Distinct neuronal oscillatory responses between patients with bipolar and unipolar disorders: a magnetoencephalographic study

Sex-specific effects of subchronic NMDA receptor antagonist MK-801 treatment on hippocampal gamma oscillations

N-methyl-D-aspartate (NMDA) receptor antagonists are widely used to pharmacologically model schizophrenia and have been recently established in the treatment of treatment-resistant major depression demonstrating that the pharmacology of this substance class is complex. Cortical gamma oscillations, a rhythmic neuronal activity associated with cognitive processes, are increased in schizophrenia and deteriorated in depressive disorders and are increasingly used as biomarker in these neuropsychiatric diseases. The opposite use of NMDA receptor antagonists in schizophrenia and depression raises the question how their effects are in accordance with the observed disease pathophysiology and if these effects show a consequent sex-specificity. In this study in rats, we investigated the effects of subchronic (14 days) intraperitoneal injections of the NMDA receptor antagonist MK-801 at a subanesthetic daily dose of 0.2 mg/kg on the behavioral phenotype of adult female and male rats and on pharmacologically induced gamma oscillations measured ex vivo from the hippocampus. We found that MK-801 treatment leads to impaired recognition memory in the novel object recognition test, increased stereotypic behavior and reduced grooming, predominantly in female rats. MK-801 also increased the peak power of hippocampal gamma oscillations induced by kainate or acetylcholine only in female rats, without affecting the peak frequency of the oscillations. The findings indicate that blockade of NMDA receptors enhances gamma oscillations predominantly in female rats and this effect is associated with behavioral changes in females. The results are in accordance with clinical electrophysiological findings and highlight the importance of hippocampal gamma oscillations as a biomarker in schizophrenia and depression.

Major depressive disorder recognition by quantifying EEG signal complexity using proposed APLZC and AWPLZC

BACKGROUND

Seeking objective quantitative indicators is important for accurately recognizing major depressive disorder (MDD). Lempel-Ziv complexity (LZC), employed to characterize neurological disorders, faces limitations in tracking dynamic changes in EEG signals due to defects in the coarse-graining process, hindering its precision for MDD objective quantitative indicators.

METHODS

This work proposed Adaptive Permutation Lempel-Ziv Complexity (APLZC) and Adaptive Weighted Permutation Lempel-Ziv Complexity (AWPLZC) algorithms by refining the coarse-graining process and introducing weight factors to effectively improve the precision of LZC in characterizing EEGs and further distinguish MDD patients better. APLZC incorporated the ordinal pattern, while False Nearest Neighbor and Mutual Information algorithms were introduced to determine and adjust key parameters adaptively. Furthermore, we proposed AWPLZC by assigning different weights to each pattern based on APLZC. Thirty MDD patients and 30 healthy controls (HCs) were recruited and their 64-channel resting EEG signals were collected. The complexities of gamma oscillations were then separately computed using LZC, APLZC, and AWPLZC algorithms. Subsequently, a multi-channel adaptive K-nearest neighbor model was constructed for identifying MDD patients and HCs.

RESULTS

LZC, APLZC, and AWPLZC algorithms achieved accuracy rates of 78.29 %, 90.32 %, and 95.13 %, respectively. Sensitivities reached 67.96 %, 85.04 %, and 98.86 %, while specificities were 88.62 %, 95.35 %, and 89.92 %, respectively. Notably, AWPLZC achieved the best performance in accuracy and sensitivity, with a specificity limitation.

LIMITATION

The sample size is relatively small.

CONCLUSION

APLZC and AWPLZC algorithms, particularly AWPLZC, demonstrate superior effectiveness in differentiating MDD patients from HCs compared with LZC. These findings hold significant clinical implications for MDD diagnosis.

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.

Neuroplasticity of the left dorsolateral prefrontal cortex in patients with treatment-resistant depression as indexed with paired associative stimulation: a TMS-EEG study

Major depressive disorder affects over 300 million people globally, with approximately 30% experiencing treatment-resistant depression (TRD). Given that impaired neuroplasticity underlies depression, the present study focused on neuroplasticity in the dorsolateral prefrontal cortex (DLPFC). Here, we aimed to investigate the differences in neuroplasticity between 60 individuals with TRD and 30 age- and sex-matched healthy controls (HCs). To induce neuroplasticity, participants underwent a paired associative stimulation (PAS) paradigm involving peripheral median nerve stimulation and transcranial magnetic stimulation (TMS) targeting the left DLPFC. Neuroplasticity was assessed by using measurements combining TMS with EEG before and after PAS. Both groups exhibited significant increases in the early component of TMS-evoked potentials (TEP) after PAS (P < 0.05, paired t-tests with the bootstrapping method). However, the HC group demonstrated a greater increase in TEPs than the TRD group (P = 0.045, paired t-tests). Additionally, event-related spectral perturbation analysis highlighted that the gamma power significantly increased after PAS in the HC group, whereas it was decreased in the TRD group (P < 0.05, paired t-tests with the bootstrapping method). This gamma power modulation revealed a significant group difference (P = 0.006, paired t-tests), indicating an inverse relationship for gamma power modulation. Our findings underscore the impaired neuroplasticity of the DLPFC in individuals with TRD.

Predictive Biomarkers of Treatment Response in Major Depressive Disorder

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain's electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Logistic regression modeling was used to predict treatment response, defined as at least a 50% improvement on the Beck's Depression Inventory, in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). The results show that both age and baseline symptom severity were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance. These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.

