Disorganization and cognitive impairment in schizophrenia: New insights from electrophysiological findings

Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity

Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.

Conceptual disorganization as a mediating variable between visual learning and metacognition in schizophrenia

Objectives

The aim of this study was to evaluate the relative contributions of visual learning and conceptual disorganization to specific metacognitive domains in a sample of outpatients with stable schizophrenia.

Methods

A total of 92 consecutive outpatients with stable schizophrenia were recruited in a cross-sectional study. We analyzed the data with five path analyses based on multiple regressions to analyze the specific effect of visual learning on metacognitive capacity and metacognitive domains and the possible mediating role of conceptual disorganization.

Results

We found that (i) visual learning was negatively correlated to metacognitive capacity and its domains on the one hand and conceptual disorganization on the other hand; (ii) conceptual disorganization was negatively associated with metacognition and its domains; and (iii) when the mediation effect was considered, conceptual disorganization fully mediated the relationship between visual learning and mastery, whereas it served as a partial mediator of the effect of visual learning on the other metacognition domains, i.e., self-reflectivity, understanding others' mind, and decentration.

Conclusion

These results delineate an articulated panorama of relations between different dimensions of metacognition, visual learning, and conceptual disorganization. Therefore, studies unable to distinguish between different components of metacognition fail to bring out the possibly varying links between neurocognition, disorganization, and metacognition.

Linguistic and non-linguistic markers of disorganization in psychotic illness

BACKGROUND

Disorganization, presenting as impairment in thought, language and goal-directed behavior, is a core multidimensional syndrome of psychotic disorders. This study examined whether scalable computational measures of spoken language, and smartphone usage pattern, could serve as digital biomarkers of clinical disorganization symptoms.

METHODS

We examined in a longitudinal cohort of adults with a psychotic disorder, the associations between clinical measures of disorganization and computational measures of 1) spoken language derived from monthly, semi-structured, recorded clinical interviews; and 2) smartphone usage pattern derived via passive sensing technologies over the month prior to the interview. The language features included speech quantity, rate, fluency, and semantic regularity. The smartphone features included data missingness and phone usage during sleep time. The clinical measures consisted of the Positive and Negative Symptom Scale (PANSS) conceptual disorganization, difficulty in abstract thinking, and poor attention, items. Mixed linear regression analyses were used to estimate both fixed and random effects.

RESULTS

Greater severity of clinical symptoms of conceptual disorganization was associated with greater verbosity and more disfluent speech. Greater severity of conceptual disorganization was also associated with greater missingness of smartphone data, and greater smartphone usage during sleep time. While the observed associations were significant across the group, there was also significant variation between individuals.

CONCLUSIONS

The findings suggest that digital measures of speech disfluency may serve as scalable markers of conceptual disorganization. The findings warrant further investigation into the use of recorded interviews and passive sensing technologies to assist in the characterization and tracking of psychotic illness.

Genotypic and Haplotypic Association of Catechol-O-Methyltransferase rs4680 and rs4818 Gene Polymorphisms with Particular Clinical Symptoms in Schizophrenia

Catechol-O-methyl transferase (COMT) gene variants are involved in different neuropsychiatric disorders and cognitive impairments, associated with altered dopamine function. This study investigated the genotypic and haplotypic association of COMT rs4680 and rs4618 polymorphisms with the severity of cognitive and other clinical symptoms in 544 male and 385 female subjects with schizophrenia. COMT rs4818 G carriers were more frequent in male patients with mild abstract thinking difficulties, compared to CC homozygotes or C allele carriers. Male carriers of COMT rs4680 A allele had worse abstract thinking (N5) scores than GG carriers, whereas AA homozygotes were more frequent in male subjects with lower scores on the intensity of the somatic concern (G1) item, compared to G carriers. Male carriers of COMT rs4818-rs4680 GA haplotype had the highest scores on the G1 item (somatic concern), whereas GG haplotype carriers had the lowest scores on G2 (anxiety) and G6 (depression) items. COMT GG haplotype was less frequent in female patients with severe disturbance of volition (G13 item) compared to the group with mild symptoms, while CG haplotype was more frequent in female patients with severe then mild symptoms. These findings suggest the sex-specific genotypic and haplotypic association of COMT variants with a severity of cognitive and other clinical symptoms of schizophrenia.

