Changes in electroencephalographic microstates between evening and morning are associated with overnight sleep slow waves in healthy individuals.

STUDY OBJECTIVES: Microstates are semi-stable voltage topographies that account for most of electroencephalogram (EEG) variance. However, the impact of time of the day and sleep on microstates has not been examined. To address this gap, we assessed whether microstates differed between the evening and morning and whether sleep slow waves correlated with microstate changes in healthy participants. METHODS: Forty-five healthy subjects were recruited. Each participant underwent six minutes of resting state EEG recordings in the evening and morning, interleaved by sleep EEGs. Evening-to-morning changes in microstate duration, coverage, and occurrence were assessed. Furthermore, correlation between microstate changes and sleep slow-wave activity (SWA) and slow-wave density (SWD) were performed. RESULTS: Two-way ANOVAs with Microstate Class (A, B, C, and D) and Time (evening and morning) revealed significant Microstate Class*Time interaction for duration (F(44) = 5.571, p = 0.002), coverage (F(44) = 6.833, p = 0.001), and occurrence (F(44) = 5.715, p = 0.002). Post-hoc comparisons showed significant effects for microstate C duration (padj=0.048, Cohen's d = -0.389), coverage (padj=0.002, Cohen's d = -0.580), and occurrence (padj=0.002, Cohen's d= -0.606). Topographic analyses revealed inverse correlations between SWD, but not SWA, and evening-to-morning changes in microstate C duration (r = - 0.51, padj = 0.002), coverage (r = - 0.45, padj = 0.006), and occurrence (r = - 0.38, padj = 0.033). CONCLUSION: Microstate characteristics showed significant evening-to-morning changes associated with, and possibly regulated by, sleep slow-waves. These findings suggest that future microstate studies should control for time of day and sleep effects.

Continuous theta burst stimulation to dorsomedial prefrontal cortex in young adults with depression: Changes in resting frontostriatal functional connectivity relevant to positive mood.

Depression is associated with diminished positive affect (PA), postulated to reflect frontostriatal reward circuitry disruptions. Depression has consistently been associated with higher dorsomedial prefrontal cortex (dmPFC) activation, a region that regulates PA through ventral striatum (VS) connections. Low PA in depression may reflect dmPFC's aberrant functional connectivity (FC) with the VS. To test this, we applied theta burst stimulation (TBS) to dmPFC in 29 adults with depression (79% female, Mage = 21.4, SD = 2.04). Using a randomized, counterbalanced design, we administered 3 types of TBS at different sessions: intermittent (iTBS; potentiating), continuous (cTBS; depotentiating), and sham TBS (control). We used neuronavigation to target personalized dmPFC targets based on VS-dmPFC FC. PA and negative affect (NA), and resting-state fMRI were collected pre- and post-TBS. We found no changes in PA or NA with time (pre/post), condition (iTBS, cTBS, sham), or their interaction. Functional connectivity (FC) between the nucleus accumbens and dmPFC showed a significant condition (cTBS, iTBS, and sham) by time (pre-vs. post-TBS) interaction, and post-hoc testing showed decreased pre-to post-TBS for cTBS but not iTBS or sham. For cTBS only, reduced FC pre/post stimulation was associated with increased PA (but not NA). Our findings lend support to the proposed mechanistic model of aberrant FC between the dmPFC and VS in depression and suggest a way forward for treating depression in young adults. Future studies need to evaluate multi-session TBS to test clinical effects.

Reduced slow wave density is associated with worse positive symptoms in clinical high risk: An objective readout of symptom severity for early treatment interventions?

Individuals at clinical high risk for psychosis (CHR) present subsyndromal psychotic symptoms that can escalate and lead to the transition to a diagnosable psychotic disorder. Identifying biological parameters that are sensitive to these symptoms can therefore help objectively assess their severity and guide early interventions in CHR. Reduced slow wave oscillations (∼1 Hz) during non-rapid eye movement sleep were recently observed in first-episode psychosis patients and were linked to the intensity of their positive symptoms. Here, we collected overnight high-density EEG recordings from 37 CHR and 32 healthy control (HC) subjects and compared slow wave (SW) activity and other SW parameters (i.e., density and negative peak amplitude) between groups. We also assessed the relationships between clinical symptoms and SW parameters in CHR. While comparisons between HC and the entire CHR group showed no SW differences, CHR individuals with higher positive symptom severity (N = 18) demonstrated a reduction in SW density in an EEG cluster involving bilateral prefrontal, parietal, and right occipital regions compared to matched HC individuals. Furthermore, we observed a negative correlation between SW density and positive symptoms across CHR individuals, suggesting a potential target for early treatment interventions.

