Introduction: To obtain a baseline for clinical application of Electroencephalography in children and to evaluate the Electroencephalography findings in children with various acute and chronic CNS disorders and non epileptic events.Methods: electroencephalography Electroencephalography records of 250 patients were studied in neurophysiology departments of Queen Rania AL-Abdullah Hospital for children in Jordan. For each patient who had undergone Electroencephalography the following data were recorded: age, sex, source of referral (inpatient or outpatient department), reason for electroencephalography Electroencephalography, diagnostic impressions, clinical presentation, the result of the Electroencephalography examinations and clinical correlation between the seizure type and Electroencephalography finding.Results: Males slightly outnumbered females: 55% males. The majority of cases were Electroencephalography between 6-12 years, Total of 63.2% of all referrals for Electroencephalography were from outpatient clinics while inpatients accounted for 36.8% of referred cases, with pediatric neurology department referrals being the highest (28.8%). majority of diagnosis at referral were suspected epilepsy (80%) with epileptiform Electroencephalography abnormalities in 32%. Over all 64% the Electroencephalography records were normal, including all Electroencephalography records of children with syncope and headache.Conclusions: We conclude that there are many unnecessary routine Electroencephalography recordings in children. Investigation of epilepsy and acute encephalopathies appear to be the most valuable indications for routine pediatric Electroencephalography. Electroencephalography can be helpful in classification of seizures. Finding a way to reduce Electroencephalography requests is recommended.

Objective: ELECTROENCEPHALOGRAM is a reliable reflection of many physiological factors modulating the brain. The Bispectrum is very useful for analyzing non-Gaussian signals such as EEG, and detecting the quadratic phase coupling between distinct frequency components in EEG signals. The main aim of this study was to test the existence of nonlinear phase coupling within the EEG signals in a certain psycho-physiological state; meditation.Methods: Eleven meditators and four non-meditators were asked to do meditation by listening to the guidance of the master, and 10 subjects were asked to do meditation by themselves. Bispectrum estimation was applied to analyze EEG signals, before and during meditation. EEG signals were recorded using 16-channel PowerLab. ANOVA test was used to establish significant changes in Bispectrum parameters, during two different states (before and during meditation).Results: Mean Bispectrum magnitude of each channel increased during meditation. These increments of phase coupling are more obvious in occipital region (Pz channel) than frontal and central regions (Fz and Cz channels). Besides that phase coupled harmonics are shifted to the higher frequencies during meditation.Conclusion: Bispectrum methods can be useful for distinction between two states (before and during meditation).

There are three main views in computational neuroscience including deterministic, stochastic, and nonlinear approaches. In the deterministic ap-proach, the human brain is considered a linear and stationary system with determined parameters. . . .

Background: This study aimed to determine the ELECTROENCEPHALOGRAM (EEG) findings in children with hepatic cirrhosis, which occurred without clinical encephalopathy. Methods: The present study was conducted in an observational-analytical way at Amir-al-momenin Zabol Hospital, Zabol University of Medical Sciences, Iran. In this study, 50 children with hepatic cirrhosis without encephalopathy symptoms and 50 healthy children were evaluated and studied regarding abnormal findings in EEG. Finally, the data were analyzed using SPSS V22 software. Results: The mean and standard deviation of the age of the studied population was 57. 6 ± 76. 17 months. Out of a total of 50 children with hepatic cirrhosis, 21 children (42%) had abnormal findings in EEG, while none of the children in the healthy group had abnormal findings in EEG. There was a significant relationship between abnormal EEG findings and older age (P=0. 001), underlying autoimmune hepatitis disease (P=0. 011), and abnormal (increased) serum levels of Alanineamino Transferase (ALT) (P=0. 030) and aspartate amino transferase (AST) (P=0. 010) enzymes. Children with cirrhosis who had abnormal EEG findings had a higher average Pediatric End-Stage Liver Disease (PELD) score (18. 1 ± 4. 1) than patients with normal EEG findings (17. 2 ± 3. 7), but these findings were not statistically significant and noticeable (P=0. 073). The sensitivity of EEG for predicting the severity of cirrhosis was estimated to be 70% and its specificity was 65%. Conclusion: The results of the present study indicated that the higher sensitivity of EEG compared to the specificity in predicting the severity of cirrhosis indicates that EEG is more useful to rule out severe cirrhosis or to screen cirrhosis patients at risk of deterioration than to confirm its diagnosis.

