Resting EEG in first-episode and chronic schizophrenia

EEG alpha reactivity on eyes opening discriminates patients with schizophrenia and schizoaffective disorder

OBJECTIVE

Alpha activity in the electroencephalogram (EEG) is typically dominant during rest with closed eyes but suppressed by visual stimulation. Previous research has shown that alpha-blockade is less pronounced in schizophrenia patients compared to healthy individuals, but no studies have examined it in schizoaffective disorder.

METHODS

A resting state EEG was used for the analysis of the alpha-reactivity between the eyes closed and the eyes opened conditions in overall (8 - 13 Hz), low (8 - 10 Hz) and high (10 - 13 Hz) alpha bands in three groups: schizophrenia patients (SC, n = 30), schizoaffective disorder (SA, n = 30), and healthy controls (HC, n = 36). All patients had their first psychotic episode and were receiving antipsychotic therapy.

RESULTS

A significant decrease in alpha power was noted across all subjects from the eyes-closed to eyes-open condition, spanning all regions. Alpha reactivity over the posterior regions was lower in SC compared to HC within overall and high alpha. SA showed a trend towards reduced alpha reactivity compared to HC, especially evident over the left posterior region within the overall alpha. Alpha reactivity was more pronounced over the middle and right posterior regions of SA as compared to SC, particularly in the high alpha. Alpha reactivity in SC and SA patients was associated with various negative symptoms.

CONCLUSIONS

Our findings imply distinct alterations in arousal mechanisms in SC and SA and their relation to negative symptomatology. Arousal is more preserved in SA.

SIGNIFICANCE

This study is the first to compare the EEG features of arousal in SC and SA.

Sex differences in neuronal oscillatory activity and memory in the methylazoxymethanol acetate model of schizophrenia

The methylazoxymethanol acetate (MAM) rodent model is used to study aspects of schizophrenia. However, numerous studies that have employed this model have used only males, resulting in a dearth of knowledge on sex differences in brain function and behaviour. The purpose of this study was to determine whether differences exist between male and female MAM rats in neuronal oscillatory function within and between the prefrontal cortex (PFC), ventral hippocampus (vHIP) and thalamus, behaviour, and in proteins linked to schizophrenia neuropathology. We showed that female MAM animals exhibited region-specific alterations in theta power, elevated low and high gamma power in all regions, and elevated PFC-thalamus high gamma coherence. Male MAM rats had elevated beta and low gamma power in PFC, and elevated vHIP-thalamus coherence. MAM females displayed impaired reversal learning whereas MAM males showed impairments in spatial memory. Glycogen synthase kinase-3 (GSK-3) was altered in the thalamus, with female MAM rats displaying elevated GSK-3α phosphorylation. Male MAM rats showed higher expression and phosphorylation GSK-3α, and higher expression of GSK-β. Sex-specific changes in phosphorylated Tau levels were observed in a region-specific manner. These findings demonstrate there are notable sex differences in behaviour, oscillatory network function, and GSK-3 signaling in MAM rats, thus highlighting the importance of inclusion of both sexes when using this model to study schizophrenia.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders

BACKGROUND AND HYPOTHESIS

The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample.

STUDY DESIGN

Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task.

STUDY RESULTS

We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well.

CONCLUSIONS

These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

Spectral decomposition of resting state electroencephalogram reveals unique theta/alpha activity in schizophrenia

Resting state electroencephalographic (EEG) activity in schizophrenia (SZ) is frequently characterised by increased power at slow frequencies and/or a reduction of peak alpha frequency. Here we investigated the nature of these effects. As most studies to date have been limited by reliance on a priori frequency bands which impose an assumed structure on the data, we performed a data-driven analysis of resting EEG recorded in SZ patients and healthy controls (HC). The sample consisted of 39 chronic SZ and 36 matched HC. The EEG was recorded with a dense electrode array. Power spectral densities were decomposed via Varimax-rotated principal component analysis (PCA) over all participants and for each group separately. Spectral PCA was repeated at the cortical level on cortical current source density computed from standardised low resolution brain electromagnetic tomography. There was a trend for power in the theta/alpha range to be increased in SZ compared to HC, and peak alpha frequency was significantly reduced in SZ. PCA revealed that this frequency shift was because of the presence of a spectral component in the theta/alpha range (6-9 Hz) that was unique to SZ. The source distribution of the SZ > HC theta/alpha effect involved mainly prefrontal and parahippocampal areas. Abnormal low frequency resting EEG activity in SZ was accounted for by a unique theta/alpha oscillation. Other reports have described a similar phenomenon suggesting that the neural circuits oscillating in this range are relevant to SZ pathophysiology.

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

Neuroimaging resting state paradigms have revealed synchronised oscillatory activity is present even in the absence of completing a task or mental operation. One function of this neural activity is likely to optimise the brain's sensitivity to forthcoming information that, in turn, likely promotes subsequent learning and memory outcomes. The current study investigated whether this extends to implicit forms of learning. A total of 85 healthy adults participated in the study. Resting state electroencephalography was first acquired from participants before they completed a serial reaction time task. On this task, participants implicitly learnt a visuospatial-motor sequence. Permutation testing revealed a negative correlation between implicit sequence learning and resting state power in the upper theta band (6-7 Hz). That is, lower levels of resting state power in this frequency range were associated with superior levels of implicit sequence learning. This association was observed at midline-frontal, right-frontal and left-posterior electrodes. Oscillatory activity in the upper theta band supports a range of top-down processes including attention, inhibitory control and working memory, perhaps just for visuospatial information. Our results may be indicating that disengaging theta-supported top-down attentional processes improves implicit learning of visuospatial-motor information that is embedded in sensory input. This may occur because the brain's sensitivity to this type of information is optimally achieved when learning is driven by bottom-up processes. Moreover, the results of this study further demonstrate that resting state synchronised brain activity influences subsequent learning and memory.

Short-term PM2.5 exposure and cognitive function: Association and neurophysiological mechanisms

BACKGROUND

Although converging evidence has demonstrated that exposure to fine particulate matter (PM_2.5) caused adverse effects on brain structure and cognitive function, the association between the short-term exposure to PM_2.5 and cognition dysfunction remained underexplored, especially possible neurophysiological mechanisms.

METHODS

We conducted a longitudinal observational study with four repeated measurement sessions among 90 young adults from September 2020 to June 2021. During each measurement session, we measured participants' personal-level air pollution exposure for one week with portable monitors, followed by executive function assessment and electrophysiological signal recording at an assessment center. Standard Stroop color-word test was used accompanied with electroencephalogram (EEG) recording to assess performance on executive function. We used linear mixed-effect model with lagged values of PM_2.5 levels to analyze the association between PM_2.5 exposure and changes in executive function, and mediation analysis to investigate mediation effect by EEG signal.

RESULTS

Adjusted mixed-effect models demonstrated that elevated PM_2.5 exposure three days prior to cognitive assessment (lag-3) was associated with (1) declined performance in both congruent and incongruent tasks in Stroop test, (2) reduced lower and upper alpha event-related desynchronization (ERD) during 500-1000 ms after stimuli, both indicating impaired executive control. Lower and upper alpha ERD also mediated observed associations between short-term PM_2.5 exposure and executive function. No significant associations were found between short-term PM_2.5 exposure or aperiodic exponents in tonic and phasic states, or periodic alpha oscillations in tonic state.

CONCLUSION

Our results provided evidence that short-term PM_2.5 exposure was associated with executive dysfunction. Reduced alpha ERD was likely to be the underlying pathway through which PM_2.5 induced adverse effects on neuron activities during cognitive tasks.

