State EEG Research Articles

S53. Combined Resting State fMRI and EEG Investigation of Irritability

S53. Combined Resting State fMRI and EEG Investigation of Irritability

F114. DISORGANIZATION AND COGNITIVE DYSFUNCTIONS IN SCHIZOPHRENIA: A STUDY OF RESTING STATE EEG

BackgroundA disorganization factor was found by several factor-analytic studies of schizophrenia symptoms. This factor does not appear to be affected by age, severity of other symptoms and chronicity of illness. A greater severity of disorganization is associated with poor functioning. Despite the general similarity of different factorial model, there is no consensus about which symptoms have to be included in the disorganization factor. Using the Positive and Negative Syndrome Scale (PANSS), Conceptual disorganization’ (P2), ‘Difficulty in abstract thinking’ (N5) and ‘Poor attention’ (G11) were core features of the disorganization factor.The overlap of these items with neurocognitive functions is still debated. However, the heterogeneity of this factor and its neurobiological basis should be further investigated.In the context of the multicenter study of the Italian Network for Research on Psychoses, the main aims of our study were to investigate electrophysiological and neurocognitive correlates of the disorganization factor, and to assess if each PANSS item, loading on the disorganization factor, could be underpinned by similar electrophysiological or cognitive alterations.MethodsResting state EEGs were recorded for 5 minutes in 145 stabilized subjects with schizophrenia (SCZ) and 69 matched healthy controls (HC). The disorganization factor was evaluated using three PANSS items: P2, N5, and G11 (4).Neurocognitive functions were assessed using the MATRICS Consensus Cognitive Battery (MCCB). Spectral amplitude was quantified in nine frequency bands. All statistical analyses of the scalp multichannel spectral amplitude (SAmp) data were performed using RAGU software.Statistical comparisons between the SAmp maps of SCZ and HC were assessed by topographic analyses of variance (TANOVA). In SCZ, topographic analyses of covariance (TANCOVA) evaluated correlations between SAmp and disorganization, its constituent items and MCCB domains. Furthermore, Pearson’s correlations were performed between disorganization and its constituent items and MCCB neurocognitive domains.ResultsTANOVA, comparing the group SAmp maps revealed increased Delta, Theta, and Beta1 and decreased Alpha2 SAmp in SCZ.In the SCZ group, disorganization was significantly correlated to the Alpha1 SAmp. This relation was negative and most pronounced at occipital sites. At the items level, only N5 showed the same negative correlation at occipital sites.MCCB neurocognitive composite score was associated with disorganization factor, and its constituent items P2 and N5. No significant correlation between Alpha1 SAmp and MCCB cognitive domains was observed.DiscussionOur findings illustrate the heterogeneity of disorganization dimension and a partial overlap with neurocognitive domains. ‘Difficulty in abstract thinking’ showed a unique association with Alpha1 activity, which is thought to be involved in the construction of conceptual maps.Furthermore, the observed association of Alpha1 with ‘Difficulty in abstract thinking’ suggests that some aspects of disorganization could be underpinned by the impairment of basic neurobiological functions that are only partially evaluated using MCCB.

Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction

Abstract This study proposes a new model which is fully specified for automated seizure onset detection and seizure onset prediction based on electroencephalography (EEG) measurements. We processed two archetypal EEG databases, Freiburg (intracranial EEG) and CHB-MIT (scalp EEG), to find if our model could outperform the state-of-the art models. Four key components define our model: (1) multiscale principal component analysis for EEG de-noising, (2) EEG signal decomposition using either empirical mode decomposition, discrete wavelet transform or wavelet packet decomposition, (3) statistical measures to extract relevant features, (4) machine learning algorithms. Our model achieved overall accuracy of 100% in ictal vs. inter-ictal EEG for both databases. In seizure onset prediction, it could discriminate between inter-ictal, pre-ictal, and ictal EEG with the accuracy of 99.77%, and between inter-ictal and pre-ictal EEG states with the accuracy of 99.70%. The proposed model is general and should prove applicable to other classification tasks including detection and prediction regarding bio-signals such as EMG and ECG.

Electrographic Seizures in Preterm Neonates in the Neonatal Intensive Care Unit.