Reductions in regional theta power and fronto-parietal theta-gamma phase-amplitude coupling during gaze processing in bipolar disorder

Impaired social cognition is common in bipolar disorder (BD) and predicts poor functional outcomes. A critical determinant of social cognition is the ability to discriminate others' gaze direction, and its alteration may contribute to functional impairment in BD. However, the neural mechanisms underlying gaze processing in BD are unclear. Because neural oscillations are crucial neurobiological mechanisms supporting cognition, we aimed to understand their role in gaze processing in BD. Using electroencephalography (EEG) data recorded during a gaze discrimination task for 38 BD and 34 controls (HC), we examined: theta and gamma power over bilateral posterior and midline anterior locations associated with early face processing and higher-level cognitive processing, and theta-gamma phase-amplitude coupling (PAC) between locations. Compared to HC, BD showed reduced midline-anterior and left-posterior theta power, and diminished bottom-up/top-down theta-gamma PAC between anterior/posterior sites. Reduced theta power and theta-gamma PAC related to slower response times. These findings suggest that altered theta oscillations and anterior-posterior cross-frequency coupling between areas associated with higher-level cognition and early face processing may underlie impaired gaze processing in BD. This is a crucial step towards translational research that may inform novel social cognitive interventions (e.g., neuromodulation to target specific oscillatory dynamics) to improve functioning in BD.

Ketamine supresses REM sleep and markedly increases EEG gamma oscillations in the Wistar Kyoto rat model of treatment-resistant depression

Wistar-Kyoto (WKY) rats exhibit depression-like characteristics and decreased sensitivity to monoamine-based antidepressants, making them a suitable model of treatment-resistant depression (TRD). Ketamine has emerged recently as a rapidly acting antidepressant with high efficacy in TRD. Our aim was to determine whether subanaesthetic doses of ketamine can correct sleep and electroencephalogram (EEG) alterations in WKY rats and whether any ketamine-induced changes differentially affect WKY rats compared to Sprague-Dawley (SD) rats. Thus, we surgically implanted 8SD and 8 WKY adult male rats with telemetry transmitters and recorded their EEG, electromyogram, and locomotor activity after vehicle or ketamine (3, 5 or 10mg/kg, s.c.) treatment. We also monitored the plasma concentration of ketamine and its metabolites, norketamine and hydroxynorketamine in satellite animals. We found that WKY rats, have an increased amount of rapid eye movement (REM) sleep, fragmented sleep-wake pattern, and increased EEG delta power during non-REM sleep compared to SD rats. Ketamine suppressed REM sleep and increased EEG gamma power during wakefulness in both strains, but the gamma increase was almost twice as large in WKY rats than in SD rats. Ketamine also increased beta oscillations, but only in WKY rats. These differences in sleep and EEG are unlikely to be caused by dissimilarities in ketamine metabolism as the plasma concentrations of ketamine and its metabolites were similar in both strains. Our data suggest an enhanced antidepressant-like response to ketamine in WKY rats, and further support the predictive validity of acute REM sleep suppression as a measure of antidepressant responsiveness.

Sex differences in amygdalohippocampal oscillations and neuronal activation in a rodent anxiety model and in response to infralimbic deep brain stimulation

Introduction

Depression and anxiety are highly comorbid mental disorders with marked sex differences. Both disorders show altered activity in the amygdala, hippocampus, and prefrontal cortex. Infralimbic deep brain stimulation (DBS-IL) has anxiolytic and antidepressant effects, but the underlying mechanisms remain unclear. We aimed to contribute to understanding sex differences in the neurobiology of these disorders.

Methods

In male and female rats, we recorded neural oscillations along the dorsoventral axis of the hippocampus and the amygdala in response to an anxiogenic drug, FG-7142. Following this, we applied DBS-IL.

Results

Surprisingly, in females, the anxiogenic drug failed to induce most of the changes observed in males. We found sex differences in slow, delta, theta, and beta oscillations, and the amygdalo-hippocampal communication in response to FG-7142, with modest changes in females. Females had a more prominent basal gamma, and the drug altered this band only in males. We also analyzed c-Fos expression in both sexes in stress-related structures in response to FG-7142, DBS-IL, and combined interventions. With the anxiogenic drug, females showed reduced expression in the nucleus incertus, amygdala, septohippocampal network, and neocortical levels. In both experiments, the DBS-IL reversed FG-7142-induced effects, with a more substantial effect in males than females.

Discussion

Here, we show a reduced response in female rats which contrasts with the higher prevalence of anxiety in women but is consistent with other studies in rodents. Our results open compelling questions about sex differences in the neurobiology of anxiety and depression and their study in animal models.

Discriminating between bipolar and major depressive disorder using a machine learning approach and resting-state EEG data

OBJECTIVE

Distinguishing major depressive disorder (MDD) from bipolar disorder (BD) is a crucial clinical challenge as effective treatment is quite different for each condition. In this study electroencephalography (EEG) was explored as an objective biomarker for distinguishing MDD from BD using an efficient machine learning algorithm (MLA) trained by a relatively large and balanced dataset.

METHODS

A 3 step MLA was applied: (1) a multi-step preprocessing method was used to improve the quality of the EEG signal, (2) symbolic transfer entropy (STE), an effective connectivity measure, was applied to the resultant EEG and (3) the MLA used the extracted STE features to distinguish MDD (N = 71) from BD (N = 71) subjects.

