The lesion method has been important for understanding brain-behavior relationships in humans, but has previously used maps based on structural damage. Lesion measurement based on structural damage may label partly damaged but functional tissue as abnormal, and moreover, ignores distant dysfunction in structurally intact tissue caused by deafferentation, diaschisis, and other processes. A reliable method to map functional integrity of tissue throughout the brain would provide a valuable new approach to measuring lesions. Here, we use machine learning on four dimensional resting state fMRI data obtained from left-hemisphere stroke survivors in the chronic period of recovery and control subjects to generate graded maps of functional anomaly throughout the brain in individual patients. These functional anomaly maps identify areas of obvious structural lesions and are stable across multiple measurements taken months and even years apart. Moreover, the maps identify functionally anomalous regions in structurally intact tissue, providing a direct measure of remote effects of lesions on the function of distant brain structures. Multivariate lesion-behavior mapping using functional anomaly maps replicates classic behavioral localization, identifying inferior frontal regions related to speech fluency, lateral temporal regions related to auditory comprehension, parietal regions related to phonology, and the hand area of motor cortex and descending corticospinal pathways for hand motor function. Further, this approach identifies relationships between tissue function and behavior distant from the structural lesions, including right premotor dysfunction related to ipsilateral hand movement, and right cerebellar regions known to contribute to speech fluency. Brain-wide maps of the functional effects of focal lesions could have wide implications for lesion-behavior association studies and studies of recovery after brain injury. Declining auditory spatial processing is hypothesized to contribute to the difficulty older adults have detecting, locating, and selecting a talker from among others in noisy listening environments. Though auditory spatial processing has been associated with several cortical structures, little is known regarding the underlying white matter architecture or how age-related changes in white matter microstructure may affect it. The arcuate fasciculus is a target for understanding age-related differences in auditory spatial attention based on normative spatial attention findings in humans. Similarly, animal and human clinical studies suggest that the corpus callosum plays a role in the cross-hemispheric integration of auditory spatial information important for spatial localization and attention. The current investigation used diffusion imaging to examine the extent to which age-group differences in the identification of spatially cued speech were accounted for by individual differences in the white matter microstructure of the right arcuate fasciculus and the corpus callosum. Higher right arcuate and callosal fractional anisotropy (FA) predicted better segregation and identification of spatially cued speech across younger and older listeners. Further, individual differences in callosal microstructure mediated age-group differences in auditory spatial processing. Follow-up analyses suggested that callosal tracts connecting left and right pre-frontal and posterior parietal cortex are particularly important for auditory spatial processing. The results are consistent with previous work in animals and clinical human samples and provide a cortical mechanism to account for age-related deficits in auditory spatial processing. Further, the results suggest that both intrahemispheric and interhemispheric mechanisms are involved in auditory spatial processing. https://www.selleckchem.com/products/triapine.html The hippocampus is a brain region critical for learning and memory, and is also implicated in several neuropsychiatric disorders that show sex differences in prevalence, symptom expression, and mean age of onset. On average, males have larger hippocampal volumes than females, but findings are inconclusive after adjusting for overall brain size. Although the hippocampus is a heterogenous structure, few studies have focused on sex differences in the hippocampal subfields - with little consensus on whether there are regionally specific sex differences in the hippocampus after adjusting for brain size, or whether it is important to adjust for total hippocampal volume (HPV). Here, using two young adult cohorts from the Queensland Twin IMaging study (QTIM; N ​= ​727) and the Human Connectome Project (HCP; N ​= ​960), we examined differences between males and females in the volumes of 12 hippocampal subfields, extracted using FreeSurfer 6.0. After adjusting the subfield volumes for either HPV or brain size (brain se of differences in HPV, there are regionally specific sex differences in the hippocampus, which may be most prominent in the fimbria and parasubiculum. Further, given sex differences were less consistent across cohorts after controlling for BSV, adjusting for HPV rather than BSV may benefit future studies. This work may help in disentangling sex effects, and provide a better understanding of the implications of sex differences for behaviour and neuropsychiatric disorders. The C56R mutation associated with factor XI deficiency has been first evidenced in individuals from the French Basque Country. Genetic investigations revealed that this mutation occurred about 5400 years ago as a founder effect in this zone. Other cases were subsequently described in Southwestern Europe. Noticeably a cluster of cases was evidenced in Yecla, a small city from the province of Murcia, in Southeastern Spain. In correlation with historical sources our genetic data and surname analysis argue for associating this mutation with the migration of people from Western Pyrenees (and more probably from the Navarra province) toward Southeastern Spain during the Reconquista period. BACKGROUND AND OBJECTIVE Brain-computer interfaces (BCI) have started to be used with the development of computer technology in order to enable individuals who are in this situation to communicate with their environment or move. This study focused on the spelling system that transforms the brain activities obtained with EEG signals into writing. In BCI systems working with P300 obtained from 64 electrodes, data recording and processing cause high cost and high processing load. By reducing the number of electrodes used, the physical dimensions, costs, and processing loads of the systems can be reduced. The main problem at this stage is to determine which electrodes are more effective. Randomness-based optimization methods perform their experiments within the framework of a specific fitness function, resulting in near-best results rather than the best result. The electrodes chosen as a result of the study are expected to contribute positively to the classifier performance. At the same time, an unbalanced data set is balanced, and an increase in system performance is expected.