Resting EEG in psychosis and at-risk populations--a possible endophenotype?

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.

Coherent activity within and between hemispheres: cortico-cortical connectivity revealed by rTMS of the right posterior parietal cortex

Introduction

Low frequency (1 Hz) repetitive transcranial stimulation (rTMS) applied over right posterior parietal cortex (rPPC) has been shown to reduce cortical excitability both of the stimulated area and of the interconnected contralateral homologous areas. In the present study, we investigated the whole pattern of intra- and inter-hemispheric cortico-cortical connectivity changes induced by rTMS over rPPC.

Methods

To do so, 14 healthy participants underwent resting state EEG recording before and after 30 min of rTMS at 1 Hz or sham stimulation over the rPPC (electrode position P6). Real stimulation was applied at 90% of motor threshold. Coherence values were computed on the electrodes nearby the stimulated site (i.e., P4, P8, and CP6) considering all possible inter- and intra-hemispheric combinations for the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-50 Hz).

Results and discussion

Results revealed a significant increase in coherence in delta, theta, alpha and beta frequency bands between rPPC and the contralateral homologous sites. Moreover, an increase in coherence in theta, alpha, beta and gamma frequency bands was found between rPPC and right frontal sites, reflecting the activation of the fronto-parietal network within the right hemisphere. Summarizing, subthreshold rTMS over rPPC revealed cortico-cortical inter- and intra-hemispheric connectivity as measured by the increase in coherence among these areas. Moreover, the present results further confirm previous evidence indicating that the increase of coherence values is related to intra- and inter-hemispheric inhibitory effects of rTMS. These results can have implications for devising evidence-based rehabilitation protocols after stroke.

Computational psychiatry: from synapses to sentience

This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.

Alpha3/alpha2 power ratios relate to performance on a virtual reality shopping task in ageing adults

Background

Aspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer’s disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio – a marker of AD, and a novel virtual reality (VR) functional cognition task – VStore, in discriminating between young and ageing healthy adults.

Materials and methods

Twenty young individuals aged 20–30, and 20 older adults aged 60–70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden’s J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong’s test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance.

Results

The difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer’s Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer’s Battery (r = -0.67), and Cogstate Composite Score (r = -0.76).

Conclusion

While we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.

Fractal Structure of Brain Electrical Activity of Patients With Mental Disorders

This work was aimed at a comparative analysis of the degree of multifractality of electroencephalographic time series obtained from a group of healthy subjects and from patients with mental disorders. We analyzed long-term records of patients with paranoid schizophrenia and patients with depression. To evaluate the properties of multifractal scaling of various electroencephalographic time series, the method of maximum modulus of the wavelet transform and multifractal analysis of fluctuations without a trend were used. The stability of the width and position of the singularity spectrum for each of the test groups was revealed, and a relationship was established between the correlation and anticorrelation dynamics of successive values of the electroencephalographic time series and the type of mental disorders. It was shown that the main differences between the multifractal properties of brain activity in normal and pathological conditions lie in the different width of the multifractality spectrum and its location associated with the correlated or anticorrelated dynamics of the values of successive time series. It was found that the schizophrenia group is characterized by a greater degree of multifractality compared to the depression group. Thus, the degree of multifractality can be included in a set of tests for differential diagnosis and research of mental disorders.

Intrinsic neural activity predisposes susceptibility to a body illusion

Susceptibility to the rubber hand illusion (RHI) varies. To date, however, there is no consensus explanation of this variability. Previous studies, focused on the role of multisensory integration, have searched for neural correlates of the illusion. But those studies have failed to identify a sufficient set of functionally specific neural correlates. Because some evidence suggests that frontal α power is one means of tracking neural instantiations of self, we hypothesized that the higher the frontal α power during the eyes-closed resting state, the more stable the self. As a corollary, we infer that the more stable the self, the less susceptible are participants to a blurring of boundaries—to feeling that the rubber hand belongs to them. Indeed, we found that frontal α amplitude oscillations negatively correlate with susceptibility. Moreover, since lower frequencies often modulate higher frequencies, we explored the possibility that this might be the case for the RHI. Indeed, some evidence suggests that high frontal α power observed in low-RHI participants is modulated by δ frequency oscillations. We conclude that while neural correlates of multisensory integration might be necessary for the RHI, sufficient explanation involves variable intrinsic neural activity that modulates how the brain responds to incompatible sensory stimuli.