Sleep spindles as neurophysiological biomarkers of schizophrenia.

Schizophrenia (SCZ) is a complex psychiatric disorder characterized by a wide range of clinical symptoms, including disrupted sleep. In recent years, there has been growing interest in assessing alterations in sleep parameters in patients with SCZ. Sleep spindles are brief (0.5-2 s) bursts of 12- to 16-Hz rhythmic electroencephalogram (EEG) oscillatory activity occurring during non-rapid eye movement (NREM) sleep. Spindles have been implicated in several critical brain functions, including learning, memory and plasticity, and are thought to reflect the integrity of underlying thalamocortical circuits. This review aims to provide an overview of the current research investigating sleep spindles in SCZ. After briefly describing the neurophysiological features of sleep spindles, I will discuss alterations in spindle characteristics observed in SCZ, their associations with the clinical symptomatology of these patients and their putative underlying neuronal and molecular mechanisms. I will then discuss the utility of sleep spindle measures as predictors of treatment response and disease progression. Finally, I will highlight future directions for research in this emerging field, including the prospect of utilizing sleep spindles as neurophysiological biomarkers of SCZ.

N-Acetylaspartate and Choline Metabolites in Cortical and Subcortical Regions in Clinical High Risk Relative to Healthy Control Subjects: An Exploratory 7T MRSI Study.

N-acetylaspartate (NAA) and choline (Cho) are two brain metabolites implicated in several key neuronal functions. Abnormalities in these metabolites have been reported in both early course and chronic patients with schizophrenia (SCZ). It is, however, unclear whether NAA and Cho's alterations occur even before the onset of the disorder. Clinical high risk (CHR) individuals are a population uniquely enriched for psychosis and SCZ. In this exploratory study, we utilized 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to examine differences in total NAA (tNAA; NAA + N-acetylaspartylglutamate [NAAG]) and major choline-containing compounds, including glycerophosphorylcholine and phosphorylcholine [tCho], over the creatine (Cre) levels between 26 CHR and 32 healthy control (HC) subjects in the subcortical and cortical regions. While no tCho/Cre differences were found between groups in any of the regions of interest (ROIs), we found that CHR had significantly reduced tNAA/Cre in the right dorsal lateral prefrontal cortex (DLPFC) compared to HC, and that the right DLPFC tNAA/Cre reduction in CHR was negatively associated with their positive symptoms scores. No tNAA/Cre differences were found between CHR and HC in other ROIs. In conclusion, reduced tNAA/Cre in CHR vs. HC may represent a putative molecular biomarker for risk of psychosis and SCZ that is associated with symptom severity.

Natural Oscillatory Frequency Slowing in the Premotor Cortex of Early-Course Schizophrenia Patients: A TMS-EEG Study.

Despite the heavy burden of schizophrenia, research on biomarkers associated with its early course is still ongoing. Single-pulse Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) has revealed that the main oscillatory frequency (or "natural frequency") is reduced in several frontal brain areas, including the premotor cortex, of chronic patients with schizophrenia. However, no study has explored the natural frequency at the beginning of illness. Here, we used TMS-EEG to probe the intrinsic oscillatory properties of the left premotor cortex in early-course schizophrenia patients (<2 years from onset) and age/gender-matched healthy comparison subjects (HCs). State-of-the-art real-time monitoring of EEG responses to TMS and noise-masking procedures were employed to ensure data quality. We found that the natural frequency of the premotor cortex was significantly reduced in early-course schizophrenia compared to HCs. No correlation was found between the natural frequency and age, clinical symptom severity, or dose of antipsychotic medications at the time of TMS-EEG. This finding extends to early-course schizophrenia previous evidence in chronic patients and supports the hypothesis of a deficit in frontal cortical synchronization as a core mechanism underlying this disorder. Future work should further explore the putative role of frontal natural frequencies as early pathophysiological biomarkers for schizophrenia.