RESULTS

14 connectivity features were selected by the proposed algorithm. Most of the selected features were related to the frontal, parietal, and temporal lobe electrodes. The major involved regions were the Broca region in the frontal lobe and the somatosensory association cortex in the parietal lobe. These regions are near electrodes FC5 and CPz and are involved in processing language and sensory information, respectively. The resulting classifier delivered an evaluation accuracy of 88.5% and a test accuracy of 89.3%, using 80% of the data for training and evaluation and the remaining 20% for testing, respectively.

CONCLUSIONS

The high evaluation and test accuracies of our algorithm, derived from a large balanced training sample suggests that this method may hold significant promise as a clinical tool.

SIGNIFICANCE

The proposed MLA may provide an inexpensive and readily available tool that clinicians may use to enhance diagnostic accuracy and shorten time to effective treatment.

Convergent and divergent cognitive impairment of unipolar and bipolar depression: A magnetoencephalography resting-state study

BACKGROUND

Unipolar depression (UD) and bipolar depression (BD) showed convergent and divergent cognitive impairments. Neural oscillations are linked to the foundational cognitive processes. We aimed to investigate the underpinning spectral neuronal power patterns by magnetoencephalography (MEG), which combinates high spatial and temporal resolution. We hypothesized that patients with UD and BD exhibit common and distinct patterns, which may contribute to their cognitive impairments.

METHODS

Group cognitive tests were performed. Eyes closed resting-state MEG data were collected from 61 UD, 55 BD, and 52 healthy controls (HC). Nonparametric cluster-based permutation tests were performed to deal with the multiple comparison problem on channel-frequency MEG data. Correlation analysis of cognitive dysfunction scores and MEG oscillation were conducted by Spearman or partial correlation analysis.

RESULTS

Wisconsin Card Sorting Test showed similar cognitive impairment in patients with UD and BD. Moreover, patients with BD exhibited extensive cognitive deficits in verbal executive functions and visuospatial processing. Compare to HC, both patients with UD and BD showed increased frontal-central beta power while high gamma power was decreased in UD groups during the resting-state. The significant correlations between cognitive function and average beta power were observed.

CONCLUSIONS

Patients with BD had more cognitive impairments on different dimensions than those with UD, involving disrupted beta power modulations. Our investigation provides a better understanding of the neuroelectrophysiological process underlying cognitive impairments in patients with UD and BD.

Dysfunction of Emotion Regulation in Mild Cognitive Impairment Individuals Combined With Depressive Disorder: A Neural Mechanism Study

Depression increases the risk of progression from mild cognitive impairment (MCI) to dementia, where impaired emotion regulation is a core symptom of depression. However, the neural mechanisms underlying the decreased emotion regulation in individuals with MCI combined with depressive symptoms are not precise. We assessed the behavioral performance by emotion regulation tasks and recorded event-related electroencephalography (EEG) signals related to emotion regulation tasks simultaneously. EEG analysis, including event-related potential (ERP), event-related spectral perturbation (ERSP), functional connectivity and graph theory, was used to compare the difference between MCI individuals and MCI depressed individuals in behavioral performance, the late positive potential (LPP) amplitudes, neural oscillations and brain networks during the processing of emotional stimuli. We found that MCI depressed individuals have negative preferences and are prone to allocate more attentional resources to negative stimuli. Results suggested that theta and alpha oscillations activity is increased, and gamma oscillations activity is decreased during negative stimulus processing in MCI depressed individuals, thus indicating that the decreased emotion regulation in MCI depressed individuals may be associated with enhanced low-frequency and decreased high-frequency oscillations activity. Functional connectivity analysis revealed a decrease in functional connectivity in the left cerebral hemisphere of the alpha band and an increase in functional connectivity in the right cerebral hemisphere of the alpha band in MCI depressed individuals. Graph theory analysis suggested that global network metrics, including clustering coefficients and disassortative, decreased, while nodal and modular network metrics regarding local nodal efficiency, degree centrality, and betweenness centrality were significantly increased in the frontal lobe and decreased in the parieto-occipital lobe, which was observed in the alpha band, further suggesting that abnormal alpha band network connectivity may be a potential marker of depressive symptoms. Correlational analyses showed that depressive symptoms were closely related to emotion regulation, power oscillations and functional connectivity. In conclusion, the dominant processing of negative stimuli, the increased low-frequency oscillations activity and decreased high-frequency activity, so as the decrease in top-down information processing in the frontal parieto-occipital lobe, results in the abnormality of alpha-band network connectivity. It is suggested that these factors, in turn, contribute to the declined ability of MCI depressed individuals in emotion regulation.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

Hypofunction of directed brain network within alpha frequency band in depressive patients: a graph-theoretic analysis

