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We wished to contrast cortical activation during hand movements in profoundly weak patients with motor neuropathy and in normal controls using a paradigm that is behaviourally matched between the two groups. Previous work has suggested that a passive movement task could be appropriate. Using functional magnetic resonance imaging (fMRI), we first characterised patterns of brain activation during active and passive index finger movements in healthy controls (n=10). Although the relative activation differences were highly variable, there was a trend for the mean number of significantly activated voxels in the primary motor cortex contralateral to the hand moved (CMC) to be lower for the passive than for the active task (40% relative decrease, P=0.09). There was a small posterior shift in the centre of mass of the CMC (mean, 8 mm, P<0.02) and of the ipsilateral sensorimotor cortex (IMC) (mean, 11 mm, P<0.05). No activation with passive movement was found in the patients with severe distal sensory neuropathy (n=2), suggesting that activation with passive movements is dependent on sensory feedback and unlikely to be due to mental imagery alone. In contrast, patients with severe pure motor neuropathies (MN, n=2) showed substantial increases in the volumes of activation compared to controls. The relative increases in numbers of voxels activated above threshold in different regions of interest for both the active (MN/controls: CMC, 2.1; IMC, 8.1; supplementary motor area [SMA], 5.2) and passive (CMC, 2.6; IMC, 8.0; SMA, 5.1) tasks were similar. These results confirm expansion of cortical representation for finger movement in patients with motor neuropathy and demonstrate central reorganisation as a consequence of the motor nerve loss. An expanded representation for finger movement in the primary motor cortex with peripheral weakness suggests the possibility that the primary motor cortex may encode motor unit activation rather directly. [ABSTRACT FROM AUTHOR]

Abstract: The medial geniculate body (MGB) of the thalamus is a key component of the auditory system. It is involved in relaying and transforming auditory information to the cortex and in top-down modulation of processing in the midbrain, brainstem, and ear. Functional imaging investigations of this region in humans, however, have been limited by the difficulty of distinguishing MGB from other thalamic nuclei. Here, we introduce two methods for reliably delineating MGB anatomically in individuals based on conventional and diffusion MRI data. The first uses high-resolution proton density weighted scanning optimized for subcortical grey–white contrast. The second uses diffusion-weighted imaging and probabilistic tractography to automatically segment the medial and lateral geniculate nuclei from surrounding structures based on their distinctive patterns of connectivity to the rest of the brain. Both methods produce highly replicable results that are consistent with published atlases. Importantly, both methods rely on commonly available imaging sequences and standard hardware, a significant advantage over previously described approaches. In addition to providing useful approaches for identifying the MGB and LGN in vivo, our study offers further validation of diffusion tractography for the parcellation of grey matter regions on the basis of their connectivity patterns. [Copyright &y& Elsevier]

Abstract: Functional magnetic resonance imaging (fMRI) studies of the human brain have suggested that low-frequency fluctuations in resting fMRI data collected using blood oxygen level dependent (BOLD) contrast correspond to functionally relevant resting state networks (RSNs). Whether the fluctuations of resting fMRI signal in RSNs are a direct consequence of neocortical neuronal activity or are low-frequency artifacts due to other physiological processes (e.g., autonomically driven fluctuations in cerebral blood flow) is uncertain. In order to investigate further these fluctuations, we have characterized their spatial and temporal properties using probabilistic independent component analysis (PICA), a robust approach to RSN identification. Here, we provide evidence that: i. RSNs are not caused by signal artifacts due to low sampling rate (aliasing); ii. they are localized primarily to the cerebral cortex; iii. similar RSNs also can be identified in perfusion fMRI data; and iv. at least 5 distinct RSN patterns are reproducible across different subjects. The RSNs appear to reflect “default” interactions related to functional networks related to those recruited by specific types of cognitive processes. RSNs are a major source of non-modeled signal in BOLD fMRI data, so a full understanding of their dynamics will improve the interpretation of functional brain imaging studies more generally. Because RSNs reflect interactions in cognitively relevant functional networks, they offer a new approach to the characterization of state changes with pathology and the effects of drugs. [Copyright &y& Elsevier]

Cortical grey matter (cGM) develops a substantial burden of pathology in multiple sclerosis (MS). Previous cross-sectional studies have suggested a relationship between measures of cortical atrophy and disability. Our objective was to develop a method for automatically measuring the apparent cGM thickness as well as the integrity of the interface between cGM and subcortical white matter (GM/WM) both globally and regionally on T1-weighted MRI, and use this method in a longitudinal investigation of how these measures differed between patients with stable MS and patients with progressing disability. Measurements were made over the whole brain and for anatomically specified cortical regions, both cross-sectionally at baseline and longitudinally on two MRI scans performed on average 1 year apart. We found a higher average rate of apparent loss of cGM thickness across the whole brain in the group that progressed over the interscan interval compared to the group that remained stable (progressing = −3.13 ± 2.88%/year, stable = 0.06 ± 2.31%/year, P = 0.002). This difference was detected with regional measures in parietal and precentral cortex. In contrast, change in the GM/WM interface integrity did not show detectable regional differences, although the group of MS patients whose disability progressed showed a significant decrease in GM/WM interface integrity compared to the stable group (P = 0.003). Regional measures of apparent loss of cGM thickness enhance sensitivity to cortical pathological changes. A measure of integrity offers a new index of disease-associated cortical changes at the GM/WM interface. The results suggest that progression of disability in MS is associated with the progression of MRI-detectable cortical pathology. [Copyright &y& Elsevier]

While a detailed understanding of brain activity with hand movements has developed, less is known about the functional anatomy of motor control for foot movements. Here we have used fMRI to define brain activity associated with unilateral foot extension and flexion, component movements of gait. We studied brain responses to visually cued active and passive movements and periods of either preparation (before active movement) or anticipation (before passive movement) with a pseudo-randomized block design. A mixed-effects (n = 12) contrast of the active movement condition vs. rest identified brain activation in regions including the medial wall of the primary sensorimotor cortex, consistent with expected somatotopy. Medial wall activation during passive movement vs. rest was less intense and localized to the same region. Frontal and association cortices were more active during preparation or anticipation periods than during the movements themselves. A contrast of preparation to move vs. active movement showed significant activation in the medial frontal and frontopolar gyri and the precuneus. Contrast of the anticipation of movement with the passive movement condition revealed activation in the dorsal premotor cortex and precuneus. Our study thus provides evidence for somatotopy in multiple functional regions in the motor control network. The anterior prefrontal activity is involved in the preparation for cued movement with distinct regions of the medial motor cortex (including SMA and CMA) preferentially involved in motor program planning and execution. This direct characterization of brain activation patterns associated with foot movements promises use of fMRI for the functional analysis of pathologies of gait. [Copyright &y& Elsevier]