EEG Parameters Research Articles

CRS-R score in disorders of consciousness is strongly related to spectral EEG at rest

Patients suffering from disorders of consciousness still present a diagnostic challenge due to the fact that their assessment is mainly based on behavioral scales with their motor responses often being strongly impaired. We therefore focused on resting electroencephalography (EEG) in order to reveal potential alternative measures of the patient's current state independent of rather complex abilities (e.g., language comprehension). Resting EEG was recorded in nine minimally conscious state (MCS) and eight vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients. Behavioral assessments were conducted using the Coma-Recovery Scale-Revised (CRS-R). The signal was analyzed in the frequency domain and association between resting EEG and CRS-R score as well as clinical diagnosis were calculated using Pearson correlation and repeated-measures ANOVAs. The analyses revealed robust positive correlations between CRS-R score and ratios between frequencies above 8 Hz and frequencies below 8 Hz. Furthermore, the frequency of the spectral peak was also highly indicative of the patient's CRS-R score. Concerning differences between clinical diagnosis and healthy controls, it could be revealed that while VS/UWS patients showed higher delta and theta activity than controls, MCS did not differ from controls in this frequency range. Alpha activity, on the other hand, was strongly decreased in both patient groups as compared to controls. The strong relationship between various resting EEG parameters and CRS-R score provides significant clinical relevance. Not only is resting activity easily acquired at bedside, but furthermore, it does not depend on explicit cooperation of the patient. Especially in cases where behavioral assessment is difficult or ambiguous, spectral analysis of resting EEG can therefore complement clinical diagnosis.

APPLICATION OF EEG FEEDBACK FOR THE CORRECTION OF PSYCHOEMOTIONAL STATE OF CHILDREN

Evaluated the efficacy of neurofeedbacktherapy to normalize the psychoemotional state of children. Trained parameters of EEG were the amplitude of alpha-rhythm, the ratio of amplitudes of alphaand theta-rhythms, sensorimotor and theta-rhythms. In the experimental group showed an increase in the trained parameters of the electroencephalogram, reduced anxiety, “feelings of inferiority” and improvement of voluntary attention. The results indicate the feasibility of neurofeedbacktherapy to optimize the psychoemotional state of children.

An ensemble with the Chinese pentatonic scale using electroencephalogram from both hemispheres.

To listen to brain activity as a piece of music, we previously proposed scale-free brainwave music (SFBM) technology, which translated the scalp electroencephalogram (EEG) into musical notes according to the power law of both the EEG and music. In this study, the methodology was further extended to ensemble music on two channels from the two hemispheres. EEG data from two channels symmetrically located on the left and right hemispheres were translated into MIDI sequences by SFBM, and the EEG parameters modulated the pitch, duration and volume of each note. Then, the two sequences were filtered into an ensemble with two voices: the pentatonic scale (traditional Chinese music) or the heptatonic scale (standard Western music). We demonstrated differences in harmony between the two scales generated at different sleep stages, with the pentatonic scale being more harmonious. The harmony intervals of this brain ensemble at various sleep stages followed the power law. Compared with the heptatonic scale, it was easier to distinguish the different stages using the pentatonic scale. These results suggested that the hemispheric ensemble can represent brain activity by variations in pitch, tempo and harmony. The ensemble with the pentatonic scale sounds more consonant, and partially reflects the relations of the two hemispheres. This can be used to distinguish the different states of brain activity and provide a new perspective on EEG analysis.

EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery

Monitoring the neural activities from the ischemic penumbra provides critical information on neurological recovery after stroke. The purpose of this study is to evaluate the temporal alterations of neural activities using electroencephalography (EEG) from the acute phase to the chronic phase, and to compare EEG with the degree of post-stroke motor function recovery in a rat model of focal ischemic stroke. Male Sprague–Dawley rats were subjected to 90 min transient middle cerebral artery occlusion surgery followed by reperfusion for seven days (n = 58). The EEG signals were recorded at the pre-stroke phase (0 h), acute phase (3, 6 h), subacute phase (12, 24, 48, 72 h) and chronic phase (96, 120, 144, 168 h) (n = 8). This study analyzed post-stroke seizures and polymorphic delta activities (PDAs) and calculated quantitative EEG parameters such as the alpha-to-delta ratio (ADR). The ADR represented the ratio between alpha power and delta power, which indicated how fast the EEG activities were. Forelimb and hindlimb motor functions were measured by De Ryck's test and the beam walking test, respectively. In the acute phase, delta power increased fourfold with the occurrence of PDAs, and the histological staining showed that the infarct was limited to the striatum and secondary sensory cortex. In the subacute phase, the alpha power reduced to 50% of the baseline, and the infarct progressed to the forelimb cortical region. ADRs reduced from 0.23 ± 0.09 to 0.04 ± 0.01 at 3 h in the acute phase and gradually recovered to 0.22 ± 0.08 at 168 h in the chronic phase. In the comparison of correlations between the EEG parameters and the limb motor function from the acute phase to the chronic phase, ADRs were found to have the highest correlation coefficients with the beam walking test (r = 0.9524, p < 0.05) and De Ryck's test (r = 0.8077, p < 0.05). This study measured EEG activities after focal cerebral ischemia and showed that functional recovery was closely correlated with the neural activities in the penumbra. Longitudinal EEG monitoring at different phases after a stroke can provide information on the neural activities, which are well correlated with the motor function recovery.

