Neuroscience
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Focal Cortical Dysplasia (FCD) & Mesial Temporal Lobe Epilepsy-Hippocampal Sclerosis (MTLE-HS) are two common pathologies of drug-resistant focal epilepsy (DRE). Inappropriate localization of the epileptogenic zones (EZs) in FCD is a significant contributing factor to the unsatisfactory surgical results observed in FCD cases. Currently, no molecular or cellular indicators are available which can aid in identifying the epileptogenic zones (EZs) in FCD. ⋯ These findings suggest that employing distinct lipid mass spectra could be an effective method for identifying the EZs in FCD. The unique lipid mass spectra of cortical tissues from patients with FCD can be utilized for real-time surgical guidance. Additionally, the plasma triglyceride (TAG) level has the potential to act as a biomarker once validated on a larger cohort.
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Media multitasking has become pervasive in our daily lives, yet its impact on cognitive abilities remains contentious, with more evidence supporting adverse effects (scattered attention hypothesis) than benefits (trained attention hypothesis). Recent studies have increasingly focused on the training effects of behavioral training on anticipatory brain functions, which involve cognitive and motor preparation before stimulus onset, assessed using event-related potentials (ERPs). This study investigated whether media multitasking enhances anticipatory brain functions and how task difficulty influences this relationship. ⋯ Our results suggest that HMM can flexibly adjust resource allocation based on task demands to maintain their response speed advantage. These findings suggest that LMM may possess a relatively steady acceleration/brake system, whereas HMM exhibit a more adaptable system capable of responding flexibly to diverse situations. Overall, these results underscore the training effects of media multitasking on anticipatory brain functions, supporting the trained attention hypothesis.
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The optimal stimulation frequency for inducing neuromodulatory effects remains unclear. The purpose of our study was to investigate the effect of neuromuscular electrical stimulation (NMES) with different frequencies on cortical and spinal excitability. Thirteen able-bodied individuals participated in the experiment involving NMES: (i) low-frequency at 25 Hz, (ii) high-frequency at 100 Hz, and (iii) mixed-frequency at 25 and 100 Hz switched every one second. ⋯ Our results showed that mixed frequency was most effective in modulating corticospinal excitability, although motor performance was not affected by any intervention. The cortical silent period was prolonged and Mmax was inhibited by all frequencies, while the F-wave and MVC were unaffected. Mixed-frequency stimulation could recruit a more diverse range of motor units, which are recruited in a stimulus frequency-specific manner, than single-frequency stimulation, and thus may have affected corticospinal facilitation.
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The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such as dataset limitations and clinical variability. Resting-state functional magnetic resonance imaging (Rs-fMRI) can reflect the fluctuation data of brain activity in a resting state, which can find the interrelationships, functional connections, and network characteristics among brain regions of the patients. In this paper, a brain functional connectivity matrix is constructed using Pearson correlation based on the characteristics of multi-site Rs-fMRI data and brain atlas, and an adaptive propagation operator graph convolutional network (APO-GCN) model is designed. ⋯ The experimental results on Rs-fMRI data from 1601 participants (830 MDD and 771 HC) and 16 sites of REST-meta-MDD project show that the APO-GCN achieved a classification accuracy of 91.8%, outperforming those of the state-of-the-art classifier methods. The classification process is driven by multiple significant brain regions, and our method further reveals functional connectivity abnormalities between these brain regions, which are important biomarkers of classification. It is worth noting that the brain regions identified by the classifier and the networks involved are consistent with existing research results, which suggest that the pathogenesis of depression may be related to dysfunction of multiple brain networks.
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We used the framework of the uncontrolled manifold (UCM) hypothesis to explore the origin of inter-trial variance within the UCM, which by definition does not affect the salient performance variable, during accurate two-finger force production. Specifically, we tested several hypotheses on two main sources of variance within the UCM, variability in the sharing patterns between the fingers across trials and covaried variability in finger forces within individual trials. We also explored effects on unintentional changes in the structure of variance during preparation for a quick force change and during force drift without visual feedback. ⋯ Changing the initial magnitude of variance along the UCM was reflected in its magnitude during anticipatory synergy adjustments prior to the force pulse and following the unintentional force drift. We interpret the results assuming a hierarchical control with two commands, reciprocal and coactivation. The results support the scheme with two contributing factors to variance along the UCM, likely associated with feed-forward and feedback mechanisms.