Spectral perturbations of cortical dipoles during a dynamic visuo-spatial working memory task in schizophrenia

Altered neural oscillations during prestimulus-task conditions have been reported to be associated with aberrant information processing in schizophrenia. Spectral perturbations induced by visuo-spatial working memory (VSWM) task were investigated in patients and their first-degree relatives in order to study the biomarkers in schizophrenia. EEG was recorded using 128-channel during VSWM task in 28 patients, 27 first-degree relatives and 25 controls. After pre-processing and ICA, current dipole was estimated for each IC. Total of 1609 independent and localizable EEG components across all groups were used to compute ERSP during different events of task. Patients deactivated DMN, RSN, auditory cortex more compared to controls during search period to perform VSWM task. Relatives showed altered activation of right medial and inferior frontal gyri during different events and loads of task in lower frequencies compared to controls. Relatives also showed hyperactivity in right cingulate and parahippocampal gyri compared to controls. This is suggestive of genetic predisposition in schizophrenia and could act as vulnerability markers, further strengthened by no significant differences between patients and relatives. Altered processing of simultaneous ongoing events in patients and relatives can serve as state and trait-specific features of schizophrenia.

Alteration of Resting Electroencephalography by Acute Caffeine Consumption in Early Phase Psychosis

Individuals with schizophrenia use twice as much caffeine on average when compared to healthy controls. Knowing the high rates of consumption, and the potential negative effects of such, it is important we understand the cortical mechanisms that underlie caffeine use, and the consequences of caffeine use on neural circuits in this population. Using a randomized, placebo controlled, double-blind, repeated measures design, the current study examines caffeine's effects on resting electroencephalography (EEG) power in those who have been recently diagnosed with schizophrenia (SZ) compared to regular-using healthy controls (HC). Correlations between average caffeine consumption, withdrawal symptoms, drug related symptoms and clinical psychosis symptoms were measured and significant correlations with neurophysiological data were examined. Results showed caffeine had no effect on alpha asymmetry in the SZ group, although caffeine produced a more global effect on the reduction of alpha₂ power in the SZ group. Further, those with more positive symptoms were found to have a greater reduction in alpha₂ power following caffeine administration. Caffeine also reduced beta power during eyes closed and eyes open resting in HC, but only during eyes closed resting conditions in the SZ group. These findings provide a descriptive profile of the resting EEG state following caffeine administration in individuals with schizophrenia. The findings ultimately suggest caffeine does not affect alpha or beta power as readily in this population and a higher dose may be needed to achieve the desired effects, which may elucidate motivational factors for high caffeine use.

Sleep-Wake Rhythm and Oscillatory Pattern Analysis in a Multiple Hit Schizophrenia Rat Model (Wisket)

Electroencephalography studies in schizophrenia reported impairments in circadian rhythm and oscillatory activity, which may reflect the deficits in cognitive and sensory processing. The current study evaluated the circadian rhythm and the state-dependent oscillatory pattern in control Wistar and a multiple hit schizophrenia rat model (Wisket) using custom-made software for identification of the artifacts and the classification of sleep-wake stages and the active and quiet awake substages. The Wisket animals have a clear light-dark cycle similar to controls, and their sleep-wake rhythm showed only a tendency to spend more time in non-rapid eye movement (NREM) and less in rapid eye movement (REM) stages. In spite of the weak diurnal variation in oscillation in both groups, the Wisket rats had higher power in the low-frequency delta, alpha, and beta bands and lower power in the high-frequency theta and gamma bands in most stages. Furthermore, the significant differences between the two groups were pronounced in the active waking substage. These data suggest that the special changes in the oscillatory pattern of this schizophrenia rat model may have a significant role in the impaired cognitive functions observed in previous studies.

Current findings and perspectives on aberrant neural oscillations in schizophrenia

There is now consistent evidence that neural oscillation at low- and high-frequencies constitute an important aspect of the pathophysiology of schizophrenia. Specifically, impaired rhythmic activity may underlie the deficit to generate coherent cognition and behavior, leading to the characteristic symptoms of psychosis and cognitive deficits. Importantly, the generating mechanisms of neural oscillations are relatively well-understood and thus enable the targeted search for the underlying circuit impairments and novel treatment targets. In the following review, we will summarize and assess the evidence for aberrant rhythmic activity in schizophrenia through evaluating studies that have utilized Electro/Magnetoencephalography to examine neural oscillations during sensory and cognitive tasks as well as during resting-state measurements. These data will be linked to current evidence from post-mortem, neuroimaging, genetics, and animal models that have implicated deficits in GABAergic interneurons and glutamatergic neurotransmission in oscillatory deficits in schizophrenia. Finally, we will highlight methodological and analytical challenges as well as provide recommendations for future research.

A self-learned decomposition and classification model for schizophrenia diagnosis

BACKGROUND

Schizophrenia (SZ) is a type of neurological disorder that is diagnosed by professional psychiatrists based on interviews and manual screening of patients. The procedures are time-consuming, burdensome, and prone to human error. This urgently necessitates the development of an effective and precise computer-aided design for the detection of SZ. One such efficient source for SZ detection is the electroencephalogram (EEG) signals. Because EEG signals are non-stationary, it is challenging to find representative information in its raw form. Decomposing the signals into multi-modes can provide detailed insight information from it. But the choice of uniform decomposition and hyper-parameters leads to information loss affecting system performance drastically.

METHOD

In this paper, automatic signal decomposition and classification methods are proposed for the detection of SZ and healthy control EEG signals. The Fisher score method is used for the selection of the most discriminant channel. Flexible tunable Q wavelet transform (F-TQWT) is developed for efficient decomposition of EEG signals by reducing root mean square error with grey wolf optimization (GWO) algorithm. Five features are extracted from the adaptively generated subbands and selected by the Kruskal Wallis test. The feature matrix is given as an input to the flexible least square support vector machine (F-LSSVM) classifier. The hyper-parameters and kernel of classifier are selected such that the accuracy of each subband is maximized using GWO algorithm.

RESULTS

The effectiveness and superiority of the proposed method is tested by evaluating seven performance parameters. An accuracy of 91.39%, sensitivity, specificity, precision, F-1 measure, false positive rate and error of 92.65%, 93.22%, 95.57%, 0.9306, 6.78% and 8.61% is achieved. The results prove superiority of the developed F-TQWT decomposition and F-LSSVM classifier over existing methodologies.

CONCLUSION

The EEG signals of healthy control and SZ subjects performing motor and auditory tasks simultaneously provide higher discrimination ability over the subjects performing auditory and motory tasks separately. The developed model is accurate, robust, and effective as it is developed on a relatively larger data-set, obtained maximum performance, and tested using ten-fold cross-validation technique. This proposed model is ready to be put to test for real-time SZ detection.

