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It is estimated that short association fibers, or 'U-shaped' fibers running immediately beneath the cortex, may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in U-fiber tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several U-fiber systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in superficial white matter throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of U-fiber volume and length decrease with age in a heterogenous manner across the brain, with prominent effects observed for pre- and post-central gyri. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.

ObjectiveHippocampal volume is a sensitive marker of neurodegeneration and a well-established predictor of age-related cognitive impairment. Recently, free-water (FW) magnetic resonance imaging (MRI) has shown associations with pathology in Alzheimer’s disease (AD), but it is still unclear whether these metrics are associated with measures of cognitive impairment. Here, we investigate whether FW and FW-corrected fractional anisotropy (FAT) within medial temporal lobe white matter tracts (cingulum, fornix, uncinate fasciculus, inferior longitudinal fasciculus, and tapetum) provides meaningful contribution to cognition and cognitive decline beyond hippocampal volume.Participants and MethodsVanderbilt Memory & Aging Project participants (n=319, 73±7 years, 59% male) with normal cognition and mild cognitive impairment (40% of cohort) underwent baseline brain MRI, including structural MRI to quantify hippocampal volume, diffusion MRI to quantify medial temporal lobe white matter tract FW and FAT, and longitudinal neuropsychological assessment with a mean follow-up of 3.5 years. Linear regressions were conducted to determine how hippocampal volume and white matter tract FW and FAT interact with baseline memory and executive function performances. Competitive model analyses determined the unique variance provided by white matter tract FW and FAT beyond that of hippocampal volume and other comorbidities. Linear mixed-effects models were conducted to determine how baseline hippocampal volume and white matter tract FW and FAT interact to explain longitudinal change in memory and executive function performances.ResultsFW in the inferior longitudinal fasciculus, tapetum, uncinate fasciculus, and cingulum were robustly associated with baseline memory and executive function. Further, competitive model analysis showed that tract FW contributed unique variance beyond other comorbidities and hippocampal volume for memory (ΔRadj2 range: 0.82-2.00%) and executive function (ΔRadj2 range: 0.88-1.87%). Longitudinal analyses demonstrated significant interactions of hippocampal volume and FAT in the inferior longitudinal fasciculus (p=0.02), tapetum (p=0.02), uncinate fasciculus (p=0.02), and cingulum (p=0.002) with decline in memory. For decline in executive function, we found significant interactions of hippocampal volume and FAT in inferior longitudinal fasciculus (p=0.03), tapetum (p=0.02), uncinate fasciculus (p=0.02), and fornix (p=0.02), as well as cingulum (p=0.02) and fornix (p=0.02) FW.ConclusionsOur results highlight novel associations between FW and FAT measures of medial temporal lobe tract microstructure and cognitive performance such that individuals with smaller hippocampal volumes and lower tract microstructure experience greater cognitive decline. These results suggest that white matter has a unique role in cognitive decline and, therefore, could be used to provide better disease staging, allowing for more precise disease monitoring in AD.

OBJECTIVE Accurate diagnosis is particularly challenging in Parkinson's disease (PD), multiple system atrophy (MSAp), and progressive supranuclear palsy (PSP). We compare the utility of 3 promising biomarkers to differentiate disease state and explain disease severity in parkinsonism: the Automated Imaging Differentiation in Parkinsonism (AID-P), the Magnetic Resonance Parkinsonism Index (MRPI), and plasma-based neurofilament light chain protein (NfL). METHODS For each biomarker, the area under the curve (AUC) of receiver operating characteristic curves were quantified for PD versus MSAp/PSP and MSAp versus PSP and statistically compared. Unique combinations of variables were also assessed. Furthermore, each measures association with disease severity was determined using stepwise multiple regression. RESULTS For PD versus MSAp/PSP, AID-P (AUC, 0.900) measures had higher AUC compared with NfL (AUC, 0.747) and MRPI (AUC, 0.669), P