Characterize clinical and electroencephalography (EEG) characteristics of preterm neonates undergoing continuous EEG in the neonatal intensive care unit. Retrospective study of preterm neonates born less than 37 weeks' gestational age undergoing continuous EEG in the neonatal intensive care unit at Boston Children's Hospital over a 2-year period. Fifty-two preterms (46% male) had a mean gestational age of 32.8 weeks (standard deviation = 4.17). Seizures were detected in 12/52 (23%), with EEG seizures detected in 4/12 (33%). The median time from EEG to the first seizure was 0.5 hours (interquartile range 0.24-4). Factors associated with seizures were male gender (odds ratio = 4.65 [95% confidence interval = 1.02-21.24], P = .047) and lack of EEG state change (odds ratio = 0.043 [95% confidence interval = 0.005-0.377], P = .04). Twenty-three percent of preterms undergoing continuous EEG had EEG seizures or electrographic seizures with no clear clinical correlate. This confirms recent American Clinical Neurophysiology Society guidelines suggesting that preterm neonates are at high risk for seizures.

The state of everyday quantitative EEG use in Canada: A national technologist survey

PurposeThis study sought to determine the state of quantitative EEG (QEEG) use in Canada, as QEEG may provide a partial solution to the issue of escalating EEG demand against insufficient health care resources. MethodsA 10-item survey questionnaire was administered to participants at the annual meeting of the Canadian Association of Electroneurophysiology Technologists, which was held in parallel with the annual meeting of the Canadian Neurological Sciences Federation. ResultsAt least 70% of the Canadian population has QEEG access through academic medical institutions with applicability to adults and children. QEEG was clinically used 50% in real-time and 50% retrospectively in the critical care and epilepsy monitoring units for long-term monitoring and automated seizure detection. QEEG trend use, montage use, and duration were variable. ConclusionTo cope with insufficient health care resources, QEEG is in surprisingly frequent clinical use across Canada. There is no consensus on optimal QEEG trends and montages. The relative ubiquity of QEEG affords an excellent opportunity for research as increasing EEG demand outpaces dwindling health care resources into the foreseeable future.

A New Kind of Permutation Entropy Used to Classify Sleep Stages from Invisible EEG Microstructure

Permutation entropy and order patterns in an EEG signal have been applied by several authors to study sleep, anesthesia, and epileptic absences. Here, we discuss a new version of permutation entropy, which is interpreted as distance to white noise. It has a scale similar to the well-known χ 2 distributions and can be supported by a statistical model. Critical values for significance are provided. Distance to white noise is used as a parameter which measures depth of sleep, where the vigilant awake state of the human EEG is interpreted as “almost white noise”. Classification of sleep stages from EEG data usually relies on delta waves and graphic elements, which can be seen on a macroscale of several seconds. The distance to white noise can anticipate such emerging waves before they become apparent, evaluating invisible tendencies of variations within 40 milliseconds. Data segments of 30 s of high-resolution EEG provide a reliable classification. Application to the diagnosis of sleep disorders is indicated.

The Comparison and Study of WVD, PWVD, SPWVD Time Frequency Analysis Technologies Based on Observed Dynamic EEG Data

For the observed EEG data under +Gz acceleration, the traditional Fourier transformation can not express the change regularity of EEG frequency spectrum characteristic with time, so it is tried to make data treatment with the help of analysis tool of WVD. Through the theory comparison on WVD, PWVD and SPWVD-this three analysis methods and the comparison analysis on the application results of the actually measured EEG data under centrifuge +Gz acceleration, the respective advantage and disadvantage of the three methods is studied, and SPWVD is found to be relatively a better analysis method. It can eliminate effectively crossing term interference which is innate for quadratic form distribution and has better focusing characteristic, and can better reflect the state of EEG under different G acceleration and frequency spectrum change characteristic.