Dissociative symptoms and sleep parameters — an all-night polysomnography study in patients with insomnia

BackgroundDissociative disorders encompass a range of symptoms varying from severe absent-mindedness and memory problems to confusion about one's own identity. Recent studies suggest that these symptoms may be the by-products of a labile sleep–wake cycle. MethodsIn the current study, we explored this issue in patients suffering from insomnia (N=46). We investigated whether these patients have raised levels of dissociative symptoms and whether these are related to objective sleep parameters. Patients stayed for at least one night in a specialized sleep clinic, while sleep EEG data were obtained. In addition, they completed self-report measures on dissociative symptoms, psychological problems, and sleep characteristics. ResultsDissociative symptom levels were elevated in patients suffering from insomnia, and were correlated with unusual sleep experiences and poor sleep quality. Longer REM sleep periods and less time spent awake during the night were predictive of dissociation. ConclusionsThis is the first study to show that insomnia patients have raised dissociative symptom levels and that their dissociative symptoms are related to objective EEG parameters. These findings are important because they may inspire sleep-related treatment methods for dissociative disorders.

Modelling a BCI system to estimate FES stimulation intensity for individual stroke survivors in foot drop cases

This work provides a model to estimate stimulation level required for hemiplegic patient to achieve foot dorsiflexion using BCI approach. The model’s input is EEG from motor cortex of hemiplegic patient. The model’s output is estimation of stimulation strength. The delta mean and alpha peak frequencies are found to be suitable as EEG features to establish the relationship between EEG parameters and stimulus strength for this model. This model is self-adaptive in nature. As therapeutic procedure continues, the model uses a feedback loop, so that it can fine tune the stimulus strength to optimum value for individual patients. The model is prepared by using analysis of EEG feature from all the frequency bands and stimulus strength as observed clinically in 15 stroke patients while achieving dorsiflexion.

Transcranial magnetic stimulation in complex therapy of epilepsy

Analysis of clinical, electroencephalographic and neuroimaging data of 19 patients with epilepsy after a course of repetitive transcranial magnetic stimulation (rTMS) in combination with subtherapeutic doses of anticonvulsants was performed. It was found that 1 Hz low-frequency temporal rTMS combined with anticonvulsants helps to reduce the number of weekly seizures by 91.9% during the course of this procedure, and by 75% during the month after completion of the combined course. rTMS courses lead to reduction of interictal epileptiform activity and decrease in the number of patients with pathological epileptic EEG phenomena, which may be seen not only in the stimulation period, but also during the following 4–12 weeks. rTMS has the long lasting effects on EEG parameters: increase in the alpharhythm power with frequency-spatial structure improvement, and decrease in the theta-rhythm and pathological beta-rhythm with minimization of the number and size of their focuses. The use of low-frequency and low-intensity rTMS together with subtherapeutic doses of anticonvulsants allows avoiding the development of side effects and ensuring high anti-seizure activity

1862 – The effects of eeg-neurofeedback on adhd symptoms and eeg parameters

Introduction EEG-neurofeedback is used as a component of therapy in patients diagnosed with ADHD. The efficacy of NF on inattentive symptoms has been previously suggested. Objective The aim of the study was to assess the efficacy of 20 sessions training of eeg-neurofeedback (NF) in patients suffered from ADHD. Methods The studied group consisted of 44 patients (34 boys and 7 girls).To determine the efficacy of EEG-B on symptoms intensity, The Symptoms of ADHD Questionnaire was used: before the treatment and after 20 sessions of NF. NF trainings took place once or twice a week. The trainings were conduct based on two protocols: theta/beta and theta/SMR for left hemisphere and for right hemisphere, respectively. The changes in theta/beta and theta/SMR ratios were estimated to assess the influence of NF on eeg parameters. Results The significant reduction in symptoms intensity was found after 20 sessions of NF. Theta/beta and theta/SMR ratios median values have been significantly decreased. Conclusions The results of the study indicate the 20 sessions NF training being efficacious in reduction of the intensity of ADHD symptoms. The improvement of eeg parameters responsible for attention functions was also observed.