Shared and distinct abnormalities in sleep-wake patterns and their relationship with the negative symptoms of Schizophrenia Spectrum Disorder patients.

Sleep and rest-activity-rhythm (RAR) abnormalities are commonly reported in schizophrenia spectrum disorder (SSD) patients. However, an in-depth characterization of sleep/RAR alterations in SSD, including patients in different treatment settings, and the relationship between these alterations and SSD clinical features (e.g., negative symptoms) is lacking. SSD (N = 137 altogether, N = 79 residential and N = 58 outpatients) and healthy control (HC) subjects (N = 113) were recruited for the DiAPAson project. Participants wore an ActiGraph for seven consecutive days to monitor habitual sleep-RAR patterns. Sleep/rest duration, activity (i.e., M10, calculated on the 10 most active hours), rhythm fragmentation within days (i.e., intra-daily variability, IV; beta, steepness of rest-active changes), and rhythm regularity across days (i.e., inter-daily stability, IS) were computed in each study participant. Negative symptoms were assessed in SSD patients with the Brief Negative Symptom Scale (BNSS). Both SSD groups showed lower M10 and longer sleep/rest duration vs. HC, while only residential patients had more fragmented and irregular rhythms than HC. Compared to outpatients, residential patients had lower M10 and higher beta, IV and IS. Furthermore, residential patients had worse BNSS scores relative to outpatients, and higher IS contributed to between-group differences in BNSS score severity. Altogether, residentials and outpatients SSD had both shared and unique abnormalities in Sleep/RAR measures vs. HC and relative to one another, which also contributed to the patients' negative symptom severity. Future work will help establish whether improving some of these measures may ameliorate the quality of life and clinical symptoms of SSD patients.

Resting-State Functional Connectivity Differences Following Experimental Manipulation of the Orbitofrontal Cortex in Two Directions via Theta-Burst Stimulation.

Compulsive behaviors (CBs) have been linked to orbitofrontal cortex (OFC) function in animal and human studies. However, brain regions function not in isolation but as components of widely distributed brain networks-such as those indexed via resting-state functional connectivity (RSFC). Sixty-nine individuals with CB disorders were randomized to receive a single session of neuromodulation targeting the left OFC-intermittent theta-burst stimulation (iTBS) or continuous TBS (cTBS)-followed immediately by computer-based behavioral "habit override" training. OFC seeds were used to quantify RSFC following iTBS and following cTBS. Relative to cTBS, iTBS showed increased RSFC between right OFC (Brodmann's area 47) and other areas, including dorsomedial prefrontal cortex (dmPFC), occipital cortex, and a priori dorsal and ventral striatal regions. RSFC connectivity effects were correlated with OFC/frontopolar target engagement and with subjective difficulty during habit-override training. Findings help reveal neural network-level impacts of neuromodulation paired with a specific behavioral context, informing mechanistic intervention development.

Sleep disturbance in schizophrenia spectrum disorders: more than just a symptom?

Sleep disturbance is commonly reported in patients with schizophrenia spectrum disorder (SSD) in the clinical setting. Sleep features can be assessed subjectively, with self-report sleep questionnaires, and objectively with actigraphy and electroencephalogram recordings. Traditionally, electroencephalogram studies have focused on sleep architecture. More recently, numerous studies have investigated alterations in sleep-specific rhythms, including electroencephalogram oscillations, such as sleep spindles and slow waves, in patients with SSD compared with control subjects. Here, I briefly discuss how sleep disturbance is highly prevalent in patients with SSD and I present findings from studies demonstrating abnormalities in sleep architecture and sleep-oscillatory rhythms, with an emphasis on sleep spindles and slow-wave deficits, in these patients. This increasing body of evidence highlights the importance of sleep disturbance in SSD and points to several future research directions with related clinical implications, thus showing that sleep disturbance is more than just a symptom in these patients.

Military tactical adaptive decision making during simulated military operational stress is influenced by personality, resilience, aerobic fitness, and neurocognitive function.