Disorganization in schizophrenia: A resting EEG study

IntroductionIn subjects with schizophrenia (SCZ), the disorganization factor was found to be a strong predictor of real-life functioning. “Conceptual disorganization” (P2), “difficulties in abstract thinking” (N5) and “poor attention” (G11) are considered core aspects of the disorganization factor, as assessed by PANSS. The overlap of these items with neurocognitive functions is debated and should be further investigated.AimsWithin the Italian network for research on psychoses study, electrophysiological and neurocognitive correlates of the disorganization factor and its component items were investigated.MethodsResting state EEGs were recorded in 145 stabilized SCZ and 69 matched healthy controls (HC). Spectral amplitude (SAmp) was averaged in nine frequency bands. MATRICS consensus cognitive battery (MCCB) was used for neurocognitive assessment. Band SAmp differences and correlations with psychopathology and MCCB scores were explored by global randomization statistics.ResultsSCZ showed increased delta, theta, and beta1 and decreased alpha2 SAmp. A negative correlation between alpha1 and disorganization was observed in SCZ. At the item level, only N5 showed this correlation. MCCB neurocognitive composite was associated with P2 and N5 but not with alpha1 SAmp.ConclusionsOur findings suggest an heterogeneity of the disorganization dimension and a partial overlap with neurocognitive domains. The N5, “difficulties in abstract thinking”, had a unique association with alpha1 SAmp, which is thought to be involved in the formation of conceptual maps.Disclosure of interestThe authors have not supplied their declaration of competing interest.

P156 Ongoing EEG oscillations modulate MEP amplitudes: A possible mechanism of MEP variability

Objective Although the resting motor threshold (RMT) is relatively stable, the variability of MEPs produced by TMS over the primary motor cortex (M1) is well known, and its precise mechanism is still unclear. We hypothesized that EEG oscillations just before TMS could modulate the MEP amplitudes that underlie the MEP variability. Thus, we evaluated the relationship between EEG oscillations and MEP amplitudes. Methods Two experiments were conducted in this study. EEGs were obtained at 19 locations (international 10–20 system) and MEPs were recorded from right FDI in Exp. 1 (n = 12). Left M1 hotspot was stimulated by TMS with the intensity to obtain about 1 mV MEP amplitudes (S-1 mV). MEPs and EEGs were recorded for 200 times in total for each subject under the eyes-open (EO) and eyes-close (EC) conditions. EEGs were segmented between −500 and 0 ms of the TMS onset, and the power values (8–30 Hz) were calculated by wavelet analysis. EEG powers were compared between the epochs of higher and lower amplitude MEPs. In Exp. 2 (n = 9), the effect of low TMS intensity was evaluated under the EO condition. EEG oscillations were compared between the high (S-1 mV) and low intensity (RMT) TMS conditions. Results EEG powers of α and β range were significantly increased (synchronization) at C3 when MEP amplitudes were larger in both EO and EC conditions. When the EEG power difference of higher/lower MEPs was compared between the EO and EC conditions, these differences under EO were more pronounced than that of EC at frontal and parietal leads. In contrast, EEG powers were reduced (desynchronization) at C3 when MEP amplitudes were larger in the low TMS condition (Exp. 2). Discussion We found that EEG synchronization of α / β bands prior to TMS was a determinant factor for the MEP amplitudes at S-1 mV (Exp. 1). Distributed networks over the frontal areas may modulate MEPs differently under EO and EC conditions. However, desynchronization of α / β bands produced MEPs at RMT (Exp. 2). From this complex interaction between EEG synchronization/desynchronization and TMS intensity, we assume that ongoing EEG oscillations of α / β bands performs the dual functions of gateway and gatekeeper. Like a push–pull system, that depends on the ongoing EEG state and TMS intensity, the dual system may allow the TMS impulses to M1 by which the MEP variability occurs.

自己の脳波状態を反映した協調仮想空間の構築と評価(「BMI/BCI時代の心理学とVR」特集)

自己の脳波状態を反映した協調仮想空間の構築と評価(「BMI/BCI時代の心理学とVR」特集)

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Learning curves of theta/beta neurofeedback in children with ADHD

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and specificity of this intervention. A total of 38 children (aged between 7 and 13 years) with a DSM-IV-TR diagnosis of ADHD, completed on average 29 sessions of theta (4–8 Hz)/beta (13–20 Hz) neurofeedback training. Dependent variables included training-related measures as well as theta and beta power during baseline and training runs for each session. Learning effects were analyzed both within and between sessions. To further specify findings, individual learning curves were explored and correlated with behavioral changes in ADHD symptoms. Over the course of the training, there was a linear increase in participants’ mean training level, highest obtained training level and the number of earned credits (range b = 0.059, −0.750, p < 0.001). Theta remained unchanged over the course of the training, while beta activity increased linearly within training sessions (b = 0.004, 95% CI = [0.0013–0.0067], p = 0.005) and over the course of the intervention (b = 0.0052, 95% CI = [0.0039–0.0065], p < 0.001). In contrast to the group analyses, significant individual learning curves were found for both theta and beta over the course of the intervention in 39 and 53%, respectively. Individual learning curves were not significantly correlated with behavioral changes. This study shows that children with ADHD can gain control over EEG states during neurofeedback, although a lack of behavioral correlates may indicate insufficient transfer to daily functioning, or to confounding reinforcement of electromyographic activity. Clinical Trials Registration: This trial is registered at the US National Institutes of Health (ClinicalTrials.gov, ref. no: NCT01363544); https://clinicaltrials.gov/show/NCT01363544.

