Quantitative Electroencephalographic Measures Research Articles

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders.

Background: People diagnosed with substance use disorders (SUDs) are at risk for impairment of brain function and structure. However, physicians still do not have any clinical biomarker of brain impairment that helps diagnose or treat these patients when needed. The most common method to study these patients is the classical electroencephalographic (EEG) analyses of absolute and relative powers, but this has limited individual clinical applicability. Other non-classical measures such as frequency band ratios and entropy show promise in these patients. Therefore, there is a need to expand the use of quantitative (q)EEG beyond classical measures in clinical populations. Our aim is to assess a group of classical and non-classical qEEG measures in a population with SUDs. Methods: We selected 56 non-medicated and drug-free adult patients (30 males) diagnosed with SUDs and admitted to Rehabilitation Clinics. According to qualitative EEG findings, patients were divided into four groups. We estimated the absolute and relative powers and calculated the entropy, and the alpha/(delta + theta) ratio. Results: Our findings showed a significant variability of absolute and relative powers among patients with SUDs. We also observed a decrease in the EEG-based entropy index and alpha/(theta + delta) ratio, mainly in posterior regions, in the patients with abnormal qualitative EEG. Conclusions: Our findings support the view that the power spectrum is not a reliable biomarker on an individual level. Thus, we suggest shifting the approach from the power spectrum toward other potential methods and designs that may offer greater clinical possibilities.

Quantitative electroencephalography as a potential biomarker in migraine.

The aim of this study was to investigate the utility of quantitative electroencephalography (QEEG) as a diagnostic tool for migraine and as an indicator of treatment response by comparing QEEG characteristics between migraine patients and controls, and monitoring changes in these characteristics alongside clinical symptoms in response to treatment BACKGROUND: We hypothesized that patients with migraine exhibit distinctive characteristics in QEEG measurements, which could be used as potential diagnostic biomarkers and as a tool for monitoring treatment response. A total of 720 patients were included in the study, comprising 619 patients with migraine and 101 subjects as a control group. QEEG measurements were analyzed for absolute power across specific frequency bands: delta wave (0.5-4Hz), theta wave (4-8Hz), alpha wave (8-12Hz), beta wave (12-25Hz), and high beta wave (25-30Hz). The absolute power was normalized against a normative dataset from NeuroGuide, with electrodes being highlighted for significance if they exceeded 1.96. Clinical symptoms were also monitored for correlation with QEEG changes. Our analysis showed that patients with migraine exhibited significantly higher absolute power across all frequencies, most markedly within the high beta frequency range. When considering electrodes with z-scores exceeding the threshold of 1.96 in the high beta range, a significant association with migraine diagnosis was observed (per 1 electrode increase, OR 1.06; 95% CI 1.01-1.11; p=.012). Moreover, pre- and posttreatment changes in QEEG measurements corresponded with changes in clinical symptoms. Patients with migraine have distinctive QEEG measurements, particularly regarding absolute power and the number of electrodes that surpassed the z-score threshold in high beta wave activity. These findings suggest the potential of QEEG as a diagnostic biomarker and as a tool for monitoring treatment response in migraine patients, warranting further large-scale studies for confirmation and expansion.

Deep transcranial magnetic stimulation alters resting-state neurophysiological traits in major depressive disorder

ObjectiveMajor depressive disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide; unfortunately, many patients do not respond to traditional antidepressant medication or talk therapy approaches. Deep transcranial magnetic stimulation (Deep TMS) has emerged as an effective treatment option for such “treatment-resistant” cases; however, the mechanisms by which Deep TMS attenuates depressive symptoms are still ambiguous. MethodsIn the current study, resting-state quantitative electroencephalography (QEEG) measures were assessed pre-and-post treatment to illustrate neurophysiological changes resulting from Deep TMS. ResultsThe results showed reduced slow-frequency brain activity (delta and theta waves) in the prefrontal cortex following 36 treatments. Additionally, baseline QEEG measures predicted treatment response with 93 % accuracy. ConclusionsThese findings provide preliminary evidence that TMS improves depressive symptoms by mitigating slow-wave brain activity in the prefrontal cortex. SignificanceDeep TMS paired with QEEG should continue to be utilized for treatment of MDD in clinical practice and future studies should explore its potential for other neuropsychiatric conditions.

