A Study of Long-range Correlations in Schizophrenia EEG using Detrended Fluctuation Analysis

In this paper, we have studied electroencephalogram (EEG) activity of schizophrenia patients, in resting eyes closed condition, with detrended fluctuation analysis (DFA). The DFA gives information about scaling and long-range correlations in time series. We computed DFA exponents from 30 scalp locations of 18 male neuroleptic-naIve, recent-onset schizophrenia (NRS) subjects and 15 healthy male control subjects. Our results have shown two scaling regions in all the scalp locations in all the subjects, with different slopes, corresponding to two scaling exponents. No significant differences between the groups were found with first scaling exponent (short-range). However, the second scaling exponent (long-range) were significantly lower in control subjects at all scalp locations (p<0.05, Kruskal-Wallis test). These findings suggest that the long-range scaling behavior of EEG is sensitive to schizophrenia, and this may provide an additional insight into the brain dysfunction in schizophrenia.

Data compression by linear prediction for storage and transmission of EEG signals

The EEG time series has been subjected to various formalisms of analysis to extract meaningful information regarding the underlying neural events. In this paper the linear prediction (LP) method has been used for analysis and presentation of spectral array data for the better visualisation of background EEG activity. It has also been used for signal generation, efficient data storage and transmission of EEG. The LP method is compared with the standard Fourier method of compressed spectral array (CSA) of the multichannel EEG data. The autocorrelation autoregressive (AR) technique is used for obtaining the LP coefficients with a model order of 15. While the Fourier method reduces the data only by half, the LP method just requires the storage of signal variance and LP coefficients. The signal generated using white Gaussian noise as the input to the LP filter has a high correlation coefficient of 0.97 with that of original signal, thus making LP as a useful tool for storage and transmission of EEG. The biological significance of Fourier method and the LP method in respect to the microstructure of neuronal events in the generation of EEG is discussed.

Use of finite wordlength FIR digital filter structures with improved magnitude and phase characteristics for reduction of muscle noise in EEG signals

One of the main disturbances in EEG signals is EMG artefacts generated by muscle movements. In the paper, the use of a linear phase FIR digital low-pass filter with finite wordlength precision coefficients is proposed, designed using the compensation procedure, to minimise EMG artefacts in contaminated EEG signals. To make the filtering more effective, different structures are used, i.e. cascading, twicing and sharpening (apart from simple low-pass filtering) of the designed FIR filter Modifications are proposed to twicing and sharpening structures to regain the linear phase characteristics that are lost in conventional twicing and sharpening operations. The efficacy of all these transformed filters in minimising EMG artefacts is studied, using SNR improvements as a performance measure for simulated signals. Time plots of the signals are also compared. Studies show that the modified sharpening structure is superior in performance to all other proposed methods. These algorithms have also been applied to real or recorded EMG-contaminated EEG signal. Comparison of time plots, and also the output SNR, show that the proposed modified sharpened structure works better in minimising EMG artefacts compared with other methods considered.

Post-seizure EEG fractal dimension of first ECT predicts antidepressant response at two weeks

Background: Duration of seizure by itself is an insufficient criterion for a therapeutically adequate seizure in ECT. Therefore, measures of seizure EEG other than its duration need to be explored as indices of seizure adequacy and predictors of treatment response. We measured the EEG seizure using a geometrical method-fractal dimension (FD) and examined if this measure predicted remission. Methods: Data from an efficacy study on melancholic depressives (n = 40) is used for the present exploration. They received thrice or once weekly ECTs, each schedule at two energy levels - high or low energy level. FD was computed for early-, mid- and post-seizure phases of the ictal EEG. Average of the two channels was used for analysis. Results: Two-thirds of the patients (n = 25) were remitted at the end of 2 weeks. As expected, a significantly higher proportion of patients receiving thrice weekly ECT remitted than in patients receiving once weekly ECT. Smaller post-seizure FD at first ECT is the only variable which predicted remission status after six ECTs. within the once weekly ECT group too, smaller post-seizure FD was associated with remission status. Conclusions: Post-seizure FD is proposed as a novel measure of seizure adequacy and predictor of treatment response. Clinical implications: Seizure measures at first ECT may guide selection of ECT schedule to optimize ECT. Limitations: The study examined short term antidepressant effects only. The results may not be generalized to medication-resistant depressives. (C) 1999 Elsevier Science B.V. All rights reserved.