The 40-Hz Auditory Steady-State Response in Patients With Schizophrenia

The neurobiological mechanisms underlying circuit dysfunctions in schizophrenia remain poorly understood. The 40-Hz auditory steady-state response (ASSR) has been suggested as a potential biomarker for schizophrenia. To provide a meta-analytical insight into the presence of 40-Hz ASSR impairments in patients with schizophrenia and to examine the effects of the participant group, stimulus parameters, and analysis and recording techniques. Searches were conducted in PubMed and reference lists of appropriate publications to identify relevant studies published from November 1999 to March 2016. Initial literature searches were performed with combinations of the following search terms: (1) auditory steady state response, (2) schizophrenia, (3) 40 Hz, (4) EEG, (5) MEG, and (6) steady state response. Original articles reporting 40-Hz ASSR data on patients with schizophrenia (chronic or first episode) compared with healthy controls using electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings. Hedges g effect sizes were calculated using sample sizes, P values, and/or Cohen d effect sizes from 20 studies. Effect size data were pooled using random-effects models. Publication bias was corrected for using funnel plots, the Egger regression test, and a trim and fill test. The contributions of study design parameters and participant characteristics were assessed using a mixed linear model approach and subsequent post hoc t tests. The present analysis was performed during the period from November 2015 to March 2016. Random model Hedges g effect sizes for auditory steady-state amplitude and phase-locking measures from sensor/electrode and sources-space responses in EEG and MEG studies. Of the 20 studies analyzed (representing a total of 590 healthy controls and 606 patients with schizophrenia), 17 reported significant reductions in 40-Hz ASSR spectral power and/or phase locking in patients with schizophrenia compared with healthy controls (Hedges g effect: -0.58 [power] and -0.46 [phase]). Effect sizes from spectral power and phase-locking measures did not differ significantly (95% CI, -0.49 to 0.22; t = -0.80; P = .43). Stimulus characteristics and analysis methods were not associated with the findings of 40-Hz ASSR impairment in schizophrenia. The 40-Hz ASSR spectral power and phase-locking deficits are robust in schizophrenia, which suggests that these measures could be useful probes for assessing circuit dysfunctions in the disorder. Moreover, these findings should motivate large-scale studies of the longitudinal expression in patients with schizophrenia and at-risk populations, to further validate the 40-Hz ASSR as a potential biomarker.

Abstract # 1865 Altered brain intrinsic activity in allergy

Research has shown that allergic people have significantly impaired psychological well-being and impaired cognitive functioning. The origin of such deficits is currently unknown. Given the tight and bidirectional link between the brain and the immune system, we hypothesized that allergic people might show altered intrinsic brain activity, as compared to non allergic people. We also hypothesized that such alterations are manifested already at rest, that is, when the subjects are not actively engaged in any task. The brain indeed spontaneously generates neural oscillations. Such oscillations at various frequencies are a prominent feature of the spontaneous electroencephalogram (EEG) and are believed to reflect functional states of the brain and carry information about behaviour. Here, resting state (64 channels) EEG during eyes open and eyes closed was recorded from 15 allergic patients and 15 age matched healthy control participants. The peak frequency (PF) and power amplitude (PA) in the delta (

EEG and ERP determinants and correlates of cognitive processing in Go/NoGo paradigms. II: Current EEG state impacts ERP components and behaviour

EEG and ERP determinants and correlates of cognitive processing in Go/NoGo paradigms. II: Current EEG state impacts ERP components and behaviour

Hibernation in a primate: does sleep occur?