Directed brain networks may provide new insights into exploring physiological mechanism and neuromarkers for depression. This study aims to investigate the abnormalities of directed brain networks in depressive patients. We constructed the directed brain network based on resting electroencephalogram for 19 depressive patients and 20 healthy controls with eyes closed and eyes open. The weighted directed brain connectivity was measured by partial directed coherence for α, β, γ frequency band. Furthermore, topological parameters (clustering coefficient, characteristic path length, and et al.) were computed based on graph theory. The correlation between network metrics and clinical symptom was also examined. Depressive patients had a significantly weaker value of partial directed coherence at alpha frequency band in eyes-closed state. Clustering coefficient and characteristic path length were significantly lower in depressive patients (both p < .01). More importantly, in depressive patients, disruption of directed connectivity was noted in left-to-left (p < .05), right-to-left (p < .01) hemispheres and frontal-to-central (p < .01), parietal-to-central (p < .05), occipital-to-central (p < .05) regions. Furthermore, connectivity in LL and RL hemispheres was negatively correlated with depression scale scores (both p < .05). Depressive patients showed a more randomized network structure, disturbed directed interaction of left-to-left, right-to-left hemispheric information and between different cerebral regions. Specifically, left-to-left, right-to-left hemispheric connectivity was negatively correlated with the severity of depression. Our analysis may serve as a potential neuromarker of depression.

The Oscillatory Profile Induced by the Anxiogenic Drug FG-7142 in the Amygdala-Hippocampal Network Is Reversed by Infralimbic Deep Brain Stimulation: Relevance for Mood Disorders

Anxiety and depression exhibit high comorbidity and share the alteration of the amygdala–hippocampal–prefrontal network, playing different roles in the ventral and dorsal hippocampi. Deep brain stimulation of the infralimbic cortex in rodents or the human equivalent—the subgenual cingulate cortex—constitutes a fast antidepressant treatment. The aim of this work was: (1) to describe the oscillatory profile in a rodent model of anxiety, and (2) to deepen the therapeutic basis of infralimbic deep brain stimulation in mood disorders. First, the anxiogenic drug FG-7142 was administered to anaesthetized rats to characterize neural oscillations within the amygdala and the dorsoventral axis of the hippocampus. Next, deep brain stimulation was applied. FG-7142 administration drastically reduced the slow waves, increasing delta, low theta, and beta oscillations in the network. Moreover, FG-7142 altered communication in these bands in selective subnetworks. Deep brain stimulation of the infralimbic cortex reversed most of these FG-7142 effects. Cross-frequency coupling was also inversely modified by FG-7142 and by deep brain stimulation. Our study demonstrates that the hyperactivated amygdala–hippocampal network associated with the anxiogenic drug exhibits an oscillatory fingerprint. The study contributes to comprehending the neurobiological basis of anxiety and the effects of infralimbic deep brain stimulation.

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.

The activity and connectivity of the facial emotion processing neural circuitry in bipolar disorder: a systematic review

BACKGROUND

Facial emotion processing abnormalities may be a trait feature of bipolar disorder (BD). These social cognitive impairments may be due to alterations in the neural processing of facial affective information in visual ("core"), and limbic and prefrontal ("extended") networks, however, the precise neurobiological mechanism(s) underlying these symptoms are unclear.

METHODS

We conducted a systematic review to appraise the literature on the activity and connectivity of the facial emotion processing neural circuitry in BD. Two reviewers undertook a search of the electronic databases PubMed, Scopus and PsycINFO, to identify relevant literature published since inception up until September 2019. Study eligibility criteria included; BD participants, neuroimaging, and facial emotion processing tasks.

RESULTS

Out of an initial yield of 6121 articles, 66 were eligible for inclusion in this review. We identified differences in neural activity and connectivity within and between occipitotemporal, limbic, and prefrontal regions, in response to facial affective stimuli, in BD compared to healthy controls.

LIMITATIONS

The methodologies used across studies varied considerably.

CONCLUSIONS

The findings from this review suggest abnormalities in both the activity and connectivity of facial emotion processing neural circuitry in BD. It is recommended that future research aims to further define the connectivity and spatiotemporal course of neural events within and between occipitotemporal, limbic, and prefrontal regions.

The Impact of Repetitive Transcranial Magnetic Stimulation on Functional Connectivity in Major Depressive Disorder and Bipolar Disorder Evaluated by Directed Transfer Function and Indices Based on Graph Theory

The objective of this work was to study the impact of repetitive Transcranial Magnetic Stimulation (rTMS) on the EEG connectivity evaluated by indices based on graph theory, derived from Directed Transfer Function (DTF), in patients with major depressive disorder (MDD) or with bipolar disorder (BD). The results showed the importance of beta and gamma rhythms. The indices density, degree and clustering coefficient increased in MDD responders in beta and gamma bands after rTMS. Interestingly, the density and the degree changed in theta band in both groups of nonresponders (decreased in MDD nonresponders but increased in BD nonresponders). Moreover, both indices of integration (the characteristic path length and the global efficiency) as well as the clustering coefficient increased in BD nonresponders for gamma band. In BD responders, the activity increased in the frontal lobe, mainly in the left hemisphere, while in MDD responders in the central posterior part of brain. The fronto-posterior asymmetry decreased in both groups of responders in delta and beta bands. Changes in inter-hemispheric asymmetry were found only in BD nonresponders in all bands, except gamma band. Comparison between groups showed that the degree increased in delta band independently on disease (BD, MDD). These preliminary results showed that the DTF may be a useful marker allowing for evaluation of effectiveness of the rTMS therapy as well for group differentiation between MDD and BD considering separately groups of responders and nonresponders. However, further investigation should be performed over larger groups of patients to confirmed our findings.

