NeuroImage
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Wallerian degeneration of the corticospinal tract (CST) after motor pathway ischemic stroke can be characterized by diffusion tensor imaging (DTI). However, the dynamic evolution of the diffusion indices in the degenerated CST has not previously been completely identified. We investigated this dynamic evolution and the relationship between early changes of the diffusion indices in the degenerated CST and long-term clinical outcomes. ⋯ The rlambda(23) increased during the first 3 months and then stabilized. We also found that the changes in the rFA between the first 2 time points were correlated with the NIHSS (P=0.00003) and the Motricity Indices (P=0.0004) after 1 year. Our results suggest that for patients with motor pathway stroke the diffusion indices in the degenerated CST stabilize within 3 months and that early changes in the rFA of the CST may predict long-term clinical outcomes.
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For efficient and fast encoding of our complex acoustic environment, not only aspects of bottom-up processing are significant, but rather top-down influences such as attention, memory, and anticipation promote specific behavior and perception. Neural oscillatory activity in the gamma-range (30-80 Hz) is discussed as a conceivable candidate to represent very rapid modulations of top-down factors. We investigated effects of anticipation on early gamma-band responses (GBRs) of the EEG and event-related potentials (ERPs) in response to tone sequences. ⋯ The early phase-locked portion of the gamma-band activity was significantly increased when tones were in line with the good continuation of sequences compared to deviant tones. Further, a pronounced early negative ERP response, starting at 150 ms, was elicited by deviant tones at the third and fifth position. Our results support the notion that gamma-band oscillations reflect perceptual grouping processes of concurrent sounds and anticipatory top-down modulation, which involves some of the first stages of auditory information processing.
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Magnetic resonance parameters, such as longitudinal (T1) and transverse (T2) relaxation times and proton density (PD) provide intrinsic information about the human brain. In vivo quantification of these parameters may enable detection of subtle regional grey matter (GM) or white matter (WM) differences and permit neurological disease detection and monitoring. The aims of the study were to quantify T1, T2 and PD values in all cortical gray matter regions for a group of healthy volunteers scanned at 1.5 T and to cluster regions showing statistically distinguishable tissue characteristics. ⋯ Correspondence analysis (CA) and hierarchical clustering (HC) were combined and applied to averaged T1, T2 and PD values within each VOI in order to identify groups of anatomical structures that are related statistically. Interestingly, except for one structure, all VOIs were grouped with left-right symmetry and showed an interesting pattern: the four lobes (frontal, occipital, parietal and temporal) were roughly clustered and the precentral and postcentral gyri were merged together. Our study shows that CA and HC analysis of MRI relaxation parameters and proton density can be used for cortical clustering of atlas-defined cortical regions.
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The neural underpinnings of major depressive disorder (MDD) are unknown but there is evidence for structural alteration in the hippocampus that may become more pronounced over the course of illness. The aim of the present study was to examine metabolite levels of N-acetyl-aspartate (NAA), Myo-inositol (MI), Glutamate-glutamine (Glx) and choline-containing compounds (GPC and GPC+PCh) in patients presenting for first treatment of a depressive episode compared to those with multiple past episodes and age and sex matched controls. ⋯ The group presenting for first treatment had only increases in MI levels compared with matched controls. These results suggest that abnormal membrane turnover in the hippocampus is greater in patients with highly recurrent illness, and provide support for the hypothesis that there are neuronal changes in this region over the course of illness.
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Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. ⋯ Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions--for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil.