55 research outputs found
Corrigendum: Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics
Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics
Lots of studies have been carried out on characteristic of epileptic Electroencephalograph (EEG). However, traditional EEG characteristic research methods lack exploration of spatial information. To study the characteristics of epileptic EEG signals from the perspective of the whole brain,this paper proposed combination methods of multi-channel characteristics from time-frequency and spatial domains. This paper was from two aspects: Firstly, signals were converted into 2D Hilbert Spectrum (HS) images which reflected the time-frequency characteristics by Hilbert-Huang Transform (HHT). These images were identified by Convolutional Neural Network (CNN) model whose sensitivity was 99.8%, accuracy was 98.7%, specificity was 97.4%, F1-score was 98.7%, and AUC-ROC was 99.9%. Secondly, the multi-channel signals were converted into brain networks which reflected the spatial characteristics by Symbolic Transfer Entropy (STE) among different channels EEG. And the results show that there are different network properties between ictal and interictal phase and the signals during the ictal enter the synchronization state more quickly, which was verified by Kuramoto model. To summarize, our results show that there was different characteristics among channels for the ictal and interictal phase, which can provide effective physical non-invasive indicators for the identification and prediction of epileptic seizures
Effects of external stimulations on transition behaviors in neural network with time-delay
Firing patterns transition induced by system size in coupled Hindmarsh–Rose neural system
Firing patterns transition and desynchronization induced by time delay in neural networks
Effects of external stimuli on the pacemaker function of the sinoatrial node in sodium channel gene mutations models.
Loss of function and gain of function mutations of the sodium channel were investigated using an intact two-dimensional rabbit sinoatrial node (SAN) and atrial cell model. The effects of three external stimuli (acetylcholine secretion by the vagal nerve, acid-base concentration, and tissue temperature) on cardiac pacemaker function and conduction were studied. Our results show that these two groups of mutations have different effects on pacemaker function and conduction. Furthermore, we found that the negative effects of these mutations could be altered by external stimuli. The bradycardic effects of mutations were magnified by an increase in acetylcholine level. Changes in acid-base concentration and tissue temperature increased the ability of the SAN to recover its pacemaker function. The results of this study increase our understanding of sodium channel disorders, and help to advance research on the treatment of these conditions
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