Why Voluntary Postural Training Improves Recovery of Mental and Motor Functions in Patients with Traumatic Brain Injury?

There are data about the positive effect of rehabilitation with postural training in traumatic brain injury (TBI) patients. Brain mechanisms of functional recovery have been investigated insufficiently. In this study, functional recovery was examined in TBI patients with primary motor (20 patients) or higher mental impairment (10 patients)—post-traumatic Korsakov syndrome compared to healthy volunteers (n = 20). Integral clinical, stabilographic, and EEG approach was used as a tool for estimation of functional deficit in TBI patients before and after rehabilitation course. Specific alterations of stabilographic and EEG parameters were observed in TBI patients with primary motor or mental deficit before rehabilitation. Rehabilitation course with postural training improved recovery of all functions in both patient groups. To understand brain mechanisms of rehabilitation, we examined EEG findings during standing and postural task performance in healthy volunteers (n = 10). EEG coherence increase was marked for different spectral bands predominantly in the right hemisphere and more in alpha-2 and beta bands during postural task performance. These EEG findings were discussed in relation to rehabilitation effect on TBI patients and proved that postural training with visual feedback may provoke primary activation of the right hemisphere and can serve as a trigger for integration of cortical and subcortical structures and for recovery of motor and higher mental function in TBI patients.

1349 – Evidence of neurophysiological distinction between schizophrenia and schizoaffective disorder

Background To date, studies investigating the neurobiological basis of distinction between schizophrenia and schizoaffective disorder are rare, although patients with schizophrenia and schizoaffective disorder demonstrate different clinical and functional outcomes. Methods We analysed the EEG parameters (spectral power and coherence) in resting state and while performance of the arithmetical task (subsequent subtraction from 200-7) in 32 patients with first episode of schizophrenia (SCH, n = 32), 32 patients with frist episode of schizoaffective disorder (SAD, n = 32) and healthy controls (HC, n = 40). Results In resting state in SCH spectral power (SP) of theta and gamma band was higher, and lower in alpha band comparing to HC. In SAD SP was higher only in beta2 band in contrast to HC. Coherence in resting state in SAD was higher comparing to HC as well as SCH in prefrontal areas in theta band and in the posterior regions in fast frequency bands (gamma1 and gamma2). Comparison of task performance with resting state in HC showed increase of SP in theta and gamma bands in anterior midline sites with synchronous increase of coherence in prefrontal areas. In SCH reduced SP of theta, alpha and beta bands and decreased coherence in all bands was obtained. In SAD we observed elevation of SP in gamma band as well as increase of coherence in all frequency bands except theta band. Conclusions Our findings indicate the neurophysiological distinction between schizophrenia and schizoaffective disorders and provide the basement for further research.

Accuracy of Combined EEG Parameters in Prediction the Depth of Anesthesia

BackgroundThe importance of proper qualitative evaluation of EEG parameters during surgery has been recognized since many years. Although none of the characteristics based on the frequency, entropy, and Bi spectral characteristics have been regarded as a good predictor for detection of the depth of anesthesia alone. So it seems necessary to study multiple characteristics together.ObjectivesIn this study we tried to introduce the best combination of the mentioned characteristics.Materials and MethodsEEG data of 64 patients undergoing general anesthesia with the same anesthesia protocol (total intravenous anesthesia) were recorded in all anesthetic stages in Shohada Tajrish Hospital. Quantitative EEG characteristics are classified into 4 categories: time, frequency, bi spectral and entropy based characteristics. Their sensitivity, specificity and accuracy in determination of the depth of anesthesia are yielded by comparison with recorded reference signal in awake, light anesthesia, deep anesthesia and brain death patients. Then, with combining 2, 3, 4 and 5 of characteristics and using coded algorithm we determined the error degree and introduced the combination yielding the least error.ResultsFifteen vectors (of dimension two to five) which yielded the best results were introduced. Vectors combined of entropy based characteristics obtained 100% specificity and sensitivity during all 4 stages.ConclusionsThe combination entropy based characteristics had high accuracy in predicting the depth of anesthesia. Reevaluation of classic indices cortical status index and BIS seems necessary. The next step is to find a system to simplify the evaluation of this information for technicians.