The beta component of gamma-band auditory steady-state responses in patients with schizophrenia

The mechanisms underlying circuit dysfunctions in schizophrenia (SCZ) remain poorly understood. Auditory steady-state responses (ASSRs), especially in the gamma and beta band, have been suggested as a potential biomarker for SCZ. While the reduction of 40 Hz power for 40 Hz drive has been well established and replicated in SCZ patients, studies are inconclusive when it comes to an increase in 20 Hz power during 40 Hz drive. There might be several factors explaining the inconsistencies, including differences in the sensitivity of the recording modality (EEG vs MEG), differences in stimuli (click-trains vs amplitude-modulated tones) and large differences in the amplitude of the stimuli. Here, we used a computational model of ASSR deficits in SCZ and explored the effect of three SCZ-associated microcircuit alterations: reduced GABA activity, increased GABA decay times and NMDA receptor hypofunction. We investigated the effect of input strength on gamma (40 Hz) and beta (20 Hz) band power during gamma ASSR stimulation and saw that the pronounced increase in beta power during gamma stimulation seen experimentally could only be reproduced in the model when GABA decay times were increased and only for a specific range of input strengths. More specifically, when the input was in this specific range, the rhythmic drive at 40 Hz produced a strong 40 Hz rhythm in the control network; however, in the 'SCZ-like' network, the prolonged inhibition led to a so-called 'beat-skipping', where the network would only strongly respond to every other input. This mechanism was responsible for the emergence of the pronounced 20 Hz beta peak in the power spectrum. The other two microcircuit alterations were not able to produce a substantial 20 Hz component but they further narrowed the input strength range for which the network produced a beta component when combined with increased GABAergic decay times. Our finding that the beta component only existed for a specific range of input strengths might explain the seemingly inconsistent reporting in experimental studies and suggests that future ASSR studies should systematically explore different amplitudes of their stimuli. Furthermore, we provide a mechanistic link between a microcircuit alteration and an electrophysiological marker in schizophrenia and argue that more complex ASSR stimuli are needed to disentangle the nonlinear interactions of microcircuit alterations. The computational modelling approach put forward here is ideally suited to facilitate the development of such stimuli in a theory-based fashion.

Individual alpha peak frequency is slower in schizophrenia and related to deficits in visual perception and cognition

The brain at rest generates cycles of electrical activity that have been shown to be abnormal in people with schizophrenia. The alpha rhythm (~ 10 Hz) is the dominant resting state electrical cycle and each person has a propensity toward a particular frequency of oscillation for this rhythm. This individual alpha peak frequency (IAPF) is hypothesized to be central to visual perceptual processes and may have downstream influences on cognitive functions such as attention, working memory, or problem solving. In the current study we sought to determine whether IAPF was slower in schizophrenia, and whether lower IAPF predicted deficits in visual perception and cognition that are often observed in schizophrenia. Eyes-closed resting state EEG activity, visual attention, and global cognitive functioning were assessed in individuals with schizophrenia (N = 104) and a group of healthy controls (N = 101). Compared to controls, the schizophrenia group showed slower IAPF and was associated with poorer discrimination of visual targets and nontargets on a computerized attention task, as well as impaired global cognition measured using neuropsychological tests across groups. Notably, disruptions in visual attention fully mediated the relationship between IAPF and global cognition across groups. The current findings demonstrate that slower alpha oscillatory cycling accounts for global cognitive deficits in schizophrenia by way of impairments in perceptual discrimination measured during a visual attention task.

Alterations of Resting EEG in Hallucinating and Nonhallucinating Schizophrenia Patients

Auditory hallucinations (AHs) are a common symptom of schizophrenia and contribute significantly to disease burden. Research on schizophrenia and AHs is limited and fails to adequately address the effect of AHs on resting EEG in patients with schizophrenia. This study assessed changes in frequency bands (delta, theta, alpha, beta) of resting EEG taken from hallucinating patients (n = 12), nonhallucinating patients (n = 11), and healthy controls (n = 12). Delta and theta activity were unaffected by AHs but differed between patients with schizophrenia and healthy controls. Alpha activity was affected by AHs: nonhallucinators had more alpha activity than hallucinators and healthy controls. Additionally, beta activity was inversely related to trait measures of AHs. These findings contribute to the literature of resting eyes closed EEG recordings of schizophrenia and AHs, and indicate the role of delta, theta, alpha, and beta as markers for schizophrenia and auditory hallucinations.

Separating scale-free and oscillatory components of neural activity in schizophrenia

INTRODUCTION

Alterations in narrow-band spectral power of electroencephalography (EEG) recordings are commonly reported in patients with schizophrenia (SZ). It is well established however that electrophysiological signals comprise a broadband scale-free (or fractal) component generated by mechanisms different from those producing oscillatory neural activity. Despite this known feature, it has not yet been investigated if spectral abnormalities found in SZ could be attributed to scale-free or oscillatory brain function.

METHODS

In this study, we analyzed resting-state EEG recordings of 14 SZ patients and 14 healthy controls. Scale-free and oscillatory components of the power spectral density (PSD) were separated, and band-limited power (BLP) of the original (mixed) PSD, as well as its fractal and oscillatory components, was estimated in five frequency bands. The scaling property of the fractal component was characterized by its spectral exponent in two distinct frequency ranges (1-13 and 13-30 Hz).

RESULTS

Analysis of the mixed PSD revealed a decrease of BLP in the delta band in SZ over the central regions; however, this difference could be attributed almost exclusively to a shift of power toward higher frequencies in the fractal component. Broadband neural activity expressed a true bimodal nature in all except frontal regions. Furthermore, both low- and high-range spectral exponents exhibited a characteristic topology over the cortex in both groups.

CONCLUSION

Our results imply strong functional significance of scale-free neural activity in SZ and suggest that abnormalities in PSD may emerge from alterations of the fractal and not only the oscillatory components of neural activity.

Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia

Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.

Diagnosing Schizophrenia Using Effective Connectivity of Resting-State EEG Data

Schizophrenia is a serious mental illness associated with neurobiological deficits. Even though the brain activities during tasks (i.e., P300 activities) are considered as biomarkers to diagnose schizophrenia, brain activities at rest have the potential to show an inherent dysfunctionality in schizophrenia and can be used to understand the cognitive deficits in these patients. In this study, we developed a machine learning algorithm (MLA) based on eyes closed resting-state electroencephalogram (EEG) datasets, which record the neural activity in the absence of any tasks or external stimuli given to the subjects, aiming to distinguish schizophrenic patients (SCZs) from healthy controls (HCs). The MLA has two steps. In the first step, symbolic transfer entropy (STE), which is a measure of effective connectivity, is applied to resting-state EEG data. In the second step, the MLA uses the STE matrix to find a set of features that can successfully discriminate SCZ from HC. From the results, we found that the MLA could achieve a total accuracy of 96.92%, with a sensitivity of 95%, a specificity of 98.57%, precision of 98.33%, F1-score of 0.97, and Matthews correlation coefficient (MCC) of 0.94 using only 10 out of 1900 STE features, which implies that the STE matrix extracted from resting-state EEG data may be a promising tool for the clinical diagnosis of schizophrenia.

The song of Anorexia Nervosa: a specific evoked potential response to musical stimuli in affected participants

PURPOSE

Research applying electroencephalography (EEG) to Anorexia Nervosa (AN) is still limited, even though in other psychiatric disorders EEG has permitted to find out the hallmarks of the disorder. The aim of the study was to explore whether EEG basal activity and reactivity to musical stimulation differ in participants with AN as compared to healthy subjects (HS).

METHODS

Twenty female participants (respectively 10 with AN and 10 healthy controls) were administered a battery of psychometric tests and underwent EEG under three different conditions: (1) at baseline; (2) after a generic music stimulation; and (3) after a favorite musical stimulation.

RESULTS

In participants with AN, basal EEG showed the higher absolute amplitude of cortical slow waves (theta) in the parieto-occipital and temporal derivations, with a deficit in the beta band. In AN, there was a higher N100 latency and a reduced P300 latency compared to HS. While the N100 and P300 latencies were sensitive to the musical stimulus in HS, there was no difference after music stimulation in AN.

CONCLUSION

These data suggest that AN is accompanied by a state of brain hyperarousal with abnormal reactivity to environmental stimuli, similar to the state of HS after musical stimulation. If confirmed, this finding may have treatment implications.

LEVEL OF EVIDENCE

III, Evidence obtained from well-designed cohort or case-control analytic studies.

