Negative symptoms in neuroleptic-naïve patients with first-episode psychosis correlate with QEEG parameters

An electroencephalographic signature predicts craving for methamphetamine

Craving is central to methamphetamine use disorder (MUD) and both characterizes the disease and predicts relapse. However, there is currently a lack of robust and reliable biomarkers for monitoring craving and diagnosing MUD. Here, we seek to identify a neurobiological signature of craving based on individual-level functional connectivity pattern differences between healthy control and MUD subjects. We train high-density electroencephalography (EEG)-based models using data recorded during the resting state and then calculate imaginary coherence features between the band-limited time series across different brain regions of interest. Our prediction model demonstrates that eyes-open beta functional connectivity networks have significant predictive value for craving at the individual level and can also identify individuals with MUD. These findings advance the neurobiological understanding of craving through an EEG-tailored computational model of the brain connectome. Dissecting neurophysiological features provides a clinical avenue for personalized treatment of MUD.

Macroscale EEG characteristics in antipsychotic-naïve patients with first-episode psychosis and healthy controls

Electroencephalography in patients with a first episode of psychosis (FEP) may contribute to the diagnosis and treatment response prediction. Findings in the literature vary due to small sample sizes, medication effects, and variable illness duration. We studied macroscale resting-state EEG characteristics of antipsychotic naïve patients with FEP. We tested (1) for differences between FEP patients and controls, (2) if EEG could be used to classify patients as FEP, and (3) if EEG could be used to predict treatment response to antipsychotic medication. In total, we studied EEG recordings of 62 antipsychotic-naïve patients with FEP and 106 healthy controls. Spectral power, phase-based and amplitude-based functional connectivity, and macroscale network characteristics were analyzed, resulting in 60 EEG variables across four frequency bands. Positive and Negative Symptom Scale (PANSS) were assessed at baseline and 4-6 weeks follow-up after treatment with amisulpride or aripiprazole. Mann-Whitney U tests, a random forest (RF) classifier and RF regression were used for statistical analysis. Our study found that at baseline, FEP patients did not differ from controls in any of the EEG characteristics. A random forest classifier showed chance-level discrimination between patients and controls. The random forest regression explained 23% variance in positive symptom reduction after treatment in the patient group. In conclusion, in this largest antipsychotic- naïve EEG sample to date in FEP patients, we found no differences in macroscale EEG characteristics between patients with FEP and healthy controls. However, these EEG characteristics did show predictive value for positive symptom reduction following treatment with antipsychotic medication.

Resting frontal EEG asymmetry and schizotypal traits: a test-retest study

Introduction: Increase in right relative to left frontal electroencephalography (EEG) activity has been observed in patients with schizophrenia, both in cognitive tasks and during rest; and this lateralisation may be related to the severity of schizotypal traits. Methods: We used the Schizotypal Personality Questionnaire (SPQ) to assess schizotypal traits, and examined the correlation between these traits and resting EEG frontal asymmetry (left-right) in 52 college students, as well as the reliability of this correlation over a three-month interval. Results: A higher total score on the SPQ was correlated with reduced asymmetry in different frequency bands: gamma and beta2 frequency bands at baseline, and delta and alpha frequency bands three months later. Additionally, the reduced left relative to right frontal gamma and beta2 asymmetry was correlated with the participants' verbal fluency ability. However, this correlation was no longer statistically significant after the total SPQ score was controlled. Conclusions: These findings suggest that resting frontal EEG asymmetry is correlated with powers in different frequency bands, and may be an endophenotype for schizophrenia spectrum disorders.

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

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.

Neural oscillations in antipsychotic-naïve patients with a first psychotic episode

OBJECTIVES

In chronic schizophrenic psychoses, oscillatory abnormalities predominantly occur in prefrontal cortical regions and are associated with reduced communication across cortical areas. Nevertheless, it remains unclear whether similar alterations can be observed in patients with a first episode of psychosis (FEP), a state characterised by pathological features occurring in both late prodromal patients and initial phases of frank schizophrenic psychoses.

METHODS

We assessed resting-state electroencephalographic data of 31 antipsychotic-naïve FEP patients and 29 healthy controls (HC). We investigated the three-dimensional (3D) current source density (CSD) distribution and lagged phase synchronisation (LPS) of oscillations across small-scale and large-scale brain networks. We additionally investigated LPS relationships with clinical symptoms using linear mixed-effects models.

