Notes

Extreme O-GlcNAcylation Will cause Heart Failing and also Sudden Death.
Interestingly, high and low-frequency bands behaved in an opposite manner as a function of condition. We also found significant band*condition interactive effects in clustering coefficient, efficiency and strength both on local and global scales.Early diagnosis of mild traumatic brain injury (mTBI) is of great interest to the neuroscience and medical communities. Widefield optical imaging of neuronal populations over the cerebral cortex in animals provides a unique opportunity to study injury-induced alternations in brain function. Using this technique, along with deep learning, the goal of this paper is to develop a framework for the detection of mTBI. Cortical activities in transgenic calcium reporter mice expressing GCaMP6s are obtained using widefield imaging from 8 mice before and after inducing an injury. MIRA-1 mouse Two deep learning models for differentiating mTBI from normal conditions are proposed. One model is based on the convolutional neural network-long short term memory (CNN-LSTM), and the second model is based on a 3D-convolutional neural network (3D-CNN). These two models offer the ability to capture features both in the spatial and temporal domains. Results for the average classification accuracy for the CNN-LSTM and the 3D-CNN are 97.24% and 91.34%, respectively. These results are notably higher than the case of using the classical machine learning methods, demonstrating the importance of utilizing both the spatial and temporal information for early detection of mTBI.Multisensory stimulation plays an important role in the recovery of ischemic stroke. However, little is known about the interactions between neuronal activities with multi-afferent stimulations and their effects on hemodynamic responses. Optogenetics has been a useful tool in neuroscience research to unravel the mechanisms of neurovascular coupling at cell-specific level. In this study, we applied laser speckle contrast imaging (LSCI) to map the cortical hemodynamic response with high spatiotemporal resolution. The results showed that optogenetic inhibition of pyramidal neurons in sensorimotor cortex induced both local and distant increases of cerebral blood flow (CBF) with dual peaks, and the full width at half maximum (FWHM) was significantly larger than that of the CBF response to optogenetic excitation. Furthermore, optogenetic excitation of pyramidal neurons could significantly increase the local CBF response to sensory stimulation, whereas optogenetic inhibition of pyramidal neurons decreased the local CBF response at the early stage after sensory stimulation and increased the distant CBF response during the recovery period. Our work provided useful insights into the mechanisms of brain stimulation, which might help in clinical neurological applications.Fragile X-associated Tremor/Ataxia Syndrome is a genetic neurodegenerative disorder affecting carriers of the FMR1 premutation. Not all carriers develop the condition and the age of onset is somewhat variable. A greater understanding of disease progression would be beneficial. Eight carriers and five controls matched by age, sex, and dominant hand volunteered to perform a sway task on a force platform while EEG was simultaneously recorded. Sway parameters were extracted from the movement data at important timepoints throughout their sway cycles and matched to their EEG activity. Distributed source analysis was applied. While there initially appeared to be differences in neural activity between the two groups in the anterior lobe, the right posterior lobe, the right superior parietal lobule and the right parietal lobe, these differences did not survive correction for multiple comparisons.Mindfulness interventions are increasingly used in clinical settings. Neurophysiological mechanisms underlying mindfulness offer objective evidence that can help us evaluate the efficacy of mindfulness. Recent advances in technology have facilitated the use of functional Near-Infrared Spectroscopy (fNIRS) as a light weight, portable, and relatively lower cost neuroimaging device as compared to functional Magnetic Resonance Imaging (fMRI). In contrast to numerous fMRI studies, there are scanty investigations using fNIRS to study mindfulness. Hence, this study was done to investigate the feasibility of using a continuous-wave multichannel fNIRS system to study cerebral cortex activations on a mindfulness task versus a baseline task. NIRS data from 14 healthy Asian subjects were collected. A statistical parametric mapping toolbox specific for statistical analysis of NIRS signal called NIRS_SPM was used to study the activations. The results from group analysis performed on the contrast of the mindfulness versus baseline tasks showed foci of activations on the left and central parts of the prefrontal cortex. The findings are consistent with prevailing fMRI studies and show promise of using fNIRS system for studying real-time neurophysiological cortical activations during mindfulness practice.This paper reported data-driven functional connectivity (FC) analytical method to investigate functional near infrared spectroscopy (fNIRS)-based connectivity. We evaluated the synchronization of oxygenated hemoglobin using Pearson's correlation and employed orthogonal minimal spanning trees (OMSTs) in characterizing brain connectivity. Then we compared the resultant global cost efficiency and robustness with those generated by non-human i.e. lattice and random networks. We also further benchmarked our method using proportional threshold. Results from 59 healthy subjects demonstrated global cost efficiency and assortativity varied in lattice and random network significantly (p less then 0.05), highlighting the potential of OMSTs in extracting true neuronal network. Moreover, the inadequate of proportional threshold in extracting small world network from the same dataset supported that the OMSTs might be the better alternative in FC analysis especially in evaluating cost-efficiency and robustness of network.It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory.
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