Distinct alterations in resting-state electroencephalogram during eyes closed and eyes open and between morning and evening are present in first-episode psychosis patients

Abnormalities in resting-state electroencephalogram (rs-EEG) activity have been previously reported in schizophrenia. While most rs-EEG recordings were performed in patients with chronic schizophrenia during eyes closed (EC), only a handful of studies have investigated rs-EEG activity during both EC and eyes open (EO) conditions. It is also unknown whether EC and EO rs-EEG alterations are present at illness onset, and whether they change during the day. Here, we performed EC and EO rs-EEG recordings in the morning (AM) and evening (PM) in twenty-six first-episode psychosis (FEP) patients and seventeen matched healthy controls (HC). In AM/EC rs-EEG, a widespread reduction was found in low alpha power in FEP relative to HC. In PM/EC, the FEP group demonstrated a trend toward decreased theta power in parietal regions, while decreased high alpha power in frontal and left parietal regions was present during PM/EO. Moreover, reduced low alpha power during AM/EC was associated with worse positive symptoms. Altogether, those findings indicate that rs-EEG alterations are present in FEP patients at illness onset, that they are linked to the severity of their psychosis, and that distinct RS abnormalities can be detected in different conditions of visual alertness and time of the day. Future work should therefore account for those factors, which will help reduce variability of rs-EEG findings across studies and may serve as monitoring biomarkers of illness severity in schizophrenia and related psychotic disorders.

Overexpression of neuregulin 1 in GABAergic interneurons results in reversible cortical disinhibition

Cortical disinhibition is a common feature of several neuropsychiatric diseases such as schizophrenia, autism and intellectual disabilities. However, the underlying mechanisms are not fully understood. To mimic increased expression of Nrg1, a schizophrenia susceptibility gene in GABAergic interneurons from patients with schizophrenia, we generated gtoNrg1 mice with overexpression of Nrg1 in GABAergic interneurons. gtoNrg1 mice showed cortical disinhibition at the cellular, synaptic, neural network and behavioral levels. We revealed that the intracellular domain of NRG1 interacts with the cytoplasmic loop 1 of Na_v1.1, a sodium channel critical for the excitability of GABAergic interneurons, and inhibits Na_v currents. Intriguingly, activation of GABAergic interneurons or restoring NRG1 expression in adulthood could rescue the hyperactivity and impaired social novelty in gtoNrg1 mice. These results identify mechanisms underlying cortical disinhibition related to schizophrenia and raise the possibility that restoration of NRG1 signaling and GABAergic function is beneficial in certain neuropsychiatric disorders.

The molecular and cellular mechanisms of cortical disinhibition as a common feature of many psychiatric diseases are not fully understood. The authors identify an interaction between NRG1 and Nav1.1 sodium channel as a mechanism of how NRG1 modulates the excitability of GABAergic interneurons.

Genetic underpinnings of schizophrenia-related electroencephalographical intermediate phenotypes: A systematic review and meta-analysis

Although substantial research into genetics of psychotic disorders has been conducted, a large proportion of their genetic architecture has remained unresolved. Electroencephalographical intermediate phenotypes (EIP) have the potential to constitute a valuable tool when studying genetic risk loci for schizophrenia, in particular P3b amplitude, P50 suppression, mismatch negativity (MMN) and resting state power spectra of the electroencephalogram (EEG). Here, we systematically reviewed studies investigating the association of single nucleotide polymorphisms (SNPs) with these EIPs and meta-analysed them when appropriate. We retrieved 45 studies (N = 34,971 study participants). Four SNPs investigated in more than one study were genome-wide significant for an association with schizophrenia and three were genome-wide suggestive, based on a lookup in the influential 2014 GWAS (Ripke et al., 2014). However, in our meta-analyses, rs1625579 failed to reach a statistically significant association with p3b amplitude decrease and rs4680 risk allele carrier status was not associated with p3b amplitude decrease or with impaired p50 suppression. In conclusion, evidence for SNP associations with EIPs remains limited to individual studies. Careful selection of EIPs and SNPs, combined with consistent reporting of effect sizes, directions of effect and p-values would aid future meta-analyses.

Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia

Current theories of schizophrenia emphasize the role of altered information integration as the core dysfunction of this illness. While ample neuroimaging evidence for such accounts comes from investigations of spatial connectivity, understanding temporal disruptions is important to fully capture the essence of dysconnectivity in schizophrenia. Recent electrophysiology studies suggest that long-range temporal correlation (LRTC) in the amplitude dynamics of neural oscillations captures the integrity of transferred information in the healthy brain. Thus, in this study, 25 schizophrenia patients and 25 controls (8 females/group) were recorded during two five-minutes of resting-state magnetoencephalography (once with eyes-open and once with eyes-closed). We used source-level analyses to investigate temporal dysconnectivity in patients by characterizing LRTCs across cortical and sub-cortical brain regions. In addition to standard statistical assessments, we applied a machine learning framework using support vector machine to evaluate the discriminative power of LRTCs in identifying patients from healthy controls. We found that neural oscillations in schizophrenia patients were characterized by reduced signal memory and higher variability across time, as evidenced by cortical and subcortical attenuations of LRTCs in the alpha and beta frequency bands. Support vector machine significantly classified participants using LRTCs in key limbic and paralimbic brain areas, with decoding accuracy reaching 82%. Importantly, these brain regions belong to networks that are highly relevant to the symptomology of schizophrenia. These findings thus posit temporal dysconnectivity as a hallmark of altered information processing in schizophrenia, and help advance our understanding of this pathology.

A multimodal magnetoencephalography 7 T fMRI and 7 T proton MR spectroscopy study in first episode psychosis

We combined magnetoencephalography (MEG), 7 T proton magnetic resonance spectroscopy (MRS), and 7 T fMRI during performance of a task in a group of 23 first episode psychosis (FEP) patients and 26 matched healthy controls (HC). We recorded both the auditory evoked response to 40 Hz tone clicks and the resting state in MEG. Neurometabolite levels were obtained from the anterior cingulate cortex (ACC). The fMRI BOLD response was obtained during the Stroop inhibitory control task. FEP showed a significant increase in resting state low frequency theta activity (p < 0.05; Cohen d = 0.69), but no significant difference in the 40 Hz auditory evoked response compared to HC. An across-groups whole brain analysis of the fMRI BOLD response identified eight regions that were significantly activated during task performance (p < 0.01, FDR-corrected); the mean signal extracted from those regions was significantly different between the groups (p = 0.0006; d = 1.19). In the combined FEP and HC group, there was a significant correlation between the BOLD signal during task performance and MEG resting state low frequency activity (p < 0.05). In FEP, we report significant alteration in resting state low frequency MEG activity, but no alterations in auditory evoked gamma band response, suggesting that the former is a more robust biomarker of early psychosis. There were no correlations between gamma oscillations and GABA levels in either HC or FEP. Finally, in this study, each of the three imaging modalities differentiated FEP from HC; fMRI with good and MEG and MRS with moderate effect size.