Background Rasagiline has received attention as a potential disease-modifying therapy for Parkinson's disease (PD). Whether rasagiline is disease modifying remains in question. Objective The main objective of this study was to determine whether rasagiline has disease-modifying effects in PD over 1 year. Secondarily we evaluated two diffusion magnetic resonance imaging pulse sequences to determine the best sequence to measure disease progression. Methods This prospective, randomized, double-blind, placebo-controlled trial assessed the effects of rasagiline administered at 1 mg/day over 12 months in early-stage PD. The primary outcome was 1-year change in free-water accumulation in posterior substantia nigra (pSN) measured using two diffusion magnetic resonance imaging pulse sequences, one with a repetition time (TR) of 2500 ms (short TR; n = 90) and one with a TR of 6400 ms (long TR; n = 75). Secondary clinical outcomes also were assessed. Results Absolute change in pSN free-water accumulation was not significantly different between groups (short TR: P = 0.346; long TR: P = 0.228). No significant differences were found in any secondary clinical outcomes between groups. Long TR, but not short TR, data show pSN free-water increased significantly over 1 year (P = 0.025). Movement Disorder Society Unified Parkinson's Disease Rating Scale testing of motor function, Part III increased significantly over 1 year (P = 0.009), and baseline free-water in the pSN correlated with the 1-year change in Movement Disorder Society Unified Parkinson's Disease Rating Scale testing of motor function, Part III (P = 0.004) and 1-year change in bradykinesia score (P = 0.044). Conclusions We found no evidence that 1 mg/day rasagiline has a disease-modifying effect in PD over 1 year. We found pSN free-water increased over 1 year, and baseline free-water relates to clinical motor progression, demonstrating the importance of diffusion imaging parameters for detecting and predicting PD progression. © 2021 International Parkinson and Movement Disorder Society.

Understanding the architecture of transcallosal connections would allow for more specific assessments of neurodegeneration across many fields of neuroscience, neurology, and psychiatry. To map these connections, we conducted probabilistic tractography in 100 Human Connectome Project subjects in 32 cortical areas using novel post-processing algorithms to create a spatially precise Trancallosal Tract Template (TCATT). We found robust transcallosal tracts in all 32 regions, and a topographical analysis in the corpus callosum largely agreed with well-established subdivisions of the corpus callosum. We then obtained diffusion MRI data from a cohort of patients with Alzheimer’s disease (AD) and another with progressive supranuclear palsy (PSP) and used a two-compartment model to calculate free-water corrected fractional anisotropy (FA(T)) and free-water (FW) within the TCATT. These metrics were used to determine between-group differences and to determine which subset of tracts was best associated with cognitive function (Montreal Cognitive Assessment (MoCA)). In AD, we found robust between-group differences in FW (31/32 TCATT tracts) in the absence of between-group differences in FA(T). FW in the inferior temporal gyrus TCATT tract was most associated with MoCA scores in AD. In PSP, there were widespread differences in both FA(T) and FW, and MoCA was predicted by FA(T) in the inferior frontal pars triangularis, preSMA, and medial frontal gyrus TCATT tracts as well as FW in the inferior frontal pars opercularis TCATT tract. The TCATT improves spatial localization of corpus callosum measurements to enhance the evaluation of treatment effects, as well as the monitoring of brain microstructure in relation to cognitive dysfunction and disease progression. Here, we have shown its direct relevance in capturing between-group differences and associating it with the MoCA in AD and PSP.

Introduction When using free-water diffusion imaging or positron emission tomography (PET), it is established that substania nigra microstructure and presynaptic dopamine activity are impaired in early PD. It is not well understood if these two forms of degeneration are redundant, or if they each provide a unique contribution to the clinical motor and cognitive symptoms. Methods A total of 129 PD and 75 control individuals underwent motor and cognitive evaluations, and in vivo [11C]dihydrotetrabenazine (DTBZ) monoaminergic brain PET imaging and diffusion imaging. Correlations between free-water in the substantia nigra and striatal PET measures were analyzed. Unbiased multiple regression using a backward elimination method was performed between clinical severity and all imaging measures. Results Inverse correlations were found between free-water in posterior substantia nigra and DTBZ binding in putamen and caudate. Multiple regression revealed that increased free-water in the posterior substantia nigra, decreased DTBZ binding in putamen, and age were predictors of higher Hoehn and Yahr stage, MDS-UPDRS III scores, and posture and gait sub-scores. Increased posterior substantia nigra free-water alone was associated tremor scores. Free-water in caudate and putamen did not predict measures of motor performance. Decreased DTBZ binding in caudate, increased free-water in caudate and posterior substantia nigra were associated with higher dementia ratings. Conclusions These findings suggest that free-water in the posterior substantia nigra and presynaptic dopamine imaging in striatum are uniquely associated with the clinical symptoms of PD, indicating that each imaging modality may be measuring a unique mechanism relevant to nigrostriatal degeneration.