Relationship of Neuropeptide S (NPS) with Neurocognitive, Clinical, and Electrophysiological Parameters of Patients during Structured Rehabilitation Therapy for Schizophrenia.

Introduction: Neuropeptide S is a biomarker related to various neuropsychiatric and neurocognitive functions. Since the need to improve cognitive functions in schizophrenia is unquestionable, it was valuable to investigate the possible relationships of plasma levels of NPS with neurocognitive, psychopathological and EEG parameters in patients with schizophrenia. Aim: Relationships between the serum NPS level and neurocognitive, clinical, and electrophysiological parameters were investigated in patients diagnosed with schizophrenia who underwent structured rehabilitation therapy. Methods: Thirty-three men diagnosed with schizophrenia were randomized into two groups. The REH group (N16) consisted of patients who underwent structured rehabilitation therapy, the CON group (N17) continued its previous treatment. Additionally, the reference NPS serum results were checked in a group of healthy people (N15). In the study several tests assessing various neurocognitive functions were used: d2 Sustained-Attention Test (d2), Color Trails Test (CTT), Beck Cognitive Insight Scale (BCIS), Acceptance of Illness Scale (AIS), and General Self-Efficacy Scale (GSES). The clinical parameters were measured with Positive and Negative Syndrome Scale (PANSS) and electrophysiological parameters were analyzed with auditory evoked potentials (AEPs) and quantitative electroencephalography (QEEG). The NPS, neurocognitive, clinical, and electrophysiological results of REH and CON groups were recorded at the beginning (T1) and after a period of 3 months (T2). Results: A decreased level of NPS was associated with the improvement in specific complex indices of d2 and BCIS neurocognitive tests, as well as the improvement in the clinical state (PANSS). No correlation was observed between the level of NPS and the results of AEPs and QEEG measurements. Conclusions: A decreased level of NPS is possibly related to the improvement in metacognition and social cognition domains, as well as to clinical improvement during the rehabilitation therapy of patients with schizophrenia.

Quantitative electroencephalography measures in rapid eye movement and nonrapid eye movement sleep are associated with apnea-hypopnea index and nocturnal hypoxemia in men.

Quantitative electroencephalography (EEG) measures of sleep may identify vulnerability to obstructive sleep apnea (OSA) sequelae, however, small clinical studies of sleep microarchitecture in OSA show inconsistent alterations. We examined relationships between quantitative EEG measures during rapid eye movement (REM) and non-REM (NREM) sleep and OSA severity among a large population-based sample of men while accounting for insomnia. All-night EEG (F4-M1) recordings from full in-home polysomnography (Embletta X100) in 664 men with no prior OSA diagnosis (age ≥ 40) were processed following exclusion of artifacts. Power spectral analysis included non-REM and REM sleep computed absolute EEG power for delta, theta, alpha, sigma, and beta frequency ranges, total power (0.5-32 Hz) and EEG slowing ratio. Apnea-hypopnea index (AHI) ≥10/h was present in 51.2% (severe OSA [AHI ≥ 30/h] 11.6%). In mixed effects regressions, AHI was positively associated with EEG slowing ratio and EEG power across all frequency bands in REM sleep (all p < 0.05); and with beta power during NREM sleep (p = 0.06). Similar associations were observed with oxygen desaturation index (3%). Percentage total sleep time with oxygen saturation <90% was only significantly associated with increased delta, theta, and alpha EEG power in REM sleep. No associations with subjective sleepiness were observed. In a large sample of community-dwelling men, OSA was significantly associated with increased EEG power and EEG slowing predominantly in REM sleep, independent of insomnia. Further study is required to assess if REM EEG slowing related to nocturnal hypoxemia is more sensitive than standard PSG indices or sleepiness in predicting cognitive decline.

