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Objective: Vibratory sensation is a quantifiable measure of physical dysfunction and is often related to spinal cord pathology; however, its association with relevant brain areas has not been fully explored. Our objective was to establish a cortical structural substrate for vibration sensation. Methods: Eighty‐four individuals with multiple sclerosis (MS) (n = 54 relapsing, n = 30 progressive) and 28 controls participated in vibratory sensation threshold quantification at the great toe and a 3T MRI evaluating volume of the thalamus and cortical thickness primary and secondary sensory cortices. Results: After controlling for age, sex, and disability level, vibratory sensation thresholds were significantly related to cortical thickness of the anterior cingulate (P = 0.041), parietal operculum (P = 0.022), and inferior frontal gyrus pars operculum (P = 0.044), pars orbitalis (P = 0.007), and pars triangularis (P = 0.029). Within the progressive disease subtype, there were significant relationships between vibratory sensation and thalamic volume (P = 0.039) as well as reduced inferior frontal gyrus pars operculum (P = 0.014) and pars orbitalis (P = 0.005) cortical thickness. Conclusions: The data show significant independent relationships between quantitative vibratory sensation and measures of primary and secondary sensory cortices. Quantitative clinical measurement of vibratory sensation reflects pathological changes in spatially distinct brain areas and may supplement information captured by brain atrophy measures. Without overt relapses, monitoring decline in progressive forms of MS has proved challenging; quantitative clinical assessment may provide a tool to examine pathological decline in this cohort. These data suggest that quantitative clinical assessment may be a reliable way to examine pathological decline and have broader relevance to progressive forms of MS. [ABSTRACT FROM AUTHOR]

Objective The aim of this study is to evaluate the correlation between resting state functional MRI (RS-fMRI) activity and motor and cognitive impairment in spinocerebellar ataxia type 6 (SCA6). Methods Twelve patients with genetically confirmed SCA6 and 14 age matched healthy controls were imaged with RS-fMRI. Whole brain gray matter was automatically parcellated into 1000 regions of interest (ROIs). For each ROI, the first eigenvariate of voxel time courses was extracted. For each patient, Pearson correlation coefficients between each pair of ROI time courses were calculated across the 1000 ROIs. The set of average control correlation coefficients were fed as an undirected weighted adjacency matrix into the Rubinov and Sporns (2010) modularity algorithm. The intranetwork global efficiency of the thresholded adjacency sub-matrix was calculated and correlated with ataxia scores and cognitive performance. Results SCA6 patients showed mild cognitive impairments in executive function and visual-motor processing compared to control subjects. These neuropsychological impairments were correlated with decreased RS functional connectivity (FC) in the attention network. Conclusions Mild cognitive executive functions and visual-motor coordination impairments seen in SCA6 patients correlate with decreased resting-state connectivity in the attention network, suggesting a possible metric for the study of cognitive dysfunction in cerebellar disease. Hum Brain Mapp 38:3001-3010, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Cortical atrophy has been reported in a number of diseases, such as multiple sclerosis and Alzheimer's disease, that are also associated with white matter (WM) lesions. However, most cortical reconstruction techniques do not account for these pathologies, thereby requiring additional processing to correct for the effect of WM lesions. In this work, we introduce CRUISE+, an automated process for cortical reconstruction from magnetic resonance brain images with WM lesions. The process extends previously well validated methods to allow for multichannel input images and to accommodate for the presence of WM lesions. We provide new validation data and tools for measuring the accuracy of cortical reconstruction methods on healthy brains as well as brains with multiple sclerosis lesions. Using this data, we validate the accuracy of CRUISE+ and compare it to another state-of-the-art cortical reconstruction tool. Our results demonstrate that CRUISE+ has superior performance in the cortical regions near WM lesions, and similar performance in other regions. Hum Brain Mapp 35:3385-3401, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Examination of associations between specific disorders and physical properties of functionally relevant frontal lobe sub-regions is a fundamental goal in neuropsychiatry. Here, we present and evaluate automated methods of frontal lobe parcellation with the programs FreeSurfer(FS) and TOADS-CRUISE(T-C), based on the manual method described in Ranta et al. [2009]: Psychiatry Res 172:147-154 in which sulcal-gyral landmarks were used to manually delimit functionally relevant regions within the frontal lobe: i.e., primary motor cortex, anterior cingulate, deep white matter, premotor cortex regions (supplementary motor complex, frontal eye field, and lateral premotor cortex) and prefrontal cortex (PFC) regions (medial PFC, dorsolateral PFC, inferior PFC, lateral orbitofrontal cortex [OFC] and medial OFC). Dice's coefficient, a measure of overlap, and percent volume difference were used to measure the reliability between manual and automated delineations for each frontal lobe region. For FS, mean Dice's coefficient for all regions was 0.75 and percent volume difference was 21.2%. For T-C the mean Dice's coefficient was 0.77 and the mean percent volume difference for all regions was 20.2%. These results, along with a high degree of agreement between the two automated methods (mean Dice's coefficient = 0.81, percent volume difference = 12.4%) and a proof-of-principle group difference analysis that highlights the consistency and sensitivity of the automated methods, indicate that the automated methods are valid techniques for parcellation of the frontal lobe into functionally relevant sub-regions. Thus, the methodology has the potential to increase efficiency, statistical power and reproducibility for population analyses of neuropsychiatric disorders with hypothesized frontal lobe contributions. Hum Brain Mapp 35:2009-2026, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]