NeuroImage
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Comparative Study
Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares.
Brain imaging is increasingly recognised as an intermediate phenotype to understand the complex path between genetics and behavioural or clinical phenotypes. In this context, a first goal is to propose methods to identify the part of genetic variability that explains some neuroimaging variability. Classical univariate approaches often ignore the potential joint effects that may exist between genes or the potential covariations between brain regions. ⋯ We estimate the generalisability of the multivariate association with a cross-validation scheme and demonstrate the significance of this link, using a permutation procedure. Univariate selection appears to be necessary to reduce the dimensionality. However, the significant association uncovered by this two-step approach combining univariate filtering and L1-regularised PLS suggests that discovering meaningful genetic associations calls for a multivariate approach.
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Myelin water imaging, a magnetic resonance imaging technique capable of resolving the fraction of water molecules which are located between the layers of myelin, is a valuable tool for investigating both normal and pathological brain structure in vivo. There is a strong need for pulse sequences which improve the quality and applicability of myelin water imaging in a clinical setting. ⋯ Region of interest analysis indicates that this fast GRASE imaging sequence produces results which are in good agreement with pure spin echo measurements (R(2)=0.95, p<0.0001). This drastic improvement in speed and brain coverage compared to current spin echo standards will allow increased inclusion of myelin water imaging in neurological research protocols and opens up the possibility of applications in a clinical setting.
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The brain is organized into a set of widely distributed networks. Therefore, although structural damage from stroke is focal, remote dysfunction can occur in regions connected to the area of lesion. Historically, neuroscience has focused on local processing due in part to the absence of tools to study the function of distributed networks. ⋯ Early results suggest that disruption of inter-hemispheric connectivity in the somatomotor network and the dorsal attention network is more strongly associated with behavioral impairment in those domains than is intra-hemispheric connectivity within either the lesioned or unaffected hemisphere. We also observe in the somatomotor network an interesting interaction between corticospinal tract damage and decreased inter-hemispheric connectivity that suggests that both processes combine to contribute to neuromotor impairment after stroke. A connectivity-based approach will provide greater insight into network reorganization in the acute and chronic phases after stroke and will contribute to improving prognostic ability and the development of therapeutic interventions.