Highlights • RDT within several white matter tracts is associated with SCD. • RDT contributes unique variance to SCD beyond that of CSF Aβ42. • Our findings suggest that RDT is a sensitive marker of SCD., Subjective cognitive decline (SCD) is a perceived cognitive change prior to objective cognitive deficits, and although it is associated with Alzheimer’s disease (AD) pathology, it likely results from multiple underlying pathologies. We investigated the association of white matter microstructure to SCD as a sensitive and early marker of cognitive decline and quantified the contribution of white matter microstructure separate from amyloidosis. Vanderbilt Memory & Aging Project participants with diffusion MRI data and a 45-item measure of SCD were included [n = 236, 137 cognitively unimpaired (CU), 99 with mild cognitive impairment (MCI), 73 ± 7 years, 37% female]. A subset of participants (64 CU, 40 MCI) underwent a fasting lumbar puncture for quantification of cerebrospinal fluid (CSF) amyloid-β(CSF Aβ42), total tau (CSF t-tau), and phosphorylated tau (CSF p-tau). Diffusion MRI data was post-processed using the free-water (FW) elimination technique, which allowed quantification of extracellular (FW) and intracellular compartment (fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity) microstructure. Microstructural values were quantified within 11 cognitive-related white matter tracts, including medial temporal lobe, frontal transcallosal, and fronto-parietal tracts using a region of interest approach. General linear modeling related each tract to SCD scores adjusting for age, sex, race/ethnicity, education, Framingham Stroke Risk Profile scores, APOE ε4 carrier status, diagnosis, Geriatric Depression Scale scores, hippocampal volume, and total white matter volume. Competitive models were analyzed to determine if white matter microstructural values have a unique role in SCD scores separate from CSF Aβ42. FW-corrected radial diffusivity (RDT) was related to SCD scores in 8 tracts: cingulum bundle, inferior longitudinal fasciculus, as well as inferior frontal gyrus (IFG) pars opercularis, IFG orbitalis, IFG pars triangularis, tapetum, medial frontal gyrus, and middle frontal gyrus transcallosal tracts. While CSF Aβ42 was related to SCD scores in our cohort (Radj2 = 39.03%; β = −0.231; p = 0.020), competitive models revealed that fornix and IFG pars triangularis transcallosal tract RDT contributed unique variance to SCD scores beyond CSF Aβ42 (Radj2 = 44.35% and Radj2 = 43.09%, respectively), with several other tract measures demonstrating nominal significance. All tracts which demonstrated nominal significance (in addition to covariates) were input into a backwards stepwise regression analysis. ILF RDT, fornix RDT, and UF FW were best associated with SCD scores (Radj2 = 46.69%; p = 6.37 × 10-12). Ultimately, we found that medial temporal lobe and frontal transcallosal tract microstructure is an important driver of SCD scores independent of early amyloid deposition. Our results highlight the potential importance of abnormal white matter diffusivity as an early contributor to cognitive decline. These results also highlight the value of incorporating multiple biomarkers to help disentangle the mechanistic heterogeneity of SCD as an early stage of cognitive decline.

Summary 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.

Background Evidence from functional imaging in essential tremor suggests that activity within parietal and motor cortices may be associated with worsening of tremor at increased visual feedback. Objectives Examine how cortical oscillations within these regions and the connectivity between these regions is associated with worsening of tremor in essential tremor in response to high visual feedback. Method The study included 24 essential tremor participants and 17 controls. We measured cortical activity and tremor magnitude at low and high feedback conditions. Cortical activity was measured using high-density electroencephalogram and isolated using source localization. Results Changes in power across feedback in the 4-12 Hz and 12-30 Hz bands were reduced within the contralateral motor cortex of essential tremor patients compared to controls. The 12-30 Hz bidirectional connectivity between the parietal and contralateral motor cortex was decreased in essential tremor patients. Worsening of tremor from low to high visual feedback was associated with 4-12 Hz activity in contralateral motor cortex. The greatest separation between groups was found when using the difference of the contralateral motor cortex activity at high and low feedback, rather than either feedback condition alone. Conclusion Our findings provide new evidence that tremor in essential tremor is associated with reduced power across feedback in the motor cortex and reduced connectivity between the parietal and motor cortices. Combined with previous work on the cerebellar-thalamo-cortical motor circuit, our findings suggest that the network level disturbances associated with essential tremor extend to the cortico-cortical pathway between the parietal cortex and motor cortex. © 2018 International Parkinson and Movement Disorder Society.

