Detection and Prediction of Absence Seizures Based on Nonlinear Analysis of the EEG in Wag/Rij Animal Model

 Background: Epilepsy is a common neurological disorder with a prevalence of 1% of the world population. Absence epilepsy is a form of generalized seizures with Spike wave discharge in EEG. Epileptic patients have frequent absence seizures that cause immediate loss of consciousness.Methods: In this study, it has been tried to explore whether EEG changes can effectively detect epilepsy in animal model applying non-linear features. To predict the occurrence of absence epilepsy, a long-term EEG signal has been recorded from frontal cortex in seven Wag/Rij rats. After preprocessing, the data was transferred to the phase space to extract the brain system dynamic and geometric properties of this space. Finally, the ability of each features to predict and detect absence epilepsy with two criteria of predictive time and the accuracy of detection and its results were compared with previous studies.Results: The results indicate that the brain system dynamic changes during the transition from free-seizure to pre-seizure and then seizure. Proposed approach diagnostic characteristics yielded 97% accuracy of absence epilepsy diagnosis indicating that due to the nonlinear and complex nature of the system and the brain signal, the use of methods consistent with this nature is important in understanding the dynamic transfer between different epileptic seizures.Conclusion: By changing the state of the absence Seizures, the dynamics are changing, and the results of this research can be useful in real-time applications such as predicting epileptic seizures

Enhancement of Sleep Quality and Stability Using Acoustic Stimulation During Slow Wave Sleep

Background: One of the challenges today is that the quality of sleep has weakened by many external factors, which we are not even aware of and which directly affect sleep. Sleep quality has an essential role in maintaining the cognitive function and memory consolidation of individuals. So far, various studies have been done to improve the quality of sleep by using external electrical stimulation, vestibular and olfactory system stimulation.Methods: In this study, the increase in sleep quality was considered by simultaneous acoustic stimulation in a deep sleep to increase the density of slow oscillations. Slow oscillations are the important events recorded in electroencephalography (EEG) and hallmark deep sleep. Acoustic stimulation of pink noise with random frequency ranging from 0.8 to 1.1 Hz was used to improve sleep quality.Results: Eight healthy adults (mean age: 28.4±7.8 years) studied in 3 nights under 3 conditions: accommodation night, stimulation night (STIM) and no stimulation night (SHAM), in counter-balanced order. Significant characteristics of the objective and subjective quality of sleep have been extracted from the acquired EEG and compared in the last 2 nights. Also, the arousal and cyclic alternating pattern characteristics have been measured to assess sleep stability over 2 nights of STIM and SHAM.Conclusion: Our findings confirm this goal of the study that applying designed acoustic stimulation simultaneously in the slow wave sleep (SWS) stage increases the duration of deep sleep and ultimately improves overall sleep stability and quality

Evaluation of Cerebral Cortex Function in Clients with Bipolar Mood Disorder I (BMD I) Compared With BMD II Using QEEG Analysis

Objective: Early diagnosis of type I and type II bipolar mood disorder is very challenging particularly in adolescence. Hence, we aimed to investigate the cerebral cortex function in these patients, using quantitative electroencephalography analysis to obtain significant differences between them. Methods: Thirty- eight adolescents (18 patients with bipolar disorder I and 20 with BMD II) participated in this study. We recorded the electroencephalogram signals based on 10-20 international system by 21 electrodes in eyes open and eyes closed condition resting conditions. Forty seconds segments were selected from each recorded signals with minimal noise and artifacts. Periodogram Welch was used to estimate power spectrum density from each segment. Analysis was performed in five frequency bands (delta, theta, alpha, beta and gamma), and we assessed power, mean, entropy, variance and skewness of the spectrums, as well as mean of the thresholded spectrum and thresholded spectrogram. We only used focal montage for comparison. Eventually, data were analyzed by independent Mann-Whitney test and independent t test. Results: We observed significant differences in some brain regions and in all frequency bands. There were significant differences in prefrontal lobe, central lobe, left parietal lobe, occipital lobe and temporal lobe between BMD I and BMD II (P < 0.05). In patients with BMD I, spectral entropy was compared to patients with BMD II. The most significant difference was observed in the gamma frequency band. Also, the power and entropy of delta frequency band was larger in the left parietal lobe in the BMD I patients compared to BMD II patients (P < 0.05). In the temporal lobe, significant differences were observed in the spectrum distribution of beta and gamma frequency bands (P < 0.05). Conclusion: The QEEG and entropy measure are simple and available tools to help detect cerebral cortex deficits and distinguish BMD I from BMD II