During hibernation, critical physiological processes are downregulated and thermogenically induced arousals are presumably needed periodically to fulfil those physiological demands. Among the processes incompatible with a hypome tabolic state is sleep. However, one hibernating primate, the dwarf lemur Cheirogaleus medius, experiences rapid eye movement (REM)-like states during hibernation, whenever passively reaching temperatures above 30°C, as occurs when it hibernates in poorly insulated tree hollows under tropical conditions. Here, we report electroencephalographic (EEG) recordings, temperature data and metabolic rates from two related species (C. crossleyi and C. sibreei), inhabiting high-altitude rainforests and hibernating underground, conditions that mirror, to some extent, those experienced by temperate hibernators. We compared the physiology of hibernation and spontaneous arousals in these animals to C. medius, as well as the much more distantly related non-primate hibernators, such as Arctic, golden-mantled and European ground squirrels. We observed a number of commonalities with non-primate temperate hibernators including: (i) monotonous ultra-low voltage EEG during torpor bouts in these relatively cold-weather hibernators, (ii) the absence of sleep during torpor bouts, (iii) the occurrence of spontaneous arousals out of torpor, during which sleep regularly occurred, (iv) relatively high early EEG non-REM during the arousal, and (v) a gradual transition to the torpid EEG state from non-REM sleep. Unlike C. medius, our study species did not display sleep-like states during torpor bouts, but instead exclusively exhibited them during arousals. During these short euthermic periods, non-REM as well as REM sleep-like stages were observed. Differences observed between these two species and their close relative, C. medius, for which data have been published, presumably reflect differences in hibernaculum temperature.

Electroencephalographic features of anti-N-methyl-D-aspartate receptor encephalitis in children

To investigate electroencephalographic (EEG) characteristics of anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis in children. Clinical data of 28 children diagnosed as anti-NMDAR encephalitis were retrospectively analyzed for EEG characteristics in different periods and severity of disease and outcome. Among the 28 patients with anti-NMDAR encephalitis, 15 were males and 13 were females. Their age at disease onset ranged from 1 year 3 months to 12 years 4 months. Patients were divided into mild group (5 cases) and severe group (23 cases). In the different stage of the disease, occipital background activity of the EEG was preserved in more than half of patients. Accompanied by the evolution of disease course, the occipital background activity and slow waves gradually recovered to normal. In the peak phase of disease, occipital background activity in the awake state was preserved in 4/5 patients of the mild group and 9/17 patients of the severe group. Alpha and theta band rhythms in non-rapid eye movement (NREM) sleep existed in 77% (17/22) patients. EEG monitoring showed delta brushes in 2 cases, and the delta brushes were mixed with background fast waves in one case; 71% (20/28) patients had epileptiform discharges in EEG during the course, and among them, 6 patients had secondary epilepsy. The background activity in the awake state and abnormal diffuse slow waves of EEG were evolved and gradually recovered during the course of the disease. Regardless milder or severe illness condition, occipital background activity was still preserved during different stages in most patients. Alpha and theta rhythms in NREM sleep might represent a relatively overt EEG characteristic. The presence of delta brush in EEG was rare, and sometimes they were difficult to be distinguished from fast wave activities caused by drugs. The presence of epileptiform discharges in EEG suggested the possibility of secondary epilepsy.

Towards medical education neuroscience: pilot results of integrative affective analytics from clinical skills workshops

Towards medical education neuroscience: pilot results of integrative affective analytics from clinical skills workshops

Inappropriate assumptions about EEG state changes and their impact on the quantification of EEG state dynamics

Inappropriate assumptions about EEG state changes and their impact on the quantification of EEG state dynamics

Cortical neuronal activity does not regulate sleep homeostasis

The neural substrate of sleep homeostasis is unclear, but both cortical and subcortical structures are thought to be involved in sleep regulation. To test whether prior neuronal activity in the cortex or in subcortical regions drives sleep rebound, we systemically administered atropine (100mg/kg) to rats, producing a dissociated state with slow-wave cortical electroencephalogram (EEG) but waking behavior (e.g. locomotion). Atropine injections during the light period produced 6h of slow-wave cortical EEG but also subcortical arousal. Afterward, rats showed a significant increase in non-rapid eye movement (NREM) sleep, compared to the same period on a baseline day. Consistent with the behavioral and cortical EEG state produced by systemic atropine, c-Fos expression was low in the cortex but high in multiple subcortical arousal systems. These data suggest that subcortical arousal and behavior are sufficient to drive sleep homeostasis, while a sleep-like pattern of cortical activity is not sufficient to satisfy sleep homeostasis.