Measures from diffusion MRI have been used to characterize the corticospinal tract in chronic stroke. However, diffusivity can be influenced by partial volume effects from free-water, region of interest placement, and lesion masking. We collected diffusion MRI from a cohort of chronic stroke patients and controls and used a bitensor model to calculate free-water corrected fractional anisotropy (FAT) and free water (FW) in the primary motor corticospinal tract (M1-CST) and the dorsal premotor corticospinal tract (PMd-CST). Region of interest analyses and whole-tract slice-by-slice analyses were used to assess between-group differences in FAT and FW in each tract. Correlations between FAT and FW and grip strength were also examined. Following lesion masking and correction for multiple comparisons, relative increases in FW were found for the stroke group in large portions of the M1-CST and PMd-CST in the lesioned hemisphere. FW in cortical regions was the strongest predictor of grip strength in the stroke group. Our findings also demonstrated that FAT is sensitive to the direct effects of the lesion itself, thus after controlling for the lesion, differences in FAT in nonlesioned tissue were small and generally similar between hemispheres and groups. Our observations suggest that FW may be a robust biological measurement that can be used to assess microstructure in residual white matter after stroke. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

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.

The translation of 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-s, 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 used 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%. The development of biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work.NEW & NOTEWORTHY The development of a biological marker for pain continues to gain traction in literature. Our findings show that high- and low-pain perception in human subjects can be classified with 89% accuracy using high-density EEG data from prefrontal cortex and contralateral sensorimotor cortex. Our approach represents a novel neurophysiological paradigm that advances the literature on biological markers for pain.

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.

Dystonia is a movement disorder characterized by involuntary muscle co-contractions that give rise to disabling movements and postures. A recent expert consensus labelled the incidence of tremor as a core feature of dystonia that can affect body regions both symptomatic and asymptomatic to dystonic features. We are only beginning to understand the neural network-level signatures that relate to clinical features of dystonic tremor. At the same time, clinical features of dystonic tremor can resemble that of essential tremor and present a diagnostic confound for clinicians. Here, we examined network-level functional activation and connectivity in patients with dystonic tremor and essential tremor. The dystonic tremor group included primarily cervical dystonia patients with dystonic head tremor and the majority had additional upper-limb tremor. The experimental paradigm included a precision grip-force task wherein online visual feedback related to force was manipulated across high and low spatial feedback levels. Prior work using this paradigm in essential tremor patients produced exacerbation of grip-force tremor and associated changes in functional activation. As such, we directly compared the effect of visual feedback on grip-force tremor and associated functional network-level activation and connectivity between dystonic tremor and essential tremor patient cohorts to better understand disease-specific mechanisms. Increased visual feedback similarly exacerbated force tremor during the grip-force task in dystonic tremor and essential tremor cohorts. Patients with dystonic tremor and essential tremor were characterized by distinct functional activation abnormalities in cortical regions but not in the cerebellum. We examined seed-based functional connectivity from the sensorimotor cortex, globus pallidus internus, ventral intermediate thalamic nucleus, and dentate nucleus, and observed abnormal functional connectivity networks in dystonic tremor and essential tremor groups relative to controls. However, the effects were far more widespread in the dystonic tremor group as changes in functional connectivity were revealed across cortical, subcortical, and cerebellar regions independent of the seed location. A unique pattern for dystonic tremor included widespread reductions in functional connectivity compared to essential tremor within higher-level cortical, basal ganglia, and cerebellar regions. Importantly, a receiver operating characteristic determined that functional connectivity z-scores were able to classify dystonic tremor and essential tremor with 89% area under the curve, whereas combining functional connectivity with force tremor yielded 94%. These findings point to network-level connectivity as an important feature that differs substantially between dystonic tremor and essential tremor and should be further explored in implementing appropriate diagnostic and therapeutic strategies.

