Increased lower alpha power in the TPJ was further associated with worse results on verbal and spatial working memory tests, whereas an increased lower/upper alpha power ratio was associated with slower information processing speed.  https://www.selleckchem.com/products/zongertinib.html  In conclusion, multiple sclerosis patients with increased brain atrophy, lesion and thalamic volumes demonstrated increased lower alpha power in the TPJ and reduced cognitive abilities.The role of white matter pathways in cognition is a topic of active investigation that is vital to both the fields of clinical neurology and cognitive neuroscience. White matter pathways provide critical connectivity amongst numerous specialized brain regions thereby enabling higher level cognition. While the effects of dissections and lesions of the corpus callosum have been reported, it is less understood how unilateral focal white matter lesions may impact cognitive processes. Here, we report a unique case study in which a small left lateralized stroke in the white matter adjacent to the body of the corpus callosum selectively impaired the ability to name letters and numbers presented to the ipsilesional, left hand. Naming of letters, numbers and objects was tested in both the visual and tactile modalities in both hands. Diffusion-weighted imaging showed a marked reduction in white matter pathway integrity through the body of the corpus callosum. Clinically, this case highlights the significant impact that a focal white matter lesion can have on higher-level cognition, specifically the integration of verbal and tactile information. Moreover, this case adds to prior reports on tactile agnosia by including DTI imaging data and emphasizing the role that white matter pathways through the body of the corpus callosum play in integrating tactile input from the right hemisphere with verbal naming capabilities of the left hemisphere. Finally, the findings also provoke fresh insight into alternative strategies for rehabilitating cognitive functioning when structural connectivity may be compromised.Although the mechanisms responsible for migraine initiation remain unknown, recent evidence shows that brain function is different immediately preceding a migraine. This is consistent with the idea that altered brain function, particularly in brainstem sites, may either trigger a migraine or facilitate a peripheral trigger that activates the brain, resulting in pain. The aim of this longitudinal study is therefore to expand on the above findings, and to determine if brainstem function oscillates over a migraine cycle in individual subjects. We performed resting state functional magnetic resonance imaging in three migraineurs and five controls each weekday for four weeks. We found that although resting activity variability was similar in controls and interictal migraineurs, brainstem variability increased dramatically during the 24-hour period preceding a migraine. This increase occurred in brainstem areas in which orofacial afferents terminate the spinal trigeminal nucleus and dorsal pons. These increases were characterized by increased power at infra-slow frequencies, principally between 0.03 and 0.06 Hz. Furthermore, these power increases were associated with increased regional homogeneity, a measure of local signal coherence. The results show within-individual alterations in brain activity immediately preceding migraine onset and support the hypothesis that altered regional brainstem function before a migraine attack is involved in underlying migraine neurobiology.Behavioral variant frontotemporal degeneration (bvFTD) is clinically characterized by progressive decline in social and executive domains. Previous work suggests that early lifestyle factors such as education and occupational attainment may relate to structural integrity and moderate the rate of cognitive decline in bvFTD, but the role of other cognitively stimulating activities is understudied. We sought to investigate the effect of such activities on cortical thickness (CT) in bvFTD. bvFTD patients (n = 31) completed a baseline MRI scan, and informants for the patients completed the Lifetime of Experiences Questionnaire (LEQ), which measures specific activities considered to be undertaken primarily within one particular life phase, such as education (young-life), occupation (mid-life), and social/leisure activity (late-life). At baseline, linear models assessed the effect of LEQ scores from each life phase on regional CT. A subset (n = 19) of patients completed longitudinal MRI, and to evaluate the association of LEQ with longitudinal rates of CT decline, we derived individualized slopes of decline using linear mixed effects models and these were related to LEQ scores from each life phase. At baseline, a higher late-life LEQ score was associated with less atrophy in left superior and inferior anterior temporal regions as well as right middle temporal gyrus. Longitudinally, we observed that higher late-life LEQ scores were associated with an attenuated rate of CT loss in insular cortex. Late-life LEQ score was positively associated with both relatively preserved CT early in bvFTD and a slower rate of cortical loss in regions important for social functioning. These findings suggest that social and leisure activities may contribute to a form of resilience against pathologic effects of disease.
  Automatic screening tools can be applied to detect cardiovascular diseases (CVDs), which are the leading cause of death worldwide. As an effective and non-invasive method, electrocardiogram (ECG) based approaches are widely used to identify CVDs. Hence, this paper proposes a deep convolutional neural network (CNN) to classify five CVDs using standard 12-lead ECG signals.
 
  The Physiobank (PTB) ECG database is used in this study. Firstly, ECG signals are segmented into different intervals (one-second, two-seconds and three-seconds), without any wave detection, and three datasets are obtained. Secondly, as an alternative to any complex preprocessing, durations of raw ECG signals have been considered as input with simple min-max normalization. Lastly, a ten-fold cross-validation method is employed for one-second ECG signals and also tested on other two datasets (two-seconds and three-seconds).
 
  Comparing to the competing approaches, the proposed CNN acquires the highest performance, having an accuracy, sensitivity, and specificity of 99.