Comparison of Parametric and Non-parametric EEG Feature Extraction Methods in Detection of Pediatric Migraine without Aura

Migraine headache without aura is the most common type of migraine especially among pediatric patients. It has always been a great challenge of migraine diagnosis using quantitative electroencephalography measurements through feature classification. It has been proven that different feature extraction and classification methods vary in terms of performance regarding detection and diagnostic accuracy. Previous work on the subject was controversial, hence a comparison of these methods seems necessary. The aim of this research is to compare two parametric and non-parametric feature extraction methods and also two classification methods in order to obtain optimal combinations of diagnostic accuracy. Having recorded background EEG from 24 pediatric migraineurs and 19 control subjects, data was processed by Welch's and Yule-Walker's methods. Features were selected using genetic algorithm, and then given to a support vector machine and the linear discriminant analysis for the classification. Accuracy was calculated for all combinations having the dominant frequency and the correlated absolute power of each EEG wave band (theta, alpha, and beta) and for all wave bands combined. The highest migraine detection accuracy of 93% was obtained utilizing Welch's method for EEG feature extraction alongside support vector machine for a classifier. Besides, Yule-Walker autoregressive method showed better performance than Welch's, when only power bands (and not the dominant frequency) were used as classification input. The superiority of Welch's method over Yule-Walker's and the support vector machine over linear discriminant analysis can be great help for further researches on computer aided EEG-based diagnosis of migraine.

Exposure to contact sports predicts the reliability of daily quantitative electroencephalographic measurements

Exposure to contact sports predicts the reliability of daily quantitative electroencephalographic measurements

Response to Pharmacological Treatment in Major Depression Predicted by Electroencephalographic Alpha Power - a Pilot Naturalistic Study.

Pharmacological treatment of depression is currently led by the trial and error principle mainly because of lack of reliable biomarkers. Earlier findings suggest that baseline alpha power and asymmetry could differentiate between responders and non-responders to specific antidepressants. The current study investigated quantitative electroencephalographic (QEEG) measures before and early in treatment as potential response predictors to various antidepressants in a naturalistic sample of depressed patients. We were aiming at developing markers for early prediction of treatment response based on different QEEG measures. EEG data from 25 depressed subjects were acquired at baseline and after one week of treatment. Mean and total alpha powers were calculated at eight electrode sites F3, F4, C3, C4, P3, P4, O1, O2. Response to treatment was defined as 50% decrease in MADRS score at week 4. Mean P3 alpha predicted response with sensitivity and specificity of 80%, positive and negative predictive values of 92.31% and 71.43%, respectively. The combined model of response prediction using mean baseline P3 alpha and mean week 1 C4 alpha values correctly identified 80% of the cases with sensitivity of 84.62%, and specificity of 71.43%. Simple QEEG measures (alpha power) acquired before initiation of antidepressant treatment could be useful in outcome prediction with an overall accuracy of about 80%. These findings add to the growing body of evidence that alpha power might be developed as a reliable biomarker for the prediction of antidepressant response.

Cerebral Recovery Index: Reliable Help for Prediction of Neurologic Outcome After Cardiac Arrest.

Early electroencephalography measures contribute to outcome prediction of comatose patients after cardiac arrest. We present predictive values of a new cerebral recovery index, based on a combination of quantitative electroencephalography measures, extracted every hour, and combined by the use of a random forest classifier. Prospective observational cohort study. Medical ICU of two large teaching hospitals in the Netherlands. Two hundred eighty-three consecutive comatose patients after cardiac arrest. None. Continuous electroencephalography was recorded during the first 3 days. Outcome at 6 months was dichotomized as good (Cerebral Performance Category 1-2, no or moderate disability) or poor (Cerebral Performance Category 3-5, severe disability, comatose, or death). Nine quantitative electroencephalography measures were extracted. Patients were randomly divided over a training and validation set. Within the training set, a random forest classifier was fitted for each hour after cardiac arrest. Diagnostic accuracy was evaluated in the validation set. The relative contributions of resuscitation parameters and patient characteristics were evaluated. The cerebral recovery index ranges from 0 (prediction of death) to 1 (prediction of full recovery). Poor outcome could be predicted at a threshold of 0.34 without false positives at a sensitivity of 56% at 12 hours after cardiac arrest. At 24 hours, sensitivity of 65% with a false positive rate of 6% was obtained. Good neurologic outcome could be predicted with sensitivities of 63% and 58% at a false positive rate of 6% and 7% at 12 and 24 hours, respectively. Adding patient characteristics was of limited additional predictive value. A cerebral recovery index based on a combination of intermittently extracted, optimally combined quantitative electroencephalography measures provides unequalled prognostic value for comatose patients after cardiac arrest and enables bedside EEG interpretation of unexperienced readers.

