Power spectral aspects of the default mode network in schizophrenia: an MEG study

Power spectral density-based resting-state EEG classification of first-episode psychosis

Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and cognitive tasks have been studied many times. However, any significant dissimilarity in the resting-state low-frequency bands is yet to be established. Spectral analysis of the alpha and delta band waves shows the effectiveness of stimulus-independent EEG in identifying the abnormal activity patterns of pathological brains. A generalized model incorporating multiple frequency bands should be more efficient in associating potential EEG biomarkers with first-episode psychosis (FEP), leading to an accurate diagnosis. We explore multiple machine-learning methods, including random-forest, support vector machine, and Gaussian process classifier (GPC), to demonstrate the practicality of resting-state power spectral density (PSD) to distinguish patients of FEP from healthy controls. A comprehensive discussion of our preprocessing methods for PSD analysis and a detailed comparison of different models are included in this paper. The GPC model outperforms the other models with a specificity of 95.78% to show that PSD can be used as an effective feature extraction technique for analyzing and classifying resting-state EEG signals of psychiatric disorders.

The Pathophysiological Underpinnings of Gamma-Band Alterations in Psychiatric Disorders

Investigating the biophysiological substrates of psychiatric illnesses is of great interest to our understanding of disorders' etiology, the identification of reliable biomarkers, and potential new therapeutic avenues. Schizophrenia represents a consolidated model of γ alterations arising from the aberrant activity of parvalbumin-positive GABAergic interneurons, whose dysfunction is associated with perineuronal net impairment and neuroinflammation. This model of pathogenesis is supported by molecular, cellular, and functional evidence. Proof for alterations of γ oscillations and their underlying mechanisms has also been reported in bipolar disorder and represents an emerging topic for major depressive disorder. Although evidence from animal models needs to be further elucidated in humans, the pathophysiology of γ-band alteration represents a common denominator for different neuropsychiatric disorders. The purpose of this narrative review is to outline a framework of converging results in psychiatric conditions characterized by γ abnormality, from neurochemical dysfunction to alterations in brain rhythms.

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.

Atypical cortical networks in children at high-genetic risk of psychiatric and neurodevelopmental disorders

Although many genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. In this study, magnetoencephalography (MEG) was used to investigate electrophysiological markers of local and global network function in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Resting-state oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, neurodevelopmental symptoms and IQ. Children with 22q11.2DS had altered network activity and connectivity in high and low frequency bands, reflecting modified local and long-range cortical circuitry. Alpha and theta band connectivity were negatively associated with ASD symptoms while frontal high frequency (gamma band) activity was positively associated with ASD symptoms. Alpha band activity was positively associated with cognitive ability. These findings suggest that haploinsufficiency at the 22q11.2 locus impacts short and long-range cortical circuits, which could be a mechanism underlying neurodevelopmental and psychiatric vulnerability in this high-risk group.

Transcranial Alternating Current Stimulation (tACS) and Its Role in Schizophrenia: A Scoping Review

Transcranial alternating current stimulation (tACS) may modulate neuronal oscillations by applying sinusoidal alternating current, thereby alleviating associated symptoms in schizophrenia. Considering its possible utility in schizophrenia, we reviewed the literature for tACS protocols administered in schizophrenia and their findings. A scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline in databases and clinical trial registers. The search resulted in 59 publications. After excluding review articles unrelated to tACS, trials without published results or not involving patients with schizophrenia, 14 studies were included. Among the included studies/case reports only 5 were randomized controlled therapeutic trials. The studies investigated the utility of tACS for clinical and neurobiological outcomes. All studies reported good tolerability with only transient mild side effects. It was administered mostly during the working memory task (such as computerized n-back task, dual back task, and computerized digit symbol substitution task) for schizophrenia patients with cognitive deficits and during resting state while targeting positive symptoms. A possible reduction in hallucinations and delusions using alpha tACS, and improvement in negative and cognitive deficits with theta and gamma tACS were reported. Nevertheless, one of the randomized controlled trials targeting hallucinations was negative and rigorous large-sample studies are lacking for other domains. The current evidence for tACS in schizophrenia is preliminary though promising. In future, more sham controlled randomized trials assessing the effect of tACS on various domains are needed to substantiate these early findings.

DNMT1 SNPs (rs2114724 and rs2228611) associated with positive symptoms in Chinese patients with schizophrenia

OBJECTIVE

Schizophrenia is a serious mental disorder with complex clinical manifestations, while its pathophysiological mechanism is not fully understood. Accumulated evidence suggested the alteration in epigenetic pathway was associated with clinical features and brain dysfunctions in schizophrenia. DNA methyltransferases (DNMTs), a key enzyme for DNA methylation, are related to the development of schizophrenia, whereas the current research evidence is not sufficient. The aim of study was to explore the effects of gene polymorphisms of DNMTs on the susceptibility and symptoms of schizophrenia.

