemisphere: putamen, caudate, external globus pallidus (GPe), and internal globus pallidus (GPi). For each seed region, group-averaged connectivity maps were compared among OHC, PDN, and PDSI groups using a multivariate ANCOVA controlling for the effects of age and sex. Subsequent planned pairwise t-tests were performed to determine differences between the three groups using a voxel-wise threshold of p < 0.001 and cluster-extent threshold of 272 mm3 (FWE<0.05). RESULTS: In comparison with OHCs, both PDN and PDSI groups demonstrated significant differences in cortical connectivity with bilateral putamen, bilateral GPe, and right caudate. Compared to the PDN group, the PDSI subjects demonstrated significant differences in cortical connectivity with left putamen and left GPi. PDSI subjects had lower connectivity between the left putamen and left superior temporal gyrus compared to PDN. In addition, PDSI subjects had greater connectivity between left GPi and three cortical regions: left dorsal premotor/laryngeal motor cortex, left angular gyrus, and right angular gyrus. CONCLUSIONS: The present findings suggest that speech impairment in PD is associated with altered cortical connectivity with left putamen and left GPi.

Subthalamic nucleus--sensorimotor cortex functional connectivity in de novo and moderate Parkinson's disease.

Previous research has indicated increased functional connectivity between subthalamic nucleus (STN) and sensorimotor cortex in off-medication Parkinson's disease (PD) compared with control subjects. It is not clear if the increase in functional connectivity between STN and sensorimotor cortex occurs in de novo PD, which is before patients begin dopamine therapy. Resting-state functional magnetic resonance imaging was carried out in 20 de novo (drug naïve) patients with PD (Hoehn and Yahr stage: I-II), 19 patients with moderate PD (Hoehn and Yahr stage: II-III), and 19 healthy controls. The functional connectivity analysis in de novo and moderate PD patients focused on the connectivity of the more affected STN and the sensorimotor cortex. Using resting-state functional connectivity analysis, we provide new evidence that people with de novo PD and off-medicated moderate PD have increased functional connectivity between the more affected STN and different regions within the sensorimotor cortex. The overlapping sensorimotor cortex found in both de novo and moderate PD had functional connectivity values that correlated positively with the Unified Parkinson's Disease Rating Scale part III. This key finding suggests that changes in functional connectivity between STN and sensorimotor cortex occur early in the disease following diagnosis and before dopamine therapy.

Distinct functional and macrostructural brain changes in Parkinson's disease and multiple system atrophy.

Parkinson's disease (PD) and the parkinsonian variant of multiple system atrophy (MSAp) are neurodegenerative disorders that can be difficult to differentiate clinically. This study provides the first characterization of the patterns of task-related functional magnetic resonance imaging (fMRI) changes across the whole brain in MSAp. We used fMRI during a precision grip force task and also performed voxel-based morphometry (VBM) on T1 -weighted images in MSAp patients, PD patients, and healthy controls. All groups were matched on age, and the patient groups had comparable motor symptom durations and severities. There were three main findings. First, MSAp and PD had reduced fMRI activation in motor control areas, including the basal ganglia, thalamus, insula, primary sensorimotor and prefrontal cortices, and cerebellum compared with controls. Second, there were no activation differences among the disease groups in the basal ganglia, thalamus, insula, or primary sensorimotor cortices, but PD had more extensive activation deficits throughout the cerebrum compared with MSAp and controls. Third, VBM revealed reduced volume in the basal ganglia, middle and inferior cerebellar peduncles, pons, and throughout the cerebrum in MSAp compared with controls and PD, and additionally throughout the cerebellar cortex and vermis in MSAp compared with controls. Collectively, these results provide the first evidence that fMRI activation is abnormal in the basal ganglia, cerebellum, and cerebrum in MSAp, and that a key distinguishing feature between MSAp and PD is the extensive and widespread volume loss throughout the brain in MSAp.

Functional Brain Activity Relates to 0-3 and 3-8 Hz Force Oscillations in Essential Tremor.

It is well-established that during goal-directed motor tasks, patients with essential tremor have increased oscillations in the 0-3 and 3-8 Hz bands. It remains unclear if these increased oscillations relate to activity in specific brain regions. This study used task-based functional magnetic resonance imaging to compare the brain activity associated with oscillations in grip force output between patients with essential tremor, patients with Parkinson's disease who had clinically evident tremor, and healthy controls. The findings demonstrate that patients with essential tremor have increased brain activity in the motor cortex and supplementary motor area compared with controls, and this activity correlated positively with 3-8 Hz force oscillations. Brain activity in cerebellar lobules I-V was reduced in essential tremor compared with controls and correlated negatively with 0-3 Hz force oscillations. Widespread differences in brain activity were observed between essential tremor and Parkinson's disease. Using functional connectivity analyses during the task evidenced reduced cerebellar-cortical functional connectivity in patients with essential tremor compared with controls and Parkinson's disease. This study provides new evidence that in essential tremor 3-8 Hz force oscillations relate to hyperactivity in motor cortex, 0-3 Hz force oscillations relate to the hypoactivity in the cerebellum, and cerebellar-cortical functional connectivity is impaired.

Differences in brain activation between tremor- and nontremor-dominant Parkinson disease.

OBJECTIVE To compare differences in functional brain activity between tremor- and nontremor-dominant subtypes of Parkinson disease (PD) using functional magnetic resonance imaging. DESIGN In our study, patients with tremor-dominant PD and those with nontremor-dominant PD performed a grip task, and the results obtained were compared using voxelwise analysis. Areas of the brain that were significantly different were then examined using a region-of-interest analysis to compare these patients with healthy controls. Voxel-based morphometry was used to determine macroscopic differences in gray and white matter volume between patient groups. SETTING University-affiliated research institution. PARTICIPANTS A total of 20 drug-naive patients with PD (10 with tremor-dominant PD and 10 with nontremor-dominant PD) and a total of 20 healthy controls. MAIN OUTCOME MEASURES Blood oxygenation level-dependent activation and percent signal change. RESULTS Robust findings across both voxelwise and region-of-interest analyses showed that, compared with patients with tremor-dominant PD, patients with nontremor-dominant PD had reduced activation in the ipsilateral dorsolateral prefrontal cortex, the globus pallidus interna, and the globus pallidus externa. Region-of-interest analyses confirmed that patients with nontremor-dominant PD had reduced activity in the ipsilateral dorsolateral prefrontal cortex, the globus pallidus interna, and the globus pallidus externa compared with patients with tremor-dominant PD and healthy controls. Patients with tremor-dominant PD had increased activity in the contralateral dorsolateral prefrontal cortex compared with patients with nontremor-dominant PD and healthy controls. These results could not be explained by differences in gray or white matter volume. CONCLUSIONS Reduced brain activity occurs in the prefrontal cortex and globus pallidus of patients with nontremor-dominant PD compared with both patients with tremor-dominant PD and healthy controls, which suggests that functional magnetic resonance imaging is a promising technique to understand differences in brain activation between subtypes of PD.