EEG spectral analysis of NREM sleep in a large sample of patients with insomnia and good sleepers: effects of age, sex and part of the night.

Previous studies of the differences between patients with insomnia and good sleepers with regard to quantitative electroencephalographic measures have mostly utilized small samples and consequently had limited ability to account for potentially important confounding factors of age, sex and part of the night. We conducted a power spectral analysis using a large database of sleep electroencephalographic recordings to evaluate differences between patients with insomnia (N=803) and good sleepers (N=811), while simultaneously accounting for these factors and their interaction. Comparisons of power as a function of age and part of the night were made between cohorts (patients with insomnia versus good sleepers) by sex. Absolute power in the delta, theta and sigma bands declined with age for both females and males. Females had significantly greater power than males at all ages, and for each band, cohort and part of the night. These sex differences were much greater than differences between patients with insomnia and good sleepers. Compared with good sleepers, patients with insomnia under age 40-45years had reduced delta band power during Part 1 of the night. Females with insomnia over age 45years had increased delta and theta band power in Parts 2 and 3 of the night, and males with insomnia under age 40years had reduced theta power in Part 1. Females with insomnia had increased beta2 power in all parts of the night, and males with insomnia had reduced alpha power during all parts of the night. Relative power (the proportion that an individual frequency band contributes to the total power) decreased in the delta band and increased in all other bands with age for both cohorts, sexes and all parts of the night. This analysis provides a unique resource for quantitative information on the differences in power spectra between patients with insomnia and good sleepers accounting for age, sex and part of the night.

MicroVolt Variations of The Human Brain (Quantitative Electroencephalography) Display Differential Torque Effects During West-East versus North-South Orientation in the Geomagnetic Field

         The human brain was assumed to be an elliptical electric dipole. Repeated quantitative electroencephalographic measurements over several weeks were completed for a single subject who sat in either a magnetic eastward or magnetic southward direction. The predicted potential difference equivalence for the torque while facing perpendicular (west-to-east) to the northward component of the geomagnetic field (relative to facing south) was 4 μV. The actual measurement was 10 μV. The oscillation frequency around the central equilibrium based upon the summed units of neuronal processes within the cerebral cortices for the moment of inertia was 1 to 2 ms which are the boundaries for the action potential of axons and the latencies for diffusion of neurotransmitters. The calculated additional energy available to each neuron within the human cerebrum during the torque condition was ~10-20 J which is the same order of magnitude as the energy associated with action potentials, resting membrane potentials, and ligand-receptor binding. It is also the basic energy at the level of the neuronal cell membrane that originates from gravitational forces upon a single cell and the local expression of the uniaxial magnetic anisotropic constant for ferritin which occurs in the brain. These results indicate that the more complex electrophysiological functions that are strongly correlated with cognitive and related human properties can be described by basic physics and may respond to specific geomagnetic spatial orientation.

Improving test-retest reliability of quantitative electroencephalography using different preprocessing approaches.

This work aims to assess the effect of preprocessing approaches over test-retest reliability of quantitative electroencephalography measurements. Two electroencephalography sessions were recorded during an eyes-closed resting state condition in 15 young healthy individuals. The second session was 4 to 6 weeks after the first one. Clean recordings were obtained from the implementation of different preprocessing approaches commonly used in the literature. We then estimated the power spectrum density, for each individual and preprocessing approach, in six frequency bands: delta, theta, alpha1, alpha2, beta, and gamma. Test-retest reliability using the intraclass correlation coefficient was calculated for power spectrum in each methodology and frequency band. We found that the test-retest reliability varied considerably across frequency bands and preprocessing approaches. Reliability was higher for theta, alpha1, and alpha2 frequency bands. Also, the use of preprocessing approach that includes a robust reference to average and independent component analysis, can improve test-retest reliability in other bands such as beta and gamma. Results suggest that quantitative electroencephalography are test-retest reliable and can be used in longitudinal studies.