METHODS

The study was case-control study that designed and employed the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) as the diagnostic standard. 134 hospitalized patients with schizophrenia in the Third People's Hospital of Zhongshan City from January 2018 to April 2020 (Case group) as well as 64 healthy controls (Control group) from the same region were involved. Single nucleotide polymorphisms (SNPs) of DNMT1 genes (r s2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) were determined with massARRAY. Linkage disequilibrium analysis and haplotype analysis were performed, and genotype and allele frequencies were compared. The Hardy-Weinberg equilibrium was tested by the Chi-square test in SPSS software (version 20.0, SPSS Inc., USA). The severity of clinical symptoms was assessed by the Positive and Negative Syndrome Scale (PANSS). The correlation between DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs2424932, rs1569686, rs6119954 and rs2424908) and clinical features was analyzed.

RESULTS

There were no significant differences in genotype, allele frequency and haplotype of DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) between the case and healthy control group. There were significant differences in the PANSS total positive symptom scores, P3 (hallucinatory behavior), P6 (suspicious/persecution), G7 (motor retardation), and G15 (preoccupation) in patients with different DNMT1 gene rs 2114724 and rs 2228611 genotypes. The linkage disequilibrium analysis of gene polymorphic loci revealed that rs 2114724-rs 2228611 was complete linkage disequilibrium, and rs 1569686-rs 2424908, rs 2424932-rs 1569696 and rs 2424932-rs 2424908 were strongly linkage disequilibrium.

CONCLUSION

The polymorphisms alteration in genetic pathway may be associated with development of specific clinical features in schizophrenia.

Altered functional connectivity in anterior cingulate cortex subregions in treatment-resistant schizophrenia patients

BACKGROUND

The anterior cingulate cortex (ACC) plays a key role in motor control, attention, and cognitive control. It is well established that schizophrenia is associated with impaired functional connectivity (FC) of the ACC pathway. So far, however, there has been little discussion about the ACC subregions function in patients with treatment-resistant schizophrenia (TRS).

AIM

This study aims to characterize resting-state functional connectivity (rs-FC) profiles of ACC subregions in patients with TRS. The association between these FC and clinical symptoms, neurocognitive function, and grey matter volume (GMV) was studied as well.

METHODS

A total of 81 patients with schizophrenia (40 patients with TRS = 40, 41 patients with non-treatment-resistant schizophrenia (NTRS)) and 39 age- and gender-matched healthy controls (HC) were enrolled, and underwent structural magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), clinical evaluation. The ACC subregions, including subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC), were selected as seed regions from the automated anatomical labelling atlas 3 (AAL3). The GMV of the ACC subregions were calculated and seed-based FC maps for all ACC subregions were generated and compared between the TRS and NTRS, HC group. Additionally, correlations between altered FC and clinical symptoms, GMV, and neurocognitive functions in the TRS patients were explored.

RESULT

Compared with HC, increased FC was observed in TRS and NTRS groups between bilateral sgACC and left cuneus, right cuneus, and left lingual gyrus, while decreased FC was found between bilateral dACC and thalamic. Additionally, compared with NTRS, the TRS group showed increased FC between bilateral dACC and right cuneus and decreased FC between bilateral dACC and thalamic. The TRS group showed decreased GMV in all ACC subregions than the HC group, and there is no significant difference between the TRS group and the NTRS group.

CONCLUSION

The findings in this study suggest that disrupted FC of subregional ACC has the potential as a marker for TRS. The dysconnectivity of bilateral dACC- right cuneus and bilateral dACC-thalamus, are likely to be the unique FC profiles of TRS. These findings further our understanding of the neurobiological impairments in TRS.

Online Left-Hemispheric In-Phase Frontoparietal Theta tACS Modulates Theta-Band EEG Source-Based Large-Scale Functional Network Connectivity in Patients with Schizophrenia: A Randomized, Double-Blind, Sham-Controlled Clinical Trial