Electrophysiological biomarkers of antidepressant response to ketamine in treatment-resistant depression: Gamma power and long-term potentiation

Over the last two decades, the discovery of ketamine's antidepressant properties has galvanized research into the neurobiology of treatment-resistant depression. Nevertheless, the mechanism of action underlying antidepressant response to ketamine remains unclear. This study reviews electrophysiological studies of ketamine's effects in individuals with depression as well as healthy controls, with a focus on two putative markers of synaptic potentiation: gamma oscillations and long-term potentiation. The review focuses on: 1) measures of gamma oscillations and power and their relationship to both acute, psychotomimetic drug effects as well as delayed antidepressant response in mood disorders; 2) changes in long-term potentiation as a promising measure of synaptic potentiation following ketamine administration; and 3) recent efforts to model antidepressant response to ketamine using novel computational modeling techniques, in particular the application of dynamic causal modeling to electrophysiological data. The latter promises to better characterize the mechanisms underlying ketamine's antidepressant effects.

Current understanding of bipolar disorder: Toward integration of biological basis and treatment strategies

Biological studies of bipolar disorder initially focused on the mechanism of action for antidepressants and antipsychotic drugs, and the roles of monoamines (e.g., serotonin, dopamine) have been extensively studied. Thereafter, based on the mechanism of action of lithium, intracellular signal transduction systems, including inositol metabolism and intracellular calcium signaling, have drawn attention. Involvement of intracellular calcium signaling has been supported by genetics and cellular studies. Elucidation of the neural circuits affected by calcium signaling abnormalities is critical, and our previous study suggested a role of the paraventricular thalamic nucleus. The genetic vulnerability of mitochondria causes calcium dysregulation and results in the hyperexcitability of serotonergic neurons, which are suggested to be susceptible to oxidative stress. Efficacy of anticonvulsants, animal studies of candidate genes, and studies using induced pluripotent stem cell-derived neurons have suggested a relation between bipolar disorder and the hyperexcitability of neurons. Recent genetic findings suggest the roles of polyunsaturated acids. At the systems level, social rhythm therapy targets circadian rhythm abnormalities, and cognitive behavioral therapy may target emotion/cognition (E/C) imbalance. In the future, pharmacological and psychosocial treatments may be combined and optimized based on the biological basis of each patient, which will realize individualized treatment.

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.

Gamma oscillations as a biomarker for major depression: an emerging topic

Identifying biomarkers for major depression is of high importance for improving diagnosis and treatment of this common and debilitating neuropsychiatric disorder, as the field seeks to move toward both personalized and more effective treatments. Here we focus on electroencephalography (EEG) or direct scalp voltage recordings as such a biomarker, with an emphasis on gamma and high gamma oscillations (or "rhythms"). In the last several decades, alpha and theta band rhythms have been found to provide information on depressive state as well as recovery, but the gamma band is less well characterized with respect to depression. We summarize some key findings on gamma rhythms (especially their amplitude) as a biomarker or endophenotype for major depression. These studies suggest: (1) under certain conditions gamma rhythms can distinguish subjects with major depression from healthy controls, (2) gamma may distinguish bipolar disorder from unipolar depression, (3) various pharmacological and non-pharmacological treatments that counteract depression also alter gamma, (4) animal models of depression-like behavior show gamma abnormalities, with changes in gamma associated with therapeutic recovery. The most informative approaches in the future may combine profiles of gamma band power across the brain to assess ratios of activity across regions. Overall we have good evidence to suggest that gamma rhythms may provide objective information on major depressive disease status, but we will need further work to better define the precise measures to follow.

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.

Stream of consciousness: Quantum and biochemical assumptions regarding psychopathology

The accepted paradigms of mainstream neuropsychiatry appear to be incompletely adequate and in various cases offer equivocal analyses. However, a growing number of new approaches are being proposed that suggest the emergence of paradigm shifts in this area. In particular, quantum theories of mind, brain and consciousness seem to offer a profound change to the current approaches. Unfortunately these quantum paradigms harbor at least two serious problems. First, they are simply models, theories, and assumptions, with no convincing experiments supporting their claims. Second, they deviate from contemporary mainstream views of psychiatric illness and do so in revolutionary ways. We suggest a possible way to integrate experimental neuroscience with quantum models in order to address outstanding issues in psychopathology. A key role is played by the phenomenon called the "stream of consciousness", which can be linked to the so-called "Gamma Synchrony" (GS), which is clearly demonstrated by EEG data. In our novel proposal, a unipolar depressed patient could be seen as a subject with an altered stream of consciousness. In particular, some clues suggest that depression is linked to an "increased power" stream of consciousness. It is additionally suggested that such an approach to depression might be extended to psychopathology in general with potential benefits to diagnostics and therapeutics in neuropsychiatry.