Quantitative Shifts in the Second Harmonic (12-14 Hz) of the Schumann Resonance Are Commensurate with Estimations of the Sleeping Population: Implications of a Causal Relationship

Recent spectral power densities of quantitative electroencephalographic measurements of normal brains indicate they reveal peaks that correspond with the fundamental and harmonics of the Schumann Resonance. Coherence between the human brain and Schumann power occurs for about 300 ms every 30 s. We examined the conspicuous diurnal complex variation in Schumann values and the estimated numbers of people asleep at the time globally. The overlap was visibly obvious for the 12-14 Hz (second harmonic), which is the Stage 2 sleep spindle range, with peak-to-peak changes of ~0.1 Hz and 0.1 pT. Residuals from multiple regression analyses after potential artifacts were removed showed that as the estimated numbers of people sleeping increased the frequency increment within the 12-14 Hz range increased while the intensity decreased by about 1 pT. The Lorentz Lemma for population brain-Schumann activity and comparable current densities for the ionosphere-earth gradient and human brain current densities are similar magnitudes and suggest potential interactions. Experimental manipulation by HAARP of the Schumann Resonance employed a power density (10 mW per m2 range) that is comparable to that from the photon power densities emitted from the brain activities of billions of people. Although causality is not demonstrated, the presence of a strong coherence could suggest interactions at global levels.

Psychophysiological Effects of Orchid and Rose Fragrances on Humans

This study aimed to determine the effects of floral fragrances on human brain waves and moods. A total of 44 subjects participated in this experiment. Group 1 consisted of 11 male and 14 female college students with a mean age of 24.5 years (± 2.23) and Group 2 consisted of 10 males and 9 females with a mean age of 54.3 years (± 2.98). Subjects were exposed to floral fragrances of Rosa hybrida , ‘Hera’ (hereafter referred to as “rose”), Cymbidium faberi(hereafter referred to as “orchid”), or odorless control flowers (hereafter referred to as “control”). Experiments took place in three rooms (rose, orchid, and control). Electroencephalographs (EEGs) were recorded during exposure to the odors and the data were processed using quantitative electroencephalographic (QEEG) techniques. The changing EEG patterns wereanalyzed by brain mapping and compressed spectral arrays, and the subjects’ preferences (hedonic evaluations) were quantified with an A1 index. Increased activation of absolute alpha waves was verified on six of the eight EEG channels, with the right frontal and left occipital lobes exhibiting no changes and the left parietal region showing the greatest activation. According to the QEEG measurements in the electrode sites over the frontal, temporal, parietal, and occipital lobes, the strongest absolute alpha waves were induced in the parietal lobes, followed by the temporal lobes, with the other lobes showing no significant changes. On brain maps, the orchid fragrance induced greater absolute alpha and absolute mid-beta activities compared with the rose and control fragrances, and the rose fragrance induced high absolute mid-beta activation. To identify emotional responses to floral fragrances, the subjects were requested to fill in a questionnaire and the resulting odor-related emotional descriptors were analyzed using semantic differential and factor analysis. Principal component analysis identified “elegant” as the first principal component describing the floral fragrance, followed by “refreshing” and “aromatic.” The subjects gave orchid higher scores for “elegant” and “refreshing,” while finding rose more “aromatic.” Differences in hedonic evaluation revealed by the A1 index appeared in the 65-115 sec range of scent exposure time. The subjects with ages of around 50 years showed olfactory preferences throughout the entire experimental time of 160 sec, most markedly in the later time segment (115-165 sec), showing an increasing preference with increasing exposure time. We conclude that rose fragrance can improve concentration by creating an aromatic environment conducive to a concentrated and calm state of mind, and orchid fragrance can make people feel pampered and relaxed by creating an elegant and refreshing environment.

Differential spectral quantitative electroencephalography patterns between control and Parkinson's disease cohorts.

