An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

TL;DR: Early cross‐sensory activations and audiovisual interactions at the visual and auditory cortices are reported using magnetoencephalography (MEG) to obtain accurate timing information and it is suggested that the origins of the cross-sensing activations may be in the primary sensory cortices of the opposite modality.

TL;DR: Visual rating assessment of the MTL gave similar prediction accuracy to multivariate classification and manual hippocampal volumes, suggesting a potential future role for computerized methods as a complement to clinical assessment of AD.

TL;DR: In this paper, the authors used weighted stochastic block models to uncover the meso-scale architecture of the human connectome and found that while many communities are assortative, others form core-periphery and disassortative structures.

TL;DR: This work compared ADNI's MCI classifications to the neuropsychological approach, which more broadly assesses cognitive abilities, and found that the latter is more accurate and accurate than the former.

TL;DR: An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute was performed and it is believed that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain.

TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.

TL;DR: In this article, the authors propose three basic concepts: devising the items, selecting the items and selecting the responses, from items to scales, reliability and validity of the responses.