Thalamocortical dysrhythmia in patients with schizophrenia spectrum disorder and individuals at clinical high risk for psychosis

Thalamocortical dysrhythmia (TCD) is a model characterized by abnormal resting-state thalamic oscillatory patterns where the alpha rhythm is replaced by cross-frequency coupling of low- and high-frequency rhythms. Although disrupted thalamic function is a suggested important pathophysiological mechanism underlying schizophrenia, knowledge regarding the TCD model in schizophrenia spectrum disorder (SSD) patients and individuals at clinical high risk (CHR) for psychosis is limited. A total of 169 SSD patients, 106 individuals at CHR for psychosis, and 105 healthy controls (HCs) underwent resting-state electroencephalography recordings. We performed mean global field power (MGFP) spectral analysis between 1 and 49 Hz as well as source-level theta phase-gamma amplitude coupling (TGC) analysis and compared resting-state oscillatory patterns across groups. Correlations between altered TGC values and psychotic symptom severity in the patient group were investigated. Spectral MGFP of low- and high-frequencies was larger in the SSD and CHR groups than in the HC group. The TGC of SSD patients was greater than that of HCs in the right frontal, right parietal, and left and right limbic lobes. Greater TGC in the right frontal and limbic lobes was associated with positive symptom severity in SSD patients. However, TGC in the CHR group was comparable to that in the HCs and was smaller than that in the SSD group in widespread cortical regions. The TCD pattern may be apparent after frank psychotic disorder onset in tandem with overt positive symptoms. A psychosis-risk state without overt psychotic symptoms could be characterized by abnormally increased low- and high-frequency activities with relatively preserved TGC.

Identifying Electroencephalography Biomarkers in Individuals at Clinical High Risk for Psychosis in an International Multi-Site Study

BACKGROUND

The clinical high-risk for psychosis (CHR-P) paradigm was introduced to detect individuals at risk of developing psychosis and to establish preventive strategies. While current prediction of outcomes in the CHR-P state is based mostly on the clinical assessment of presenting features, several emerging biomarkers have been investigated in an attempt to stratify CHR-P individuals according to their individual trajectories and refine the diagnostic process. However, heterogeneity across subgroups is a key challenge that has limited the impact of the CHR-P prediction strategies, as the clinical validity of the current research is limited by a lack of external validation across sites and modalities. Despite these challenges, electroencephalography (EEG) biomarkers have been studied in this field and evidence suggests that EEG used in combination with clinical assessments may be a key measure for improving diagnostic and prognostic accuracy in the CHR-P state. The PSYSCAN EEG study is an international, multi-site, multimodal longitudinal project that aims to advance knowledge in this field.

METHODS

Participants at 6 international sites take part in an EEG protocol including EEG recording, cognitive and clinical assessments. CHR-P participants will be followed up after 2 years and subcategorised depending on their illness progression regarding transition to psychosis. Differences will be sought between CHR-P individuals and healthy controls and between CHR-P individuals who transition and those who do not transition to psychosis using data driven computational analyses.

DISCUSSION

This protocol addresses the challenges faced by previous studies of this kind to enable valid identification of predictive EEG biomarkers which will be combined with other biomarkers across sites to develop a prognostic tool in CHR-P. The PSYSCAN EEG study aims to pave the way for incorporating EEG biomarkers in the assessment of CHR-P individuals, to refine the diagnostic process and help to stratify CHR-P subjects according to risk of transition. This may improve our understanding of the CHR-P state and therefore aid the development of more personalized treatment strategies.

EEG microstate features for schizophrenia classification

Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes in brain state in neuropsychiatric diseases. However, previous studies have only reported differences in each microstate feature and have not determined whether microstate features are suitable for schizophrenia classification. Therefore, it is necessary to validate microstate features for schizophrenia classification. Nineteen microstate features, including duration, occurrence, and coverage as well as thirty-one conventional EEG features, including statistical, frequency, and temporal characteristics were obtained from resting-state EEG recordings of 14 patients diagnosed with schizophrenia and from 14 healthy (control) subjects. Machine-learning based multivariate analysis was used to evaluate classification performance. EEG recordings of patients and controls showed different microstate features. More importantly, when differentiating among patients and controls, EEG microstate features outperformed conventional EEG ones. The performance of the microstate features exceeded that of conventional EEG, even after optimization using recursive feature elimination. EEG microstate features applied with conventional EEG features also showed better classification performance than conventional EEG features alone. The current study is the first to validate the use of microstate features to discriminate schizophrenia, suggesting that EEG microstate features are useful for schizophrenia classification.

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.

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.