Inter-relationships among psychopathology, cognition, and real-life functioning in early and late phase schizophrenia: A network analysis approach

Many illness-related factors contribute to the reduction of the real-life functioning observed in people with schizophrenia (SZ). These include the psychopathological dimensions of the disorder such as positive, negative, disorganization, and depressive symptoms as well as impairment in neurocognition, social cognition, and metacognition. The associations between some of these variables change with the duration of illness (DOI), but this aspect was not explored with a network approach. This study aimed at describing and comparing the inter-relationships between psychopathological, cognitive, and functioning variables in early (DOI ≤ 5 years) and late (DOI > 5 years) phase SZ with network analyses and at assessing which variables were more strictly and directly associated with the real-life functioning. A network representation of the relationships between variables and the calculation of centrality indices were performed within each group. The two groups were compared with a network comparison test. Seventy-five patients with early and ninety-two with late phase SZ were included. No differences in the global network structure and strength were found between the two groups. In both groups, visual learning and disorganization exhibited high centrality indices and disorganization, negative symptoms, and metacognition were directly and strongly associated with real-life functioning. In conclusion, regardless of the DOI, a rehabilitation aimed at improving visual learning and disorganization (i.e., the most central variables) might reduce the strength of the associations that compose the network and therefore indirectly facilitate functional recovery. Simultaneously, therapeutic interventions targeting disorganization and metacognition might directly improve real-life functioning.

Resting-State EEG Connectivity at High-Frequency Bands and Attentional Performance Dysfunction in Stabilized Schizophrenia Patients

Background and Objectives: Attentional dysfunction has long been viewed as one of the fundamental underlying cognitive deficits in schizophrenia. There is an urgent need to understand its neural underpinning and develop effective treatments. In the process of attention, neural oscillation has a central role in filtering information and allocating resources to either stimulus-driven or goal-relevant objects. Here, we asked if resting-state EEG connectivity correlated with attentional performance in schizophrenia patients. Materials and Methods: Resting-state EEG recordings were obtained from 72 stabilized patients with schizophrenia. Lagged phase synchronization (LPS) was used to measure whole-brain source-based functional connectivity between 84 intra-cortical current sources determined by eLORETA (exact low-resolution brain electromagnetic tomography) for five frequencies. The Conners' Continuous Performance Test-II (CPT-II) was administered for evaluating attentional performance. Linear regression with a non-parametric permutation randomization procedure was used to examine the correlations between the whole-brain functional connectivity and the CPT-II measures. Results: Greater beta-band right hemispheric fusiform gyrus (FG)-lingual gyrus (LG) functional connectivity predicted higher CPT-II variability scores (r = 0.44, p < 0.05, corrected), accounting for 19.5% of variance in the CPT-II VAR score. Greater gamma-band right hemispheric functional connectivity between the cuneus (Cu) and transverse temporal gyrus (TTG) and between Cu and the superior temporal gyrus (STG) predicted higher CPT-II hit reaction time (HRT) scores (both r = 0.50, p < 0.05, corrected), accounting for 24.6% and 25.1% of variance in the CPT-II HRT score, respectively. Greater gamma-band right hemispheric Cu-TTG functional connectivity predicted higher CPT-II HRT standard error (HRTSE) scores (r = 0.54, p < 0.05, corrected), accounting for 28.7% of variance in the CPT-II HRTSE score. Conclusions: Our study indicated that increased right hemispheric resting-state EEG functional connectivity at high frequencies was correlated with poorer focused attention in schizophrenia patients. If replicated, novel approaches to modulate these networks may yield selective, potent interventions for improving attention deficits in schizophrenia.

Neurocognitive Deficits in First-Episode and Chronic Psychotic Disorders: A Systematic Review from 2009 to 2022

Cognitive impairment in patients suffering from schizophrenia spectrum disorders has been discussed as a strong predictor for multiple disease outcome variables, such as response to psychotherapy, stable relationships, employment, and longevity. However, the consistency and severity of cognitive deficits across multiple domains in individuals with first-episode and chronic psychotic disorders is still undetermined. We provide a comprehensive overview of primary research from the years 2009 to 2022. Based on a Cochrane risk assessment, a systematic synthesis of 51 out of 3669 original studies was performed. Impairment of cognitive functioning in patients diagnosed with first-episode psychotic disorders compared with healthy controls was predicted to occur in all assessed cognitive domains. Few overall changes were predicted for chronically affected patients relative to those in the first-episode stage, in line with previous longitudinal studies. Our research outcomes support the hypothesis of a global decrease in cognitive functioning in patients diagnosed with psychotic disorders, i.e., the occurrence of cognitive deficits in multiple cognitive domains including executive functioning, memory, working memory, psychomotor speed, and attention. Only mild increases in the frequency of cognitive impairment across studies were observed at the chronically affected stage relative to the first-episode stage. Our results confirm and extend the outcomes from prior reviews and meta-analyses. Recommendations for psychotherapeutic interventions are provided, considering the broad cognitive impairment already observed at the stage of the first episode. Based on the risk of bias assessment, we also make specific suggestions concerning the quality of future original studies.

