Functional Imaging Predicts Dystonia Symptoms

Abstract

Burciu et al. (2017)
https://www.ncbi.nlm.nih.gov/pubmed/28594097

Cervical dystonia (CD) is the most common type of focal dystonia, causing abnormal movements of the neck and head. In this study, we used noninvasive imaging to investigate the motor system of patients with CD and uncover the neural correlates of dystonic symptoms. Furthermore, we examined whether a commonly prescribed anticholinergic medication in CD has an effect on the dystonia-related brain abnormalities. Participants included 16 patients with CD and 16 healthy age-matched controls. We collected functional MRI scans during a force task previously shown to extensively engage the motor system, and diffusion and T1-weighted MRI scans from which we calculated free-water and brain tissue densities. The dystonia group was also scanned ca. 2 h after a 2-mg dose of trihexyphenidyl. Severity of dystonia was assessed pre- and post-drug using the Burke-Fahn-Marsden Dystonia Rating Scale. Motor-related activity in CD was altered relative to controls in the primary somatosensory cortex, cerebellum, dorsal premotor and posterior parietal cortices, and occipital cortex. Most importantly, a regression model showed that increased severity of symptoms was associated with decreased functional activity of the somatosensory cortex and increased activity of the cerebellum. Structural imaging measures did not differ between CD and controls. The single dose of trihexyphenidyl altered the fMRI signal in the somatosensory cortex but not in the cerebellum. Symptom severity was not significantly reduced post-treatment. Findings show widespread changes in functional brain activity in CD and most importantly that dystonic symptoms relate to disrupted activity in the somatosensory cortex and cerebellum.

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A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI.

Cereb Cortex. 2017 Mar 14:1-15. doi: 10.1093/cercor/bhx066. [Epub ahead of print]
A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI.
Archer DB, Vaillancourt DE, Coombes SA.

Abstract
The purpose of this study was to develop a high-resolution sensorimotor area tract template (SMATT) which segments corticofugal tracts based on 6 cortical regions in primary motor cortex, dorsal premotor cortex, ventral premotor cortex, supplementary motor area (SMA), pre-supplementary motor area (preSMA), and primary somatosensory cortex using diffusion tensor imaging. Individual probabilistic tractography analyses were conducted in 100 subjects using the highest resolution data currently available. Tractography results were refined using a novel algorithm to objectively determine slice level thresholds that best minimized overlap between tracts while preserving tract volume. Consistent with tracing studies in monkey and rodent, our observations show that cortical topography is generally preserved through the internal capsule, with the preSMA tract remaining most anterior and the primary somatosensory tract remaining most posterior. We combine our results into a freely available white matter template named the SMATT. We also provide a probabilistic SMATT that quantifies the extent of overlap between tracts. Finally, we assess how the SMATT operates at the individual subject level in another independent data set, and in an individual after stroke. The SMATT and probabilistic SMATT provide new tools that segment and label sensorimotor tracts at a spatial resolution not previously available.

https://www.ncbi.nlm.nih.gov/pubmed/28334314

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Automated classification of pain perception using HD-EEG

J Neurophysiol. 2016 Nov 30:jn.00650.2016. doi: 10.1152/jn.00650.2016. [Epub ahead of print]
Automated Classification of Pain Perception using High Density Electroencephalography Data.
Misra G, Wang WE, Archer DB, Roy A, Coombes SA1.

Translating brief millisecond-long pain-eliciting stimuli to the subjective perception of pain is associated with changes in theta, alpha, beta, and gamma oscillations over sensorimotor cortex. However, when a pain-eliciting stimulus continues for minutes, regions beyond the sensorimotor cortex such as the prefrontal cortex are also engaged. Abnormalities in prefrontal cortex have been associated with chronic pain states, but conventional millisecond-long EEG paradigms do not engage prefrontal regions. In the current study we collected high-density EEG data during an experimental paradigm in which subjects experienced a 4 second low or high intensity pain-eliciting stimulus. EEG data were analyzed using independent component analyses, EEG source localization analyses, and measure projection analyses. We report three novel findings. First, an increase in pain perception was associated with an increase in gamma and theta power in a cortical region that included medial prefrontal cortex. Second, a decrease in lower beta power was associated with an increase in pain perception in a cortical region that included the contralateral sensorimotor cortex. Third, we employed machine learning for automated classification of EEG data into low and high pain classes. Theta and gamma power in the medial prefrontal region and lower beta power in the contralateral sensorimotor region served as features for classification. We found a leave-one-out cross-validation accuracy of 89.58%. Developing biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work.