EEG markers of upright posture in healthy individuals

The EEG spectral-coherence parameters were analyzed in 10 healthy individuals (mean age, 22 ± 0.67 years) at different steps of verticalization, from the lying position to the sitting and standing positions. The maximal changes in all EEG parameters were revealed when the upright posture was maintained in the absence of visual control. Under these conditions, a power increase for the fast EEG components (the β- and γ-bands) was observed, as was an additional increase when the conditions of maintaining the upright posture were complicated. According to the results of the EEG’s coherent analysis, human verticalization revealed a specific increase for most of the EEG rhythm ranges in the right hemisphere, especially in the frontocentral and occipitoparietal regions, as well as for the interhemispheric coherences for these leads reflecting the involvement of both cortical and subcortical structures in these processes. When the posture maintenance conditions were complicated, an additional coherence increase in the fast EEG bands (the β-rhythm) was observed in the frontal cortical regions, which was evidence of the increase in the executive functions under these conditions.

A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder

Attention deficit hyperactivity disorder (ADHD) symptoms can be difficult to treat. We previously reported that a 20-session brain-computer interface (BCI) attention training programme improved ADHD symptoms. Here, we investigated a new more intensive BCI-based attention training game system on 20 unmedicated ADHD children (16 males, 4 females) with significant inattentive symptoms (combined and inattentive ADHD subtypes). This new system monitored attention through a head band with dry EEG sensors, which was used to drive a feed forward game. The system was calibrated for each user by measuring the EEG parameters during a Stroop task. Treatment consisted of an 8-week training comprising 24 sessions followed by 3 once-monthly booster training sessions. Following intervention, both parent-rated inattentive and hyperactive-impulsive symptoms on the ADHD Rating Scale showed significant improvement. At week 8, the mean improvement was −4.6 (5.9) and −4.7 (5.6) respectively for inattentive symptoms and hyperactive-impulsive symptoms (both p<0.01). Cohen’s d effect size for inattentive symptoms was large at 0.78 at week 8 and 0.84 at week 24 (post-boosters). Further analysis showed that the change in the EEG based BCI ADHD severity measure correlated with the change ADHD Rating Scale scores. The BCI-based attention training game system is a potential new treatment for ADHD.Trial RegistrationClinicalTrials.gov NCT01344044

A new multimodal indicator design integrating standard monitoring and electroencephalographic data for quantification of depth of anesthesia

Electroencephalographic (EEG) monitoring of the hypnotic component of anesthesia has been suggested as a monitoring technique supplementing standard monitoring to prevent intraoperative awareness. While the EEG reflects brain activity, standard monitoring of anesthesia is based on cardiovascular and respiratory parameters providing indirect information on the effects of anesthetics. The present investigation evaluates the ability of a new multimodal indicator linking EEG and standard monitoring parameters to one index quantifying “anesthetic depth” from wakefulness to deep anesthesia.

Intelligent Computing Method for the Interpretation of Neuropsychiatric Diseases

based system (KBS) has been widely used in the detection and interpretation of EEG based neuropsychiatric diseases. Heuristic-based detection methods of EEG (Electroencephalography) parameters for a particular disease have been reported in the literature but little effort has been made by researchers to combine rule-based reasoning (RBR) and probabilistic method i.e Bayesian method. A combined method improves the computational and reasoning efficiency of the problem- solving strategy. We have hierarchically structured the neuropsychiatric diseases in terms of their physio-pyscho (physical, cognitive and psychological) parameters and EEG and FMRI (Functional magnetic resonance imaging) based parameters. RBR model use to create Bayesian network for each disease. The diseases considered are ADHD, Dementia, Mood Disorder, OCD and SI. The basic objective of this work is to develop an intelligent method of RBR and Bayesian model in which RBR is used to hierarchical correlate sign and symptom of the disease and also compute probabilities of diseases. Bayesian method is used for diagnosing the neuropsychiatric diseases and to find the probability of relative importance of sign and symptoms of diseases to other diseases.

The topography of awareness: a classification of intra‐operative cognitive states

The topography of awareness: a classification of intra‐operative cognitive states

Ammonia-related changes in cerebral electrogenesis in healthy subjects and patients with cirrhosis

ObjectiveTo study the effect of hyperammonaemia on the wake electroencephalogram (EEG) of patients with cirrhosis and healthy volunteers. MethodsWake EEGs were recorded prior to and after the induction of controlled hyperammonaemia in 10 patients with cirrhosis and 10 matched healthy volunteers. ResultsAt baseline, patients had higher ammonaemia than healthy volunteers and their dominant EEG rhythm was slower and of higher amplitude. Induced hyperammonaemia resulted in increased spectral power over most of the scalp in healthy volunteers and decreased frequency along the anterior–posterior midline in patients. ConclusionsThese findings suggest different effects of hyperammonaemia on the wake EEG in relation to baseline/peak ammonia levels. SignificanceThe wake EEG is sensitive to hyperammonaemia and power-based EEG parameters may help in its neurophysiological definition, which, to date, has generally been based on EEG frequency indices.