Bayesian Optimization of Machine Learning Classification of Resting-State EEG Microstates in Schizophrenia: A Proof-of-Concept Preliminary Study Based on Secondary Analysis

Resting-state electroencephalography (EEG) microstates reflect sub-second, quasi-stable states of brain activity. Several studies have reported alterations of microstate features in patients with schizophrenia (SZ). Based on these findings, it has been suggested that microstates may represent neurophysiological biomarkers for the classification of SZ. To explore this possibility, machine learning approaches can be employed. Bayesian optimization is a machine learning approach that selects the best-fitted machine learning model with tuned hyperparameters from existing models to improve the classification. In this proof-of-concept preliminary study based on secondary analysis, 20 microstate features were extracted from 14 SZ patients and 14 healthy controls' EEG signals. These parameters were then ranked as predictors based on their importance, and an optimized machine learning approach was applied to evaluate the performance of the classification. SZ patients had altered microstate features compared to healthy controls. Furthermore, Bayesian optimization outperformed conventional multivariate analyses and showed the highest accuracy (90.93%), AUC (0.90), sensitivity (91.37%), and specificity (90.48%), with reliable results using just six microstate predictors. Altogether, in this proof-of-concept study, we showed that machine learning with Bayesian optimization can be utilized to characterize EEG microstate alterations and contribute to the classification of SZ patients.

Demographics, clinical characteristics and cognitive symptoms of heavy smokers and non-heavy smokers in Chinese male patients with chronic schizophrenia

Many studies have shown a high smoking rate and cognitive impairment in patients with schizophrenia. The effects of smoking and nicotine intake on cognitive function in schizophrenia are still controversial. In this study, we divided patients into heavy smoking and non-heavy smoking groups and compared the clinical characteristics and cognitive symptoms between the two groups in Chinese male patients with schizophrenia. A total of 154 heavy smoking patients and 372 non-heavy smoking patients were recruited. They completed a detailed questionnaire including general and socio-demographic data. Positive and Negative Syndrome Scale (PANSS) was rated for psychopathology. The Fagerstrom Test for Nicotine Dependence (FTND) was used to assess the degree of nicotine dependence. Heavy smokers were younger, started smoking earlier and had a higher FTND total score than non-heavy smoking patients. Moreover, we found that heavy smokers had significantly lower negative symptom scores and cognitive factor scores than non-heavy smokers. Logistic regression analysis showed that cognitive factor score and age of initial smoking were significantly associated with heavy smoking. Linear regression analysis showed that cognitive factor score, age of initial smoking and dose of antipsychotics were significant predictors of the amount of smoking. Our findings suggest that there are significant differences in some demographic and clinical variables between heavy and non-heavy smokers in Chinese male patients with chronic schizophrenia. Moreover, heavy smokers have less cognitive symptoms, suggesting that heavy smoking may be beneficial for cognition of patients with schizophrenia.

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.

(Attenuated) hallucinations join basic symptoms in a transdiagnostic network cluster analysis

Hallucinations are considered characteristic symptoms of psychosis and part of the 'psychosis superspectrum' of the Hierarchical Taxonomy Of Psychopathology (HiTOP) initiative. To gain insight into their psychopathological relevance, we studied their dimensional placement within a single dense transdiagnostic network constituting of basic symptoms as well as of attenuated and frank psychotic, and related symptoms. Newman's modularity analysis was used to detect symptom clusters in an earlier generated network (Jimeno, N., et al., 2020. Main symptomatic treatment targets in suspected and early psychosis: New insights from network analysis. Schizophr. Bull. 46, 884-895. https://doi.org/10.1093/schbul/sbz140). The constituting 86 symptoms were assessed with the Schizophrenia Proneness Instrument, Adult version (SPI-A), the Structured Interview for Psychosis-Risk Syndromes (SIPS), and the Positive And Negative Syndrome Scale (PANSS) in three adult samples of an early detection service: clinical high-risk (n = 203), first-episode psychosis (n = 153), and major depression (n = 104). Three clusters were detected: "subjective disturbances", "positive symptoms and behaviors", and "negative and anxious-depressive symptoms". The predominately attenuated hallucinations of both SIPS and PANSS joined the basic symptoms in "subjective disturbances", whereas other positive symptoms entered "positive symptoms and behaviors". Our results underline the importance of insight in separating true psychotic hallucinations from other hallucinatory experiences that, albeit phenomenologically similar are still experienced with some insight, i.e., are present in an attenuated form. We conclude that, strictly, hallucinations held with any degree of insight should not be used to diagnose transition to or presence of frank psychoses and, relatedly, to justify antipsychotic medication.