Convolutional neural networks are ubiquitous in Machine Learning applications for solving a variety of problems. They however can not be used in their native form when the domain of the data is commonly encountered manifolds such as the sphere, the special orthogonal group, the Grassmannian, the manifold of symmetric positive definite matrices and others. Most recently, generalization of CNNs to Riemannian homogeneous spaces have been reported in literature. In this work, we propose an end-to-end CNN architecture for classification of diffusion MRI (dMRI) signals, dubbed dMR-CNN. In each voxel of the dMRI scan, the signal is acquired as a real number along each diffusion sensitizing magnetic field direction over a hemisphere of directions in 3D. Hence, in each voxel, we have a function $f : \mathbf { S } ^ { 2 } \times P _ { 1 } \rightarrow \mathbf { R }$. We formulate a definition of correlation on this space to extract intra-voxel features and then use standard CNN model to capture the spatial interactions between the intra-voxel features. Our proposed framework comprises of architectures to extract these intra- and inter- voxel features. We present an experimental setup to classify dMRI scans acquired from a cohort of 44 Parkinson Disease patients and 50 control$/$normal subjects.

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. Hum Brain Mapp 37:2039-2054, 2016. © 2016 Wiley Periodicals, Inc.

Modulating visual feedback may be a viable option to improve motor function after stroke, but the neurophysiological basis for this improvement is not clear. Visual gain can be manipulated by increasing or decreasing the spatial amplitude of an error signal. Here, we combined a unilateral visually guided grip force task with functional MRI to understand how changes in the gain of visual feedback alter brain activity in the chronic phase after stroke. Analyses focused on brain activation when force was produced by the most impaired hand of the stroke group as compared to the non-dominant hand of the control group. Our experiment produced three novel results. First, gain-related improvements in force control were associated with an increase in activity in many regions within the visuomotor network in both the stroke and control groups. These regions include the extrastriate visual cortex, inferior parietal lobule, ventral premotor cortex, cerebellum, and supplementary motor area. Second, the stroke group showed gain-related increases in activity in additional regions of lobules VI and VIIb of the ipsilateral cerebellum. Third, relative to the control group, the stroke group showed increased activity in the ipsilateral primary motor cortex, and activity in this region did not vary as a function of visual feedback gain. The visuomotor network, cerebellum, and ipsilateral primary motor cortex have each been targeted in rehabilitation interventions after stroke. Our observations provide new insight into the role these regions play in processing visual gain during a precisely controlled visuomotor task in the chronic phase after stroke., Highlights • Increased visual gain engaged visuomotor network in stroke and control groups. • Stroke group also showed visual gain effect in cerebellar lobule VI/VIIb. • Stroke group showed increased contralesional M1 activity for all visual gain levels.

Essential tremor is a neurological syndrome of heterogeneous pathology and aetiology that is characterized by tremor primarily in the upper extremities. This tremor is commonly hypothesized to be driven by a single or multiple neural oscillator(s) within the cerebello-thalamo-cortical pathway. Several studies have found an association of blood-oxygen level-dependent (BOLD) signal in the cerebello-thalamo-cortical pathway with essential tremor, but there is behavioural evidence that also points to the possibility that the severity of tremor could be influenced by visual feedback. Here, we directly manipulated visual feedback during a functional MRI grip force task in patients with essential tremor and control participants, and hypothesized that an increase in visual feedback would exacerbate tremor in the 4-12 Hz range in essential tremor patients. Further, we hypothesized that this exacerbation of tremor would be associated with dysfunctional changes in BOLD signal and entropy within, and beyond, the cerebello-thalamo-cortical pathway. We found that increases in visual feedback increased tremor in the 4-12 Hz range in essential tremor patients, and this increase in tremor was associated with abnormal changes in BOLD amplitude and entropy in regions within the cerebello-thalamo-motor cortical pathway, and extended to visual and parietal areas. To determine if the tremor severity was associated with single or multiple brain region(s), we conducted a birectional stepwise multiple regression analysis, and found that a widespread functional network extending beyond the cerebello-thalamo-motor cortical pathway was associated with changes in tremor severity measured during the imaging protocol. Further, this same network was associated with clinical tremor severity measured with the Fahn, Tolosa, Marin Tremor Rating Scale, suggesting this network is clinically relevant. Since increased visual feedback also reduced force error, this network was evaluated in relation to force error but the model was not significant, indicating it is associated with force tremor but not force error. This study therefore provides new evidence that a widespread functional network is associated with the severity of tremor in patients with essential tremor measured simultaneously at the hand during functional imaging, and is also associated with the clinical severity of tremor. These findings support the idea that the severity of tremor is exacerbated by increased visual feedback, suggesting that designers of new computing technologies should consider using lower visual feedback levels to reduce tremor in essential tremor.