Correlation of continuous electroencephalogram with clinical assessment scores in acute stroke patients

To compare electroencephalogram (EEG) symmetry values between stroke patients with different 28-day outcomes, and to assess correlations between clinical characteristics and 28-day outcomes. Twenty-two patients presenting with acute ischemic stroke and persistent neurological deficits at EEG recording were incrementally included. At 28 days after admission, the modified Rankin scale (mRS) was used to evaluate the outcomes, based on which the patients were divided into two a posteriori groups, mRS = 6 and mRS <6. Student's t-test was used to compare these two groups in terms of brain symmetry index (BSI), National Institutes of Health stroke scale (NIHSS), Glasgow coma scale (GCS) and acute physiology and chronic health evaluation II (APACHE II) assessed at admission. Then EEG parameters, NIHSS, GCS and APACHE II were correlated with the mRS. There were significant differences in BSI, NIHSS, GCS, and APACHE II between the two groups. Survivors had lower BSI, NIHSS and APACHE II, and higher GCS values, compared with patients who died within 28 days after admission. Besides, BSI at admission had a positive correlation with mRS at 28 days (r = 0.441, P = 0.040). NIHSS and APACHE II were also correlated with mRS (r = 0.736, P <0.000 1; r = 0.667, P = 0.001, respectively). GCS at admission had a negative correlation with mRS (r = -0.656, P = 0.001). A higher BSI predicts a poorer short-term prognosis for stroke patients. Acute EEG monitoring may be of prognostic value for 28-day outcomes. The early prediction of functional outcomes after stroke may enhance clinical management and minimize short-term mortality.

Attention-Related Potentials Allow for a Highly Accurate Discrimination of Mild Cognitive Impairment Subtypes

The three most frequent forms of mild cognitive impairment (MCI) are single-domain amnestic MCI (sd-aMCI), single-domain dysexecutive MCI (sd-dMCI) and multiple-domain amnestic MCI (md-aMCI). Brain imaging differences among single domain subgroups of MCI were recently reported supporting the idea that electroencephalography (EEG) functional hallmarks can be used to differentiate these subgroups. We performed event-related potential (ERP) measures and independent component analysis in 18 sd-aMCI, 13 sd-dMCI and 35 md-aMCI cases during the successful performance of the Attentional Network Test. Sensitivity and specificity analyses of ERP for the discrimination of MCI subgroups were also made. In center-cue and spatial-cue warning stimuli, contingent negative variation (CNV) was elicited in all MCI subgroups. Two independent components (ICA1 and 2) were superimposed in the time range on the CNV. The ICA2 was strongly reduced in sd-dMCI compared to sd-aMCI and md-aMCI (4.3 vs. 7.5% and 10.9% of the CNV component). The parietal P300 ERP latency increased significantly in sd-dMCI compared to md-aMCI and sd-aMCI for both congruent and incongruent conditions. This latency for incongruent targets allowed for a highly accurate separation of sd-dMCI from both sd-aMCI and md-aMCI with correct classification rates of 90 and 81%, respectively. This EEG parameter alone performed much better than neuropsychological testing in distinguishing sd-dMCI from md-aMCI. Our data reveal qualitative changes in the composition of the neural generators of CNV in sd-dMCI. In addition, they document an increased latency of the executive P300 component that may represent a highly accurate hallmark for the discrimination of this MCI subgroup in routine clinical settings.

Organization of the cortical bioelectric activity at different stages of a relaxation session

The dynamics of electroencephalographic (EEG) parameters in adults were studied during active relaxation (which involved simple psychological techniques) and passive relaxation (without using any techniques). The experiment included four stages: background 1, active relaxation, passive relaxation, and background 2. During the experiment, the EEG was recorded in the occipital, parietal-temporal-occipital, central, and frontal regions of both hemispheres of the brain. Comparative analysis of the dynamics of EEG parameters during changing experimental conditions was performed in the frequency range from 5 to 40 Hz divided into ten frequency subranges. It was possible to establish the general pattern in the dynamics of EEG parameters at different relaxation stages, as well as differences in system-level brain performance in the active and passive relaxation states.