Brain's alpha activity is highly reduced in euthymic bipolar disorder patients

Neural oscillation in bipolar disorder: a systematic review of resting-state electroencephalography studies

Bipolar disorder (BD) is a severe psychiatric disease with high rates of misdiagnosis and underdiagnosis, resulting in a significant disease burden on both individuals and society. Abnormal neural oscillations have garnered significant attention as potential neurobiological markers of BD. However, untangling the mechanisms that subserve these baseline alternations requires measurement of their electrophysiological underpinnings. This systematic review investigates consistent abnormal resting-state EEG power of BD and conducted an initial exploration into how methodological approaches might impact the study outcomes. This review was conducted in Pubmed-Medline and Web-of-Science in March 2024 to summarize the oscillation changes in resting-state EEG (rsEEG) of BD. We focusing on rsEEG to report spectral power in different frequency bands. We identified 10 studies, in which neural oscillations was compared with healthy individuals (HCs). We found that BD patients had abnormal oscillations in delta, theta, beta, and gamma bands, predominantly characterized by increased power, indicating potential widespread neural dysfunction, involving multiple neural networks and cognitive processes. However, the outcomes regarding alpha oscillation in BD were more heterogeneous, which is thought to be potentially influenced by the disease severity and the diversity of samples. Furthermore, we conducted an initial exploration into how demographic and methodological elements might impact the study outcomes, underlining the importance of implementing standardized data collection methods. Key aspects we took into account included gender, age, medication usage, medical history, the method of frequency band segmentation, and situation of eye open/eye close during the recordings. Therefore, in the face of abnormal multiple oscillations in BD, we need to adopt a comprehensive research approach, consider the multidimensional attributes of the disease and the heterogeneity of samples, and pay attention to the standardized experimental design to improve the reliability and reproducibility of the research results.

Peak Alpha Frequency in Schizophrenia, Bipolar Disorder, and Healthy Volunteers: Associations With Visual Information Processing and Cognition

BACKGROUND

Schizophrenia (SCZ) and bipolar disorder (BD) are associated with information processing abnormalities, including visual perceptual and cognitive impairments, that impact daily functioning. Recent work with healthy samples suggests that peak alpha frequency (PAF) is an electrophysiological index of visual information processing speed that is correlated with cognitive ability. There is evidence that PAF is slowed in SCZ, but it remains unclear whether PAF is reduced in BD or whether slower PAF is associated with impaired visual perception and cognition in these clinical disorders.

METHODS

We recorded resting-state brain activity (both eyes open and closed) with electroencephalography in 90 participants with SCZ, 62 participants with BD, and 69 healthy control participants. Most participants also performed a visual perception task (backward masking) and cognitive testing (MATRICS Concensus Cognitive Battery).

RESULTS

We replicated previous findings of reduced PAF in patients with SCZ compared with healthy control participants. In contrast, PAF in patients with BD did not differ significantly from that in healthy control participants. Furthermore, PAF was significantly correlated with performance on the perceptual and cognitive measures in SCZ but not BD. PAF was also correlated with visual perception in the healthy control group and showed a trend-level correlation with cognition.

CONCLUSIONS

Together, these results suggest that PAF deficits characterize SCZ, but not BD, and that individual differences in PAF are related to abnormalities in visual information processing and cognition in SCZ.

Predictive Value of qEEG in Manic Switch of Depressed Patients

Backgrounds: More than half of the patients with bipolar disorder (BD) had depressive episodes at the onset of BD. Despite some suggested clinical predictors, there are no certain criteria for predicting which unipolar depression patient switch to manic episodes during the treatment course. Electrophysiological markers can address this issue. Methods: Pretreatment quantitative electroencephalography (qEEG) records of patients diagnosed with major depressive disorder (MDD) or BD at the first visit were included in the study. Patients with MDD were also grouped with manic switch (MS) or MDD based on the diagnosis of later visits. The qEEG spectral power was analyzed across 3 groups, that is, MS, MDD, and BD. Results: Compared to patients whose diagnosis did not change, patients with MS had accelerated high-frequency activities predominantly in the left hemisphere (central-parietal-occipital regions). In contrast, they showed increased slow wave activity predominantly in the right hemisphere (parietal-occipital regions). Conclusion: It can be concluded that searching for electrophysiological markers, which have distinct advantages of repeatability, noninvasiveness, and cost-effectiveness, can facilitate the prediction of the MS.

Point of Care Testing (POCT) in Psychopathology Using Fractal Analysis and Hilbert Huang Transform of Electroencephalogram (EEG)

Research has shown that relying only on self-reports for diagnosing psychiatric disorders does not yield accurate results at all times. The advances of technology as well as artificial intelligence and other machine learning algorithms have allowed the introduction of point of care testing (POCT) including EEG characterization and correlations with possible psychopathology. Nonlinear methods of EEG analysis have significant advantages over linear methods. Empirical mode decomposition (EMD) is a reliable nonlinear method of EEG pre-processing. In this chapter, we compare two existing EEG complexity measures - Higuchi fractal dimension (HFD) and sample entropy (SE), with our newly proposed method using Higuchi fractal dimension from the Hilbert Huang transform (HFD-HHT). We present an example using the three complexity measures on a 2-minute EEG recorded from a healthy 20-year-old male after signal pre-processing. Furthermore, we showed the usefulness of these complexity measures in the classification of major depressive disorder (MDD) with healthy controls. Our study is in line with previous research and has shown an increase in HFD and SE values in the full, alpha and beta frequency bands suggestive of an increase in EEG irregularity. Moreover, the HFD-HHT values decreased in those three bands for majority of electrodes which is suggestive of a decrease in irregularity in the frequency-time domain. We conclude that all three complexity measures can be vital features useful for EEG analysis which could be incorporated in POCT systems.

Resting Electroencephalography Differences Between Eyes-Closed and Eyes-Open Conditions in Children with Subclinical Hypothyroidism

OBJECTIVE

Electroencephalography changes that occur during the transition from eyes-closed to the eyes-open state in resting condition are related to the early phase of sensory processing and are defined as activation. The present study aimed to reveal the potential deteriorations that may occur in the initial period of sensory processing in resting electroencephalography between children with subclinical hypothyroidism and a control group.

MATERIALS AND METHODS

Electroencephalographies of 15 children with subclinical hypothyroidism and 15 healthy children aged 10 to 17 years were recorded for 2 minutes for EC and 2 minutes for eyes-open conditions in resting state. Absolute electroencephalography band powers (μV2 ) within the delta, theta, alpha, and beta frequency bands were calculated in Fz, Cz, Pz, and Oz electrodes, respectively, for eyes-closed and eyes-open conditions.

RESULTS

The results show that, although there was no noteworthy difference between the powers of the electroencephalography frequency bands of children with subclinical hypothyroidism and healthy children during the eyes-open condition, the alpha powers of the control group were significantly higher in all electrodes during the eyes-closed condition. Furthermore, the powers of all frequency bands were observed to decrease in the eyes-open condition in the control group. However, the same net decrease was not observed in the frequency powers of children with subclinical hypothyroidism.

CONCLUSION

According to the results of this study, children with subclinical hypothyroidism may experience information processing impairments starting in the early stages of sensory processing.