It is believed that progressive Lewy-type synucleinopathy (LTS) is primarily responsible for the worsening of motor and non-motor Parkinson's disease (PD) signs and symptoms. Characterization of quantitative electroencephalography (QEEG) abnormalities across the spectrum of LTS to PD dementia (PD-D) may provide insight into the pathophysiology of PD cortical dysfunction. Here our enlarged EEG database was leveraged to characterize spectral QEEG abnormalities in asymptomatic autopsy-defined groups of control participants and incidental Lewy body disease (ILBD) and three clinically defined groups of participants with PD (cognitively normal PD, mild cognitive impairment PD, and PD-D). The PD cohort was studied as part of the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND). AZSAND utilizes its Brain and Body Donation Program to perform prospective, standardized, regular longitudinal pre-mortem assessments until death. Resting EEG from subjects was analyzed for spectral domain QEEG measures of background rhythm frequency and global relative power in delta, theta, alpha and beta bands. The various spectral QEEG measures showed differential changes specific to the groups compared. Important findings were background rhythm frequency showing the most pairwise differences across the groups, and this also was the only significant difference between control and ILBD. An increase in delta bandpower was characteristic of worsening cognitive deficits. Different patterns of change amongst QEEG measures across LTS and PD cognitive states suggest that they correlate with heterogeneous pathophysiologies of cortical dysfunction within the PD clinical spectrum. In addition, the biomarker application of a specific spectral QEEG measure needs to be selectively suited to its study purpose.

Longitudinal EEG changes correlate with cognitive measure deterioration in Parkinson's disease.

QEEG could provide physiological biomarkers for changes over time in Parkinson's disease (PD) cognitive decline if they track with longitudinal neuropsychological performance. Our aim was to correlate longitudinal changes in frequency domain quantitative electroencephalography (QEEG) measures with change in neuropsychological performance testing in PD. 71 PD subjects, not demented at baseline, were studied from the Arizona Study of Aging and Neurodegenerative Disorders cohort. Baseline and follow-up digital EEG from PD subjects were analyzed for QEEG measures of background rhythm frequency and global relative power in delta (2.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands. Baseline and subsequent evaluation included Mini Mental Status Examination and five other neuropsychological tests that load on cognitive domains known to decline in PD. Pearson coefficient was used to assess correlations. Multiple linear regression modeling was used to assess the effect of variable combinations of QEEG and other measures, including age and PD duration. Changes in delta bandpower showed the highest and most consistent pattern of correlations with longitudinal changes in neuropsychological testing. The highest correlation was between delta bandpower increase and decline in the Rey Auditory-Verbal Learning Test (-0.59:p < 0.001). Delta bandpower was also increased in the incident dementia group compared to non-dementia at followup. 1) Longitudinal change in the QEEG frequency domain measure of delta bandpower correlated best with longitudinal neuropsychological performance change in PD; 2) These results constitute preliminary evidence that delta bandpower may be a suitable biomarker for evaluating PD cognitive deterioration longitudinally.

Quantitative Evidence for Direct Effects between Earth-Ionosphere Schumann Resonances and Human Cerebral Cortical Activity

The multiple quantitative similarities of basic frequencies, harmonics, magnetic field intensities, voltages, band widths, and energetic solutions that define the Schumann resonances within the separation between the earth and ionosphere and the activity within the human cerebral cortices suggest the capacity for direct interaction. The recent experimental demonstration of the representations of the Schumann resonances within the spectral densities of normal human quantitative electroencephalographic (QEEG) activity suggests a casual interaction. Calculations supported by correlations between amplitudes of the global Schumann resonances measured several thousands of km away (which were nearly identical to our local measurements) and the coherence and current densities or these frequency bands between cerebral hemispheres for a large population of human QEEG measures indicate that such interaction occurs. The energies are within the range that would allow information to be exchanged between cerebral and Schumann sources. The near-identical solution for current density from the increasing human population and background vertical electric fields suggests that changes in the former might determine the degree of coherence between the Schumann resonances. Direct comparisons of local Schumann measurements and brain activity exhibited powerful intermittent coherence within the first three harmonics. Implications of the contributions of solar transients, surface temperature, and rapidly developing technologies to modify the ionosphere’s Schumann properties are considered.

Quantitative Evidence for Direct Effects between Earth-Ionosphere Schumann Resonances and Human Cerebral Cortical Activity

The multiple quantitative similarities of basic frequencies, harmonics, magnetic field intensities, voltages, band widths, and energetic solutions that define the Schumann resonances within the separation between the earth and ionosphere and the activity within the human cerebral cortices suggest the capacity for direct interaction. The recent experimental demonstration of the representations of the Schumann resonances within the spectral densities of normal human quantitative electroencephalographic (QEEG) activity suggests a casual interaction. Calculations supported by correlations between amplitudes of the global Schumann resonances measured several thousands of km away (which were nearly identical to our local measurements) and the coherence and current densities or these frequency bands between cerebral hemispheres for a large population of human QEEG measures indicate that such interaction occurs. The energies are within the range that would allow information to be exchanged between cerebral and Schumann sources. The near-identical solution for current density from the increasing human population and background vertical electric fields suggests that changes in the former might determine the degree of coherence between the Schumann resonances. Direct comparisons of local Schumann measurements and brain activity exhibited powerful intermittent coherence within the first three harmonics. Implications of the contributions of solar transients, surface temperature, and rapidly developing technologies to modify the ionosphere’s Schumann properties are considered.

EPA-1261 – Rapid antidepressant effect of nmda antagonist and QEEG biomarker of sustained response

A series of clinical studies demonstrated that QEEG (quantitative electroencephalography) prefrontal theta cordance value decreases after one week of treatment in responders to antidepressants and precedes clinical improvement. Ketamine, a non-competitive antagonist of NMDA receptors, has a unique rapid antidepressant effect but its influence on QEEG measures is still unknown. To date wasn’t studied predictive value of cordance in response to single infusion of ketamine in depressive subjects. In a double-blind, cross-over, randomized, placebo-controlled experiment we studied the influence of ketamine (0.54 mg/kg) on theta cordance in a group of 27 right-handed hospitalized depressive patients on stable antidepressant medication. QEEG cordance values in theta frequency band were calculated according to UCLA algorithm. Responders (n=11) to ketamine in compare to non-responders (n=16) showed significant difference in cordance values at the end of ketamine infusion (Spearman, p= 0.039). The cordance decrease, measured between the end of infusion and next day, positively correlated with ketamine antidepressant response (MADRS decrease) fourth day after infusion (two-tailed Fisher's Exact test, df=1, p=0.0076) with NPV 90.9% (95% CI 64.3%-99.5%) and PPV 62.5% (95% CI 44.2%-68.4%). Our data indicate that ketamine infusion immediately induces similar changes as monoaminergic-based antidepressants do gradually after a series of downstream signalling steps. The reduction in theta prefrontal cordance could serve as a biomarker of sustained antidepressant response, a hypothesis that should be tested in larger depressive population.

Longitudinal analysis of the electroencephalogram and sleep phenotype in the R6/2 mouse model of Huntington’s disease

Deficits in sleep and circadian organization have been identified as common early features in patients with Huntington's disease that correlate with symptom severity and may be instrumental in disease progression. Studies in Huntington's disease gene carriers suggest that alterations in the electroencephalogram may reflect underlying neuronal dysfunction that is present in the premanifest stage. We conducted a longitudinal characterization of sleep/wake and electroencephalographic activity in the R6/2 mouse model of Huntington's disease to determine whether analogous electroencephalographic 'signatures' could be identified early in disease progression. R6/2 and wild-type mice were implanted for electroencephalographic recordings along with telemetry for the continuous recording of activity and body temperature. Diurnal patterns of activity and core body temperature were progressively disrupted in R6/2 mice, with a large reduction in the amplitude of these rhythms apparent by 13 weeks of age. The diurnal variation in sleep/wake states was gradually attenuated as sleep became more fragmented and total sleep time was reduced relative to wild-type mice. These genotypic differences were augmented at 17 weeks and evident across the entire 24-h period. Quantitative electroencephalogram analysis revealed anomalous increases in high beta and gamma activity (25-60 Hz) in all sleep/wake states in R6/2 mice, along with increases in theta activity during both non-rapid eye movement and rapid eye movement sleep and a reduction of delta power in non-rapid eye movement sleep. These dramatic alterations in quantitative electroencephalographic measures were apparent from our earliest recording (9 weeks), before any major differences in diurnal physiology or sleep/wake behaviour occurred. In addition, the homeostatic response to sleep deprivation was greatly attenuated with disease progression. These findings demonstrate the sensitivity of quantitative electroencephalographic analysis to identify early pathophysiological alterations in the R6/2 model of Huntington's disease and suggest longitudinal studies in other preclinical Huntington's disease models are needed to determine the generality of these observations as a potential adjunct in therapeutic development.