EEG studies indicated that schizophrenia patients had increased resting-state theta-band functional connectivity, which was associated with negative symptoms. We recently published the first study showing that theta (6 Hz) transcranial alternating current stimulation (tACS) over left prefrontal and parietal cortices during a working memory task for accentuating frontoparietal theta-band synchronization (in-phase theta-tACS) reduced negative symptoms in schizophrenia patients. Here, we hypothesized that in-phase theta-tACS can modulate theta-band large-scale networks connectivity in schizophrenia patients. In this randomized, double-blind, sham-controlled trial, patients received twice-daily, 2 mA, 20-min sessions of in-phase theta-tACS for 5 consecutive weekdays (n = 18) or a sham stimulation (n = 18). Resting-state electroencephalography data were collected at baseline, end of stimulation, and at one-week follow-up. Exact low resolution electromagnetic tomography (eLORETA) was used to compute intra-cortical activity. Lagged phase synchronization (LPS) was used to measure whole-brain source-based functional connectivity across 84 cortical regions at theta frequency (5-7 Hz). EEG data from 35 patients were analyzed. We found that in-phase theta-tACS significantly reduced the LPS between the posterior cingulate (PC) and the parahippocampal gyrus (PHG) in the right hemisphere only at the end of stimulation relative to sham (p = 0.0009, corrected). The reduction in right hemispheric PC-PHG LPS was significantly correlated with negative symptom improvement at the end of the stimulation (r = 0.503, p = 0.039). Our findings suggest that in-phase theta-tACS can modulate theta-band large-scale functional connectivity pertaining to negative symptoms. Considering the failure of right hemispheric PC-PHG functional connectivity to predict improvement in negative symptoms at one-week follow-up, future studies should investigate whether it can serve as a surrogate of treatment response to theta-tACS.

A review of the holy Quran listening and its neural correlation for its potential as a psycho-spiritual therapy

Since its revelation over 14 centuries ago, the Holy Quran is considered as scriptural divine words of Islam, and it is believed to promote psycho-spiritual therapeutic benefits to its reciter and/or listener. In this context, the listening of rhythmic Quranic verses among Muslims is often viewed as a form of unconventional melodic vocals, with accompanied anecdotal claims of the 'Quranic chills' pleasing effect. However, compared to music, rhythm, and meditation therapy, information on the neural basis of the anecdotal healing effects of the Quran remain largely unexplored. Current studies in this area took the leads from the low-frequency neuronal oscillations (i.e., alpha and theta) as the neural correlates, mainly using electroencephalography (EEG) and/or magnetoencephalography (MEG). In this narrative review, we present and discuss recent work related to these neural correlates and highlight several methodical issues and propose recommendations to progress this emerging transdisciplinary research. Collectively, evidence suggests that listening to rhythmic Quranic verses activates similar brain regions and elicits comparable therapeutic effects reported in music and rhythmic therapy. Notwithstanding, further research are warranted with more concise and standardized study designs to substantiate these findings, and opens avenue for the listening to Quranic verses as an effective complementary psycho-spiritual therapy.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Cortical correlation structure of aperiodic neuronal population activity

Electrophysiological population signals contain oscillatory and non-oscillatory aperiodic (1/frequency-like) components. So far research has largely focused on oscillatory activity, and only recently, interest in aperiodic population activity has gained momentum. Accordingly, while the cortical correlation structure of oscillatory population activity has been characterized, little is known about the correlation of aperiodic neuronal activity. To address this, we investigated aperiodic neuronal population activity in the human brain using resting-state magnetoencephalography (MEG). We combined source-analysis, signal orthogonalization and irregular-resampling auto-spectral analysis (IRASA) to systematically characterize the cortical distribution and correlation of aperiodic neuronal activity. We found that aperiodic population activity is robustly correlated across the cortex and that this correlation is spatially well structured. Furthermore, we found that the cortical correlation structure of aperiodic activity is similar but distinct from the correlation structure of oscillatory neuronal activity. Anterior cortical regions showed the strongest differences between oscillatory and aperiodic correlation patterns. Our results suggest that correlations of aperiodic population activity serve as robust markers of cortical network interactions. Furthermore, our results show that aperiodic and oscillatory signal components provide non-redundant information about large-scale neuronal correlations. This may reflect at least partly distinct neuronal mechanisms underlying and reflected by oscillatory and aperiodic neuronal population activity.

Modulating verbal working memory with fronto-parietal transcranial electric stimulation at theta frequency: Does it work?

Oscillatory theta activity in a fronto-parietal network has been associated with working memory (WM) processes and may be directly related to WM performance. In their seminal study, Polanía et al. (2012) (de-)coupled a fronto-parietal theta-network by applying transcranial alternating current stimulation (tACS), and showed that anti-phase tACS led to slower and in-phase tACS to faster response times in a verbal WM task compared to placebo stimulation. In the literature, this 'synchronization-desynchronization' effect has only been partly replicated, and electric field modelling suggests that it might not be the fronto-parietal network that is primarily stimulated during in-phase tACS with a shared return electrode. This provides one possible reason for inconsistency in the literature. In this study, we aimed to reproduce the findings reported by Polanía et al. (2012). We also aimed to investigate whether in-phase theta tACS with multiple close-by return electrodes for focal stimulation of the frontal and the parietal cortex will have at least as much of a facilitatory effect as the in-phase stimulation as indicated by Polania et al. (2012). In a single-trial distributional analysis, we explored whether mean, variation and right-skewness of the response time distribution are affected. Against our hypothesis, we found no 'synchronization-desynchronization' effect by fronto-parietal theta tACS on response times using the same delayed letter discrimination task and stimulation parameters in two experiments, both between-subjects and within-subjects. However, we could show that in a more demanding 3-back task, fronto-parietal in-phase and in-phase focal theta tACS substantially improved task performance compared to placebo stimulation.

DNA Methylation and Schizophrenia: Current Literature and Future Perspective

Schizophrenia is a neuropsychiatric disorder characterized by dissociation of thoughts, idea, identity, and emotions. It has no central pathophysiological mechanism and precise diagnostic markers. Despite its high heritability, there are also environmental factors implicated in the development of schizophrenia. Epigenetic factors are thought to mediate the effects of environmental factors in the development of the disorder. Epigenetic modifications like DNA methylation are a risk factor for schizophrenia. Targeted gene approach studies attempted to find candidate gene methylation, but the results are contradictory. Genome-wide methylation studies are insufficient in literature and the available data do not cover different populations like the African populations. The current genome-wide studies have limitations related to the sample and methods used. Studies are required to control for these limitations. Integration of DNA methylation, gene expression, and their effects are important in the understanding of the development of schizophrenia and search for biomarkers. There are currently no precise and functional biomarkers for the disorder. Several epigenetic markers have been reported to be common in functional and peripheral tissue. This makes the peripheral tissue epigenetic changes a surrogate of functional tissue, suggesting common epigenetic alteration can be used as biomarkers of schizophrenia in peripheral tissue.

Local Oscillatory Brain Dynamics of Mind Wandering in Schizophrenia

A number of studies have focused on brain dynamics underlying mind wandering (MW) states in healthy people. However, there is limited understanding of how the oscillatory dynamics accompanying MW states and task-focused states are characterized in clinical populations. In this study, we explored EEG local synchrony of MW associated with schizophrenia, under the premise that changes in attention that arise during MW are associated with a different pattern of brain activity. To this end, we measured the power of EEG oscillations in different frequency bands, recorded while participants watched short video clips. In the group of participants diagnosed with schizophrenia, the power in MW states was significantly lower than during task-focused states, mainly in the frontal and posterior regions. However, in the group of healthy controls, the differences in power between the task-focused and MW states occurred exclusively in the posterior region. Furthermore, the power of the frequency bands during MW and during episodes of task-focused attention correlated with cognitive variables such as processing speed and working memory. These findings on dynamic changes of local synchronization in different frequency bands and areas of the cortex can improve our understanding of mental disorders, such as schizophrenia.

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.

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Background: Interest in disordered sense of self in schizophrenia has recently re-emerged in the literature. It has been proposed that there is a basic self disturbance, underlying the diagnostic symptoms of schizophrenia, in which the person's sense of being a bounded individual continuous through time loses stability. This disturbance has been documented phenomenologically and at the level of cognitive tasks. However, the neural correlates of basic self disorder in schizophrenia are poorly understood. Methods: A search of PubMed was used to identify studies on self and schizophrenia that reported EEG or MEG data. Results: Thirty-three studies were identified, 32 using EEG and one using MEG. Their operationalizations of the self were divided into six paradigms: self-monitoring for errors, proprioception, self-other integration, self-referential processing, aberrant salience, and source monitoring. Participants with schizophrenia were less accurate on self-referential processing tasks and had slower response times across most studies. Event-related potential amplitudes differed across many early and late components, with reduced N100 suppression in source monitoring paradigms being the most replicated finding. Several studies found differences in one or more frequency band, but no coherent overall finding emerged in this area. Various other measures of brain dynamics also showed differences in single studies. Only some of the study designs were adequate to establish a causal relationship between the self and EEG or MEG measures. Conclusion: The broad range of changes suggests a global self disturbance at the neuronal level, possibly carried over from the resting state. Further studies that successfully isolate self-related effects are warranted to better understand the temporal-dynamic and spatial-topographic basis of self disorder and its relationship to basic self disturbance on the phenomenological level.

Do NMDA-R antagonists re-create patterns of spontaneous gamma-band activity in schizophrenia? A systematic review and perspective

NMDA-R hypofunctioninig is a core pathophysiological mechanism in schizophrenia. However, it is unclear whether the physiological changes observed following NMDA-R antagonist administration are consistent with gamma-band alterations in schizophrenia. This systematic review examined the effects of NMDA-R antagonists on the amplitude of spontaneous gamma-band activity and functional connectivity obtained from preclinical (n = 24) and human (n = 9) studies and compared these data to resting-state EEG/MEG-measurements in schizophrenia patients (n = 27). Overall, the majority of preclinical and human studies observed increased gamma-band power following acute administration of NMDA-R antagonists. However, the direction of gamma-band power alterations in schizophrenia were inconsistent, which involved upregulation (n = 10), decreases (n = 7), and no changes (n = 8) in spectral power. Five out of 6 preclinical studies observed increased connectivity, while in healthy controls receiving Ketamine and in schizophrenia patients the direction of connectivity results was also inconsistent. Accordingly, the effects of NMDA-R hypofunctioning on gamma-band oscillations are different than pathophysiological signatures observed in schizophrenia. The implications of these findings for current E/I balance models of schizophrenia are discussed.

Resting-state hyperconnectivity within the default mode network impedes the ability to initiate cognitive performance in first-episode schizophrenia patients

Among multiple cognitive impairments present in schizophrenia, a decline in fast information processing is one of the most severe neuropsychological deficit. Reduced ability to efficiently launch a coherent cognitive activity might be a significant factor contributing to poor results in time-limited tasks obtained by schizophrenia patients. The aim of this study was to identify neurophysiological predictors of expected cognitive initiation failures in a group of first-episode schizophrenia individuals (SZ). To evaluate the effectiveness of initiation, a dynamic analysis of design fluency test was applied, assessing to what extent the productivity was focused within the first interval of the performance, what is a typical way healthy subjects execute this task. Resting-state EEG recordings were obtained from SZ patients (n = 34) and controls (n = 30) to examine functional connectivity between 84 intra-cortical current sources determined by eLORETA (exact low-resolution brain electromagnetic tomography) for six conventionally analyzed frequencies. The nonparametric randomization approach was used to identify hypo- and hyper-connections, i.e. synchronizations significantly differentiating the studied samples in terms of connectivity strength. Generally, SZ patients obtained poor outcomes in fluency test and dynamic analysis of performance confirmed the presence of initiation deficit in clinical sample, which was a single factor explaining the intergroup difference regarding the entire task. In the majority of frequencies, the arrangement of synchronizations in SZ group was dominated by hypo-connections, except for the theta band, in which the strength of synchronizations between posterior cingulate cortex, cuneus and precuneus was significantly higher for SZ group. These theta-band hyper-connections turned out to be significant predictors of cognitive initiation failure in the clinical sample. Additionally, theta hyper-connections correlated negatively with the total number of unique designs generated by patients, however, the strength of this correlation was weaker than regarding initiation index. The results of this study suggest that baseline hyperconnectivity within the posterior hub of the Default Mode Network, containing posterior cingulate gyrus and precuneus, might disturb effective cognitive outcome, not only by interfering with task-positive functional networks but also by delaying the starting phase of performance, which might be specifically deleterious for the execution of time-limited tests.

Effect of add-on transcranial alternating current stimulation (tACS) on persistent delusions in schizophrenia

The utility of non-invasive brain stimulation techniques to alleviate resistant delusions in schizophrenia is an under-researched area. In this study, we report the effectiveness of alpha transcranial alternating current stimulation (tACS) targeting the medial prefrontal cortex in ameliorating persistent delusions. Twelve Schizophrenia patients (N=12) with persistent delusions received add-on treatment with a twice-daily 20-minutes session of 10-Hz tACS. Significant reduction in severity of delusion was noted after 5th day (z=2.67, p<0.01, n=12) with further improvement after 10th day (z=2.52, p=0.01, n=9) of stimulation. Add-on treatment with 10-Hz tACS is a potential therapeutic option for treatment-resistant delusions, which requires further systematic research.

Relationship between resting-state theta phase-gamma amplitude coupling and neurocognitive functioning in patients with first-episode psychosis

BACKGROUND

Although cognitive dysfunction is a core element of schizophrenia, the neurobiological underpinnings of the pathophysiology are not yet sufficiently understood. Because the resting state is crucial for cognitive functioning and electroencephalography (EEG) can reflect instantaneous neural activity, we investigated theta phase-gamma amplitude coupling (TGC) of resting-state EEG and its relationship with cognitive function in patients with first-episode psychosis (FEP) to reveal the neural correlates of cognitive dysfunction.

METHODS

A total of 59 FEP patients and 50 healthy controls (HCs) underwent resting-state, eyes-closed EEG recordings and performed the Trail Making Test Part A (TMT-A) and Part B (TMT-B) and California Verbal Learning Test (CVLT). TGC from the source signal of the resting-state EEG in default mode network (DMN)-related brain regions was compared between groups. Correlation analyses were performed between TGC and cognitive function test performance in FEP patients.

RESULTS

Mean resting-state TGC was larger for the FEP patients than for the HCs. Patients with FEP showed increased TGC in the left posterior cingulate cortex, which was correlated with better performance on the TMT-A and TMT-B and on immediate and delayed recall in the CVLT.

CONCLUSIONS

These results suggest that patients with FEP show compensatory hyperactivation of resting-state TGC in DMN-related brain regions, which may be related to the reallocation of cognitive resources to prepare for successful cognitive execution. This study not only highlights the neural underpinnings of cognitive dysfunction in FEP patients but also provides useful background to support the development of treatments for cognitive dysfunction in schizophrenia.

Brain mechanisms in motor control during reaching movements: Transition of functional connectivity according to movement states

Understanding how the brain controls movements is a critical issue in neuroscience. The role of brain changes rapidly according to movement states. To elucidate the motor control mechanism of brain, it is essential to investigate the changes in brain network in motor-related regions according to movement states. Therefore, the objective of this study was to investigate the brain network transitions according to movement states. We measured whole brain magnetoencephalography (MEG) signals and extracted source signals in 24 motor-related areas. Functional connectivity and centralities were calculated according to time flow. Our results showed that brain networks differed between states of motor planning and movement. Connectivities between most motor-related areas were increased in the motor-planning state. In contrast, only connectivities with cerebellum and basal ganglia were increased while those of other motor-related areas were decreased during movement. Our results indicate that most processes involved in motor control are completed before movement. Further, brain developed network related to feedback rather than motor decision during movements. Our findings also suggest that neural signals during motor planning might be more predictive than neural signals during movement. They facilitate accurate prediction of movement for brain-machine interfaces and provide insight into brain mechanisms in motor control.

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.

Prospects for Future Methodological Development and Application of Magnetoencephalography Devices in Psychiatry

Magnetoencephalography (MEG) is a functional neuroimaging tool that can record activity from the entire cortex on the order of milliseconds. MEG has been used to investigate numerous psychiatric disorders, such as schizophrenia, bipolar disorder, major depression, dementia, and autism spectrum disorder. Although several review papers on the subject have been published, perspectives and opinions regarding the use of MEG in psychiatric research have primarily been discussed from a psychiatric research point of view. Owing to a newly developed MEG sensor, the use of MEG devices will soon enter a critical period, and now is a good time to discuss the future of MEG use in psychiatric research. In this paper, we will discuss MEG devices from a methodological point of view. We will first introduce the utilization of MEG in psychiatric research and the development of its technology. Then, we will describe the principle theory of MEG and common algorithms, which are useful for applying MEG tools to psychiatric research. Next, we will consider three topics-child psychiatry, resting-state networks, and cortico-subcortical networks-and address the future use of MEG in psychiatry from a broader perspective. Finally, we will introduce the newly developed device, the optically-pumped magnetometer, and discuss its future use in MEG systems in psychiatric research from a methodological point of view. We believe that state-of-the-art electrophysiological tools, such as this new MEG system, will further contribute to our understanding of the core pathology in various psychiatric disorders and translational research.

Alterations in resting-state gamma activity in patients with schizophrenia: a high-density EEG study

Alterations of EEG gamma activity in schizophrenia have been reported during sensory and cognitive tasks, but it remains unclear whether changes are present in resting state. Our aim was to examine whether changes occur in resting state, and to delineate those brain regions where gamma activity is altered. Furthermore, we wanted to identify the associations between changes in gamma activity and psychopathological characteristics. We studied gamma activity (30-48 Hz) in 60 patients with schizophrenia and 76 healthy controls. EEGs were acquired in resting state with closed eyes using a high-density, 256-channel EEG-system. The two groups were compared in absolute power measures in the gamma frequency range. Compared to controls, in patients with schizophrenia the absolute power was significantly elevated (false discovery rate corrected p < 0.05). The alterations clustered into fronto-central and posterior brain regions, and were positively associated with the severity of psychopathology, measured by the PANSS. Changes in gamma activity can lead to disturbed coordination of large-scale brain networks. Thus, the increased gamma activity in certain brain regions that we found may result in disturbances in temporal coordination of task-free/resting-state networks in schizophrenia. Positive association of increased gamma power with psychopathology suggests that altered gamma activity provides a contribution to symptom presentation.

Anterior Cingulate Glutamate and GABA Associations on Functional Connectivity in Schizophrenia

BACKGROUND

The underlying neurobiological mechanism for abnormal functional connectivity in schizophrenia (SCZ) remains unknown. This project investigated whether glutamate and GABA, 2 metabolites that contribute to excitatory and inhibitory functions, may influence functional connectivity in SCZ.

METHODS

Resting-state functional magnetic resonance imaging and proton magnetic resonance spectroscopy were acquired from 58 SCZ patients and 61 healthy controls (HC). Seed-based connectivity maps were extracted between the anterior cingulate cortex (ACC) spectroscopic voxel and all other brain voxels. Magnetic resonance spectroscopy (MRS) spectra were processed to quantify glutamate and GABA levels. Regression analysis was performed to describe relationships between functional connectivity and glutamate and GABA levels.

RESULTS

Reduced ACC functional connectivity in SCZ was found in regions associated with several neural networks including the default mode network (DMN) compared to HC. In the HC, positive correlations were found between glutamate and both ACC-right inferior frontal gyrus functional connectivity and ACC-bilateral superior temporal gyrus functional connectivity. A negative correlation between GABA and ACC-left posterior cingulate functional connectivity was also observed in HC. These same relationships were not statistically significant in SCZ.

CONCLUSIONS

The present investigation is one of the first studies to examine links between functional connectivity and glutamate and GABA levels in SCZ. Results indicate that glutamate and GABA play an important role in the functional connectivity modulation in the healthy brain. The absence of glutamate and GABA correlations in areas where SCZ showed significantly reduced functional connectivity may suggest that this chemical-functional relationship is disrupted in SCZ.

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.

Maturation trajectories of cortical resting-state networks depend on the mediating frequency band

The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.

Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique

Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc.

Global dynamics of selective attention and its lapses in primary auditory cortex

Previous research demonstrated that while selectively attending to relevant aspects of the external world, the brain extracts pertinent information by aligning its neuronal oscillations to key time points of stimuli or their sampling by sensory organs. This alignment mechanism is termed oscillatory entrainment. We investigated the global, long-timescale dynamics of this mechanism in the primary auditory cortex of nonhuman primates, and hypothesized that lapses of entrainment would correspond to lapses of attention. By examining electrophysiological and behavioral measures we observed that besides the lack of entrainment by external stimuli, attentional lapses were characterized by high amplitude alpha oscillations, with alpha frequency structuring of neuronal ensemble and single unit operations. Strikingly, entrainment and alpha oscillation dominated periods were strongly anti-correlated and fluctuated rhythmically at an ultra-slow rate. Our results indicate that these two distinct brain states represent externally versus internally oriented computational resources engaged by large-scale task-positive and task-negative functional networks.

How do abnormalities in the brain's spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology

Schizophrenia is a complex neuropsychiatric disorder with a variety of symptoms that include sensorimotor, affective, cognitive, and social changes. The exact neuronal mechanisms underlying these symptoms remain unclear though. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's spontaneous activity, otherwise known as its resting state activity. While various spatial and temporal abnormalities have been observed in spontaneous activity in schizophrenia, their meaning and significance for the different psychopathological symptoms in schizophrenia, are yet to be defined. The first aim in this paper is to provide an overview of recent findings concerning changes in the spatial (e.g., functional connectivity) and temporal (e.g., couplings between different frequency fluctuations) properties of spontaneous activity in schizophrenia. The second aim is to link these spatiotemporal changes to the various psychopathological symptoms of schizophrenia, with a specific focus on basic symptoms, formal thought disorder, and ego-disturbances. Based on the various findings described, we postulate that the spatiotemporal changes on the neuronal level of the brain's spontaneous activity transform into corresponding spatiotemporal changes on the psychological level which, in turn, leads to the different kinds of psychopathological symptoms. We consequently suggest a spatiotemporal rather than cognitive or sensory approach to the condition, amounting to what we describe as "Spatiotemporal Psychopathology".

Abnormal Neural Oscillations in Schizophrenia Assessed by Spectral Power Ratio of MEG During Word Processing

This study investigated spectral power of neural oscillations associated with word processing in schizophrenia. Magnetoencephalography (MEG) data were acquired from 12 schizophrenia patients and 10 healthy controls during a visual word processing task. Two spectral power ratio (SPR) feature sets: the band power ratio (BPR) and the window power ratio (WPR) were extracted from MEG data in five frequency bands, four time windows of word processing, and at locations covering whole head. Cluster-based nonparametric permutation tests were employed to identify SPRs that show significant between-group difference. Machine learning based feature selection and classification techniques were then employed to select optimal combinations of the significant SPR features, and distinguish schizophrenia patients from healthy controls. We identified three BPR clusters and three WPR clusters that show significant oscillation power difference between groups. These include the theta/delta, alpha/delta and beta/delta BPRs during base-to-encode and encode time windows, and the beta band WPR from base to encode and from encode to post-encode windows. Based on two WPR and one BPR features combined, over 95% cross-validation classification accuracy was achieved using three different linear classifiers separately. These features may have potential as quantitative markers that discriminate schizophrenia patients and healthy controls; however, this needs further validation on larger samples.