Depression is a psychological condition that affects mood and impacts the global population more extensively than other mental disorders. Assessments are typically conducted subjectively through interviews, which heavily rely on the examiner's experience. This reliance introduces numerous biases and discrepancies between examiners. Quantitative ELECTROENCEPHALOGRAM (QEEG) emerges as a tool capable of satisfying human curiosity about brain conditions affecting psychology more readily and non-invasively compared to the other examinations such as PET and MRI. By recognizing various waves on the Quantitative ELECTROENCEPHALOGRAM (QEEG), a novel understanding of the benefits stemming from this assessment method and its application to psychological conditions in general and depressed patients in particular is attained.

ELECTROENCEPHALOGRAM (EEG) is a reliable reflection of many physiological factors modulating the brain. The aim of this study is to evaluate nonlinear dynamics of ELECTROENCEPHALOGRAM signals during meditation. For this purpose, we collected EEG signals of seven female meditators in two states: before meditation and during meditation. Correlation Dimension, Hurst Exponent and the maximum Lyapunov Exponents were calculated. The results of this study show that the Correlation Dimension was significantly lower during meditation, as well as the maximum Lyapunov Exponents. This reduction indicates that the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed state. Besides that, the Hurst Exponent is increased during meditation. The finite values of Correlation Dimension and positive values of Lyapunov Exponents suggest that all of the EEG signals have low dimensional chaos and the complexity of signals decrease during meditation.

Timely diagnosis of fatigue helps to improve the quality and effectiveness of neurofeedback training. Neurofeed­back training (NFT) is a method that can change brain activity by altering brain signal fluctuations and teaches individuals to produce or reproduce their brain activity patterns in order to improve performance. Neurofeedback training has been widely utilized over the recent years owing to its considerable effect on the cognitive processes. Fatigue during NFT is one of factors affecting the functioning and achievement of NFT which results in decreased learning ability. Timely diagnosis of fatigue during NFT preserves quality of NFT. Decreased learning ability reduces individuals' motivation for learning during NFT. In this paper, 12 participants` ELECTROENCEPHALOGRAM signals were investigated to detect fatigue during NFT. Two training protocols named protocol 1 and 2 have been designed to improve working memory. Each protocol includes 6 participants and 10 training sessions that each session takes three 10-minute training intervals. Training features in protocol 1 are increased in power of lower2 alpha frequency band in OZ channel and permutation entropy reduction in FZ channel, while protocol 2`s training feature is increased in power of lower2 alpha frequency band in OZ channel. Occurrence of fatigue during NFT changes trend of training features. Changing of training features slope will decrease or become opposite to the goal of NFT. Therefore, examining trend of training features slope is a novel approach in detection of fatigue during NFT. During the occurrence of fatigue, in protocol 1, trend of power of lower2 alpha frequency band`s slope in the OZ channel is decreasing and the trend of entropy` s slope in the FZ channel is increasing. Consequently, the trend of score`s slope is also decreasing. Also in the protocol 2, the trend of power of lower 2 alpha frequency band`s slope in the OZ channel and score is decreasing. This shows that training features do not change in line with the neurofeedback`s goal. Fatigue was detected for 3 subjects in the protocol 1 and 1 subject in the protocol 2. Occurrence of fatigue was less in protocol 1 compared with protocol 2 since Protocol 1 `s training features are combination of frequency and non-frequency features, while the Protocol 2 `s training feature is only frequency feature. Detection of fatigue during NFT is an essential issue which contributes to increase in the effect of training and participants` performance.

Background and purpose: Inhaling substances are hydrocarbons that are converted to gas at room temperature and enter the lungs through the nose and mouth and then our brain. Neurological and psychiatric effects are reported following inhalation, however, there are few studies about acute effect of inhalant on brain ELECTROENCEPHALOGRAM (EEG). Materials and methods: This observational study was performed in Quantitative Electroencephalography unit in Sari Zare Hospital, 2020. Twenty people who used nail polish containing aceton for cosmetic usages participated in this study. Brain signals were recorded before, during, at first and second three minutes after termination of using nail polish containing acetone, were recorded by mitsar 201 amplifier in eyes-open condition. The relative power of the band frequency waves in the occipital, frontal, parietal and midline lobes were calculated using Neurogide software. Data analysis was performed in STATA-15. Results: During acetone nail polish use and at first and second 3 minutes after that relative power in delta and beta band waves significantly increased in C3, C4, Cz, F3, F4, Fz, O1, O2, P3, P4, and Pz (P<0. 01) while relative power of alpha frequency band significantly decreased (P<0. 01). Theta frequency band showed no changes. Conclusion: In this study, acute exposure to acetone increased relative power of delta and beta waves and reduced relative power of alpha waves, in frontal, parietal, occipital, and midline regions in both hemispheres.