EEG-Based Measures in At-Risk Mental State and Early Stages of Schizophrenia: A Systematic Review

Introduction: Electrophysiological (EEG) abnormalities in subjects with schizophrenia have been largely reported. In the last decades, research has shifted to the identification of electrophysiological alterations in the prodromal and early phases of the disorder, focusing on the prediction of clinical and functional outcome. The identification of neuronal aberrations in subjects with a first episode of psychosis (FEP) and in those at ultra high-risk (UHR) or clinical high-risk (CHR) to develop a psychosis is crucial to implement adequate interventions, reduce the rate of transition to psychosis, as well as the risk of irreversible functioning impairment. The aim of the review is to provide an up-to-date synthesis of the electrophysiological findings in the at-risk mental state and early stages of schizophrenia. Methods: A systematic review of English articles using Pubmed, Scopus, and PsychINFO was undertaken in July 2020. Additional studies were identified by hand-search. Electrophysiological studies that included at least one group of FEP or subjects at risk to develop psychosis, compared to healthy controls (HCs), were considered. The heterogeneity of the studies prevented a quantitative synthesis. Results: Out of 319 records screened, 133 studies were included in a final qualitative synthesis. Included studies were mainly carried out using frequency analysis, microstates and event-related potentials. The most common findings included an increase in delta and gamma power, an impairment in sensory gating assessed through P50 and N100 and a reduction of Mismatch Negativity and P300 amplitude in at-risk mental state and early stages of schizophrenia. Progressive changes in some of these electrophysiological measures were associated with transition to psychosis and disease course. Heterogeneous data have been reported for indices evaluating synchrony, connectivity, and evoked-responses in different frequency bands. Conclusions: Multiple EEG-indices were altered during at-risk mental state and early stages of schizophrenia, supporting the hypothesis that cerebral network dysfunctions appear already before the onset of the disorder. Some of these alterations demonstrated association with transition to psychosis or poor functional outcome. However, heterogeneity in subjects' inclusion criteria, clinical measures and electrophysiological methods prevents drawing solid conclusions. Large prospective studies are needed to consolidate findings concerning electrophysiological markers of clinical and functional outcome.

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.

Frontal alpha asymmetry in schizotypy: electrophysiological evidence for motivational dysfunction

Introduction: Schizotypy is defined as personality traits reflecting an underlying risk for schizophrenia-spectrum disorders. As yet, there is a dearth of suitable objective markers for measuring schizotypy. Frontal alpha asymmetry, characterised by reduced left versus right frontal region activity, reflects trait-like diminished approach-related systems and has been found in schizophrenia. Methods: The present study used electroencephalography (EEG) recorded on a consumer-grade mobile headset to examine asymmetric resting-state frontal alpha, beta, and gamma power within the multidimensional schizotypy (e.g. positive, negative, disorganised) during a three-minute "eyes closed" resting period in college undergraduates (n=49). Results: Findings suggest that schizotypy was exclusively related to reduced left versus right-lateralised power in the alpha frequency (8.1-12.9 Hz., R²= .16). Follow-up analysis suggested that positive schizotypy was uniquely associated with increased right alpha activity, indicating increased withdrawal motivation. Conclusions: Frontal asymmetry is a possible ecologically valid objective marker for schizotypy that may be detectable using easily accessible, consumer-grade technology.

Electroencephalography and Event-Related Potential Biomarkers in Individuals at Clinical High Risk for Psychosis

Clinical outcomes vary among youths at clinical high risk for psychosis (CHR-P), with approximately 20% progressing to full-blown psychosis over 2 to 3 years and 30% achieving remission. Recent research efforts have focused on identifying biomarkers that precede psychosis onset and enhance the accuracy of clinical outcome prediction in CHR-P individuals, with the ultimate goal of developing staged treatment approaches based on the individual's level of risk. Identifying such biomarkers may also facilitate progress toward understanding pathogenic mechanisms underlying psychosis onset, which may support the development of mechanistically informed early interventions for psychosis. In recent years, electroencephalography-based event-related potential measures with established sensitivity to schizophrenia have gained traction in the study of CHR-P and its clinical outcomes. In this review, we describe the evidence for event-related potential abnormalities in CHR-P and discuss how they inform our understanding of information processing deficits as vulnerability markers for emerging psychosis and as indicators of future outcomes. Among the measures studied, P300 and mismatch negativity are notable because deficits predict conversion to psychosis and/or CHR-P remission. However, the accuracy with which these and other measures predict outcomes in CHR-P has been obscured in the prior literature by the tendency to only report group-level differences, underscoring the need for inclusion of individual predictive accuracy metrics in future studies. Nevertheless, both P300 and mismatch negativity show promise as electrophysiological markers of risk for psychosis, as target engagement measures for clinical trials, and as potential translational bridges between human studies and animal models focused on novel drug development for early psychosis.

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.