RESULTS

Compared to HC, FEP patients demonstrated abnormal CSD distributions in frontal areas of the brain; while decreased oscillations were found in the low frequencies, an increase was reported in the high frequencies (P < 0.01). Patients also exhibited deviant LPS in the high frequencies, whose dynamics changed over increasing 3D cortico-cortical distances and increasing psychotic symptoms.

CONCLUSIONS

These results indicate that in addition to prefrontal cortical abnormalities, altered synchronised neural oscillations are also present, suggesting possible disruptions in cortico-cortical communications. These findings provide new insights into the pathophysiological mechanisms of emerging schizophrenic psychoses.

Delta frequency optogenetic stimulation of the thalamic nucleus reuniens is sufficient to produce working memory deficits: relevance to schizophrenia

BACKGROUND

Low-frequency (delta/theta) oscillations in the thalamocortical system are elevated in schizophrenia during wakefulness and are also induced in the N-methyl-D-asparate receptor hypofunction rat model. To determine whether abnormal delta oscillations might produce functional deficits, we used optogenetic methods in awake rats. We illuminated channelrhodopsin-2 in the thalamic nucleus reuniens (RE) at delta frequency and measured the effect on working memory (WM) performance (the RE is involved in WM, a process affected in schizophrenia [SZ]).

METHODS

We injected RE with adeno-associated virus to transduce cells with channelrhodopsin-2. An optical fiber was implanted just dorsal to the hippocampus in order to illuminate RE axon terminals.

RESULTS

During optogenetic delta frequency stimulation, rats displayed a strong WM deficit. On the following day, performance was normal if illumination was omitted.

CONCLUSIONS

The optogenetic experiments show that delta frequency stimulation of a thalamic nucleus is sufficient to produce deficits in WM. This result supports the hypothesis that delta frequency bursting in particular thalamic nuclei has a causal role in producing WM deficits in SZ. The action potentials in these bursts may "jam" communication through the thalamus, thereby interfering with behaviors dependent on WM. Studies in thalamic slices using the N-methyl-D-asparate receptor hypofunction model show that delta frequency bursting is dependent on T-type Ca(2+) channels, a result that we confirmed here in vivo. These channels, which are strongly implicated in SZ by genome-wide association studies, may thus be a therapeutic target for treatment of SZ.

Disruptions in small-world cortical functional connectivity network during an auditory oddball paradigm task in patients with schizophrenia

P300 deficits in patients with schizophrenia have previously been investigated using EEGs recorded during auditory oddball tasks. However, small-world cortical functional networks during auditory oddball tasks and their relationships with symptom severity scores in schizophrenia have not yet been investigated. In this study, the small-world characteristics of source-level functional connectivity networks of EEG responses elicited by an auditory oddball paradigm were evaluated using two representative graph-theoretical measures, clustering coefficient and path length. EEG signals from 34 patients with schizophrenia and 34 healthy controls were recorded while each subject was asked to attend to oddball tones. The results showed reduced clustering coefficients and increased path lengths in patients with schizophrenia, suggesting that the small-world functional network is disrupted in patients with schizophrenia. In addition, the negative and cognitive symptom components of positive and negative symptom scales were negatively correlated with the clustering coefficient and positively correlated with path length, demonstrating that both indices are indicators of symptom severity in patients with schizophrenia. Our study results suggest that disrupted small-world characteristics are potential biomarkers for patients with schizophrenia.

Frontal delta power associated with negative symptoms in ultra-high risk individuals who transitioned to psychosis