Examining disorganization in patients with first episode psychosis: Findings from a 1-year follow-up of the 'Parma early psychosis' program

AIM

Disorganization has been considered as a clinical domain close to the core of psychosis. However, it has received poor attention, especially at the illness onset. Moreover, most of the studies examining disorganized symptoms have been conducted in patients with chronic psychosis and research in the early stages of illness is still relatively scarce. Thus, the aims of this study were (a) to longitudinally monitor the stability of disorganization in patients with first episode psychosis (FEP) across a 1-year follow-up period, and (b) to investigate any relevant association of disorganized symptoms with functioning, psychopathology and the specific treatment components of an 'early intervention in psychosis' (EIP) program along the 1 year of follow-up.

METHODS

At baseline, 312 FEP participants (aged 12-35 years) completed the positive and negative syndrome scale (PANSS) and the global assessment of functioning (GAF). Spearman's correlations and multiple linear regression analysis were used.

RESULTS

At baseline, disorganization showed significant associations with all PANSS subscores, and a relevant negative correlation with GAF score. Across the follow-up, FEP individuals showed a significant improvement in disorganization severity. This decrease was specifically related to both baseline antipsychotic dosage and the number of individual cognitive-behavioural therapy sessions offered across the 1-year follow-up period.

CONCLUSIONS

Disorganization is clinically relevant in FEP patients, already ate the enrollment in an EIP program. However, it tends to improve over time together with the delivery of specialized, person-tailored FEP interventions within a specific EIP protocol.

The Relationship Between the Recognition of Basic Emotions and Negative Symptoms in Individuals With Schizophrenia Spectrum Disorders - An Exploratory Study

Current research suggests that emotion recognition is impaired in individuals affected by schizophrenia spectrum disorders (SSD). However, the specific impact of negative symptoms on the ability to recognize single basic emotions has not yet been explored sufficiently and is the aim of the present study. A sample of N = 66 individuals diagnosed with SSD was recruited at the Charité - Universitätsmedizin Berlin. In a first step, correlation analyses were conducted between seven different negative symptom subdomains of the Positive and Negative Syndrome Scale (PANSS) and the accuracy and latency in recognizing the six basic emotions (anger, disgust, fear, happiness, sadness, surprise) using the Emotion Recognition Task (ERT) of the Cambridge Neuropsychological Test Automated Battery (CANTAB). The significant correlations were subjected to linear regression models that controlled for the significant covariates diagnoses, age, sex, and education. Results revealed that in individuals with SSD the negative symptom domain of blunted affect significantly predicted the accuracy of emotion recognition performance (p < 0.05), particularly, when recognizing happiness (p < 0.05). Additionally, we found that stereotyped thinking also predicted the performance of emotion recognition, especially the response latency (p < 0.05) and difficulty in abstract thinking predicted the recognition of fear (p < 0.05). However, the nominal significances did not withstand correction for multiple tests and therefore need to be followed up in further studies with a larger sample.

Mismatch Negativity and P3a Impairment through Different Phases of Schizophrenia and Their Association with Real-Life Functioning

Impairment in functioning since the onset of psychosis and further deterioration over time is a key aspect of subjects with schizophrenia (SCZ). Mismatch negativity (MMN) and P3a, indices of early attention processing that are often impaired in schizophrenia, might represent optimal electrophysiological candidate biomarkers of illness progression and poor outcome. However, contrasting findings are reported about the relationships between MMN-P3a and functioning. The study aimed to investigate in SCZ the influence of illness duration on MMN-P3a and the relationship of MMN-P3a with functioning. Pitch (p) and duration (d) MMN-P3a were investigated in 117 SCZ and 61 healthy controls (HCs). SCZ were divided into four illness duration groups: ≤ 5, 6 to 13, 14 to 18, and 19 to 32 years. p-MMN and d-MMN amplitude was reduced in SCZ compared to HCs, independently from illness duration, psychopathology, and neurocognitive deficits. p-MMN reduction was associated with lower "Work skills". The p-P3a amplitude was reduced in the SCZ group with longest illness duration compared to HCs. No relationship between P3a and functioning was found. Our results suggested that MMN amplitude reduction might represent a biomarker of poor functioning in SCZ.