Multifractal and Entropy-Based Analysis of Delta Band Neural Activity Reveals Altered Functional Connectivity Dynamics in Schizophrenia

Dynamic functional connectivity (DFC) was established in the past decade as a potent approach to reveal non-trivial, time-varying properties of neural interactions – such as their multifractality or information content –, that otherwise remain hidden from conventional static methods. Several neuropsychiatric disorders were shown to be associated with altered DFC, with schizophrenia (SZ) being one of the most intensely studied among such conditions. Here we analyzed resting-state electroencephalography recordings of 14 SZ patients and 14 age- and gender-matched healthy controls (HC). We reconstructed dynamic functional networks from delta band (0.5–4 Hz) neural activity and captured their spatiotemporal dynamics in various global network topological measures. The acquired network measure time series were made subject to dynamic analyses including multifractal analysis and entropy estimation. Besides group-level comparisons, we built a classifier to explore the potential of DFC features in classifying individual cases. We found stronger delta-band connectivity, as well as increased variance of DFC in SZ patients. Surrogate data testing verified the true multifractal nature of DFC in SZ, with patients expressing stronger long-range autocorrelation and degree of multifractality when compared to controls. Entropy analysis indicated reduced temporal complexity of DFC in SZ. When using these indices as features, an overall cross-validation accuracy surpassing 89% could be achieved in classifying individual cases. Our results imply that dynamic features of DFC such as its multifractal properties and entropy are potent markers of altered neural dynamics in SZ and carry significant potential not only in better understanding its pathophysiology but also in improving its diagnosis. The proposed framework is readily applicable for neuropsychiatric disorders other than 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.

[Neurophysiological characteristics of juvenile schizophrenia patients examined at the very remote follow up stage]

OBJECTIVE

To determine neurophysiological characteristics of patients with long-term follow up (>20 years) and to find correlations between neurophysiological parameters and clinical features of schizophrenia.

MATERIAL AND METHODS

The patients were divided into three groups: with predomination of personality changes (group 1, n=17), with negative disorders (group 2, n=23) and with positive and negative disorders (group 3, n=40). A psychopathological method and electroencephalography with evoked potentials testing were used.

RESULTS AND CONCLUSION

In group 3, the statistically significant higher frequencies of theta-rhythm and lower of alpha-rhythm were found. Also, theta frequency correlated with PANSS positive scores. The significant intergroup differences by auditory oddball P300 were lacked. The findings are discussed in view of the hypothesis of theta-rhythm as a marker of hippocampal-prefrontal connectivity.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Late-onset psychosis and very-late-onset-schizophrenia-like-psychosis: an updated systematic review

Psychotic disorders have long been known to be a condition that peaks during adolescence and early adulthood. A considerable proportion of patients have their first onset at or after the age of 40, but little is known about this population. The current systematic review examined the clinical presentation of late-onset psychosis (LOP) and very-late-onset-schizophrenia-like psychosis (VLOSLP) with focus on their psychopathological, neuropsychological, neurobiological, psychosocial and psychological correlates. A systematic search of studies published from 2000 to 2019 from Cochrane Library, Pubmed, Medline, Embase, PsycINFO, and Scopus yielded 27 original studies that were included in this review. Results revealed there is a dearth of empirical research on the conditions in the current literature and inconsistencies in the findings reported may be associated with the lack of uniformity in the definitions for LOP and VLOSLP. Future research on the topic shall (i) specify the onset age criteria for LOP and VLOSLP; (ii) study the conditions independently; (iii) involve a larger sample size, and iv) account for potential confounding variables. A comprehensive evaluation of the risks and benefits of pharmacological treatment may also be needed.

Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG

Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.

Frontal slow wave resting EEG power is higher in individuals at Ultra High Risk for psychosis than in healthy controls but is not associated with negative symptoms or functioning

Decreased brain activity in the frontal region, as indicated by increased slow wave EEG power measured by electrodes place on the skull over this area, in association with negative symptoms has previously been shown to distinguish ultra-high risk (UHR) individuals who later transitioned to psychosis (UHR-P) from those who did not transition (UHR-NP). The aims of the current study were to: 1) replicate these results and 2) investigate whether similar association between increased frontal slow wave activity and functioning shows any value in the prediction of transition to psychosis in UHR individuals. The brain activity, recorded using EEG, of 44 UHR individuals and 38 healthy controls was included in the analyses. Symptom severity was assessed in UHR participants and functioning was measured in both groups. The power in the theta frequency band in the frontal region of UHR individuals was higher than in controls. However, there was no difference between the UHR-P and the UHR-NP groups, and no change in slow frequency power following transition to psychosis. The correlation between delta frequency power and negative symptoms previously observed was not present in our UHR cohort, and there was no association between frontal delta or theta and functioning in either group. Increased delta power was rather correlated with depressive symptoms in the UHR group. Future research will be needed to better understand when, in the course of the illness, does the slow wave activity in the frontal area becomes impaired.