Evaluation of electroencephalogram signals of the professional pianists during iconic memory and working memory tests using spectral coherence

Background: Today, the neuroscience has growth in many aspects, and the effects of different factors on memory obtained many achievements. Several scientific and experimental studies evaluated effects of music on style and behavior of people; in this study, we evaluated memory between two groups of people, the professional pianists and normal people, through processing their electroencephalogram (EEG) signals using the coherence measure. Methods: In this study, EEG signals from 17 subjects during two memory tasks were recorded. After that, these signals were preprocessed, and spectral coherence connectivity measure between pair of electrodes was computed and then compared in the five frequency bands using independent t-test. Results: This statistical analysis for working memory task showed significant differences in the temporal, central, and parietal lobes, especially in P7, P3, Pz, T8, C3, and C4 electrodes. As we know, these differences are related to learned skills and activities, words and sounds perception, and memory. Furthermore, for iconic memory task, significant differences were observed in the right hemisphere of these two groups. Conclusions: From this task, we can say professional pianists are different from normal people in the perception of images and creativity. Results of this study show the effects of music on human brain and memory

The Morphology of the Prophet Moses’ Tale from Vladimir Propp’s Theoretical Perspective

Story has a very primitive role in the cultural dimension and the conveyance of the humanitarian concepts, and it is the most compatible form of language mixed with human mind. Because of this, the celestial books probably often narrate their message by use of tales. As the holy Qur’an tales make use of technical criteria of modern stories, it provides the opportunity for the sake of comparison and the analysis of the critical viewpoints. One of these ways is the morphology of tales by Vladimir Propp,s viewpoint. Propp,s manner is one of the best ways for analysis and morphology of the tales considering the interactions among Characters and their functions. The present study aimed to investigate the morphology of Moses’s story in the holy Qur’an by the use of Propp,s descriptive and analytic method. In order to draw better conclusion, the story was divided into three parts and the characters and functions of each section were analyzed and investigated. The findings of the present research showed that this story coincided with the Propp,s paradigm of the fairy tales, with a little change in function of the story. Because of the fact that from 31 functions of fairy tales, 23 of the functions among 6 characters are available in that tale, the course of the story is compatible with the peace, reaching the zenith and attaining further peace with the three movements of the sixth movements of propp,s

Identification of the Ectopic Foci of Focal Atrial Tachycardia (FAT) by Using Electrocardiogram (ECG) Signal Analysis

Background and Aim: Cardiac electrophysiology study (EPS) is the study of the electrical system of the heart. One of the most common methods of treating cardiac arrhythmias is ablation. The main problem with this method is determination of the position of the heart that must be be ablated. Electrocardiogram (ECG) signal is used as a non-invasive, safe and fast tool to understand the electrical activity of the heart. The aim of this study was to identify the focal atrial tachycardia ectopic foci based on ECG signal analysis using sparse decomposition algorithm. Materials and Methods: 12-lead ECG signals of 48 patients with focal atrial tachycardia were recorded and stored. After preprocessing the ECG signals, by using Pan-Tompkins algorithm, each pulse of each signal was separated. Sparse coefficients of test data were calculated based on the sparse decomposition algorithm and the test data were classified. 4 anatomical position in the right atrium, one in the septum and 4 anatomical position in the left atrium were considered as 9 classes and the position of the ectopic foci in each test data was determined. Results: At first, the location of the ectopic foci was identified in the right or left atrium, and then the exact anatomical position in each atrium was estimated. The average accuracy of identifying the position of ectopic foci in 5 runs of algorithm was 81.27±2.78. The mean accuracy of identification of ectopic foci was 61.73% in 4 anatomical position of right atrium, 64.05% in septum and 65.16% in 4 anatomical position of left atrium. Conclusion: Based on the findings of the study, the location of the ectopic foci of focal atrial tachycardia can be identified with appropriate accuracy using ECG signal analysis before performing electrophysiological study

A dataset of a stimulated biceps muscle of electromyogram signal by using rossler chaotic equation

Biological systems, composed of various interrelated components, are nonlinear systems. Improved disease diagnosis and the application of efficient treatment and therapeutic aids are the direct outcomes of possessing a deep understanding of such systems. Therefore, by employing diverse biological system simulations and subsequently analyzing their responses and characteristics, we can diagnose diseases. In this particular study, a novel stimulation method was utilized for the first time, employing the Rossler equation, to record the electromyogram (EMG) signals of the biceps muscle in ten participants. The presented dataset enables the extraction of biological, computational, and chaotic features, which can be utilized for disease classification and diagnosis. Furthermore, this dataset can be employed for the training, validation, and testing of neural networks