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Beta Oscillations Linked to Accuracy of Movement

Abstract

Accurate motor performance may depend on the scaling of distinct oscillatory activity within the motor cortex and effective neural communication between the motor cortex and other brain areas. Oscillatory activity within the beta-band (13-30Hz) has been suggested to provide distinct functional roles for attention and sensorimotor control, yet it remains unclear how beta-band and other oscillatory activity within and between cortical regions is coordinated to enhance motor performance. We explore this open issue by simultaneously measuring high-density cortical activity and elbow flexor and extensor neuromuscular activity during ballistic movements, and manipulating error using high and low visual gain across three target distances. Compared with low visual gain, high visual gain decreased movement errors at each distance. Group analyses in 3D source-space revealed increased theta-, alpha-, and beta-band desynchronization of the contralateral motor cortex and medial parietal cortex in high visual gain conditions and this corresponded to reduced movement error. Dynamic causal modeling was used to compute connectivity between motor cortex and parietal cortex. Analyses revealed that gain affected the directionally-specific connectivity across broadband frequencies from parietal to sensorimotor cortex but not from sensorimotor cortex to parietal cortex. These new findings provide support for the interpretation that broad-band oscillations in theta, alpha, and beta frequency bands within sensorimotor and parietal cortex coordinate to facilitate accurate upper limb movement.

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Imaging neural circuits in DYT1 Dystonia reveals new insight

Abstract

Developing in vivo functional and structural neuroimaging assays in Dyt1 ΔGAG heterozygous knock-in (Dyt1 KI) mice provide insight into the pathophysiology underlying DYT1 dystonia. In the current study, we examined in vivo functional connectivity of large-scale cortical and subcortical networks in Dyt1 KI mice and wild-type (WT) controls using resting-state functional magnetic resonance imaging (MRI) and an independent component analysis. In addition, using diffusion MRI we examined how structural integrity across the basal ganglia and cerebellum directly relates to impairments in functional connectivity. Compared to WT mice, Dyt1 KI mice revealed increased functional connectivity across the striatum, thalamus, and somatosensory cortex; and reduced functional connectivity in the motor and cerebellar cortices. Further, Dyt1 KI mice demonstrated elevated free-water (FW) in the striatum and cerebellum compared to WT mice, and increased FW was correlated with impairments in functional connectivity across basal ganglia, cerebellum, and sensorimotor cortex. The current study provides the first in vivo MRI-based evidence in support of the hypothesis that the deletion of a 3-base pair (ΔGAG) sequence in the Dyt1 gene encoding torsinA has network level effects on in vivo functional connectivity and microstructural integrity across the sensorimotor cortex, basal ganglia, and cerebellum.

https://www.ncbi.nlm.nih.gov/pubmed/27404940

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Microstructural properties of premotor pathways predict visuomotor performance in chronic stroke

Hum Brain Mapp. 2016 Feb 27. doi: 10.1002/hbm.23155.
Microstructural properties of premotor pathways predict visuomotor performance in chronic stroke.
Archer DB, Misra G, Patten C, Coombes SA.
http://www.ncbi.nlm.nih.gov/pubmed/26920656

Microstructural properties of the corticospinal tract (CST) descending from the motor cortex predict strength and motor skill in the chronic phase after stroke. Much less is known about the relation between brain microstructure and visuomotor processing after stroke. In this study, individual’s poststroke and age-matched controls performed a unimanual force task separately with each hand at three levels of visual gain. We collected diffusion MRI data and used probabilistic tractography algorithms to identify the primary and premotor CSTs. Fractional anisotropy (FA) within each tract was used to predict changes in force variability across different levels of visual gain. Our observations revealed that individuals poststroke reduced force variability with an increase in visual gain, performed the force task with greater variability as compared with controls across all gain levels, and had lower FA in the primary motor and premotor CSTs. Our results also demonstrated that the CST descending from the premotor cortex, rather than the primary motor cortex, best predicted force variability. Together, these findings demonstrate that the microstructural properties of the premotor CST predict visual gain-related changes in force variability in individuals poststroke.

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Pain-Related Suppression of Beta Oscillations Facilitates Voluntary Movement

Cereb Cortex. 2016 Mar 10. pii: bhw061.
Pain-Related Suppression of Beta Oscillations Facilitates Voluntary Movement.
Misra G, Ofori E, Chung JW, Coombes SA.
http://www.ncbi.nlm.nih.gov/pubmed/26965905

Increased beta oscillations over sensorimotor cortex are antikinetic. Motor- and pain-related processes separately suppress beta oscillations over sensorimotor cortex leading to the prediction that ongoing pain should facilitate movement. In the current study, we used a paradigm in which voluntary movements were executed during an ongoing pain-eliciting stimulus to test the hypothesis that a pain-related suppression of beta oscillations would facilitate the initiation of a subsequent voluntary movement. Using kinematic measures, electromyography, and high-density electroencephalography, we demonstrate that ongoing pain leads to shorter reaction times without affecting the kinematics or accuracy of movement. Reaction time was positively correlated with beta power prior to movement in contralateral premotor areas. Our findings corroborate the view that beta-band oscillations are antikinetic and provide new evidence that pain primes the motor system for action. Our observations provide the first evidence that a pain-related suppression of beta oscillations over contralateral premotor areas leads to shorter reaction times for voluntary movement.

