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Thus, WMTI model metrics are shown to be promising candidates as sensitive biomarkers of demyelination.<br />Limited information exists regarding the association between midlife lipid levels and late-life total and regional brain volumes.<br />We studied 1872 participants in the longitudinal community-based Atherosclerosis Risk in Communities Neurocognitive Study. Serum lipid levels were measured in 1987-1989 (mean age, 53±5 years). Participants underwent 3T brain MRI scans in 2011-2013. Brain volumes were measured using FreeSurfer image analysis software. Linear regression models were used to assess the associations between serum lipids and brain volumes modeled in standard deviation (SD) units, adjusting for potential confounders.<br />In adjusted analyses, one SD higher low-density lipoprotein cholesterol (LDL) levels were associated with larger total brain volumes (β 0.033, 95% CI 0.006-0.060) as well as larger volumes of the temporal (β 0.038, 95% CI 0.003-0.074) and parietal lobes (β 0.044, 95% CI 0.009-0.07) and Alzheimer disease-related region (β 0.048, 95% CI 0.048-0.085). Higher triglyceride levels were associated with smaller total brain volumes (β -0.033, 95% CI -0.060, -0.007). The associations between LDL levels and brain volumes were modified by age (P for interaction &lt;0.001), with higher LDL levels associated with larger total and regional brain volumes only among adults &gt;53 years at baseline, and were attenuated after application of weights to account for informative attrition, although associations with the parietal and Alzheimer's disease-related region remained significant. [https://www.selleckchem.com/products/sis17.html see more] High-density lipoprotein cholesterol was not associated with brain volumes.<br />Higher LDL levels in late midlife were associated with larger brain volumes later in life, while higher triglyceride levels were associated with smaller brain volumes. These associations were driven by adults &gt;53 years at baseline.<br />53 years at baseline.Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.Modern neuroimaging represents three-dimensional brain activity, which varies across brain regions. It remains unknown whether activity of different brain regions has similar spatial organization to reflect similar cognitive processes. We developed a rotational cross-correlation method allowing a straightforward analysis of spatial activity patterns distributed across the brain in stimulation specific contrast images. Results of this method were verified using several statistical approaches on real and simulated random datasets. We found, for example, that the seed patterns in the fusiform face area were robustly correlated to brain regions involved in face-specific representations. These regions differed from the non-specific visual network meaning that activity structure in the brain is locally preserved in stimulus-specific regions. Our findings indicate spatially correlated perceptual representations in cerebral activity and suggest that the 3D coding of the processed information is organized using locally preserved activity patterns across the brain. More generally, our results demonstrate that information is represented and shared in the local spatial configurations of brain activity.Divergent thinking tests have been used extensively in neuroscientific studies of creativity. However, output from tests of divergent thinking can be scored in different ways, and those scores can influence assessments of divergent thinking performance and its relationship with brain activation. Here we sought to investigate the relationship between various methods of scoring the Alternate Uses Task (AUT)-a well-known test of divergent thinking-and regional grey matter volume (GMV) using voxel-based morphometry (VBM). We assessed AUT performance based on (a) traditional approaches that involve scoring participants' output on fluency, flexibility, originality, and elaboration, (b) a subjective approach that involves scoring output directly on "snapshot" creativity, and (c) the definitional approach that involves scoring output separately on novelty and usefulness-the two criteria deemed necessary and jointly sufficient to categorize an idea as creative. Correcting for age, sex, intracranial volume, verbal IQ and working memory capacity, we found negative correlations between regional GMV in the left inferior temporal gyrus (ITG) and novelty and usefulness scores, but no correlation involving other scoring approaches. As part of the brain's core semantic system, this region is involved in concept retrieval and integration. We discuss the implications of these findings for our understanding of the neural bases of divergent thinking, and how ITG could be related to the generation of novel and useful responses.<br />Golden-angle single-shot PROPLLER (GA-SS-PROP) is proposed to accelerate the PROPELLER acquisition for distortion-free diffusion-weighted (DW) imaging. Acceleration is achieved by acquiring one-shot per b-value and several b-values can be acquired along a diffusion direction, where the DW signal follows a bi-exponential decay (i.e. IVIM). Sparse reconstruction is used to reconstruct full resolution DW images. Consequently, apparent diffusion coefficient (ADC) map and IVIM maps (i.e., perfusion fraction (f) and the perfusion-free diffusion coefficient (D)) are obtained simultaneously. The performance of GA-SS-PROP was demonstrated with simulation and human experiments.<br />A realistic numerical phantom of high-quality diffusion images of the brain was developed. The error of the reconstructed DW images and quantitative maps were compared to the ground truth. The pulse sequence was developed to acquire human brain data. For comparison, fully sampled PROPELLER and conventional single-shot echo planar imaging (SS-EPI) acquisitions were performed.