Impaired Self-Referential Cognitive Processing in Bipolar Disorder: A Functional Connectivity Analysis

Patients with bipolar disorder have deficits in self-referenced information. The brain functional connectivity during social cognitive processing in bipolar disorder is unclear. Electroencephalogram (EEG) was recorded in 23 patients with bipolar disorder and 19 healthy comparison subjects. We analyzed the time-frequency distribution of EEG power for each electrode associated with self, other, and font reflection conditions and used the phase lag index to characterize the functional connectivity between electrode pairs for 4 frequency bands. Then, the network properties were assessed by graph theoretic analysis. The results showed that bipolar disorder induced a weaker response power and phase lag index values over the whole brain in both self and other reflection conditions. Moreover, the characteristic path length was increased in patients during self-reflection processing, whereas the global efficiency and the node degree were decreased. In addition, when discriminating patients from normal controls, we found that the classification accuracy was high. These results suggest that patients have impeded integration of attention, memory, and other resources of the whole brain, resulting in a deficit of efficiency and ability in self-referential processing.

EEG theta and alpha oscillations in early versus late mild cognitive impairment during a semantic Go/NoGo task

Amnestic mild cognitive impairment (aMCI) is marked by episodic memory deficits, which can be used to classify individuals into early MCI (EMCI) and late MCI (LMCI). Although mounting evidence suggests that individuals with aMCI have additional cognitive alterations including deficits in cognitive control, few have examined if EMCI and LMCI differ on processes other than episodic memory. Using a semantic Go/NoGo task, we examined differences in cognitive control between EMCI and LMCI on behavioral (accuracy and reaction time) and neural (scalp-recorded event-related oscillations in theta and alpha band) measures. Although no behavioral differences were observed between the EMCI and LMCI groups, differences in neural oscillations were observed. The LMCI group had higher theta synchronization on Go trials at central electrodes compared to the EMCI group. In addition, the EMCI group showed differences in theta power at central electrodes and alpha power at central and centro-parietal electrodes between Go and NoGo trials, while the LMCI group did not exhibit such differences. These findings suggest that while behavioral differences may not be observable, neural changes underlying cognitive control processes may differentiate EMCI and LMCI stages and may be useful to understand the trajectory of aMCI in future studies.

Structural dysconnectivity in offspring of individuals with bipolar disorder: The effect of co-existing clinical-high-risk for bipolar disorder

BACKGROUND

Bipolar disorder (BD) might be associated in disturbances in brain networks. However, little is known about the abnormalities in structural brain connectivity which might be related to vulnerability to BD and predictive of the emergence of manic symptoms. No previous study has investigated the effect of subthreshold syndromes on structural dysconnectivity in offspring of parents with BD (BDoff).

METHODS

We investigated diffusion weighted images of 70 BDoff and 48 healthy controls (HC). Nineteen of the 70 BDoff had presented with subthreshold syndromes indicating a clinical high-risk (BDoff-CHR) and other 51 BDoff had no such history (BDoff-non-CHR). Global and regional network properties, rich club organization and inter-regional connectivity in BDoff and healthy controls were investigated using graph analytical methods and network-based-statistics (NBS).

RESULTS

Global properties of WM networks appeared to be intact in BDoff-CHR and BDoff-non-CHR. However, decreased regional connectivity in right occipito-parietal areas and cerebellum was a common feature of both BDoff groups. Importantly, decreased interregional connectivity between nodes in right and left prefrontal regions, nodes in right prefrontal lobe and right temporal lobe and nodes in left occipital area and left cerebellum were evident in BDoff-CHR but not BDoff-non-CHR.

LIMITATIONS

The cross-sectional nature of the study was the main consideration.

CONCLUSION

Decreased regional connectivity in right posterior brain regions might be related to vulnerability to BD. On the other hand, interregional dysconnectivity in anterior frontal and limbic regions and left posterior brain regions might be evident in individuals genetically at risk for developing BD who had experienced subthreshold mood symptoms.

Cannabis Use and Mental Illness: Understanding Circuit Dysfunction Through Preclinical Models

Patients with a serious mental illness often use cannabis at higher rates than the general population and are also often diagnosed with cannabis use disorder. Clinical studies reveal a strong association between the psychoactive effects of cannabis and the symptoms of serious mental illnesses. Although some studies purport that cannabis may treat mental illnesses, others have highlighted the negative consequences of use for patients with a mental illness and for otherwise healthy users. As epidemiological and clinical studies are unable to directly infer causality or examine neurobiology through circuit manipulation, preclinical animal models remain a valuable resource for examining the causal effects of cannabis. This is especially true considering the diversity of constituents in the cannabis plant contributing to its effects. In this mini-review, we provide an updated perspective on the preclinical evidence of shared neurobiological mechanisms underpinning the dual diagnosis of cannabis use disorder and a serious mental illness. We present studies of cannabinoid exposure in otherwise healthy rodents, as well as rodent models of schizophrenia, depression, and bipolar disorder, and the resulting impact on electrophysiological indices of neural circuit activity. We propose a consolidated neural circuit-based understanding of the preclinical evidence to generate new hypotheses and identify novel therapeutic targets.

Transcranial alternating current stimulation (tACS): from basic mechanisms towards first applications in psychiatry

Transcranial alternating current stimulation (tACS) is a unique form of non-invasive brain stimulation. Sinusoidal alternating electric currents are delivered to the scalp to affect mostly cortical neurons. tACS is supposed to modulate brain function and, in turn, cognitive processes by entraining brain oscillations and inducing long-term synaptic plasticity. Therefore, tACS has been investigated in cognitive neuroscience, but only recently, it has been also introduced in psychiatric clinical trials. This review describes current concepts and first findings of applying tACS as a potential therapeutic tool in the field of psychiatry. The current understanding of its mechanisms of action is explained, bridging cellular neuronal activity and the brain network mechanism. Revisiting the relevance of altered brain oscillations found in six major psychiatric disorders, putative targets for the management of mental disorders using tACS are discussed. A systematic literature search on PubMed was conducted to report findings of the clinical studies applying tACS in patients with psychiatric conditions. In conclusion, the initial results may support the feasibility of tACS in clinical psychiatric populations without serious adverse events. Moreover, these results showed the ability of tACS to reset disturbed brain oscillations, and thus to improve behavioural outcomes. In addition to its potential therapeutic role, the reactivity of the brain circuits to tACS could serve as a possible tool to determine the diagnosis, classification or prognosis of psychiatric disorders. Future double-blind randomised controlled trials are necessary to answer currently unresolved questions. They may aim to detect response predictors and control for various confounding factors.

EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities

Background:

A large body of evidence suggested that disruption of neural rhythms and synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes. Cognitive deficits are common features of psychiatric disorders that complicate treatment of the motivational, affective and emotional symptoms.

Objective:

Electrophysiological correlates of cognitive functions will contribute to understanding of neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and developing novel targets for the treatment of cognitive impairments.

Methods:

This review includes a description of brain oscillations in Alzheimer’s disease, bipolar disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders, anxiety disorders, schizophrenia and autism.

Results:

The review clearly shows that the reviewed neuropsychiatric diseases are associated with fundamental changes in both spectral power and coherence of EEG oscillations.

Conclusion:

In this article, we examined the nature of brain oscillations, the association of brain rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric disorders.

Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review

Background

Machine learning applications in health care have increased considerably in the recent past, and this review focuses on an important application in psychiatry related to the detection of depression. Since the advent of computational psychiatry, research based on functional magnetic resonance imaging has yielded remarkable results, but these tools tend to be too expensive for everyday clinical use.

Objective

This review focuses on an affordable data-driven approach based on electroencephalographic recordings. Web-based applications via public or private cloud-based platforms would be a logical next step. We aim to compare several different approaches to the detection of depression from electroencephalographic recordings using various features and machine learning models.

Methods

To detect depression, we reviewed published detection studies based on resting-state electroencephalogram with final machine learning, and to predict therapy outcomes, we reviewed a set of interventional studies using some form of stimulation in their methodology.

Results

We reviewed 14 detection studies and 12 interventional studies published between 2008 and 2019. As direct comparison was not possible due to the large diversity of theoretical approaches and methods used, we compared them based on the steps in analysis and accuracies yielded. In addition, we compared possible drawbacks in terms of sample size, feature extraction, feature selection, classification, internal and external validation, and possible unwarranted optimism and reproducibility. In addition, we suggested desirable practices to avoid misinterpretation of results and optimism.

Conclusions

This review shows the need for larger data sets and more systematic procedures to improve the use of the solution for clinical diagnostics. Therefore, regulation of the pipeline and standard requirements for methodology used should become mandatory to increase the reliability and accuracy of the complete methodology for it to be translated to modern psychiatry.

Reduced Brain Electric Activity and Functional Connectivity in Bipolar Euthymia: An sLORETA Source Localization Study

Bipolar disorder (BD) is a chronic illness with a relapsing and remitting time course. Relapses are manic or depressive in nature and intermitted by euthymic states. During euthymic states, patients lack the criteria for a manic or depressive diagnosis, but still suffer from impaired cognitive functioning as indicated by difficulties in executive and language-related processing. The present study investigated whether these deficits are reflected by altered intracortical activity in or functional connectivity between brain regions involved in these processes such as the prefrontal and the temporal cortices. Vigilance-controlled resting state EEG of 13 euthymic BD patients and 13 healthy age- and sex-matched controls was analyzed. Head-surface EEG was recomputed into intracortical current density values in 8 frequency bands using standardized low-resolution electromagnetic tomography. Intracortical current densities were averaged in 19 evenly distributed regions of interest (ROIs). Lagged coherences were computed between each pair of ROIs. Source activity and coherence measures between patients and controls were compared (paired t tests). Reductions in temporal cortex activity and in large-scale functional connectivity in patients compared to controls were observed. Activity reductions affected all 8 EEG frequency bands. Functional connectivity reductions affected the delta, theta, alpha-2, beta-2, and gamma band and involved but were not limited to prefrontal and temporal ROIs. The findings show reduced activation of the temporal cortex and reduced coordination between many brain regions in BD euthymia. These activation and connectivity changes may disturb the continuous frontotemporal information flow required for executive and language-related processing, which is impaired in euthymic BD patients.

Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as A Biomarker of Early Dementia

Neurodegenerative processes of various types of dementia start years before symptoms, but the presence of a "neural reserve", which continuously feeds and supports neuroplastic mechanisms, helps the aging brain to preserve most of its functions within the "normality" frame. Mild cognitive impairment (MCI) is an intermediate stage between dementia and normal brain aging. About 50% of MCI subjects are already in a stage that is prodromal-to-dementia and during the following 3 to 5 years will develop clinically evident symptoms, while the other 50% remains at MCI or returns to normal. If the risk factors favoring degenerative mechanisms are modified during early stages (i.e., in the prodromal), the degenerative process and the loss of abilities in daily living activities will be delayed. It is therefore extremely important to have biomarkers able to identify-in association with neuropsychological tests-prodromal-to-dementia MCI subjects as early as possible. MCI is a large (i.e., several million in EU) and substantially healthy population; therefore, biomarkers should be financially affordable, largely available and non-invasive, but still accurate in their diagnostic prediction. Neurodegeneration initially affects synaptic transmission and brain connectivity; methods exploring them would represent a 1st line screening. Neurophysiological techniques able to evaluate mechanisms of synaptic function and brain connectivity are attracting general interest and are described here. Results are quite encouraging and suggest that by the application of artificial intelligence (i.e., learning-machine), neurophysiological techniques represent valid biomarkers for screening campaigns of the MCI population.

Glycogen synthase kinase-3: The missing link to aberrant circuit function in disorders of cognitive dysfunction?

Elevated GSK-3 activity has been implicated in cognitive dysfunction associated with various disorders including Alzheimer's disease, schizophrenia, type 2 diabetes, traumatic brain injury, major depressive disorder and bipolar disorder. Further, aberrant neural oscillatory activity in, and between, cortical regions and the hippocampus is consistently present within these same cognitive disorders. In this review, we will put forth the idea that increased GSK-3 activity serves as a pathological convergence point across cognitive disorders, inducing similar consequent impacts on downstream signaling mechanisms implicated in the maintenance of processes critical to brain systems communication and normal cognitive functioning. In this regard we suggest that increased activation of GSK-3 and neuronal oscillatory dysfunction are early pathological changes that may be functionally linked. Mechanistic commonalities between these disorders of cognitive dysfunction will be discussed and potential downstream targets of GSK-3 that may contribute to neuronal oscillatory dysfunction identified.

The successful discrimination of depression from EEG could be attributed to proper feature extraction and not to a particular classification method

Reliable diagnosis of depressive disorder is essential for both optimal treatment and prevention of fatal outcomes. This study aimed to elucidate the effectiveness of two non-linear measures, Higuchi's Fractal Dimension (HFD) and Sample Entropy (SampEn), in detecting depressive disorders when applied on EEG. HFD and SampEn of EEG signals were used as features for seven machine learning algorithms including Multilayer Perceptron, Logistic Regression, Support Vector Machines with the linear and polynomial kernel, Decision Tree, Random Forest, and Naïve Bayes classifier, discriminating EEG between healthy control subjects and patients diagnosed with depression. This study confirmed earlier observations that both non-linear measures can discriminate EEG signals of patients from healthy control subjects. The results suggest that good classification is possible even with a small number of principal components. Average accuracy among classifiers ranged from 90.24 to 97.56%. Among the two measures, SampEn had better performance. Using HFD and SampEn and a variety of machine learning techniques we can accurately discriminate patients diagnosed with depression vs controls which can serve as a highly sensitive, clinically relevant marker for the diagnosis of depressive disorders.

EEG alpha activity increased in response to transcutaneous electrical nervous stimulation in young healthy subjects but not in the healthy elderly

Transcutaneous Electrical Nerve Stimulation (TENS) is used not only in the treatment of pain but also in the examination of sensory functions. With aging, there is decreased sensitivity to somatosensory stimuli. It is essential to examine the effect of TENS application on the sensory functions in the brain by recording the spontaneous electroencephalogram (EEG) activity and the effect of aging on the sensory functions of the brain during the application. The present study aimed to investigate the effect of the application of TENS on the brain’s electrical activity and the effect of aging on the sensory functions of the brain during application of TENS. A total of 15 young (24.2 ± 3.59) and 14 elderly (65.64 ± 4.92) subjects were included in the study. Spontaneous EEG was recorded from 32 channels during TENS application. Power spectrum analysis was performed by Fast Fourier Transform in the alpha frequency band (8–13 Hz) for all subjects. Repeated measures of analysis of variance was used for statistical analysis (p < 0.05). Young subjects had increased alpha power during the TENS application and had gradually increased alpha power by increasing the current intensity of TENS (p = 0.035). Young subjects had higher alpha power than elderly subjects in the occipital and parietal locations (p = 0.073). We can, therefore, conclude that TENS indicated increased alpha activity in young subjects. Young subjects had higher alpha activity than elderly subjects in the occipital and somatosensory areas. To our knowledge, the present study is one of the first studies examining the effect of TENS on spontaneous EEG in healthy subjects. Based on the results of the present study, TENS may be used as an objective method for the examination of sensory impairments, and in the evaluative efficiency of the treatment of pain conditions.

Staging model in psychiatry: Review of the evolution of electroencephalography abnormalities in major psychiatric disorders

AIM

Clinical staging in psychiatry aims to classify patients according to the severity of their symptoms, from stage 0 (increased risk, asymptomatic) to stage 4 (severe illness), enabling adapted treatment at each stage of the illness. The staging model would gain specificity if one or more quantifiable biological markers could be identified. Several biomarkers reflecting possible causal mechanisms and/or consequences of the pathophysiology are candidates for integration into the clinical staging model of psychiatric illnesses.

METHODS

This review covers the evolution (from stage 0 to stage 4) of the most important brain functioning impairments as measured with electroencephalography (EEG), in psychosis spectrum and in severe mood disorders.

RESULTS

The present review of the literature demonstrates that it is currently not possible to draw any conclusion with regard to the state or trait character of any of the EEG impairments in both major depressive disorder and bipolar disorder. As for schizophrenia, the most promising markers of the stage of the illness are the pitch mismatch negativity as well as the p300 event-related potentials, as these components seem to deteriorate with increasing severity of the illness.

CONCLUSIONS

Given the complexity of major psychiatric disorders, and that not a single impairment can be observed in all patients, future research should most likely consider combinations of markers in the quest for a better identification of the stages of the psychiatric illnesses.

Abnormalities of Alpha Activity in Frontocentral Region of the Brain as a Biomarker to Diagnose Adolescents With Bipolar Disorder

Objectives. To investigate brain abnormalities in adolescents with new-onset bipolar disorder (BD) during acute hypomanic and depressive episodes using electroencephalogram (EEG) analysis and to derive a computer-based method for diagnosis of the disorder. Methods. EEG spectral power and entropy of 21 adolescents with BD (included 11 patients in the hypomanic episode and 10 patients in the depressive episode) and 18 healthy adolescents were compared. Moreover, using significant differences and K-nearest-neighbors (KNN) classifier, it was attempted to distinguish the BD adolescents from normal ones. Results. The BD adolescents had higher values of spectral power in all frequency bands, particularly in the frontocentral, mid-temporal, and right parietal regions. Also, spectral entropy had significantly increased in delta, alpha, and gamma frequency bands for BD. A high accuracy of 95.8% was achieved by all significant differences in the alpha band in discriminating adolescents with BD. The depressive state showed higher values of spectral power and entropy in low-frequency bands (delta and theta) compared to the hypomanic state. Conclusion. Based on BD symptoms, especially inattention, increased alpha power is a rational finding which is associated with thalamus dysfunction. Thus, it seems that EEG alpha oscillation is the main source of abnormality in BD. Furthermore, EEG slowing in the depressive episode is related to inhibition of electrical activity and reduced cognitive functions.

Decreased peak alpha frequency and impaired visual evoked potentials in first episode psychosis

Abnormal spontaneous and evoked oscillations have been reported in several studies of patients with psychotic disorders. Resting alpha power and peak alpha frequency may be decreased in patients with psychosis. We used high-density EEG (hd-EEG) to record resting-state data and steady-state visual evoked potentials (SSVEPs) in patients with first episode psychosis (FEP) and healthy controls to compare brain resonances across multiple frequencies. We recorded hd-EEG (128 channels) from 22 FEP patients and 22 healthy controls during eyes-closed resting state and eyes-closed photic stimulation at 1 Hz, 4 Hz, 10 Hz, 20 Hz, and 40 Hz. Alpha power, peak alpha frequency, and SSVEP amplitude were analyzed using ANOVA and statistical non-parametric mapping. We found that FEP patients had lower peak alpha frequencies (9.72 Hz vs 10.40 Hz, p = .02, Cohen's d = 0.73) and this decrease was driven by slowing over the central and posterior scalp. There was no difference in alpha power. Alpha waves propagated primarily from anterior to posterior and that propagation was slowed in patients. During SSVEP, patients had smaller increases in EEG power in the stimulation band (F(1,184) = 5.3, p = .02). Patients had attenuated responses to SSVEP stimulation at alpha, beta and gamma frequencies. The gamma response was partially preserved in patients who also had depressive symptoms. We conclude that even in early stages of illness, psychotic disorders are associated with decreased alpha peak frequency and impaired evoked resonances. These findings implicate multiple patterns of dysconnectivity in cortico-cortico and cortico-thalamic networks in FEP.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Altered Electroencephalographic Resting-State Large-Scale Brain Network Dynamics in Euthymic Bipolar Disorder Patients

Background: Neuroimaging studies provided evidence for disrupted resting-state functional brain network activity in bipolar disorder (BD). Electroencephalographic (EEG) studies found altered temporal characteristics of functional EEG microstates during depressive episode within different affective disorders. Here we investigated whether euthymic patients with BD show deviant resting-state large-scale brain network dynamics as reflected by altered temporal characteristics of EEG microstates. Methods: We used high-density EEG to explore between-group differences in duration, coverage, and occurrence of the resting-state functional EEG microstates in 17 euthymic adults with BD in on-medication state and 17 age- and gender-matched healthy controls. Two types of anxiety, state and trait, were assessed separately with scores ranging from 20 to 80. Results: Microstate analysis revealed five microstates (A-E) in global clustering across all subjects. In patients compared to controls, we found increased occurrence and coverage of microstate A that did not significantly correlate with anxiety scores. Conclusion: Our results provide neurophysiological evidence for altered large-scale brain network dynamics in BD patients and suggest the increased presence of A microstate to be an electrophysiological trait characteristic of BD.

Biomarkers for bipolar disorder: current status and challenges ahead

INTRODUCTION

Bipolar disorder (BD) is a chronic psychiatric disorder marked by clinical and pathophysiological heterogeneity. There is a high expectation that personalized approaches can improve the management of patients with BD. For that, identification and validation of potential biomarkers are fundamental. Areas covered: This manuscript will critically review the current status of different biomarkers for BD, including peripheral, genetic, neuroimaging, and neurophysiological candidates, discussing the challenges to move the field forward. Expert commentary: There are no lab or complementary tests currently recommended for the diagnosis or management of patients with BD. Panels composed by multiple biomarkers will probably contribute to stratifying patients according to their clinical stage, therapeutic response, and prognosis.

Complexity analysis of spontaneous brain activity in mood disorders: A magnetoencephalography study of bipolar disorder and major depression

BACKGROUND AND PURPOSE

The lack of a biomarker for Bipolar Disorder (BD) causes problems in the differential diagnosis with other mood disorders such as major depression (MD), and misdiagnosis frequently occurs. Bearing this in mind, we investigated non-linear magnetoencephalography (MEG) patterns in BD and MD.

METHODS

Lempel-Ziv Complexity (LZC) was used to evaluate the resting-state MEG activity in a cross-sectional sample of 60 subjects, including 20 patients with MD, 16 patients with BD type-I, and 24 control (CON) subjects. Particular attention was paid to the role of age. The results were aggregated by scalp region.

RESULTS

Overall, MD patients showed significantly higher LZC scores than BD patients and CONs. Linear regression analyses demonstrated distinct tendencies of complexity progression as a function of age, with BD patients showing a divergent tendency as compared with MD and CON groups. Logistic regressions confirmed such distinct relationship with age, which allowed the classification of diagnostic groups.

CONCLUSIONS

The patterns of neural complexity in BD and MD showed not only quantitative differences in their non-linear MEG characteristics but also divergent trajectories of progression as a function of age. Moreover, neural complexity patterns in BD patients resembled those previously observed in schizophrenia, thus supporting preceding evidence of common neuropathological processes.

Shared and Disorder-Specific Event-Related Brain Oscillatory Markers of Attentional Dysfunction in ADHD and Bipolar Disorder

Attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) often present with overlapping symptoms and cognitive impairments, such as increased fluctuations in attentional performance measured by increased reaction-time variability (RTV). We previously provided initial evidence of shared and distinct event-related potential (ERP) impairments in ADHD and BD in a direct electrophysiological comparison, but no study to date has compared neural mechanisms underlying attentional impairments with finer-grained brain oscillatory markers. Here, we aimed to compare the neural underpinnings of impaired attentional processes in ADHD and BD, by examining event-related brain oscillations during a reaction-time task under slow-unrewarded baseline and fast-incentive conditions. We measured cognitive performance, ERPs and brain-oscillatory modulations of power and phase variability in 20 women with ADHD, 20 women with BD (currently euthymic) and 20 control women. Compared to controls, both ADHD and BD groups showed increased RTV in the baseline condition and increased RTV, theta phase variability and lower contingent negative variation in the fast-incentive condition. Unlike controls, neither clinical group showed an improvement from the slow-unrewarded baseline to the fast-incentive condition in attentional P3 amplitude or alpha power suppression. Most impairments did not differ between the disorders, as only an adjustment in beta suppression between conditions (lower in the ADHD group) distinguished between the clinical groups. These findings suggest shared impairments in women with ADHD and BD in cognitive and neural variability, preparatory activity and inability to adjust attention allocation and activation. These overlapping impairments may represent shared neurobiological mechanisms of attentional dysfunction in ADHD and BD, and potentially underlie common symptoms in both disorders.

Temporal Courses in EEG Theta and Alpha Activity in the Dynamic Health Qigong Techniques Wu Qin Xi and Liu Zi Jue

Health Qigong is a common technique of Traditional Chinese Medicine applied to strengthen mental and physical health. Several studies report increases in EEG theta and alpha activity after meditative Qigong techniques indicating a relaxed state of mind. To date, little is known on the effects of dynamic Health Qigong techniques that comprise bodily movements on brain activity. In the current study, we compared effects of two dynamic Health Qigong techniques on EEG brain activity. Subjects performed the techniques Wu Qin Xi (five animals play) and Liu Zi Jue (six healing sounds) in a within-subjects design. Eyes-open and eyes-closed resting EEG was recorded before and immediately after each 15-min practice block. Additionally, the Profile of Mood States (POMS) questionnaire was administered at pretest, and after each 15-min practice block. Results show a decrease in alpha activity after 15 min, followed by an increase after 30 min in the Health Qigong technique Liu Zi Jue. Theta activity was decreased after 15 min, followed by an increase after 30 min in the technique Wu Qin Xi. Results of the POMS indicated an increased vigor-activity level with decreased fatigue and tension-anxiety levels in both techniques after 30 min of practice. Our results demonstrate different temporal dynamics in EEG theta and alpha activity for the Health Qigong techniques Wu Qin Xi and Liu Zi Jue. We hypothesize that the found brain activation patterns result from different attentional focusing styles and breathing techniques performed during the investigated Health Qigong techniques.

Usage of drip drops as stimuli in an auditory P300 BCI paradigm

Recently, many auditory BCIs are using beeps as auditory stimuli, while beeps sound unnatural and unpleasant for some people. It is proved that natural sounds make people feel comfortable, decrease fatigue, and improve the performance of auditory BCI systems. Drip drop is a kind of natural sounds that makes humans feel relaxed and comfortable. In this work, three kinds of drip drops were used as stimuli in an auditory-based BCI system to improve the user-friendness of the system. This study explored whether drip drops could be used as stimuli in the auditory BCI system. The auditory BCI paradigm with drip-drop stimuli, which was called the drip-drop paradigm (DP), was compared with the auditory paradigm with beep stimuli, also known as the beep paradigm (BP), in items of event-related potential amplitudes, online accuracies and scores on the likability and difficulty to demonstrate the advantages of DP. DP obtained significantly higher online accuracy and information transfer rate than the BP (p < 0.05, Wilcoxon signed test; p < 0.05, Wilcoxon signed test). Besides, DP obtained higher scores on the likability with no significant difference on the difficulty (p < 0.05, Wilcoxon signed test). The results showed that the drip drops were reliable acoustic materials as stimuli in an auditory BCI system.

EEG Brain Activity in Dynamic Health Qigong Training: Same Effects for Mental Practice and Physical Training?

In recent years, there has been significant uptake of meditation and related relaxation techniques, as a means of alleviating stress and fostering an attentive mind. Several electroencephalogram (EEG) studies have reported changes in spectral band frequencies during Qigong meditation indicating a relaxed state. Much less is reported on effects of brain activation patterns induced by Qigong techniques involving bodily movement. In this study, we tested whether (1) physical Qigong training alters EEG theta and alpha activation, and (2) mental practice induces the same effect as a physical Qigong training. Subjects performed the dynamic Health Qigong technique Wu Qin Xi (five animals) physically and by mental practice in a within-subjects design. Experimental conditions were randomized. Two 2-min (eyes-open, eyes-closed) EEG sequences under resting conditions were recorded before and immediately after each 15-min exercise. Analyses of variance were performed for spectral power density data. Increased alpha power was found in posterior regions in mental practice and physical training for eyes-open and eyes-closed conditions. Theta power was increased after mental practice in central areas in eyes-open conditions, decreased in fronto-central areas in eyes-closed conditions. Results suggest that mental, as well as physical Qigong training, increases alpha activity and therefore induces a relaxed state of mind. The observed differences in theta activity indicate different attentional processes in physical and mental Qigong training. No difference in theta activity was obtained in physical and mental Qigong training for eyes-open and eyes-closed resting state. In contrast, mental practice of Qigong entails a high degree of internalized attention that correlates with theta activity, and that is dependent on eyes-open and eyes-closed resting state.