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

Despite being the object of a thriving field of clinical research, the investigation of intrinsic brain network alterations in psychiatric illnesses is still in its early days. Because the pathological alterations are predominantly probed using functional magnetic resonance imaging (fMRI), many questions about the electrophysiological bases of resting-state alterations in psychiatric disorders, particularly among mood disorder patients, remain unanswered. Alongside important research using electroencephalography (EEG), the specific recent contributions and future promise of magnetoencephalography (MEG) in this field are not fully recognized and valued. Here, we provide a critical review of recent findings from MEG resting-state connectivity within major depressive disorder (MDD) and bipolar disorder (BD). The clinical MEG resting-state results are compared with those previously reported with fMRI and EEG. Taken together, MEG appears to be a promising but still critically underexploited technique to unravel the neurophysiological mechanisms that mediate abnormal (both hyper- and hypo-) connectivity patterns involved in MDD and BD. In particular, a major strength of MEG is its ability to provide source-space estimations of neuromagnetic long-range rhythmic synchronization at various frequencies (i.e., oscillatory coupling). The reviewed literature highlights the relevance of probing local and interregional rhythmic synchronization to explore the pathophysiological underpinnings of each disorder. However, before we can fully take advantage of MEG connectivity analyses in psychiatry, several limitations inherent to MEG connectivity analyses need to be understood and taken into account. Thus, we also discuss current methodological challenges and outline paths for future research. MEG resting-state studies provide an important window onto perturbed spontaneous oscillatory brain networks and hence supply an important complement to fMRI-based resting-state measurements in psychiatric populations.

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.

Spectral analysis of resting state magnetoencephalogram activity in patients with bipolar disorder

We analyzed the frequency spectrum of magnetoencephalogram (MEG) background activity in 16 bipolar disorder (BD) patients and 24 age-matched healthy control. Median frequency (MF), spectral entropy (SpEn), and relative power in delta (RPδ), theta (RPθ), alpha (RPα), beta (RPβ), and gamma (RPγ) bands were computed for all 148 MEG channels. Significant differences between the two groups were found in the average level of MF, RPδ, and RPθ in the posterior region of the scalp. Moreover, the MF, SpEn, RPδ, and RPβ values of BD patients had a different dependence on age as compared with the results of control subjects, which may suggest that BD affects how the brain activity develops with age. We conclude that the spectral analysis of the background MEG in BD patients may give insights into how this condition affects the brain activity.

Shared reduction of oscillatory natural frequencies in bipolar disorder, major depressive disorder and schizophrenia

INTRODUCTION

Recent studies have demonstrated that cortical brain areas tend to oscillate at a specific natural frequency when directly perturbed by transcranial magnetic stimulation (TMS). Fast electroencephalographic (EEG) oscillations, which typically originate from frontal regions, have been reported to be markedly reduced in schizophrenia.

METHODS

Here we employed TMS/EEG to assess the natural frequency of the premotor area in a sample of 48 age-matched participants (12 each in major depression disorder (MDD)), bipolar disorder (BPD), schizophrenia (SCZ) and healthy controls. Event related spectral perturbations (ERSP) were obtained for each study participant using wavelet decomposition.

RESULTS

TMS resulted in a significant activation of the beta/gamma band response (21-50 Hz) to frontal cortical perturbation in healthy control subjects. By contrast, the main frequencies of frontal EEG responses to TMS were significantly reduced in patients with BPD, MDD and SCZ (11-27 Hz) relative to healthy subjects.

CONCLUSIONS

Patients with bipolar disorder, major depression and schizophrenia showed a significantly lower natural frequency of frontal cortico-thalamocortical circuits compared to healthy controls. These results suggest a common neurobiological mechanism of corticothalamic impairment. The most likely candidates include dysfunction of GABAergic circuits.

LIMITATIONS

Further studies are needed to consider other biological markers, gene variants, and their interaction with clinical variables.

The effect of body-mind relaxation meditation induction on major depressive disorder: A resting-state fMRI study

BACKGROUND

Meditation has been increasingly evaluated as an important complementary therapeutic tool for the treatment of depression. The present study employed resting-state functional magnetic resonance imaging (rs-fMRI) to examine the effect of body-mind relaxation meditation induction (BMRMI) on the brain activity of depressed patients and to investigate possible mechanisms of action for this complex intervention.

METHOD

21 major depressive disorder patients (MDDs) and 24 age and gender-matched healthy controls (HCs) received rs-fMRI scans at baseline and after listening to a selection of audio designed to induce body-mind relaxation meditation. The rs-fMRI data were analyzed using Matlab toolbox to obtain the amplitude of low-frequency fluctuations (ALFF) of the BOLD signal for the whole brain. A mixed-design repeated measures analysis of variance (ANOVA) was performed on the whole brain to find which brain regions were affected by the BMRMI. An additional functional connectivity analysis was used to identify any atypical connection patterns after the BMRMI.

RESULTS

After the BMRMI experience, both the MDDs and HCs showed decreased ALFF values in the bilateral frontal pole (BA10). Additionally, increased functional connectivity from the right dorsal medial prefrontal cortex (dmPFC) to the left dorsal lateral prefrontal cortex (dlPFC) and the left lateral orbitofrontal cortex (OFC) was identified only in the MDDs after the BMRMI.

LIMITATION

In order to exclude the impact of other events on the participants׳ brain activity, the Hamilton Rating Scales for Depression (HDRS) was not measured after the body-mind relaxation induction.

CONCLUSION

Our findings support the hypothesis that body-mind relaxation meditation induction may regulate the activities of the prefrontal cortex and thus may have the potential to help patients construct reappraisal strategies that can modulate the brain activity in multiple emotion-processing systems.

Discriminative analysis with a limited number of MEG trials in depression

BACKGROUND

In studies when exploring distinct patterns of functional abnormalities inherent in depression, experiments are generally repeated over many trials, and then the data are averaged across those trials in order to improve the signal to noise ratio. Repeated stimuli will lead to unpredictable impairment on signals, due to material familiarity or subjects׳ fatigue. In this consideration, signal processing tools powerful on small numbers of trials are expected to alleviate the work load on subjects, especially for mental disease studies.