Increased Low- and High-Frequency Oscillatory Activity in the Prefrontal Cortex of Fibromyalgia Patients

Recent human neuroimaging studies have suggested that fibromyalgia (FM), a chronic widespread pain disorder, exhibits altered thalamic structure and function. Since the thalamus has extensive reciprocal connection with the cortex, structural and functional thalamic alterations in FM might be linked to aberrant thalamocortical oscillation. This study investigated the presence of abnormal brain rhythmicity in low- and high-frequency bands during resting state in patients with FM and their relationship to clinical pain symptom. Spontaneous magnetoencephalography (MEG) activity was recorded in 18 females with FM and 18 age- and sex-matched healthy control (HC) subjects. The most remarkable finding was that FM patients had general increases in theta, beta and gamma power along with a slowing of the dominant alpha peak. Increased spectral powers in the theta-band were primarily localized to the left dorsolateral prefrontal (DLPFC) and orbitofrontal cortex (OFC). Beta and gamma over-activation were localized to insular, primary motor and primary and secondary somatosensory (S2) cortices, as well as the DLPFC and OFC. Furthermore, enhanced high-frequency oscillatory activities in the DLPFC and OFC were associated with higher affective pain scores in patients with FM. Our results demonstrate that FM patients feature enhanced low- and high-frequency oscillatory activity in the brain areas related to cognitive and emotional modulation of pain. Increased low- and high-frequency activity of the prefrontal cortex may contribute to persistent perception of pain in FM. Therapeutic intervention based on manipulating neural oscillation to restore normal thalamocortical rhythmicity may be beneficial to pain relief in FM.

Cellular and circuit models of increased resting-state network gamma activity in schizophrenia

Schizophrenia (SCZ) is a disorder characterized by positive symptoms (hallucinations, delusions), negative symptoms (blunted affect, alogia, reduced sociability, and anhedonia), as well as persistent cognitive deficits (memory, concentration, and learning). While the biology underlying subjective experiences is difficult to study, abnormalities in electroencephalographic (EEG) measures offer a means to dissect potential circuit and cellular changes in brain function. EEG is indispensable for studying cerebral information processing due to the introduction of techniques for the decomposition of event-related activity into its frequency components. Specifically, brain activity in the gamma frequency range (30-80Hz) is thought to underlie cognitive function and may be used as an endophenotype to aid in diagnosis and treatment of SCZ. In this review we address evidence indicating that there is increased resting-state gamma power in SCZ. We address how modeling this aspect of the illness in animals may help treatment development as well as providing insights into the etiology of SCZ.

COMT polymorphism modulates the resting-state EEG alpha oscillatory response to acute nicotine in male non-smokers

Performance improvements in cognitive tasks requiring executive functions are evident with nicotinic acetylcholine receptor (nAChR) agonists, and activation of the underlying neural circuitry supporting these cognitive effects is thought to involve dopamine neurotransmission. As individual difference in response to nicotine may be related to a functional polymorphism in the gene encoding catechol-O-methyltransferase (COMT), an enzyme that strongly influences cortical dopamine metabolism, this study examined the modulatory effects of the COMT Val158Met polymorphism on the neural response to acute nicotine as measured with resting-state electroencephalographic (EEG) oscillations. In a sample of 62 healthy non-smoking adult males, a single dose (6 mg) of nicotine gum administered in a randomized, double-blind, placebo-controlled design was shown to affect α oscillatory activity, increasing power of upper α oscillations in frontocentral regions of Met/Met homozygotes and in parietal/occipital regions of Val/Met heterozygotes. Peak α frequency was also found to be faster with nicotine (vs. placebo) treatment in Val/Met heterozygotes, who exhibited a slower α frequency compared to Val/Val homozygotes. The data tentatively suggest that interindividual differences in brain α oscillations and their response to nicotinic agonist treatment are influenced by genetic mechanisms involving COMT.

Posterior EEG alpha at rest and during task performance: Comparison of current source density and field potential measures

Resting and task-related EEG alpha are used in studies of cognition and psychopathology. Although Laplacian methods have been applied, apprehensions about loss of global activity dissuade researchers from greater use except as a supplement to reference-dependent measures. The unfortunate result has been continued reliance on reference strategies that differ across labs, and a systemic preference for a montage-dependent average reference over true reference-free measures. We addressed these concerns by comparing resting- and task-related EEG alpha using three EEG transformations: nose- (NR) and average-referenced (AR) EEG, and the corresponding CSD. Amplitude spectra of resting and prestimulus task-related EEG (novelty oddball) and event-related spectral perturbations were scaled to equate each transformation. Alpha measures quantified for 8-12 Hz bands were: 1) net amplitude (eyes-closed minus eyes-open) and 2) overall amplitude (eyes-closed plus eyes-open); 3) task amplitude (prestimulus baseline) and 4) task event-related desynchronization (ERD). Mean topographies unambiguously represented posterior alpha for overall, net and task, as well as poststimulus alpha ERD. Topographies were similar for the three transformations, but differed in dispersion, CSD being sharpest and NR most broadly distributed. Transformations also differed in scale, AR showing less attenuation or spurious secondary maxima at anterior sites, consistent with simulations of distributed posterior generators. Posterior task alpha and alpha ERD were positively correlated with overall alpha, but not with net alpha. CSD topographies consistently and appropriately represented posterior EEG alpha for all measures.