Multivariate multi-scale weighted permutation entropy analysis of EEG complexity for Alzheimer's disease

The complexity change of brain activity in Alzheimer's disease (AD) is an interesting topic for clinical purpose. To investigate the dynamical complexity of brain activity in AD, a multivariate multi-scale weighted permutation entropy (MMSWPE) method is proposed to measure the complexity of electroencephalograph (EEG) obtained in AD patients. MMSWPE combines the weighted permutation entropy and the multivariate multi-scale method. It is able to quantify not only the characteristics of different brain regions and multiple time scales but also the amplitude information contained in the multichannel EEG signals simultaneously. The effectiveness of the proposed method is verified by both the simulated chaotic signals and EEG recordings of AD patients. The simulation results from the Lorenz system indicate that MMSWPE has the ability to distinguish the multivariate signals with different complexity. In addition, the EEG analysis results show that in contrast with the normal group, the significantly decreased complexity of AD patients is distributed in the temporal and occipitoparietal regions for the theta and the alpha bands, and also distributed from the right frontal to the left occipitoparietal region for the theta, the alpha and the beta bands at each time scale, which may be attributed to the brain dysfunction. Therefore, it suggests that the MMSWPE method may be a promising method to reveal dynamic changes in AD.

EEG classification of adolescents with type I and type II of bipolar disorder

Bipolar disorder (BD) is a severe psychiatric disorder and has two common types: type I and type II. Early diagnosis of the subtypes is very challenging particularly in adolescence. In this study, 38 adolescents are participated including 18 patients with BD I and 20 patients with BD II. The electroencephalogram signal is recorded by 19 electrodes in open eyes at resting state. After preprocessing, the state of the art methods from various domains are implemented to provide a good feature set for classifying the two groups. In order to improve the classification accuracy, four different feature selection methods named mutual information maximization (MIM), conditional mutual information maximization (CMIM), fast correlation based filter (FCBF), and double input symmetrical relevance (DISR) are applied to select the most informative features. Multilayer perceptron (MLP) neural network with a hidden layer containing five neurons is used for classification with and without applying the feature selection methods. The accuracy of 82.68, 86.33, 89.67, 84.61, and 91.83 % were observed using entire extracted features and selected features using MIM, CMIM, FCBF, and DISR methods by MLP, respectively. Therefore, the proposed method can be used in clinical setting for more validation.

Commonalities in EEG Spectral Power Abnormalities Between Women With ADHD and Women With Bipolar Disorder During Rest and Cognitive Performance

While attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) denote distinct psychiatric conditions, diagnostic delineation is impeded by considerable symptomatic overlap. Direct comparisons across ADHD and BD on neurophysiological measures are limited. They could inform us on impairments that are specific to or shared between the disorders and, therefore, potential biomarkers that may aid in the identification of the diagnostic boundaries. Our aim was to test whether quantitative EEG (QEEG) identifies differences or similarities between women with ADHD and women with BD during resting-state and task conditions. QEEG activity was directly compared between 20 ADHD, 20 BD and 20 control women during an eyes-open resting-state condition (EO) and a cued continuous performance task (CPT-OX). Both ADHD (t₃₈ = 2.50, p = 0.017) and BD (t₃₈ = 2.54, p = 0.018) participants showed higher absolute theta power during EO than controls. No significant differences emerged between the two clinical groups. While control participants showed a task-related increase in absolute theta power from EO to CPT-OX (t₁₉ = −3.77, p = 0.001), no such change in absolute theta power was observed in the ADHD (t₁₉ = −0.605, p = 0.553) or BD (t₁₉ = 1.82, p = 0.084) groups. Our results provide evidence for commonalities in brain dysfunction between ADHD and BD. Absolute theta power may play a role as a marker of neurobiological processes in both disorders.

Alpha oscillations and their impairment in affective and post-traumatic stress disorders

Affective and anxiety disorders are debilitating conditions characterized by impairments in cognitive and social functioning. Elucidating their neural underpinnings may assist in improving diagnosis and developing targeted interventions. Neural oscillations are fundamental for brain functioning. Specifically, oscillations in the alpha frequency range (alpha rhythms) are prevalent in the awake, conscious brain and play an important role in supporting perceptual, cognitive, and social processes. We review studies utilizing various alpha power measurements to assess abnormalities in brain functioning in affective and anxiety disorders as well as obsessive compulsive and post-traumatic stress disorders. Despite some inconsistencies, studies demonstrate associations between aberrant alpha patterns and these disorders both in response to specific cognitive and emotional tasks and during a resting state. We conclude by discussing methodological considerations and future directions, and underscore the need for much further research on the role of alpha functionality in social contexts. As social dysfunction accompanies most psychiatric conditions, research on alpha's involvement in social processes may provide a unique window into the neural mechanisms underlying these disorders.

Increased Beta Frequency (15-30 Hz) Oscillatory Responses in Euthymic Bipolar Patients Under Lithium Monotherapy

The effect of lithium on neurocognition is not still fully explored. Brain oscillatory activity is altered in bipolar disorder. We aimed to assess the oscillatory responses of euthymic bipolar patients and how they are affected by lithium monotherapy. Event-related oscillations in response to visual target stimulus during an oddball paradigm in 16 euthymic drug-free and 13 euthymic lithium-treated bipolar patients were compared with 16 healthy controls. The maximum peak-to-peak amplitudes were measured for each subject's averaged beta (15-30 Hz) responses in the 0- to 300-ms time window over frontal (F3, Fz, F4), central (C3, Cz, C4), temporal (T7, T8), temporo-parietal (TP7, TP8), parietal (P3, Pz, P4), and occipital (O1, Oz, O2) areas. Patients under lithium monotherapy had significantly higher beta responses to visual target stimuli than healthy controls (P=.017) and drug-free patients (P=.015). The increase in beta response was observed at all electrode locations, however, the difference was statistically significant for the left (T7; P=.016) and right (T8; P=.031) temporal beta responses. Increased beta responses in drug-free patients and further significant increase in lithium-treated patients may be indicative of a core pathophysiological process of bipolar disorder and how it is affected by lithium. Whether the finding corresponds to lithium's corrective effect on the underlying pathology or to its neurocognitive side effect remains to be further explored. In either case, the finding is a sign that the oscillatory activity may be useful in tracking medication effect in bipolar disorder.

Brain oscillations in bipolar disorder and lithium-induced changes

Electroencephalography (EEG) studies in patients with bipolar disorder have revealed lower amplitudes in brain oscillations. The aim of this review is to describe lithium-induced EEG changes in bipolar disorder and to discuss potential underlying factors. A literature survey about lithium-induced EEG changes in bipolar disorder was performed. Lithium consistently enhances magnitudes of brain oscillations in slow frequencies (delta and theta) in both resting-state EEG studies as well as event-related oscillations studies. Enhancement of magnitudes of beta oscillations is specific to event-related oscillations. Correlation between serum lithium levels and brain oscillations has been reported. Lithium-induced changes in brain oscillations might correspond to lithium-induced alterations in neurotransmitters, signaling cascades, plasticity, brain structure, or biophysical properties of lithium. Therefore, lithium-induced changes in brain oscillations could be promising biomarkers to assess the molecular mechanisms leading to variability in efficacy. Since the variability of lithium response in bipolar disorder is due to the genetic differences in the mechanisms involving lithium, it would be highly promising to assess the lithium-induced EEG changes as biomarkers in genetic studies.