Musculoskeletal pain changes how people move. Although experimental pain is associated with increases in the variability of motor output, it is not clear whether motor-evoked pain in clinical conditions is also associated with increases in variability. In the current study, we measured jaw force production during a visually guided force paradigm in which individuals with chronic jaw pain and control subjects produced force at 2% of their maximum voluntary contraction (low target force level) and at 15% of their maximum voluntary contraction (high target force level). State measures of pain were collected before and after each trial. Trait measures of pain intensity and pain interference, self-report measures of jaw function, and measures of depression, anxiety, and fatigue were also collected. We showed that the chronic jaw pain group exhibited greater force variability compared with controls irrespective of the force level, whereas the accuracy of force production did not differ between groups. Furthermore, predictors of force variability shifted from trait measures of pain intensity and pain interference at the low force level to state measures of pain intensity at the high force level. Our observations show that motor-evoked jaw pain is associated with increases in force variability that are predicted by a combination of trait measures and state measures of pain intensity and pain interference. Perspective Chronic jaw pain is characterized by increases in variability during force production, which can be predicted by pain intensity and pain interference. This report could help clinicians better understand the long-term consequences of chronic jaw pain on the motor system.

Progression markers of Parkinson’s disease are crucial for therapeutic development. Burciu et al. validate free-water in the substantia nigra as a progression marker at one- and four-year follow-up, in an international cohort of de novo Parkinson’s disease. One-year changes in free-water predict the progression of motor symptoms over four years., Progression markers of Parkinson’s disease are crucial for successful therapeutic development. Recently, a diffusion magnetic resonance imaging analysis technique using a bitensor model was introduced allowing the estimation of the fractional volume of free water within a voxel, which is expected to increase in neurodegenerative disorders such as Parkinson’s disease. Prior work demonstrated that free water in the posterior substantia nigra was elevated in Parkinson’s disease compared to controls across single- and multi-site cohorts, and increased over 1 year in Parkinson’s disease but not in controls at a single site. Here, the goal was to validate free water in the posterior substantia nigra as a progression marker in Parkinson’s disease, and describe the pattern of progression of free water in patients with a 4-year follow-up tested in a multicentre international longitudinal study of de novo Parkinson’s disease (http://www.ppmi-info.org/). The analyses examined: (i) 1-year changes in free water in 103 de novo patients with Parkinson’s disease and 49 controls; (ii) 2- and 4-year changes in free water in a subset of 46 patients with Parkinson’s disease imaged at baseline, 12, 24, and 48 months; (iii) whether 1- and 2-year changes in free water predict 4-year changes in the Hoehn and Yahr scale; and (iv) the relationship between 4-year changes in free water and striatal binding ratio in a subgroup of Parkinson’s disease who had undergone both diffusion and dopamine transporter imaging. Results demonstrated that: (i) free water level in the posterior substantia nigra increased over 1 year in de novo Parkinson’s disease but not in controls; (ii) free water kept increasing over 4 years in Parkinson’s disease; (iii) sex and baseline free water predicted 4-year changes in free water; (iv) free water increases over 1 and 2 years were related to worsening on the Hoehn and Yahr scale over 4 years; and (v) the 4-year increase in free water was associated with the 4-year decrease in striatal binding ratio in the putamen. Importantly, all longitudinal results were consistent across sites. In summary, this study demonstrates an increase over 1 year in free water in the posterior substantia nigra in a large cohort of de novo patients with Parkinson’s disease from a multi-site cohort study and no change in healthy controls, and further demonstrates an increase of free water in Parkinson’s disease over the course of 4 years. A key finding was that results are consistent across sites and the 1-year and 2-year increase in free water in the posterior substantia nigra predicts subsequent long-term progression on the Hoehn and Yahr staging system. Collectively, these findings demonstrate that free water in the posterior substantia nigra is a valid, progression imaging marker of Parkinson’s disease, which may be used in clinical trials of disease-modifying therapies.

Poststroke central pain (PSCP) can be a debilitating medication-refractory disorder. We report a single case where right unilateral ventral capsule/ventral striatum (VC/VS) deep brain stimulation was used to treat PSCP and inadvertently induced a smile without euphoria. The patient was a 69 year-old woman who had a stroke with resultant dysesthesia and allodynia in her left hemibody and also a painful left hemibody dystonia. In her case, VC/VS stimulation induced a smile phenomenon, but without a euphoric sensation. This phenomenon was different from the typical smile responses we have observed in obsessive-compulsive disorder cases. This difference was considered to be possibly attributable to impairment in the emotional smile pathway.

Limited experimental data exist comparing the mechanical response of the tibial cortex between fixed and rotating platform (RP) total knee arthroplasty (TKA), particularly in the revision setting. We asked if RP-TKA significantly affects tibiofemoral torque and cortical stain response in both the primary and revision settings. Fixed and RP tibial trays were implanted into analogue tibias and biomechanically tested under axial and torsional loading. Torque and strain response were analyzed using digital image correlation. Fixed bearing designs exhibited 13.8 times greater torque (P0.01), and 69% (P0.01) higher cortical strain than RP designs. Strain response was similar in the primary and revision cohorts. The decrease in torque transfer could act as a safeguard to reduce stress, micromotion and torsional fatigue in scenario of poor bone stock.

The goal in the current study was to examine the analgesic effects of a pinch grip-force production task and a working memory task when pain-eliciting thermal stimulation was delivered simultaneously to the left or right hand during task performance. Control conditions for visual distraction and thermal stimulation were included, and force performance measures and working memory performance measures were collected and analyzed. Our experiments revealed 3 novel findings. First, we showed that accurate isometric force contractions elicit an analgesic effect when pain-eliciting thermal stimulation was delivered during task performance. Second, the magnitude of the analgesic effect was not different when the pain-eliciting stimulus was delivered to the left or right hand during the force task or the working memory task. Third, we found no correlation between analgesia scores during the force task and the working memory task. Our findings have clinical implications for rehabilitation settings because they suggest that acute force production by one limb influences pain perception that is simultaneously experienced in another limb. From a theoretical perspective, we interpret our findings on force and memory driven analgesia in the context of a centralized pain inhibitory response. Perspective This article shows that force production and working memory have analgesic effects irrespective of which side of the body pain is experienced on. Analgesia scores were not correlated, however, suggesting that some individuals experience more pain relief from a force task as compared to a working memory task and vice versa.

With increased precision in alignment offered by new generations of instrumentation and customized guides, this study was designed to establish a biomechanically-based target alignment for the balance of tibial loading in order to diminish the likelihood of pain and subsidence related to mechanical overload post-UKA. Sixty composite tibias were implanted with Oxford UKA tibial components with varied sagittal slope, resection depth, rotation and medial shift using patient matched instrumentation. Digital image correlation and strain gage analysis was conducted in static loading to evaluate strain distribution as a result of component alignment. In this model, minimal distal resection and most lateral positioning, neutral component rotation, and 3° of slope (from mechanical axis) exhibited the most balanced strain response to loading following UKA.

Measures from diffusion MRI have been used to characterize the corticospinal tract in chronic stroke. However, diffusivity can be influenced by partial volume effects from free‐water, region of interest placement, and lesion masking. We collected diffusion MRI from a cohort of chronic stroke patients and controls and used a bitensor model to calculate free‐water corrected fractional anisotropy (FA(T)) and free water (FW) in the primary motor corticospinal tract (M1‐CST) and the dorsal premotor corticospinal tract (PMd‐CST). Region of interest analyses and whole‐tract slice‐by‐slice analyses were used to assess between‐group differences in FA(T) and FW in each tract. Correlations between FA(T) and FW and grip strength were also examined. Following lesion masking and correction for multiple comparisons, relative increases in FW were found for the stroke group in large portions of the M1‐CST and PMd‐CST in the lesioned hemisphere. FW in cortical regions was the strongest predictor of grip strength in the stroke group. Our findings also demonstrated that FA(T) is sensitive to the direct effects of the lesion itself, thus after controlling for the lesion, differences in FA(T) in nonlesioned tissue were small and generally similar between hemispheres and groups. Our observations suggest that FW may be a robust biological measurement that can be used to assess microstructure in residual white matter after stroke. Hum Brain Mapp 38:4546–4562, 2017. © 2017 Wiley Periodicals, Inc.

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. Hum Brain Mapp 37:2039–2054, 2016. © 2016 Wiley Periodicals, Inc.