Disorganization in first episode schizophrenia: Treatment response and psychopathological findings from the 2-year follow-up of the "Parma Early Psychosis" program

OBJECTIVE

Disorganization is a core dimension of schizophrenia, yet it is relatively under-investigated compared to positive and negative ones, especially at the illness onset. Indeed, most of the empirical studies investigating the disorganized domain included patients with prolonged schizophrenia. Therefore, the aims of this research were (1) to monitor the longitudinal stability of disorganized symptoms in young patients with First Episode Schizophrenia (FES) along a 2-year follow-up period, and (2) to examine any significant association of disorganization with functioning, psychopathology and the specific treatment components of an "Early Intervention in Psychosis" (EIP) program across the 2 years of follow-up.

METHODS

At baseline, 159 FES individuals (aged 12-35 years) completed the Positive And Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning (GAF). Spearman's correlation coefficients and multiple linear regression analysis were carried out.

RESULTS

During the follow-up period, disorganization had relevant enduring positive associations with PANSS negative symptoms, lack of judgment/insight and positive symptoms representing delusional thought contents, as well as significant enduring negative correlation with GAF scores. Along the 2 years of follow-up, FES patients also showed a relevant improvement in disorganization symptoms. This reduction was specifically associated with the number of individual psychotherapy sessions provided during the first year of treatment.

CONCLUSION

Disorganization is a prominent clinical feature in FES at the recruitment in specialized EIP services, but its temporal trajectory reveals a decrease over time, together with the delivery of specific, patient-tailored EIP interventions.

Impairment of novelty-related theta oscillations and P3a in never medicated first-episode psychosis patients

We explored the neurophysiological activity underlying auditory novelty detection in antipsychotic-naive patients with a first episode of psychosis (FEP). Fifteen patients with a non-affective FEP and 13 healthy controls underwent an active involuntary attention task along with an EEG acquisition. Time-frequency representations of power, phase locking, and fronto-parietal connectivity were calculated. The P3a event-related potential was extracted as well. Compared to controls, the FEP group showed reduced theta phase-locking and fronto-parietal connectivity evoked by deviant stimuli. Also, the P3a amplitude was significantly reduced. Moreover, reduced theta connectivity was associated with more severe negative symptoms within the FEP group. Reduced activity (phase-locking and connectivity) of novelty-related theta oscillations, along with P3a reduction, may represent a failure to synchronize large-scale neural populations closely related to fronto-parietal attentional networks, and might be explored as a potential biomarker of disease severity in patients with emerging psychosis, given its association with negative symptoms.

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.

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.

A symptom combination predicting treatment-resistant schizophrenia - A strategy for real-world clinical practice

Early identification of symptoms that can predict treatment-resistant schizophrenia (TRS) could help clinicians to avoid delays in clozapine therapy. This study aims to investigate symptom patterns that could predict TRS using a discovery/replication study design. First, we followed a cohort of inpatients with schizophrenia (n = 164) in which the most discriminative items at baseline of the Positive and Negative Syndrome Scale (PANSS) were determined using logistic regression with TRS status as an outcome. Using Receiver Operating Characteristic (ROC) curves, we tested the prediction performance of multiple combinations of the identified items. The same items' combination was tested in an independent replication sample of (n = 207) outpatients with schizophrenia. In the discovery sample, the best combination to predict TRS at the discharge was the sum of three baseline PANSS items - conceptual disorganization (P2), difficulty in abstract thinking (N5), and unusual thought content (G9). The P2 + N5 + G9 model yielded an area under the curve (AUC) of 0.881, a sensitivity of 77.8%, and a specificity of 83.3%. In the outpatient sample, the model P2 + N5 + G9 predictive accuracy for TRS was only in the range of "acceptable" with an AUC of 0.756 and sensitivity of 72.3% and a specificity of 74.4%. Overall, the P2 + N5 + G9 model corresponds to the construct of formal thought disorder composed of disorganized thinking, concrete thinking, and bizarre-idiosyncratic thinking. Pronounced levels of these symptoms are easily identifiable in clinical practice and may be a feasible strategy in TRS. Replicating in first-episode cohorts is desirable to understand the likely clinical utility.