The relationship between resting electroencephalogram oscillatory abnormalities and schizotypal personality traits in the first-degree relatives of schizophrenia patients

Although a large amount of studies have manifested resting state electroencephalogram oscillatory abnormalities in schizophrenia and their first-degree relatives and in schizotype, the results are far from consistent and no research found any relationship between electroencephalograph (EEG) abnormalities and schizotypal personality in first-degree relatives. The present study is to verify the modifications of EEG power spectra in eyes-open resting state of schizophrenia and first-degree relatives, and to investigate associations between EEG band power and schizotypal personality traits in first-degree relatives of schizophrenia patients. Participant samples in this study consisted of 33 healthy normal controls, 35 unaffected first-degree relatives of schizophrenia patients and 35 schizophrenia patients. Group differences in resting EEG band power were examined via repeated-measures analysis of variance, and correlation between EEG power and schizotypal personality traits via Pearson Correlation analysis. The results showed that patients with schizophrenia exhibited increased delta, theta and alpha activity over anterior and central regions in eyes-open resting state compared with that of normal control. Gamma band power was found for the first time to be negatively correlated to schizotypal personality traits in first-degree relatives of schizophrenia patients. To conclusion, these findings suggested that low-frequency EEG activity might be neural manifestations of pathophysiological changes in the brain of schizophrenia, and gamma band activity might be an approach to measure the genetic liability of the disorder.

Minocycline Treatment Reverses Sound Evoked EEG Abnormalities in a Mouse Model of Fragile X Syndrome

Fragile X Syndrome (FXS) is a leading known genetic cause of intellectual disability. Many symptoms of FXS overlap with those in autism including repetitive behaviors, language delays, anxiety, social impairments and sensory processing deficits. Electroencephalogram (EEG) recordings from humans with FXS and an animal model, the Fmr1 knockout (KO) mouse, show remarkably similar phenotypes suggesting that EEG phenotypes can serve as biomarkers for developing treatments. This includes enhanced resting gamma band power and sound evoked total power, and reduced fidelity of temporal processing and habituation of responses to repeated sounds. Given the therapeutic potential of the antibiotic minocycline in humans with FXS and animal models, it is important to determine sensitivity and selectivity of EEG responses to minocycline. Therefore, in this study, we examined if a 10-day treatment of adult Fmr1 KO mice with minocycline (oral gavage, 30 mg/kg per day) would reduce EEG abnormalities. We tested if minocycline treatment has specific effects based on the EEG measurement type (e.g., resting versus sound-evoked) from the frontal and auditory cortex of the Fmr1 KO mice. We show increased resting EEG gamma power and reduced phase locking to time varying stimuli as well as the 40 Hz auditory steady state response in the Fmr1 KO mice in the pre-drug condition. Minocycline treatment increased gamma band phase locking in response to auditory stimuli, and reduced sound-evoked power of auditory event related potentials (ERP) in Fmr1 KO mice compared to vehicle treatment. Minocycline reduced resting EEG gamma power in Fmr1 KO mice, but this effect was similar to vehicle treatment. We also report frequency band-specific effects on EEG responses. Taken together, these data indicate that sound-evoked EEG responses may serve as more sensitive measures, compared to resting EEG measures, to isolate minocycline effects from placebo in humans with FXS. Given the use of minocycline and EEG recordings in a number of neurodegenerative and neurodevelopmental conditions, these findings may be more broadly applicable in translational neuroscience.

Altered parahippocampal gyrus activation and its connectivity with resting-state network areas in schizophrenia: An EEG study

Synchronized and coherent activity in resting-networks during normal brain functioning could be altered in disconnection syndrome like schizophrenia. Study of neural oscillations as assessed by EEG appears to be a promising proposition to understand the pathophysiology of schizophrenia in patients and their first-degree relatives, where disturbances in neural oscillations point towards genetic predisposition. Therefore, present study aims at establishing EEG based biomarkers for early detection and management strategies. Thirty-two patients with schizophrenia, 28 first-degree relatives and 31 healthy controls (HC) participated in the study. Resting brain activity was recorded using 128-channel electroencephalography. After pre-processing and independent component analysis (ICA), an equivalent current dipole was estimated for each IC. Total of 1551 independent and localizable EEG components across all groups were used in subsequent analysis. Power spectral density and source coherence between IC clusters were computed. Patients and first-degree relatives displayed significantly higher power spectral density (PSD) than HC for all frequency bands in left parahippocampal gyrus (PHG) (-7, -26, 8; BA 27). Another region within left deep PHG (-4, -28, 1), however, distinguished patients from first-degree relatives and HC in terms of significantly lower PSD in higher frequency bands. Functional connectivity (FC) was found to be lower in patients and higher in relatives compared to HC between different resting-state network areas. In patients, connectivity was lower compared to first-degree relatives. Altered activity within left PHG and FC of primarily this with other areas in resting-state network can serve as state and trait markers of schizophrenia.

Transient Dose-dependent Effects of Ketamine on Neural Oscillatory Activity in Wistar-Kyoto Rats

Ketamine is a promising therapeutic for treatment-resistant depression (TRD) but is associated with an array of short-term psychomimetic side-effects. These disparate drug effects may be elicited through the modulation of neural circuit activity. The purpose of this study was to therefore delineate dose- and time-dependent changes in ketamine-induced neural oscillatory patterns in regions of the brain implicated in depression. Wistar-Kyoto rats were used as a model system to study these aspects of TRD neuropathology whereas Wistar rats were used as a control strain. Animals received a low (10 mg/kg) or high (30 mg/kg) dose of ketamine and temporal changes in neural oscillatory activity recorded from the prefrontal cortex (PFC), cingulate cortex (Cg), and nucleus accumbens (NAc) for ninety minutes. Effects of each dose of ketamine on immobility in the forced swim test were also evaluated. High dose ketamine induced a transient increase in theta power in the PFC and Cg, as well as a dose-dependent increase in gamma power in these regions 10-min, but not 90-min, post-administration. In contrast, only low dose ketamine normalized innate deficits in fast gamma coherence between the NAc-Cg and PFC-Cg, an effect that persisted at 90-min post-injection. These low dose ketamine-induced oscillatory alterations were accompanied by a reduction in immobility time in the forced swim test. These results show that ketamine induces time-dependent effects on neural oscillations at specific frequencies. These drug-induced changes may differentially contribute to the psychomimetic and therapeutic effects of the drug.

Sleep neurophysiology in childhood onset schizophrenia

Altered sleep neurophysiology has consistently been reported in adult patients with schizophrenia. Converging evidence suggests that childhood onset schizophrenia (COS), a rare but severe form of schizophrenia, is continuous with adult onset schizophrenia. The aim of the current study was to characterize sleep neurophysiology in COS. An overnight sleep electroencephalogram (EEG) was recorded in 17 children and adolescents with COS (16 years ± 6.6) and 17 age and gender-matched controls. Non-rapid eye movement (NREM) and rapid eye movement (REM) sleep EEG power and coherence for the frequency bands delta (1.6-4.8 Hz), theta (5-8.4 Hz), alpha (8.6-11 Hz), beta 1 (16.4-20.2 Hz) and beta 2 (20.4-24.2 Hz) were compared between COS patients and controls. COS patients exhibited significant and widespread deficits in beta power during NREM and REM sleep. With regard to coherence, we found increases in COS patients across brain regions, frequency bands and sleep states. This study demonstrates the utility of the sleep EEG for studying vulnerable populations and its potential to aid diagnosis.

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.

Magnetoencephalography for Schizophrenia

Schizophrenia (Sz) is a chronic mental disorder characterized by disturbances in thought (such as delusions and confused thinking), perception (hearing voices), and behavior (lack of motivation). The lifetime prevalence of Sz is between 0.3% and 0.7%, with late adolescence and early adulthood, the peak period for the onset of psychotic symptoms. Causal factors in Sz include environmental and genetic factors and especially their interaction. About 50% of individuals with a diagnosis of Sz have lifelong impairment.

Reduced parietal alpha power and psychotic symptoms: Test-retest reliability of resting-state magnetoencephalography in schizophrenia and healthy controls

BACKGROUND

Despite increased reporting of resting-state magnetoencephalography (MEG), reliability of those measures remains scarce and predominately reported in healthy controls (HC). As such, there is limited knowledge on MEG resting-state reliability in schizophrenia (SZ).