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.

Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

BACKGROUND

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

METHODS

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

RESULTS

The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

CONCLUSIONS

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

Towards a neurodynamical understanding of the prodrome in schizophrenia

The identification of biomarkers for the early diagnosis of schizophrenia that could inform novel treatment developments is an important objective of current research. This paper will summarize recent work that has investigated changes in oscillatory activity and event-related potentials with Electro/Magnetoencephalography (EEG/MEG) in participants at high-risk for the development of schizophrenia, highlighting disruptions in sensory and cognitive operations prior to the onset of the syndrome. Changes in EEG/MEG-data are consistent with evidence for alterations in Glutamatergic and GABAergic neurotransmission as disclosed by Magnetic Resonance Spectroscopy and brain stimulation, indicating changes in Excitation/Inhibition balance parameters prior to the onset of psychosis. Together these data emphasize the importance of research into neuronal dynamics as a crucial approach to establish functional relationships between impairments in neural circuits and emerging psychopathology that together could be fundamental for early intervention and the identification of novel treatments for emerging psychosis.

Effects of Ketamine on Resting-State EEG Activity and Their Relationship to Perceptual/Dissociative Symptoms in Healthy Humans

N-methyl-D-aspartate (NMDA) receptor antagonists administered to healthy humans results in schizophrenia-like symptoms, which preclinical research suggests are due to glutamatergically altered brain oscillations. Here, we examined resting-state electroencephalographic activity in 21 healthy volunteers assessed in a placebo-controlled, double-blind, randomized study involving administration of either a saline infusion or a sub-anesthetic dose of ketamine, an NMDA receptor antagonist. Frequency-specific current source density (CSD) was assessed at sensor-level and source-level using eLORETA within regions of interest of a triple network model of schizophrenia (this model posits a dysfunctional switching between large-scale Default Mode and Central Executive networks by the monitor-controlling Salience Network). These CSDs were measured in each session along with subjective symptoms as indexed with the Clinician Administered Dissociative States Scale. Ketamine-induced CSD reductions in slow (delta/theta and alpha) and increases in fast (gamma) frequencies at scalp electrode sites were paralleled by frequency-specific CSD changes in the Default Mode, Central Executive, and Salience networks. Subjective symptoms scores were increased with ketamine and ratings of depersonalization in particular were associated with alpha CSD reductions in general and in specific regions of interest in each of the three networks. These results tentatively support the hypothesis that pathological brain oscillations associated with hypofunctional NMDA receptor activity may contribute to the emergence of the perceptual/dissociate symptoms of schizophrenia.

Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers

Current criteria identifying patients with ultra-high risk of psychosis (UHR) have low specificity, and less than one-third of UHR cases experience transition to psychosis within 3 years of initial assessment. We explored whether a Bayesian probabilistic multimodal model, combining baseline historical and clinical risk factors with biomarkers (oxidative stress, cell membrane fatty acids, resting quantitative electroencephalography (qEEG)), could improve this specificity. We analyzed data of a UHR cohort (n=40) with a 1-year transition rate of 28%. Positive and negative likelihood ratios were calculated for predictor variables with statistically significant receiver operating characteristic curves (ROCs), which excluded oxidative stress markers and qEEG parameters as significant predictors of transition. We clustered significant variables into historical (history of drug use), clinical (Positive and Negative Symptoms Scale positive, negative and general scores and Global Assessment of Function) and biomarker (total omega-3, nervonic acid) groups, and calculated the post-test probability of transition for each group and for group combinations using the odds ratio form of Bayes' rule. Combination of the three variable groups vastly improved the specificity of prediction (area under ROC=0.919, sensitivity=72.73%, specificity=96.43%). In this sample, our model identified over 70% of UHR patients who transitioned within 1 year, compared with 28% identified by standard UHR criteria. The model classified 77% of cases as very high or low risk (P>0.9, <0.1) based on history and clinical assessment, suggesting that a staged approach could be most efficient, reserving fatty-acid markers for 23% of cases remaining at intermediate probability following bedside interview.

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".

How to Link Brain and Experience? Spatiotemporal Psychopathology of the Lived Body

The focus of the present article is on sketching a psychopathology of the body in schizophrenia and linking it to brain activity. This is done providing converging data from psychopathological evidence (phenomenal), phenomenological contructs (trans-phenomenal) and neuroscientific measures (pre-phenomenal). The phenomenal level is the detailed documentation of the patients' subjective anomalous experiences. These phenomena are explicit contents in the patients' field of consciousness. The trans-phenomenal level targets the implicit yet operative matrix that underlies these anomalous subjective experiences. Abnormal phenomena are viewed as expressions of a modification of trans-phenomenal matrix, that is, in terms of an abnormal synthesis or integration through time of intero-, proprio- and extero-ceptive stimuli. Finally, we link the abnormalities of the trans-phenomenal matrix to pre-phenomenal alterations of the brain resting state and of its spatio-temporal organization, as documented by neurobiological methods providing spatial and temporal resolution of intrinsic brain activity (with many features of the resting state remaining yet unclear though). Based on phenomenological research, the body in schizophrenia is typically experienced in an itemized way as an object external to one's self and unrelated to events in the external world. Based on neurobiological data, we tentatively hypothesize that such anomalies of the lived body are related to decreased integration between intero-, extero- and proprioceptive experiences by the brain's spontaneous activity and its temporal structure. Taken all together, this suggests that we view abnormalities of bodily experience in terms of their underlying abnormal spatiotemporal features which, as we suppose, can be traced back to the spatiotemporal features of the brain's spontaneous activity.

A Preliminary Study of the Association Among Metacognition and Resting State EEG in Schizophrenia

Abstract. Metacognition refers to a spectrum of activities that range from the consideration of discrete mental experiences, such as a specific thought or emotion, to the synthesis of discrete perceptions into integrated representations of the self and others as unique agents in the world. Metacognitive deficits have been observed in schizophrenia and linked with a number of behavioral correlates and outcomes. Less is known however about the neural systems associated with such processes. Establishing the link between brain activity and metacognition therefore is an essential next step. Resting state electroencephalography (EEG) provides one possible avenue for investigating this link. EEG studies in schizophrenia suggest that the gamma frequency range may have functional significance and be related to the disturbed information processing often observed in the disorder. In the present investigation, we assessed metacognition among 20 individuals with prolonged schizophrenia using the Metacognition Assessment Scale Abbreviated, who also participated in resting state EEG recording. We hypothesized that gamma activity would be associated with those domains of metacognition that require the most integration to perform, Decentration and Mastery. We then examined the association among gamma power and each metacognitive domain. Additional exploratory analyses were conducted across a spectrum of EEG activity. We found that increased gamma activity at rest was linked with decreased decentration. This suggests that hyperactivity in the gamma range may index disrupted processing and integration, and ultimately the metacognitive processes needed to form complex ideas about oneself and others and to see the world from multiple perspectives. This link provides additional evidence of how the biological roots of schizophrenia may culminate in a disrupted life.

Altered Resting-State Cortical EEG Oscillations in Patients With Severe Asymptomatic Carotid Stenosis

Asymptomatic carotid stenosis is characterized by altered cerebral hemodynamics and cognitive impairment, but the underlying neurophysiological mechanism remains unclear. To elucidate the alterations of cortical activities, resting-state electrophysiological activities were recorded from patients with mild (<30%; n=10; age 57-85 years), moderate (30% to 50%; n=11; age 66-88 years), and severe (>50%; n=8; age 67-91 years) carotid stenosis. The current density and oscillatory power of the cortical sources were analyzed using the minimum norm estimates method combined with fast Fourier transform analysis. Our results indicate that the cortical current density among regions of the brain was similar, irrespective of the degree of carotid stenosis. With regard to the cortical oscillations, augmented theta activities in the bilateral parietal, left temporal, and left occipital regions and attenuated alpha activities in the bilateral frontal and right central regions were obtained in patients with severe asymptomatic carotid stenosis. We suggest that the source-based cortical oscillations at theta and alpha bands might reflect the alterations of the brain activities and characterize the altered neurophysiological mechanism of the brain with at least 50% occlusion of the carotid artery. Further longitudinal studies with larger populations are warranted to verify the present findings.

Can cognitive behaviour therapy beneficially influence arousal mechanisms in psychosis?

Cognitive behavioural therapy for psychosis (CBTp) is an approved adjunct therapy for patients with psychotic disorders; however, we do not fully understand the neurobiological effects that this therapy may exert. Arousal, as measured by electroencephalography (EEG), provides a useful electrophysiological marker for assessing psychotic disorders. EEG studies may therefore serve as a useful measure for assessing the underlying effects of CBTp in psychotic disorders.

Impaired prefrontal synaptic gain in people with psychosis and their relatives during the mismatch negativity

The mismatch negativity (MMN) evoked potential, a preattentive brain response to a discriminable change in auditory stimulation, is significantly reduced in psychosis. Glutamatergic theories of psychosis propose that hypofunction of NMDA receptors (on pyramidal cells and inhibitory interneurons) causes a loss of synaptic gain control. We measured changes in neuronal effective connectivity underlying the MMN using dynamic causal modeling (DCM), where the gain (excitability) of superficial pyramidal cells is explicitly parameterised. EEG data were obtained during a MMN task—for 24 patients with psychosis, 25 of their first‐degree unaffected relatives, and 35 controls—and DCM was used to estimate the excitability (modeled as self‐inhibition) of (source‐specific) superficial pyramidal populations. The MMN sources, based on previous research, included primary and secondary auditory cortices, and the right inferior frontal gyrus. Both patients with psychosis and unaffected relatives (to a lesser degree) showed increased excitability in right inferior frontal gyrus across task conditions, compared to controls. Furthermore, in the same region, both patients and their relatives showed a reversal of the normal response to deviant stimuli; that is, a decrease in excitability in comparison to standard conditions. Our results suggest that psychosis and genetic risk for the illness are associated with both context‐dependent (condition‐specific) and context‐independent abnormalities of the excitability of superficial pyramidal cell populations in the MMN paradigm. These abnormalities could relate to NMDA receptor hypofunction on both pyramidal cells and inhibitory interneurons, and appear to be linked to the genetic aetiology of the illness, thereby constituting potential endophenotypes for psychosis. Hum Brain Mapp 37:351–365, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Heritability and molecular-genetic basis of resting EEG activity: a genome-wide association study

Several EEG parameters are potential endophenotypes for different psychiatric disorders. The present study consists of a comprehensive behavioral- and molecular-genetic analysis of such parameters in a large community sample (N = 4,026) of adolescent twins and their parents, genotyped for 527,829 single nucleotide polymorphisms (SNPs). Biometric heritability estimates ranged from .49 to .85, with a median of .78. The additive effect of all SNPs (SNP heritability) varied across electrodes. Although individual SNPs were not significantly associated with EEG parameters, several genes were associated with delta power. We also obtained an association between the GABRA2 gene and beta power (p < .014), consistent with findings reported by others, although this did not survive Bonferroni correction. If EEG parameters conform to a largely polygenic model of inheritance, larger sample sizes will be required to detect individual variants reliably.

Aberrant Current Source-Density and Lagged Phase Synchronization of Neural Oscillations as Markers for Emerging Psychosis

BACKGROUND

Converging evidence indicates that neural oscillations coordinate activity across brain areas, a process which is seemingly perturbed in schizophrenia. In particular, beta (13-30 Hz) and gamma (30-50 Hz) oscillations were repeatedly found to be disturbed in schizophrenia and linked to clinical symptoms. However, it remains unknown whether abnormalities in current source density (CSD) and lagged phase synchronization of oscillations across distributed regions of the brain already occur in patients with an at-risk mental state (ARMS) for psychosis.

METHODS

To further elucidate this issue, we assessed resting-state EEG data of 63 ARMS patients and 29 healthy controls (HC). Twenty-three ARMS patients later made a transition to psychosis (ARMS-T) and 40 did not (ARMS-NT). CSD and lagged phase synchronization of neural oscillations across brain areas were assessed using eLORETA and their relationships to neurocognitive deficits and clinical symptoms were analyzed using linear mixed-effects models.

RESULTS

ARMS-T patients showed higher gamma activity in the medial prefrontal cortex compared to HC, which was associated with abstract reasoning abilities in ARMS-T. Furthermore, in ARMS-T patients lagged phase synchronization of beta oscillations decreased more over Euclidian distance compared to ARMS-NT and HC. Finally, this steep spatial decrease of phase synchronicity was most pronounced in ARMS-T patients with high positive and negative symptoms scores.

CONCLUSIONS

These results indicate that patients who will later make the transition to psychosis are characterized by impairments in localized and synchronized neural oscillations providing new insights into the pathophysiological mechanisms of schizophrenic psychoses and may be used to improve the prediction of psychosis.

Anti-NMDA Receptor Encephalitis in a Patient with Previous Psychosis and Neurological Abnormalities: A Diagnostic Challenge

Anti-N-methyl-D-aspartate (NMDA) receptor encephalitis is an autoimmune disorder characterized by IgG autoantibodies directed against the NR1 subunit of the NMDA glutamate receptor. Psychiatric symptoms are common and include psychosis, mania, depressed mood, aggression, and speech abnormalities. Neurological symptoms such as seizures, decreased responsiveness, dyskinesias, and other movement abnormalities and/or autonomic instability are frequently seen as well. We present the case of a woman who was followed up at our facility for over 14 years for the treatment of multiple neuropsychiatric symptoms. Initially, she presented with paresthesias, memory loss, and manic symptoms. Nine years later, she presented to our facility again, this time with left sided numbness, left eyelid droop, and word finding difficulties. Finally, five years later, she presented with manic symptoms, hallucinations, and memory impairment. During her hospitalization, she subsequently developed catatonic symptoms and seizures. During her stay, it was discovered that she was positive for anti-NMDA receptor antibodies and her symptoms responded well to appropriate therapy. This case demonstrates that it may be useful for clinicians to consider screening for anti-NMDA receptor antibodies in long-term patients with neuropsychiatric symptoms that have not adequately responded to therapy.