METHODS

Forty-four subjects, half-depressed patients and half-healthy subjects, were recruited for MEG scanning in response to sad facial stimuli. Multichannel matching pursuit (MMP) was implemented to manage the limited number of trials. The post-MMP MEG signals were utilized to calculate the power topography over the whole brain, as inputs for a Support Vector Machine (SVM) classifier. Standard ICA and conventional ensemble averaging plus Butterworth filtering were employed as well as benchmark studies for performance comparison.

RESULTS

A limited number of trials were required via MMP to discriminate the depressive. Post-MMP discriminative analysis revealed a deficit theta pattern and an excessive alpha/beta pattern.

LIMITATIONS

The small sample size may impair the stability of the reported findings. The transient tiny variance of the signal was excluded from exploration.

CONCLUSIONS

The deficit theta pattern together with the excessive alpha/beta pattern in depression may indicate the dysfunction of the limbic-cortical circuit in a 'top-down' process. The post-MMP discrimination helps alleviate the scanning burden, facilitating the possibility for neuroimaging supporting the affective disorder clinical diagnosis.

EEG power, cordance and coherence differences between unipolar and bipolar depression

INTRODUCTION

Understanding the biological underpinnings of unipolar (UD) and bipolar depression (BD) is vital for avoiding inappropriate treatment through the misdiagnosis of bipolar patients in their first depressive episode. One plausible way to distinguish between UD and BD is to compare EEG brain dynamics to identify potential neurophysiological biomarkers. Here we aimed to test group differences in EEG power, cordance and coherence values between UD and BD.

METHODS

Twenty-five bipolar and 56 unipolar depression patients were recruited. Sociodemographic and clinical variables were collected in addition to resting state EEG. Data was analyzed with multivariate and repeated analyses of variance where parametric assumptions were met.

RESULTS

Accordingly, we did not find any differences in the EEG absolute power and frontal asymmetry indexes between UD and BD. Regarding cordance, significant group differences were observed in the right theta cordance values (p=0.031). Regarding coherence, BD patients (as compared to UD) exhibited greater central-temporal theta (p=0.003), and parietal-temporal alpha (p=0.007) and theta (p=0.001) coherence. Lastly, less alpha coherence in BD was present at right frontal-central (p=0.007) and central inter-hemispheric (p=0.019) regions.

CONCLUSIONS

Our results demonstrate that EEG cordance and coherence values have potential to discriminate between UD and BD. The loss of temporal synchronization in the frontal interhemispheric and right sided frontolimbic neuronal networks may be a unique feature that distinguishes between BD and UD.

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.

Right fronto-parietal dysfunction underlying spatial attention in bipolar disorder

Although the neural underpinning of bipolar disorder (BD) is still unknown, recent research suggests that the right fronto-parietal cortex is particularly affected in BD patients. If this were true, we would expect atypical functional cerebral asymmetries in allocation of visuospatial attention. To test this hypothesis, euthymic BD patients and age- and gender-matched healthy controls were compared on the visual line-bisection task, a reliable measure of visuospatial attention, associated with right parietal function. Line bisection performance (i.e. absolute and directional bias) was compared between groups as a function of response hand and line position. The results showed a typical hand-use effect in healthy controls involving a larger leftward bias (i.e. pseudoneglect) with the left hand than with the right hand. Although euthymic BD patients did not differ from healthy controls in the overall accuracy (i.e. absolute bias), they differed significantly in the directional line bisection bias. In contrast to healthy controls, BD patients did not significantly deviate from the veridical center, regardless of which hand was used to bisect horizontal lines. This finding indicates an atypical functional cerebral asymmetry in visuospatial attention in euthymic BD patients, supporting the idea of a dysfunction especially in the right fronto-parietal cortex.

Multichannel matching pursuit of MEG signals for discriminative oscillation pattern detection in depression

Magnetoencephalography (MEG) power topography may be useful for obtaining discriminative brain activity patterns that can distinguish depressed patients from healthy control subjects at the individual level. However, the application is still limited due to the lack of adequate analysis strategies to remove artifacts from the MEG signals. In this study, the multichannel matching pursuit (MMP) method was designed; in this technique, a linear decomposition method that provides components by iteratively reanalysing a residual signal after removing previously found components,. Forty-four subjects, half depressed patients and half healthy subjects, were recruited for MEG scanning whilst watching a video of sad faces. MMP was implemented to manage multichannel, multi-trial MEG signals. The representative post-MMP analysis signals were utilised to calculate the power topography over the whole brain and designed as inputs for a Support Vector Machine (SVM) classifier. A statistically significant discriminative accuracy of 86% (p=0.002) after a permutation test was achieved. Comparing the system classification performance to that of the ensemble averaging method and the established Independent Component Analysis (ICA), we demonstrated the ability of MMP to represent critical MEG information and, in turn, to mark the abnormality of oscillatory activities under negative stimuli using images of sad faces.

Direct alteration of a specific inhibitory circuit of the hippocampus by antidepressants

Correct brain functioning relies on the precise activity of a myriad of synapses assembling neurons in complex networks. In the hippocampus, highly diverse inhibitory circuits differently govern several physiologically relevant network activities. Particularly, perisomatic inhibition provided by specific interneurons was proposed to control emotional states, and could therefore be affected by mood disorders and their therapy. We found that both chronic and acute administration of two major antidepressants, imipramine and fluoxetine, strongly and directly altered GABA-mediated (GABAergic) hippocampal neurotransmission in mice and rats, independently of their effects on amine reuptake systems. These drugs affected GABA release from synapses formed by fast-spiking cells, but not interneurons expressing cannabinoid receptor type 1, resulting in the disruption of γ oscillations. This differential effect, shared by two types of antidepressants, suggests a new mechanism of action of these medications, and a possible role of perisomatic inhibition in depressive disorders.

Brain oscillations in bipolar disorder in search of new biomarkers

This report presents six cardinal results obtained with methods of oscillatory brain dynamics in euthymic and manic bipolar patients in comparison to healthy controls. Measurements include changes in oscillatory response activities in the theta, alpha, beta, and gamma frequency ranges. The analysis shows that spontaneous and response activities in the alpha range are highly reduced in euthymic and manic patients, respectively; conversely, beta responses are increased in euthymic and manic patients. Lithium use seems to be associated with further and significant increase in the beta frequency range in euthymic patients. Theta responses to auditory target stimulus during odd-ball paradigm appeared in two different frequency bands (4-6 and 6-8 Hz) in healthy participants. However, only fast theta responses were highly reduced under cognitive load in drug-free euthymic patients. The analysis of connectivity was performed by assessment of long-distance coherence function in the gamma frequency range. Both manic and euthymic patients presented significantly decreased fronto-temporal coherence function during visual odd-ball task, indicating a selective reduction in connectivity during cognitive processing. The present report also discusses that these six oscillatory parameters may serve as an ensemble of biomarkers for diagnostic purposes and tracking treatment response in bipolar disorder.

Decrease of theta response in euthymic bipolar patients during an oddball paradigm

Theta oscillations are related to cognitive functions and reflect functional integration of frontal and medial temporal structures into coherent neurocognitive networks. This study assessed event-related theta oscillations in medication-free, euthymic patients with bipolar disorder upon auditory oddball paradigm. Twenty-two DSM-IV euthymic bipolar I (n = 19) and II (n = 3) patients and twenty-two healthy subjects were included. Patients were euthymic for at least 6 months, and psychotropic-free for at least 2 weeks. EEG was recorded at 30 electrode sites. Auditory oddball paradigm and sensory stimuli were used. Event-related Oscillations were analyzed using adaptive filtering in two different theta frequency bands (4-6 Hz, 6-8 Hz). In healthy subjects, slow theta (4-6 Hz) responses were significantly higher than those of euthymic patients upon target, non-target and sensory stimuli (p < 0.05). Fast theta (6-8 Hz) responses of healthy subjects were significantly higher than those of euthymic patients upon target-only stimuli (p < 0.05). Reduced theta oscillations during auditory processing provide strong quantitative evidence of activation deficits in related networks in bipolar disorder. Fast theta responses are related to cognitive functions, whereas slow theta responses are related to sensory processes more than cognitive processes.

Neural activations during auditory oddball processing discriminating schizophrenia and psychotic bipolar disorder

BACKGROUND

Reduced amplitude of the P300 event-related potential in auditory oddball tasks may characterize schizophrenia (SZ) but is also reported in bipolar disorder. Similarity of auditory processing abnormalities between these diagnoses is uncertain, given the frequent combination of both psychotic and nonpsychotic patients in bipolar samples; abnormalities may be restricted to psychosis. In addition, typically only latency and amplitude of brain responses at selected sensors and singular time points are used to characterize neural responses. Comprehensive quantification of brain activations involving both spatiotemporal and time-frequency analyses could better identify unique auditory oddball responses among patients with different psychotic disorders.

METHODS

Sixty SZ, 60 bipolar I with psychosis (BPP), and 60 healthy subjects (H) were compared on neural responses during an auditory oddball task using multisensor electroencephalography. Principal components analysis was used to reduce multisensor data before evaluating group differences on voltage and frequency of neural responses over time.

RESULTS

Linear discriminant analysis revealed five variables that best differentiated groups: 1) late beta activity to standard stimuli; 2) late beta/gamma activity to targets discriminated BPP from other groups; 3) midlatency theta/alpha activity to standards; 4) target-related voltage at the late N2 response discriminated both psychosis groups from H; and 5) target-related voltage during early N2 discriminated BPP from H.

CONCLUSIONS

Although the P300 significantly differentiated psychotic groups from H, it did not uniquely discriminate groups beyond the above variables. No variable uniquely discriminated SZ, perhaps indicating utility of this task for studying psychosis-associated neurophysiology generally and BPP specifically.

A short review of alpha activity in cognitive processes and in cognitive impairment

AIM OF THE REPORT: In the companion report (Başar, this volume), the physiological fundaments of alpha activity in integrative brain function are described. The present report is a review of the significant role of alpha activity in memory and cognitive processes in healthy subjects, and in cognitive impairment. The role of neurotransmitters is also described, briefly, in this context. TOWARDS AN UNDERSTANDING OF BRAIN ALPHA: Despite numerous experimental studies, it is indicated that the presented results are only appropriate to establish an ensemble of reasonings and suggestions for analyzing "alphas" in the whole brain. In turn, in the near future, these reasonings and suggestions may serve (or are indispensable to serve) as fundaments of more general and tenable hypotheses on the genesis and function of "alphas".