METHODS

To address test-retest reliability in psychosis, a reproducibility study of 26 participants (13-SZ, 13-HC) was performed. We collected eyes open and eyes closed resting-state data during 4 separate instances (2 Visits, 2 runs per visit) to estimate spectral power reliability (power, normalized power, alpha reactivity) across one hour and one week. Intraclass correlation coefficients (ICCs) were calculated. For source modeling, we applied an anatomically constrained linear estimation inverse model known as dynamic statistical parametric mapping (MNE dSPM) and source-based connectivity using the weighted phase lag index.

RESULTS

Across one week there was excellent test-retest reliability in global spectral measures in theta-gamma bands (HC ICC_Avg = 0.87, SZ ICC_Avg = 0.87), regional spectral measures in all bands (HC ICC_Avg = 0.86, SZ ICC_Avg = 0.80), and parietal alpha measures (HC ICC_Avg = 0.90, SZ ICC_Avg = 0.84). Conversely, functional connectivity had poor reliability, as did source spectral power across one hour for SZ. Relative to HC, SZ also had reduced parietal alpha normalized power during eyes closed only, reduced alpha reactivity, and an association between higher PANSS positive scores and lower parietal alpha power.

CONCLUSIONS

There was excellent to good test-retest reliability in most MEG spectral measures with a few exceptions in the schizophrenia patient group. Overall, these findings encourage the use of resting-state MEG while emphasizing the importance of determining reliability in clinical populations.

Deficit Versus Nondeficit Schizophrenia: An MEG-EEG Investigation of Resting State and Source Coherence-Preliminary Data

This study investigated the magneto- and electroencephalography (MEG and EEG, respectively) resting state to identify the deviations closely associated with the deficit syndrome (DS) in schizophrenia patients. Ten subjects in each group (control, DS, and nondeficit schizophrenia [NDS]) were included. Subjects underwent MEG-EEG recordings during a resting state condition. MEG coherence source imaging (CSI) in source space and spectral analysis in sensor space were performed. Significant differences were found between the 2 patient groups: (1) MEG and EEG spectral analysis showed significantly higher power at low frequencies (delta band) at sensor space in DS compared with NDS patients; (2) source analysis revealed larger power in the DS compared with NDS group at low frequencies in the frontal region; (3) NDS patients showed significantly higher MEG signal relative power in beta bands in sensor space compared with DS patients; (4) both DS and NDS patients showed higher EEG absolute power at higher beta band compared to controls; and (5) patients with DS were found to have a significantly higher MEG CSI than controls in the beta frequency band. These data support the observation of increased power in the low-frequency EEG/MEG rhythms associated with the DS. Increased power in the beta rhythms was more associated with the NDS.

Computational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathology

Pyramidal cells in layer V of the neocortex are one of the most widely studied neuron types in the mammalian brain. Due to their role as integrators of feedforward and cortical feedback inputs, they are well-positioned to contribute to the symptoms and pathology in mental disorders-such as schizophrenia-that are characterized by a mismatch between the internal perception and external inputs. In this modeling study, we analyze the input/output properties of layer V pyramidal cells and their sensitivity to modeled genetic variants in schizophrenia-associated genes. We show that the excitability of layer V pyramidal cells and the way they integrate inputs in space and time are altered by many types of variants in ion-channel and Ca²⁺ transporter-encoding genes that have been identified as risk genes by recent genome-wide association studies. We also show that the variability in the output patterns of spiking and Ca²⁺ transients in layer V pyramidal cells is altered by these model variants. Importantly, we show that many of the predicted effects are robust to noise and qualitatively similar across different computational models of layer V pyramidal cells. Our modeling framework reveals several aspects of single-neuron excitability that can be linked to known schizophrenia-related phenotypes and existing hypotheses on disease mechanisms. In particular, our models predict that single-cell steady-state firing rate is positively correlated with the coding capacity of the neuron and negatively correlated with the amplitude of a prepulse-mediated adaptation and sensitivity to coincidence of stimuli in the apical dendrite and the perisomatic region of a layer V pyramidal cell. These results help to uncover the voltage-gated ion-channel and Ca²⁺ transporter-associated genetic underpinnings of schizophrenia phenotypes and biomarkers.

Predicting Symptomatic and Functional Improvements over 1 Year in Patients with First-Episode Psychosis Using Resting-State Electroencephalography

OBJECTIVE

Although early intervention from the beginning of a psychotic episode is essential for a better prognosis, biomarkers predictive of symptomatic and functional improvement in early psychotic disorders are lacking. This study aimed to investigate whether the spectral power of resting-state electroencephalography (EEG) can be used as a predictive marker of the 1-year prognosis in patients with first-episode psychosis (FEP).

METHODS

Twenty-four patients with FEP and matched healthy control (HC) subjects were examined with resting-state EEG at baseline. The symptomatic severity and functional status of FEP patients were assessed at baseline and reassessed after 1 year of usual treatment. Repeated measures analysis of variance was conducted to compare EEG spectral powers across the groups. Multiple regression analysis revealed EEG spectral powers predictive of symptomatic and functional improvement in FEP patients at the 1-year follow-up.

RESULTS

Delta band power in the frontal and posterior regions was significantly higher in patients with FEP than in HCs. Higher delta band power in the posterior region predicted later improvement of positive symptoms and general functional status. Lower delta band power in the frontal region predicted improvement of negative symptoms and general functioning after 1 year.

CONCLUSION

These results suggest that increased delta absolute power is observed from the beginning of psychotic disorders. Furthermore, decreased delta power in the frontal region and increased delta power in the posterior region might be used as a predictive marker of a better prognosis of FEP, which would aid early intervention in clinical practice.

Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations

Genome-wide association studies have implicated many ion channels in schizophrenia pathophysiology. Although the functions of these channels are relatively well characterized by single-cell studies, the contributions of common variation in these channels to neurophysiological biomarkers and symptoms of schizophrenia remain elusive. Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta-frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a deficit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia.

Dentate Gyrus Immaturity in Schizophrenia

Hippocampal abnormalities have been heavily implicated in the pathophysiology of schizophrenia. The dentate gyrus of the hippocampus was shown to manifest an immature molecular profile in schizophrenia subjects, as well as in various animal models of the disorder. In this position paper, we advance a hypothesis that this immature molecular profile is accompanied by an identifiable immature morphology of the dentate gyrus granule cell layer. We adduce evidence for arrested maturation of the dentate gyrus in the human schizophrenia-affected brain, as well as multiple rodent models of the disease. Implications of this neurohistopathological signature for current theory regarding the development of schizophrenia are discussed.

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.

Targeting reduced neural oscillations in patients with schizophrenia by transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS) modulates endogenous neural oscillations in healthy human participants by the application of a low-amplitude electrical current with a periodic stimulation waveform. Yet, it is unclear if tACS can modulate and restore neural oscillations that are reduced in patients with psychiatric illnesses such as schizophrenia. Here, we asked if tACS modulates network oscillations in schizophrenia. We performed a randomized, double-blind, sham-controlled clinical trial to contrast tACS with transcranial direct current stimulation (tDCS) and sham stimulation in 22 schizophrenia patients with auditory hallucinations. We used high-density electroencephalography to investigate if a five-day, twice-daily 10Hz-tACS protocol enhances alpha oscillations and modulates network dynamics that are reduced in schizophrenia. We found that 10Hz-tACS enhanced alpha oscillations and modulated functional connectivity in the alpha frequency band. In addition, 10Hz-tACS enhanced the 40Hz auditory steady-state response (ASSR), which is reduced in patients with schizophrenia. Importantly, clinical improvement of auditory hallucinations correlated with enhancement of alpha oscillations and the 40Hz-ASSR. Together, our findings suggest that tACS has potential as a network-level approach to modulate reduced neural oscillations related to clinical symptoms in patients with schizophrenia.

Single Dose of the Attention Training Technique Increases Resting Alpha and Beta-Oscillations in Frontoparietal Brain Networks: A Randomized Controlled Comparison

The Attention Training Technique (ATT) was developed with the aim of reducing self-focused attention and increasing executive control as part of metacognitive therapy. So far there is a paucity of data on the neurophysiological effects of ATT. In the present study we tested for specific effects to determine if attention control components of ATT elicit a specific signature that is different from passive listening. Thirty-six healthy volunteers were randomized to an active (follow instructions) or control (ignore instructions) condition. Resting state EEG was recorded for 3 min with eyes open and eyes closed before and after exposure to training, and the power of the theta, alpha, and beta-bands were analyzed in frontal, midline, and posterior electrodes. The active ATT condition enhanced alpha and beta-band activity during eyes-open, and frontal alpha during eyes-closed (p < 0.005). Frontoparietal changes in Alpha were generally accompanied by changes in Beta in the same brain regions of interest. However, these associations were largely significant in the active ATT rather than the control condition. No between-group differences were observed in the Theta-band. These results suggest a single dose of attention training increases alpha and beta-oscillations in frontoparietal networks. These networks are associated with top-down attentional or executive control.

MEG resting-state oscillations and their relationship to clinical symptoms in schizophrenia

Neuroimaging studies suggest that schizophrenia is characterized by disturbances in oscillatory activity, although at present it remains unclear whether these neural abnormalities are driven by dimensions of symptomatology. Examining different subgroups of patients based on their symptomatology is thus very informative in understanding the role of neural oscillation patterns in schizophrenia. In the present study we examined whether neural oscillations in the delta, theta, alpha, beta and gamma bands correlate with positive and negative symptoms in individuals with schizophrenia (SZ) during rest. Resting-state brain activity of 39 SZ and 25 neurotypical controls was recorded using magnetoencephalography. Patients were categorized based on the severity of their positive and negative symptoms. Spectral analyses of beamformer data revealed that patients high in positive symptoms showed widespread low alpha power, and alpha power was negatively correlated with positive symptoms. In contrast, patients high in negative symptoms showed greater beta power in left hemisphere regions than those low in negative symptoms, and beta power was positively correlated with negative symptoms. We further discuss these findings and suggest that different neural mechanisms may underlie positive and negative symptoms in schizophrenia.

Interrogating the Relationship Between Schizotypy, the Catechol-O-Methyltransferase (COMT) Val158Met Polymorphism, and Neuronal Oscillatory Activity

The COMT Val158Met polymorphism affects the availability of synaptic dopamine in the prefrontal cortex and has been widely studied as a genetic risk factor for psychosis. Schizotypy is associated with an increased risk of psychosis, with some studies implicating similar neurobiological mechanisms to schizophrenia. The present study sought to interrogate the link between the COMT Val158Met polymorphism and schizotypy using electroencephalogram (EEG) to identify neurophysiological mechanisms underpinning psychosis risk. Neurotypical (N = 91) adults were genotyped for the COMT Val158Met polymorphism, completed the Schizotypal Personality Questionnaire (SPQ), and had eyes open resting-state EEG recorded for 4 min. SPQ suspiciousness subscale scores were higher for individuals homozygous for Val/Val and Met/Met versus Val/Met genotypes. Delta, theta, alpha-2, beta-1, and beta-2 amplitudes were lower for Val/Val than Met/Met individuals. Lower theta amplitudes were correlated with higher total SPQ scores (P = 0.050), and multiple regression revealed that higher delta, and lower theta and beta-2 amplitudes (but not COMT genotype) best predicted total SPQ scores (P = 0.014). This study demonstrates the importance of COMT genotype in determining trait suspiciousness and EEG oscillatory activity. It also highlights relationships between dopaminergic alterations, EEG and schizotypy that are dissimilar to those observed in schizophrenia.

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity

Oscillatory activity is crucial for information processing in the brain, and has a long history as a biomarker for psychopathology. Variation in oscillatory activity is highly heritable, but current understanding of specific genetic influences remains limited. We performed the largest genome‐wide association study to date of oscillatory power during eyes‐closed resting electroencephalogram (EEG) across a range of frequencies (delta 1–3.75 Hz, theta 4–7.75 Hz, alpha 8–12.75 Hz, and beta 13–30 Hz) in 8,425 subjects. Additionally, we performed KGG positional gene‐based analysis and brain‐expression analyses. GABRA2—a known genetic marker for alcohol use disorder and epilepsy—significantly affected beta power, consistent with the known relation between GABA_A interneuron activity and beta oscillations. Tissue‐specific SNP‐based imputation of gene‐expression levels based on the GTEx database revealed that hippocampal GABRA2 expression may mediate this effect. Twenty‐four genes at 3p21.1 were significant for alpha power (FDR q < .05). SNPs in this region were linked to expression of GLYCTK in hippocampal tissue, and GNL3 and ITIH4 in the frontal cortex–genes that were previously implicated in schizophrenia and bipolar disorder. In sum, we identified several novel genetic variants associated with oscillatory brain activity; furthermore, we replicated and advanced understanding of previously known genes associated with psychopathology (i.e., schizophrenia and alcohol use disorders). Importantly, these psychopathological liability genes affect brain functioning, linking the genes' expression to specific cortical/subcortical brain regions.

Electroencephalographic delta/alpha frequency activity differentiates psychotic disorders: a study of schizophrenia, bipolar disorder and methamphetamine-induced psychotic disorder

Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. It is known that increased delta and decreased alpha, which are apparent in psychosis, are indicative of inappropriate arousal state, which leads to reduced ability to attend to relevant information. On this premise, we investigated delta/alpha frequency activity, as this ratio of frequency activity may serve as an effective neurophysiological biomarker. The current study investigated differences in delta/alpha frequency activity, in schizophrenia (SCZ), bipolar I disorder with psychotic features and methamphetamine-induced psychosis. One hundred and nine participants, including individuals with SCZ (n = 28), bipolar I disorder with psychotic features (n = 28), methamphetamine-induced psychotic disorder (MPD) (n = 24) and healthy controls (CON, n = 29). Diagnosis was ascertained with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition disorders and current medication was recorded. EEG was undertaken in three testing conditions: resting eyes open, resting eyes closed and during completion of a simple cognitive task (visual continuous performance task). EEG delta/alpha frequency activity was investigated across these conditions. First, delta/alpha frequency activity during resting eyes closed was higher in SCZ and MPD globally, when compared to CON, then lower for bipolar disorder (BPD) than MPD for right hemisphere. Second, delta/alpha frequency activity during resting eyes open was higher in SCZ, BPD and MPD for all electrodes, except left frontal, when compared to CON. Third, delta/alpha frequency activity during the cognitive task was higher in BPD and MPD for all electrodes, except left frontal, when compared to CON. Assessment of EEG delta/alpha frequency activity supports the delineation of underlying neurophysiological mechanisms present in psychotic disorders, which are likely related to dysfunctional thalamo-cortical connectivity. Delta/alpha frequency activity may provide a useful neurophysiological biomarker to delineate psychotic disorders.

Identifying auditory cortex encoding abnormalities in schizophrenia: The utility of low-frequency versus 40 Hz steady-state measures

Magnetoencephalography (MEG) and EEG have identified poststimulus low frequency and 40 Hz steady-state auditory encoding abnormalities in schizophrenia (SZ). Negative findings have also appeared. To identify factors contributing to these inconsistencies, healthy control (HC) and SZ group differences were examined in MEG and EEG source space and EEG sensor space, with better group differentiation hypothesized for source than sensor measures given greater predictive utility for source measures. Fifty-five HC and 41 chronic SZ were presented 500 Hz sinusoidal stimuli modulated at 40 Hz during simultaneous whole-head MEG and EEG. MEG and EEG source models using left and right superior temporal gyrus (STG) dipoles estimated trial-to-trial phase similarity and percent change from prestimulus baseline. Group differences in poststimulus low-frequency activity and 40 Hz steady-state response were evaluated. Several EEG sensor analysis strategies were also examined. Poststimulus low-frequency group differences were observed across all methods. Given an age-related decrease in left STG 40 Hz steady-state activity in HC (HC > SZ), 40 Hz steady-state group differences were evident only in younger participants' source measures. Findings thus indicated that optimal data collection and analysis methods depend on the auditory encoding measure of interest. In addition, whereas results indicated that HC and SZ auditory encoding low-frequency group differences are generally comparable across modality and analysis strategy (and thus not dependent on obtaining construct-valid measures of left and right auditory cortex activity), 40 Hz steady-state group-difference findings are much more dependent on analysis strategy, with 40 Hz steady-state source-space findings providing the best group differentiation.

Ketamine independently modulated power and phase-coupling of theta oscillations in Sp4 hypomorphic mice

Reduced expression of Sp4, the murine homolog of human SP4, a risk gene of multiple psychiatric disorders, led to N-methyl-D-aspartate (NMDA) hypofunction in mice, producing behavioral phenotypes reminiscent of schizophrenia, including hypersensitivity to ketamine. As accumulating evidence on molecular mechanisms and behavioral phenotypes established Sp4 hypomorphism as a promising animal model, systems-level neural circuit mechanisms of Sp4 hypomorphism, especially network dynamics underlying cognitive functions, remain poorly understood. We attempted to close this gap in knowledge in the present study by recording multi-channel epidural electroencephalogram (EEG) from awake behaving wildtype and Sp4 hypomorphic mice. We characterized cortical theta-band power and phase-coupling phenotypes, a known neural circuit substrate underlying cognitive functions, and further studied the effects of a subanesthetic dosage of ketamine on theta abnormalities unique to Sp4 hypomorphism. Sp4 hypomorphic mice had markedly elevated theta power localized frontally and parietally, a more pronounced theta phase progression along the neuraxis, and a stronger frontal-parietal theta coupling. Acute subanesthetic ketamine did not affect theta power in wildtype animals but significantly reduced it in Sp4 hypomorphic mice, nearly completely neutralizing their excessive frontal/parietal theta power. Ketamine did not significantly alter cortical theta phase progression in either wildtype or Sp4 hypomorphic animals, but significantly strengthened cortical theta phase-coupling in wildtype, but not in Sp4 hypomorphic animals. Our results suggested that the resting-state phenotypes of cortical theta oscillations unique to Sp4 hypomorphic mice closely mimicked a schizophrenic endophenotype. Further, ketamine independently modulated Sp4 hypomorphic anomalies in theta power and phase-coupling, suggesting separate underlying neural circuit mechanisms.

Electrophysiological correlates of adaptive control and attentional engagement in patients with first episode schizophrenia and healthy young adults

The goal of this study was to investigate the neural dynamics of error processing and post-error adjustments in cognitive control and attention to a cognitive task in schizophrenia. We adopted a time-frequency approach in order to examine activity in the theta and alpha frequency bands as indices of cognitive control and attentional engagement. The results showed that error processing was characterized by increases in theta-band activity, accompanied by decreases in alpha-band activity, in both healthy control participants and participants with schizophrenia. However, both the theta and alpha effects were significantly reduced in participants with schizophrenia. Post-error increases in theta activity were associated with improved accuracy on subsequent trials in control participants but not in participants with schizophrenia. In addition, increases in alpha-band activity were found in the prestimulus period before partial attention lapses, but only for control participants and participants with schizophrenia with relatively low positive symptom severity. These results provide evidence for a deficit in cognitive control mechanisms mediated by midfrontal theta activity in schizophrenia, and suggest a particularly pronounced deficit in patients' ability to engage adaptive control mechanisms following errors. Our results also indicate that partial attention lapses can be indexed in both control participants and participants with schizophrenia by increases in alpha activity, but that in schizophrenia this varies as a function of positive symptom severity. We suggest that disrupted theta-band function represents a key deficit of schizophrenia, whereas disruptions in the alpha band may be the byproduct of atypically regulated attention.

Delta Vs Gamma Auditory Steady State Synchrony in Schizophrenia

Background

Delta band (1-4 Hz) neuronal responses support the precision and stability of auditory processing, and a deficit in delta band synchrony may be relevant to auditory domain symptoms in schizophrenia patients.

Methods

Delta band synchronization elicited by a 2.5 Hz auditory steady state response (ASSR) paradigm, along with those from theta (5 Hz), alpha (10 Hz), beta (20 Hz), gamma (40 Hz), and high gamma (80 Hz) frequency ASSR, were compared in 128 patients with schizophrenia, 108 healthy controls, and 55 first-degree relatives (FDR) of patients.

Results

Delta band synchronization was significantly impaired in patients compared with controls (F = 18.3, P < .001). There was a significant 2.5 Hz by 40 Hz ASSR interaction (P = .023), arising from a greater reduction of 2.5 Hz ASSR than of 40 Hz ASSR, in patients compared with controls. Greater deficit in delta ASSR was associated with auditory perceptual abnormality (P = .007) and reduced verbal working memory (P < .001). Gamma frequency ASSR impairment was also significant but more modest (F = 8.7, P = .004), and this deficit was also present in FDR (P = .022).

Conclusions

The ability to sustain delta band oscillation entrainment in the auditory pathway is significantly reduced in schizophrenia patients and appears to be clinically relevant.

Aberrant alpha and gamma oscillations ex vivo after single application of the NMDA receptor antagonist MK-801

Clinical symptoms of schizophrenia are associated with altered cortical neuronal oscillations in multiple frequency bands such as alpha (7-13Hz) and gamma (30-90Hz) rhythms. NMDA receptor antagonists induce psychotic symptoms in humans and a schizophrenia-like phenotype in animals, suggesting NMDA receptor dysfunction is involved in the generation of many symptoms of the disorder. We investigated the effects of a single intraperitoneal injection of the NMDA receptor antagonist MK-801 in rats, a model of first-episode schizophrenia, on network oscillations recorded ex vivo in the hippocampus and prefrontal cortex. We found that spontaneous gamma oscillations in hippocampal slices of MK-801-treated animals had a higher peak frequency, but that their rate of occurrence, peak power and Q factor (ratio of peak frequency to half bandwidth) were not affected. Hippocampal gamma oscillations induced by application of acetylcholine displayed a higher peak power, a reduced peak frequency and a shortened induction latency, whereas the Q factor did not change. In the prefrontal cortex, co-application of carbachol and kainate induced two types of network activity in sham animals: continuous gamma oscillations and alternating alpha/gamma oscillations. In MK-801-treated animals, the alternating pattern completely disappeared, and only continuous gamma oscillations could be detected, possessing an increased peak power, decreased peak frequency and decreased Q factor. Alpha oscillations recorded in MK-801-treated animals also had a significantly lower Q factor. In conclusion, our data suggest that NMDA receptor antagonists fundamentally alter the power, peak frequency, dynamics and periodicity of neuronal oscillations in the alpha and gamma frequency band.

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

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