Neural oscillations as a translational tool in schizophrenia research: rationale, paradigms and challenges

Neural oscillations have received recently a great deal of interest in schizophrenia research because of the possibility to integrate findings from non-invasive electro/magnetoencephalographical recordings with pre-clinical research, which could potentially lead to the identification of pathophysiological mechanisms and novel treatment targets. In the current paper, we review the potential as well as the challenges of this approach by summarizing findings on alterations in rhythmic activity from both animal models and human data which have implicated dysfunctional neural oscillations in the explanation of cognitive deficits and certain clinical symptoms of schizophrenia. Specifically, we will focus on findings that have examined neural oscillations during 1) perceptual processing, 2) working memory and executive processes and 3) spontaneous activity. The importance of the development of paradigms suitable for human and animal models is discussed as well as the search for mechanistic explanation for oscillatory dysfunctions.

Delta-9-tetrahydrocannabinol, neural oscillations above 20 Hz and induced acute psychosis

RATIONALE

An acute challenge with delta-9-tetrahydrocannabinol (THC) can induce psychotic symptoms including delusions. High electroencephalography (EEG) frequencies, above 20 Hz, have previously been implicated in psychosis and schizophrenia.

OBJECTIVES

The objective of this study is to determine the effect of intravenous THC compared to placebo on high-frequency EEG.

METHODS

A double-blind cross-over study design was used. In the resting state, the high-beta to low-gamma magnitude (21-45 Hz) was investigated (n = 13 pairs + 4 THC only). Also, the event-related synchronisation (ERS) of motor-associated high gamma was studied using a self-paced button press task (n = 15).

RESULTS

In the resting state, there was a significant condition × frequency interaction (p = 0.00017), consisting of a shift towards higher frequencies under THC conditions (reduced high beta [21-27 Hz] and increased low gamma [27-45 Hz]). There was also a condition × frequency × location interaction (p = 0.006), such that the reduction in 21-27-Hz magnitude tended to be more prominent in anterior regions, whilst posterior areas tended to show greater 27-45-Hz increases. This effect was correlated with positive symptoms, as assessed on the Positive and Negative Syndrome Scale (PANSS) (r = 0.429, p = 0.042). In the motor task, there was a main effect of THC to increase 65-130-Hz ERS (p = 0.035) over contra-lateral sensorimotor areas, which was driven by increased magnitude in the higher, 85-130-Hz band (p = 0.02) and not the 65-85-Hz band.

CONCLUSIONS

The THC-induced shift to faster gamma oscillations may represent an over-activation of the cortex, possibly related to saliency misattribution in the delusional state.

Resting state activity and the "stream of consciousness" in schizophrenia--neurophenomenal hypotheses

Schizophrenia is a multifaceted disorder with various symptoms including auditory hallucinations, egodisturbances, passivity phenomena, and delusions. Recent neurobiological approaches have focused on, especially, the abnormal contents of consciousness, the "substantive parts" as James said, to associate them with the neural mechanisms related to sensory, motor, and cognitive functions, and the brain's underlying stimulus-induced or task-evoked activity. This leaves open, however, the neural mechanisms that provide the temporal linkage or glue between the various contents, the transitive parts that makes possible the "stream of consciousness." Interestingly, schizophrenic patients seem to suffer from abnormalities specifically in the "transitive parts" when they experience contents as temporally disconnected or fragmented which in phenomenological psychiatry has been described as "temporal fragmentation." The aim of this article is to develop so-called neurophenomenal hypothesis about the direct relationship between phenomenal features of the "stream of consciousness," the "transitive parts," and the specific neuronal mechanisms in schizophrenia as based on healthy subjects. Rather than emphasizing stimulus-induced and task-evoked activity and sensory and lateral prefrontal cortical regions as in neurocognitive approaches with their focus on the "substantive parts," the focus shifts here to the brain's intrinsic activity, its resting state activity, which may account for the temporal linkage or glue between the contents of consciousness, the transitive parts.

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study

BACKGROUND

Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives.

METHODS

We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms.

RESULTS

Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures.

CONCLUSION

Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders.