State-of-the-art clinical assessment of hand function

We have assembled a multi-disciplinary team of engineers, surgeons, clinicians and neuroscientists from Johns Hopkins School of Medicine and Western University to develop a new device for assessing hand function. It will be capable of sensitively measuring fingertip forces across all five fingers and along all movement directions. Then we can use this device to develop and validate a clinical hand assessment for patients with brain injuries.https://ir.lib.uwo.ca/brainscanprojectsummaries/1005/thumbnail.jp

Structural and functional MRI abnormalities of cerebellar cortex and nuclei in SCA3, SCA6 and Friedreich\u27s ataxia

Spinocerebellar ataxia type 3, spinocerebellar ataxia type 6 and Friedreich\u27s ataxia are common hereditary ataxias. Different patterns of atrophy of the cerebellar cortex are well known. Data on cerebellar nuclei are sparse. Whereas cerebellar nuclei have long been thought to be preserved in spinocerebellar ataxia type 6, histology shows marked atrophy of the nuclei in Friedreich\u27s ataxia and spinocerebellar ataxia type 3. In the present study susceptibility weighted imaging was used to assess atrophy of the cerebellar nuclei in patients with spinocerebellar ataxia type 6 (n = 12, age range 41-76 years, five female), Friedreich\u27s ataxia (n = 12, age range 21-55 years, seven female), spinocerebellar ataxia type 3 (n = 10, age range 34-67 years, three female), and age-and gender-matched controls (total n = 23, age range 22-75 years, 10 female). T1-weighted magnetic resonance images were used to calculate the volume of the cerebellum. In addition, ultra-high field functional magnetic resonance imaging was performed with optimized normalization methods to assess function of the cerebellar cortex and nuclei during simple hand movements. As expected, the volume of the cerebellum was markedly reduced in spinocerebellar ataxia type 6, preserved in Friedreich\u27s ataxia, and mildy reduced in spinocerebellar ataxia type 3. The volume of the cerebellar nuclei was reduced in the three patient groups compared to matched controls (P-values \u3c 0.05; two-sample t-tests). Atrophy of the cerebellar nuclei was most pronounced in spinocerebellar ataxia type 6. On a functional level, hand-movement-related cerebellar activation was altered in all three disorders. Within the cerebellar cortex, functional magnetic resonance imaging signal was significantly reduced in spinocerebellar ataxia type 6 and Friedreich\u27s ataxia compared to matched controls (P-values \u3c 0.001, bootstrap-corrected cluster-size threshold; two-sample t-tests). The difference missed significance in spinocerebellar ataxia type 3. Within the cerebellar nuclei, reductions were significant when comparing spinocerebellar ataxia type 6 and Friedreich\u27s ataxia to matched controls (P \u3c 0.01, bootstrap-corrected cluster-size threshold; two-sample t-tests). Susceptibility weighted imaging allowed depiction of atrophy of the cerebellar nuclei in patients with Friedreich\u27s ataxia and spinocerebellar ataxia type 3. In spinocerebellar ataxia type 6, pathology was not restricted to the cerebellar cortex but also involved the cerebellar nuclei. Functional magnetic resonance imaging data, on the other hand, revealed that pathology in Friedreich\u27s ataxia and spinocerebellar ataxia type 3 is not restricted to the cerebellar nuclei. There was functional involvement of the cerebellar cortex despite no or little structural changes

Cortical beta oscillations are associated with motor performance following visuomotor learning

© 2019 The Authors People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45–60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session. Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes

Whole-brain in-vivo measurements of the Axonal G-Ratio in a group of 37 healthy volunteers

The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brain's prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration

Transcranial direct current stimulation of right dorsolateral prefrontal cortex does not affect model-based or model-free reinforcement learning in humans

There is broad consensus that the prefrontal cortex supports goal-directed, model-based decision-making. Consistent with this, we have recently shown that model-based control can be impaired through transcranial magnetic stimulation of right dorsolateral prefrontal cortex in humans. We hypothesized that an enhancement of model-based control might be achieved by anodal transcranial direct current stimulation of the same region. We tested 22 healthy adult human participants in a within-subject, double-blind design in which participants were given Active or Sham stimulation over two sessions. We show Active stimulation had no effect on model-based control or on model-free ('habitual') control compared to Sham stimulation. These null effects are substantiated by a power analysis, which suggests that our study had at least 60% power to detect a true effect, and by a Bayesian model comparison, which favors a model of the data that assumes stimulation had no effect over models that assume stimulation had an effect on behavioral control. Although we cannot entirely exclude more trivial explanations for our null effect, for example related to (faults in) our experimental setup, these data suggest that anodal transcranial direct current stimulation over right dorsolateral prefrontal cortex does not improve model-based control, despite existing evidence that transcranial magnetic stimulation can disrupt such control in the same brain region

ronimaimon/rsatoolbox: RSA with FSL

First RSA code using data from FS

Regressors in the null model which contains the same MB and MF regressors for the Active and Sham stimulation conditions.

<p>MF = model-free; MB = model-based; SE = standard error. Lag denotes the effect of time. Bold-face indicates p<.05 uncorrected for multiple comparisons.</p

Contrasts performed on the full model.

<p>MF = model-free; MB = model-based; SE = standard error; χ² = chi-square distribution; df = degrees of freedom; Lag denotes the effect of time. Bold-face indicates p<.05 uncorrected for multiple comparisons.</p