It has recently been shown that treatment with long-chain omega-3 polyunsaturated fatty acids (PUFAs) could decrease the rate of transition to psychosis, and improve psychiatric symptoms and global functioning in people at ultra-high risk (UHR) for psychosis. Previous studies have suggested that resting state brain activity measured with electroencephalography (EEG) may represent an objective biomarker of changes in neural function associated with supplementation with omega-3 PUFAs. It has also been proposed that although resting state EEG cannot, by itself, predict transition to psychosis in UHR individuals, the combination of resting state EEG with negative symptoms may be a valid predictor of transition. The present study investigated whether treatment with omega-3 PUFAs influenced resting state EEG in UHR participants, and whether or not the association of the participants' resting state EEG with their levels of negative symptoms was dependent on their transition status. The brain activity of 73 UHR participants was recorded in the context of a randomized, placebo-controlled trial of the effects of supplementation with omega-3 PUFAs. The UHR participants who subsequently transitioned to psychosis (UHR+) did not differ from those who did not transition (UHR-) in terms of resting state EEG power in any frequency band. However, negative symptom scores were associated with increased delta activity in the frontal region of the UHR+ participants, but not in the UHR- participants. Treatment with omega-3 PUFAs did not induce changes in resting state EEG in either group. The results suggest that decreased frontal delta activity, in combination with high levels of negative symptoms, may be a risk factor for subsequent transition to psychosis in UHR individuals.

Delta oscillation and short-term plasticity in the rat medial prefrontal cortex: modelling NMDA hypofunction of schizophrenia

Dysfunction of the prefrontal cortex (PFC) is considered to be an important factor contributing to a decrease in cognitive performance of schizophrenia patients. The medial PFC (mPFC) is innervated by the hippocampus/subiculum, and the subiculum-mPFC pathway is known to be involved in various cognitive processes. Glutamate-containing subicular axons innervate cortical pyramidal neurons and interneurons where AMPA and NMDA receptors are implicated in synaptic transmission. In our experiments, properties of subiculum-mPFC interactions were studied using pathway stimulation and local field potential (LFP) recordings of the mPFC in urethane-anaesthetized rats. Changes in paired-pulse facilitation (PPF) and LFP oscillations, effects of the NMDA receptor antagonist MK-801, and the AMPAkine LY451395 were evaluated. Effects of disruption of the thalamo-cortical loop with local microinjection of lidocaine into the mediodorsal thalamic nucleus (MD) were also studied. Our findings demonstrate that both systemic administration of MK-801 and local MD lidocaine microinjection produce similar changes in LFP oscillations and reduction in PPF. Specifically, it was observed that MK-801 (0.05 mg/kg i.v.) and intra-thalamic lidocaine changed regular, 2 Hz delta oscillation to a less regular 0.5-1.5 Hz delta rhythm. Concurrently, PPF in response to electrical stimulation of the subiculum was significantly attenuated. Administration of the AMPAkine LY451395 (0.01 mg/kg i.v.) reversed the MK-801- and lidocaine-induced changes, and was itself blocked by the AMPA receptor antagonist CP-465022. Analysis of our findings suggests a critical role of cortical interneurons in NMDA/AMPA receptor-mediated changes in thalamo-cortical oscillations and PPF, and contributes to our understanding of the NMDA hypofunction model of schizophrenia.

EEG spectral power and negative symptoms in at-risk individuals predict transition to psychosis

INTRODUCTION

EEG power in the delta, theta and beta1 bands has been shown to be positively correlated with negative symptoms in first episode psychotic patients. The present study investigates this correlation in an "at risk mental state for psychosis" (ARMS) with the aim to improve prediction of transition to psychosis.

METHODS

Thirteen ARMS patients with later transition to psychosis (ARMS-T) and fifteen without (follow-up period of at least 4 years) (ARMS-NT) were investigated using spectral resting EEG data (of 8 electrodes over the fronto-central scalp area placed according to the 10-20 system) and summary score of the Scale for the Assessment of Negative Symptoms (SANS). Linear regressions were used to evaluate the correlation of SANS and EEG power in seven bands (delta, theta, alpha1, alpha2, beta1, beta2, beta3) in both ARMS groups and logistic regressions were used to predict transition to psychosis. Potentially confounding factors were controlled.

RESULTS

ARMS-T and ARMS-NT showed differential correlations of EEG power and SANS in delta, theta, and beta1 bands (p<.05): ARMS-T showed positive and ARMS-NT negative correlations. Logistic regressions showed that neither SANS score nor EEG spectral power alone predicted transition to psychosis. However, SANS score in combination with power in the delta, theta, beta1, and beta2 bands, respectively, predicted transition significantly (p<.03).

CONCLUSIONS

ARMS-T and ARMS-NT show differential correlations of SANS summary score and EEG power in delta, theta, and beta bands. Prediction of transition to psychosis is possible using combined information from a negative symptom scale and EEG spectral data.