Topographic deficits in alpha-range resting EEG activity and steady state visual evoked responses in schizophrenia

Deficits in both resting alpha-range (8-12Hz) electroencephalogram (EEG) activity and steady state evoked potential (SSVEP) responses have been reported in schizophrenia. However, the topographic specificity of these effects, the relationship between resting EEG and SSVEP, as well as the impact of antipsychotic medication on these effects, have not been clearly delineated. The present study sought to address these questions with 256 channel high-density EEG recordings in a group of 13 schizophrenia patients, 13 healthy controls, and 10 non-schizophrenia patients with psychiatric diagnoses currently taking antipsychotic medication. At rest, the schizophrenia group demonstrated decreased alpha EEG power in frontal and occipital areas relative to healthy controls. With SSVEP stimulation centered in the alpha band (10Hz), but not with stimulation above (15Hz) or below (7Hz) this range, the occipital deficit in alpha power was partially reverted. However, the frontal deficit persisted and contributed to a significantly reduced topographic relationship between occipital and frontal alpha activity for resting EEG and 10Hz SSVEP alpha power in schizophrenia patients. No significant differences were observed between healthy and medicated controls or between medicated controls and schizophrenia. These findings suggest a potential intrinsic deficit in frontal eyes-closed EEG alpha oscillations in schizophrenia, whereby potent visual stimulation centered in that frequency range results in an increase in the occipital alpha power of these patients, which however does not extend to frontal regions. Future research to evaluate the cortical and subcortical mechanisms of these effects is warranted.

Slowed peak resting frequency and MEG overactivation in survivors of severe sepsis and septic shock

OBJECTIVE

Survivors of severe sepsis and septic shock suffer from residual severe cognitive impairments, which persist even years after intensive care unit (ICU) discharge. As the awareness of long-term consequences gradually grows, research has focused on cognitive impairments via questionnaires, but only few have focused on structural or electrophysiological features, such as the peak resting frequency, which is commonly seen as a hallmark of brain function.

METHODS

We aimed to analyze the long-term progression of the peak resting activity in terms of frequency and power in sepsis survivors. Healthy individuals with no history of ICU stay served as controls. Data were collected three times (shortly, 6 and 12 months after ICU discharge) in sepsis survivors and three times in controls. Participants also underwent behavioral neuropsychological assessment.

RESULTS

Sepsis survivors exhibited significantly higher spectral power of the dominant peak, which was shifted towards lower frequencies. Within one year, resting frequency increased to the level of controls, but power did not decrease. We observed a close correlation between resting frequency and mental status.

CONCLUSIONS

Results support the assumption of a causal relationship between brain oscillations and behavioral performance.

SIGNIFICANCE

We suggest that the postseptic frequency shift is due to abnormal thalamocortical dynamics.

Altered structure of dynamic electroencephalogram oscillatory pattern in major depression

Research on electroencephalogram (EEG) characteristics associated with major depressive disorder (MDD) has accumulated diverse neurophysiologic findings related to the content, topography, neurochemistry, and functions of EEG oscillations. Significant progress has been made since the first landmark EEG study on affective disorders by Davidson 35 years ago. A systematic account of these data is important and necessary for building a consistent neuropsychophysiologic model of MDD and other affective disorders. Given the extensive data on frequency-dependent functional significance of EEG oscillations, a frequency domain approach may reveal the types of brain functions involved and disturbed in MDD. In this review, we systematize and integrate diverse and often unconnected observations on the content, topography, neurochemistry, and functions of EEG oscillations involved in MDD within the general concept of an EEG oscillatory pattern.

Electroencephalography Spectral Power Density in First-Episode Mania: A Comparative Study with Subsequent Remission Period

INTRODUCTION

Our aim in this study was to investigate spectral power density (PSD) in first-episode mania and subsequent remission period and to evaluate their difference.

METHODS

Sixty-nine consecutive cases referring to our hospital within the previous 1 year, who were evaluated as bipolar disorder manic episode according to The Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) at the first episode and had the informed consent form signed by first degree relatives, were included in this study. Exclusion criteria included having previous depressive episode, using drugs which could influence electroencephalographic activity before electroencephalography (EEG), and having previous neurological disease, particularly epilepsy, head trauma, and/or loss of consciousness. EEG records were obtained using a digital device in 16 channels; 23 surface electrodes were placed according to the International 10-20 system. Spectral power density (dbμV/Hz) of EEG signal provided information on the power carried out by EEG waves in defined frequancy range per unit frequency in the present study.

RESULTS

A peak power value detected on the right with FP2P4 and on the left with F7T3 electrodes were found to be higher in the manic episode than in the remission period (p=0.018 and 0.025). In the remission period, in cases with psychotic symptoms during the manic period, F4C4 peak power value was found to be lower than that in cases with no psychotic findings during the manic period (p=0.027). There was no relation was found between YMRS scores and peak power scores.

CONCLUSION

Electrophysiological corollary of mood episode is present from the onset of the disease, and it differs between the manic and remission periods of bipolar disorder. In the remission period, peak power values of PSD distinguish cases with psychotic findings from cases without psychotic findings when they were manic.

Characteristics of Alpha Band Frequency in Adolescents with Bipolar II Disorder: A Resting-State QEEG Study

OBJECTIVE

The aim of this study was to compare the QEEG of adolescents affected by bipolar II disorder with age and gender matched healthy controls, and to extract the characteristics of the alpha frequency band to better understand this disorder.

METHODS

Twenty one adolescents affected by acute episodes of bipolar II disorder (BMD II), both hypomanic and depressive episodes, were selected via convenience sampling based on DSM IV criteria and child and adolescent psychiatrist diagnosis. Eleven patients were going through a hypomanic episode and 10 patients were going through a depression episode. Of the participants, 18 who were matched with the patient group participated in this study as a normal group. Any major comorbidities and intellectual disabilities were excluded through applying K-SADS-PL and Raven's IQ test for all the patients and the healthy participants. Electroencephalogram signals were obtained according to 10-20 international system by 21 electrodes from participants in open and closed eyes in a resting state. We selected 40 seconds length segments from each recorded EEG signals that had minimal noise and artifacts. Power spectrum density (PSD) was estimated for each segment and extracted alpha band frequency. We used only referential (unipolar) montage for comparison. Eventually, data were analyzed by independent Mann-Whitney test and independent t test.

RESULTS

We observed significant differences in the alpha frequency band in some brain regions. Alpha power increased in the fronto-central region and right parietal lobe in the patients (P < 0.05). In the patients with BMD II, entropy of alpha oscillations was larger than the normal participants in the central region and in the F3, F4 and P4 channels. Also, there were differences in the variance of alpha oscillations in these regions between the two groups (P < 0.05). In the occipital lobe, alpha wave had different skewness between the two groups (P < 0.05).

CONCLUSION

Thalamus as a generator and modulator of at least a part of alpha oscillations may be involved in this disorder and hence this explains the major symptoms like distractibility and inattention in both hypomanic and depressive episodes of bipolar II disorder.

Lithium excessively enhances event related beta oscillations in patients with bipolar disorder

BACKGROUND

Previous resting-state electroencephalography studies have consistently shown that lithium enhances delta and theta oscillations in default mode networks. Cognitive task based networks differ from resting-state networks and this is the first study to investigate effects of lithium on evoked and event-related beta oscillatory responses of patients with bipolar disorder.

METHODS

The study included 16 euthymic patients with bipolar disorder on lithium monotherapy, 22 euthymic medication-free patients with bipolar disorder and 21 healthy participants. The maximum peak-to-peak amplitudes were measured for each subject's averaged beta responses (14-28 Hz) in the 0-300 ms time window. Auditory simple and oddball paradigm were presented to obtain evoked and event-related beta oscillatory responses.

RESULTS

There were significant differences in beta oscillatory responses between groups (p=0.010). Repeated measures ANOVA revealed location (p=0.007), laterality X group (p=0.043) and stimulus X location (p=0.013) type effects. Serum lithium levels were correlated with beta responses.

LIMITATIONS

The lithium group had higher number of previous episodes, suggesting that patients of the lithium were more severe cases than patients of the medication-free group.

DISCUSSION

Lithium stimulates neuroplastic cascades and beta oscillations become prominent during neuroplastic changes. Excessively enhanced beta oscillatory responses in the lithium-treated patients may be indicative of excessive activation of the neuron groups of the certain cognitive networks and dysfunctional GABAergic modulation during cognitive activity.

Brain electrical source imaging in manic and depressive episodes of bipolar disorder

OBJECTIVE

Bipolar disorder (BD) electroencephalographic (EEG) studies have reported varying results. The present study compared EEG in BD during manic and depressive episodes, using brain electrical source imaging [standardized low-resolution electromagnetic tomography (sLORETA)] to assess the cortical spatial distribution of the sources of EEG oscillation frequencies.

METHODS

Two independent datasets (a total of 95 patients with bipolar I disorder, of whom 59 were female) were analyzed. Dataset #1 comprised 14 patients in a manic as well as a depressive episode. Dataset #2 comprised 26 patients in a manic episode and 55 patients in a depressive episode. From the head surface-recorded EEG, sLORETA cortical activity was computed in eight EEG frequency bands, and compared between mood states in both datasets. The results from the two datasets were combined using conjunction analysis.

RESULTS

Conjunction analysis yielded significant differences between mood states: In manic compared to depressive states, patients had lesser theta frequency band activity (right-hemispheric lateral lower prefrontal and anterior temporal, mainly Brodmann areas 13, 38, and 47), and greater beta-2 and beta-3 frequency band activity (extended bilateral prefrontal-to-parietal, mainly Brodmann area 6, and the cingulate).

CONCLUSIONS

The spatial organization of the brain's electrical oscillations differed in patients with BD between manic and depressive mood states. The brain areas implementing the main functions that show opposing abnormalities during manic and depressive episodes were affected by unduly increased or decreased activity (beta or theta). The discussion considers that facilitating (beta) or inhibiting (theta) electrical activity can in either case result in behavioral facilitation or inhibition, depending on the function of the brain area.

Non-invasive detection of high gamma band activity during motor imagery

High gamma oscillations (70-150 Hz; HG) are rapidly evolving, spatially localized neurophysiological signals that are believed to be the best representative signature of engaged neural populations. The HG band has been best characterized from invasive electrophysiological approaches such as electrocorticography because of the increased signal-to-noise ratio that results when by-passing the scalp and skull. Despite the recent observation that HG activity can be detected non-invasively by electroencephalography (EEG), it is unclear to what extent EEG can accurately resolve the spatial distribution of HG signals during active task engagement. We have overcome some of the limitations inherent to acquiring HG signals across the scalp by utilizing individual head anatomy in combination with an inverse modeling method. We applied a linearly constrained minimum variance (LCMV) beamformer method on EEG data during a motor imagery paradigm to extract a time-frequency spectrogram at every voxel location on the cortex. To confirm spatially distributed patterns of HG responses, we contrasted overlapping maps of the EEG HG signal with blood oxygen level dependence (BOLD) functional magnetic resonance imaging (fMRI) data acquired from the same set of neurologically normal subjects during a separate session. We show that scalp-based HG band activity detected by EEG during motor imagery spatially co-localizes with BOLD fMRI data. Taken together, these results suggest that EEG can accurately resolve spatially specific estimates of local cortical high frequency signals, potentially opening an avenue for non-invasive measurement of HG potentials from diverse sets of neurologically impaired populations for diagnostic and therapeutic purposes.

Decrease of event-related delta oscillations in euthymic patients with bipolar disorder

Decreased delta oscillation upon cognitive load is common in patients with Alzheimer׳s disease, mild cognitive impairment, and schizophrenia. However, there is no previous study analyzing the delta responses in euthymic medication-free patients with bipolar disorder. Participants comprised of 22 euthymic medication-free patients with DSM-IV diagnoses of bipolar disorder and 21 healthy controls who were matched to the patients for sex, age, and education. Electroencephalographic activity was recorded at 30 electrode sites using an application of an auditory oddball paradigm. The maximum peak-to-peak amplitudes for each subject׳s averaged delta response (0.5-3.5Hz) were measured. There was a significant inter-group difference in evoked and event-related delta (0.5-3.5Hz) responses. Post-hoc comparisons revealed that the event-related delta oscillatory responses of the bipolar patient group were significantly lower than those of the healthy control group over the temporo-parietal and occipital electrode sites. Euthymic bipolar patients showed reduced event-related delta oscillatory responses in comparison to healthy subjects under cognitive load. The decrease of delta oscillations may be a common phenomenon that can be observed in different neuropsychiatric disorders with cognitive dysfunction.

Brain oscillations in neuropsychiatric disease

The term “brain (or neural) oscillations” refers to the rhythmic and/or repetitive electrical activity generated spontaneously and in response to stimuli by neural tissue in the central nervous system. The importance of brain oscillations in sensory-cognitive processes has become increasingly evident. It has also become clear that event-related oscillations are modified in many types of neuropathology, in particular in cognitive impairment. This review discusses methods such as evoked/event-related oscillations and spectra, coherence analysis, and phase locking. It gives examples of applications of essential methods and concepts in bipolar disorder that provide a basis for fundamental notions regarding neurophysiologic biomarkers in cognitive impairment. The take-home message is that in the development of diagnostic and pharmacotherapeutic strategies, neurophysiologic data should be analyzed in a framework that uses a multiplicity of methods and frequency bands.

Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia

Resting state electroencephalogram (EEG) abnormalities in schizophrenia and bipolar disorder patients suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies between patient groups, and none have examined EEG coherence. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 76 bipolar patients (BP), 132 schizophrenia patients (SZ), and 136 non-psychiatric controls (NC). We conducted separate repeated-measures ANOVAs to examine group differences within seven frequency bands across several brain regions. BP showed significantly greater power relative to SZ at higher frequencies including Beta and Gamma across all regions. In terms of intra-hemispheric coherence, while SZ generally exhibited higher coherence at Delta compared to NC and BP, both SZ and BP showed higher coherence at Alpha1 and Alpha2. In contrast, BP and HC showed higher coherence within hemispheres compared to SZ at Beta 1. In terms of inter-hemispheric coherence, SZ displayed higher coherence compared to NC at temporal sites at both Alpha1 and Alpha2. Taken together, BP exhibited increased high frequency power with few disruptions in neural synchronization. In contrast, SZ generally exhibited enhanced synchronization within and across hemispheres. These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical disorders.