A high performance scheme for EEG compression using a multichannel model

The amount of data contained in electroencephalogram (EEG) recordings is quite massive and this places constraints on bandwidth and storage. The requirement of online transmission of data needs a scheme that allows higher performance with lower computation. Single channel algorithms, when applied on multichannel EEG data fail to meet this requirement. While there have been many methods proposed for multichannel ECG compression, not much work appears to have been done in the area of multichannel EEG. compression. In this paper, we present an EEG compression algorithm based on a multichannel model, which gives higher performance compared to other algorithms. Simulations have been performed on both normal and pathological EEG data and it is observed that a high compression ratio with very large SNR is obtained in both cases. The reconstructed signals are found to match the original signals very closely, thus confirming that diagnostic information is being preserved during transmission.

Connectivity analysis of multichannel EEG signals using recurrence based phase synchronization technique

Real world biological systems such as the human brain are inherently nonlinear and difficult to model. However, most of the previous studies have either employed linear models or parametric nonlinear models for investigating brain function. In this paper, a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study connectivity in the brain has been proposed. Being non-parametric, this method makes very few assumptions, making it suitable for investigating brain function in a data-driven way. CPR's utility with application to multichannel electroencephalographic (EEG) signals has been demonstrated. Brain connectivity obtained using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity between (a) epileptic seizure and pre-seizure and (b) eyes open and eyes closed states. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the superior ability of CPR for discriminating seizure from pre-seizure. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. (C) 2013 Elsevier Ltd. All rights reserved.

Study of phase synchronization in multichannel seizure EEG using nonlinear recurrence measure

Complex biological systems such as the human brain can be expected to be inherently nonlinear and hence difficult to model. Most of the previous studies on investigations of brain function have either used linear models or parametric nonlinear models. In this paper, we propose a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study seizures in the brain. The advantage of this nonparametric method is that it makes very few assumptions thus making it possible to investigate brain functioning in a data-driven way. We have demonstrated the utility of CPR measure for the study of phase synchronization in multichannel seizure EEG recorded from patients with global as well as focal epilepsy. For the case of global epilepsy, brain synchronization using thresholded CPR matrix of multichannel EEG signals showed clear differences in results obtained for epileptic seizure and pre-seizure. Brain headmaps obtained for seizure and preseizure cases provide meaningful insights about synchronization in the brain in those states. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. Comparative studies with linear correlation have shown that the nonlinear measure CPR outperforms the linear correlation measure. (C) 2014 Elsevier Ltd. All rights reserved.

Processing of EEG Signals for Study of Coupling in Brain Regions for Eyes Open and Eyes Closed Conditions

This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Avaliação da presença de mutações de resistência no gene da NS5B e do prognóstico da infecção pelo HCV através da IL-28B em pacientes monoinfectados com HCV no RJ