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Nigrostriatal changes with MAO-B Inhibitor in Parkinson’s Disease

Abstract

Rasagiline is a monoamine oxidase type B inhibitor that possesses no amphetamine-like properties, and provides symptomatic relief in early and late stages of Parkinson’s disease (PD). Data in animal models of PD suggest that chronic administration of rasagiline is associated with structural changes in the substantia nigra, and raise the question whether the structure and function of the basal ganglia could be different in PD patients treated chronically with rasagiline as compared with PD patients not treated with rasagiline. Here, we performed a retrospective cross-sectional magnetic resonance imaging (MRI) study at 3 T that investigated nigrostriatal function and structure in PD patients who had taken rasagiline before testing (∼8 months), PD who had not taken rasagiline before testing, and age-matched controls. The two PD groups were selected a priori to not differ significantly in age, sex, disease duration, severity of symptoms, cognitive status, and total levodopa equivalent daily dose of medication. We evaluated percent signal change in the posterior putamen during force production using functional MRI, free-water in the posterior substantia nigra using diffusion MRI, and performance on a bimanual coordination task using a pegboard test. All patients were tested after overnight withdrawal from antiparkinsonian medication. The rasagiline group had greater percent signal change in the posterior putamen, less free-water in the posterior substantia nigra, and better performance on the coordination task than the group not taking rasagiline. These findings point to a possible chronic effect of rasagiline on the structure and function of the basal ganglia in PD.

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Free-water diffusion imaging in Parkinson’s disease and Parkinsonism

Link to paper

Abstract

Conventional single tensor diffusion analysis models have provided mixed findings in the substantia nigra of Parkinson’s disease, but recent work using a bi-tensor analysis model has shown more promising results. Using a bi-tensor model, free-water values were found to be increased in the posterior substantia nigra of Parkinson’s disease compared with controls at a single site and in a multi-site cohort. Further, free-water increased longitudinally over 1 year in the posterior substantia nigra of Parkinson’s disease. Here, we test the hypothesis that other parkinsonian disorders such as multiple system atrophy and progressive supranuclear palsy have elevated free-water in the substantia nigra. Equally important, however, is whether the bi-tensor diffusion model is able to detect alterations in other brain regions beyond the substantia nigra in Parkinson’s disease, multiple system atrophy, and progres- sive supranuclear palsy and to accurately distinguish between these diseases. Free-water and free-water-corrected fractional an- isotropy maps were compared across 72 individuals in the basal ganglia, midbrain, thalamus, dentate nucleus, cerebellar peduncles, cerebellar vermis and lobules V and VI, and corpus callosum. Compared with controls, free-water was increased in the anterior and posterior substantia nigra of Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy. Despite no other changes in Parkinson’s disease, we observed elevated free-water in all regions except the dentate nucleus, subthalamic nucleus, and corpus callosum of multiple system atrophy, and in all regions examined for progressive supranuclear palsy. Compared with controls, free-water-corrected fractional anisotropy values were increased for multiple system atrophy in the putamen and caudate, and increased for progressive supranuclear palsy in the putamen, caudate, thalamus, and vermis, and decreased in the superior cerebellar peduncle and corpus callosum. For all disease group comparisons, the support vector machine 10-fold cross-validation area under the curve was between 0.93–1.00 and there was high sensitivity and specificity. The regions and diffusion measures selected by the model varied across comparisons and are consistent with pathological studies. In conclusion, the current study used a novel bi-tensor diffusion analysis model to indicate that all forms of parkinsonism had elevated free-water in the substantia nigra. Beyond the substantia nigra, both multiple system atrophy and progressive supranuclear palsy, but not Parkinson’s disease, showed a broad network of elevated free-water and altered free-water corrected fractional anisotropy that included the basal ganglia, thalamus, and cerebellum. These findings may be helpful in the differential diagnosis of parkinsonian disorders, and thereby facilitate the development and assessment of targeted therapies.

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Pain and motor processing in the human cerebellum

Abstract
Pain-related adaptions in movement require a network architecture that allows for integration across pain and motor circuits. Previous studies addressing this issue have focused on cortical areas such as the midcingulate cortex. Here we focus on pain and motor processing in the human cerebellum. The goal in the current study was to identify areas of activation in the cerebellum that are common to pain and motor processing and to determine whether the activation is limited to the superior and inferior cerebellar motor maps, or extends into multimodal areas of the posterior cerebellum. Our observations identified overlapping activity in left and right lobules VI and VIIb during pain and motor processing. Activation in these multimodal regions persisted when pain and motor processes were combined within the same trial, and activation in contralateral left lobule VIIb persisted when stimulation was controlled for. Functional connectivity analyses revealed significant correlations in the BOLD timeseries between multimodal cerebellar regions and sensorimotor regions in the cerebrum including anterior midcingulate cortex, supplementary motor area, and thalamus. The current findings are the first to show multimodal processing in lobules VI and VIIb for motor control and pain processing, and suggest that the posterior cerebellum may be important in understanding pain-related adaptations in motor control.

http://www.ncbi.nlm.nih.gov/pubmed/26307859

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