Estima-se que a prevalência global da população mundial com hepatite C é de 3%. Pouco se sabe sobre a resposta ao tratamento com respeito à resistência viral. Algumas mutações no fragmento de 109 aminoácidos da NS5B são associadas com resistência ao interferon (IFN) e ribavirina (RBV). Estudos moleculares e clínicos identificaram fatores associados com o hospedeiro e vírus relacionados associada com a resposta ao tratamento, tal como o gene que codifica a IL-28B. Este estudo foi dividido em duas fases, cujos objetivos foram caracterizar a frequência de mutações que conferem resistência ao HCV e avaliar a relevância das mutações em pacientes Respondedores (R) ou Não Respondedores (NR) ao tratamento e caracterizar geneticamente as populações sobre polimorfismos genéticos nos SNPs da IL-28B em relação ao prognóstico da resposta ao tratamento. As amostras dos pacientes foram submetidas a testes de genotipagem e carga viral. As sequências geradas foram comparadas no BLAST e no banco de dados Los Alamos HCV. Realizamos o alinhamento das sequências homólogas e as mutações identificadas. Com base no genótipo e carga viral determinamos a classificação dos pacientes de acordo com a resposta à terapia. O DNA genômico foi isolado a partir de sangue periférico para a realização da tipagem de SNPs de IL-28B. A metodologia utilizada foi de PCR em tempo real utilizando sondas TaqMan SNP específico. A análise dos dados foi realizada utilizando GraphPad Prism com qui-quadrado, risco relativo (RR), Odds Ratio (OR) e intervalo de confiança de 95%, com um nível de significância de P <0,05. Foi encontrado na primeira fase deste estudo uma taxa significativa mutações associadas ao tratamento nas amostras estudadas. A prevalência de mutações associadas à resistência ao IFN e RBV bem como a novos medicamentos antivirais localizados no fragmento de 109 aminoácidos da NS5B foi examinado em 69 indivíduos infectados naïve no Rio de Janeiro, Brasil. Na segunda fase, as mutações foram clinicamente relevantes. Desde então, procuramos observar as diferenças entre melhor ou pior prognóstico de acordo com a imunogenética que mostrou diferenciação entre os grupos R e NR ao tratamento em relação ao prognóstico da resposta terapêutica. Quando as diferenças entre as sequências da NS5B e a resposta ao tratamento foram consideradas verificou-se que associada a mutação R254K, estava a C316N que poderia conduzir a uma não resposta à terapia no genótipo 1b. Os nossos dados também suportaram forte associação de IL-28B rs12979860, com elevada probabilidade de resposta à terapia de IFN + RBV. Nossos dados evidenciam a presença de pacientes virgens de tratamento que abrigam mutações de resistência previamente descritas na literatura. A análise dos fatores preditores de resposta virológica mostrou que a predição de boa resposta ou não ao tratamento e ainda da progressão da doença é dependente de uma importante interação entre a genética viral e a do hospedeiro. Fato este importante para que no momento de avaliação de diagnóstico e conduta terapêutica, o médico possa tomar medidas apropriadas para o tratamento de cada paciente individualmente independentemente do genótipo do HCV em questão.

Delta EEG Activity in Left Orbitofrontal Cortex in Rats Related to Food Reward and Craving

眶额叶皮质与中脑边缘多巴胺奖赏系统有着复杂的相互纤维联系.先前的研究探讨了药物成瘾过程中眶额叶皮质的脑电活动.在本实验中,将探讨食物奖赏和渴求过程中该皮质的脑电活动.实验采用了两个环境:对照环境和食物刺激相关的环境.首先,训练大鼠在食物刺激相关的环境中吃巧克力花生豆,而后在该环境中设置两种不同的刺激方式:能看到和闻到但不能吃到(渴求实验),或者仍旧可以吃到巧克力花生豆(奖赏实验):同时进行左侧眶额叶皮质的脑电记录.结果发现,在食物刺激相关的环境中大鼠Delta频段(2-4Hz)的脑电活动与食物刺激显著相关,此外,与在对照环境中相比,其相对功率在食物渴求时下降而在食物奖赏时升高.本实验表明,食物相关的奖励可以改变大鼠眶额叶皮质的脑电活动,而且,Delta频段的脑电活动能够作为监测该奖励的一个指标.

EEG activities in the orbitofrontal cortex and dorsolateral prefrontal cortex during the development of morphine dependence, tolerance and withdrawal in rhesus monkeys

Investigating the activities of the prefrontal cortex (PFC) in the process of addiction is valuable for understanding the neural mechanism underlying the impairments of the PFC after drug abuse. However, limited data are obtained from primate animals and few studies analyze Electroencephalogram (EEG) in the gamma band, which plays an important role in cognitive functions. In addition, it is yet unclear whether drug abuse affects the orbitofrontal cortex (OFC) and dorsolateral PFC (DLPFC) - the two most important subregions of the PFC - in similar ways or not. The aim of this study is to address these issues. We recorded EEG in the OFC and DLPFC in three rhesus monkeys. All animals received a course of saline (NaCl 0.9%, 2 ml) injection (5 days) followed by 10 days of morphine injection (every 12 h), and then a further series of saline injection (7 days). A main finding in the present study was that morphine decreased EEG power in all frequency bands in a short period after injection in both the OFC and DLPFC in monkeys. And gamma power decreased not just in short period after morphine injection but lasted to 12 h after injection. Moreover, we found that although the changes in EEG activities in the OFC and DLPFC at 30-35 min after injection were similar, the DLPFC was more sensitive to the effect of morphine than the OFC. (c) 2005 Elsevier B.V. All rights reserved.