Laboratory-based studies designed to mimic combat or military field training have consistently demonstrated deleterious effects on warfighter's physical, cognitive, and emotional performance during simulated military operational stress (SMOS). Purpose: The present investigation sought to determine the impact of a 48-h simulated military operational stress (SMOS) on military tactical adaptive decision making, and the influence of select psychological, physical performance, cognitive, and physiological outcome measures on decision making performance. Methods: Male (n = 48, 26.2 ± 5.5 years, 177.7 ± 6.6 cm, 84.7 ± 14.1 kg.) subjects currently serving in the U.S. military were eligible to participate in this study. Eligible subjects completed a 96-h protocol that occurred over five consecutive days and four nights. Day 2 (D2) and day 3 (D3) consisted of 48-h of SMOS wherein sleep opportunity and caloric needs were reduced to 50%. Differences in SPEAR total block score from baseline to peak stress (D3 minus D1) were calculated to assess change in military tactical adaptive decision making and groups were stratified based on increase (high adaptors) or decrease (low adaptors) of the SPEAR change score. Results: Overall, military tactical decision-making declined 1.7% from D1 to D3 (p < 0.001). High adaptors reported significantly higher scores of aerobic capacity (p < 0.001), self-report resilience (p = 0.020), extroversion (p < 0.001), and conscientiousness (p < 0.001). at baseline compared to low adaptors, while low adaptors reported greater scores in Neuroticism (p < 0.001). Conclusion: The present findings suggest that service members whose adaptive decision making abilities improved throughout SMOS (i.e., high adaptors) demonstrated better baseline psychological/self-reported resilience and aerobic capacity. Further, changes in adaptive decision-making were distinct from those of lower order cognitive functions throughout SMOS exposure. With the transition of future military conflicts placing higher priority on enhancing and sustaining cognitive readiness and resiliency, data presented here demonstrates the importance of measuring and categorizing baseline measures inherent to military personnel, in order to change and train one's ability to suffer less of a decline during high stress conditions.

Sleep Abnormalities in Different Clinical Stages of Psychosis: A Systematic Review and Meta-analysis.

Importance: Abnormal sleep is frequent in psychosis; however, sleep abnormalities in different stages (ie, clinical high risk for psychosis [CHR-P], early psychosis [EP], and chronic psychosis [CP]) have not been characterized. Objective: To identify sleep abnormalities across psychosis stages. Data Sources: Web of Science and PubMed were searched between inception and June 15, 2022. Studies written in English were included. Study Selection: Sleep disturbance prevalence studies and case-control studies reporting sleep quality, sleep architecture, or sleep electroencephalography oscillations in CHR-P, EP, or CP. Data Extraction and Synthesis: This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Stage-specific and pooled random-effects meta-analyses were conducted, along with the assessment of heterogeneity, study quality, and meta-regressions (clinical stage, sex, age, medication status, and psychotic symptoms). Main Outcomes and Measures: Sleep disturbance prevalence, self-reported sleep quality, sleep architecture (total sleep time, sleep latency, sleep efficiency, nonrapid eye movement, rapid eye movement stages, and number of arousals), and sleep electroencephalography oscillations (spindle density, amplitude, and duration, and slow wave density). Results: Fifty-nine studies with up to 6710 patients (n = 5135 for prevalence) and 977 controls were included. Sleep disturbance prevalence in pooled cases was 50% (95% CI, 40%-61%) and it was similar in each psychosis stage. Sleep quality was worse in pooled cases vs controls (standardized mean difference [SMD], 1.00 [95% CI, 0.70-1.30]). Sleep architecture alterations included higher sleep onset latency (SMD [95% CI]: pooled cases, 0.96 [0.62-1.30]; EP, 0.72 [0.52-0.92]; CP, 1.36 [0.66-2.05]), higher wake after sleep onset (SMD [95% CI]: pooled cases, 0.5 [0.29-0.71]; EP, 0.62 [0.34-0.89]; CP, 0.51 [0.09-0.93]), higher number of arousals (SMD [95% CI]: pooled cases, 0.45 [0.07-0.83]; CP, 0.81 [0.30-1.32]), higher stage 1 sleep (SMD [95% CI]: pooled cases, 0.23 [0.06-0.40]; EP, 0.34 [0.15-0.53]), lower sleep efficiency (SMD [95% CI]: pooled cases, -0.75 [-0.98 to -0.52]; EP, -0.90 [-1.20 to -0.60]; CP, -0.73 [-1.14 to -0.33]), and lower rapid eye movement density (SMD [95% CI]: pooled cases, 0.37 [0.14-0.60]; CP, 0.4 [0.19-0.77]). Spindle parameter deficits included density (SMD [95% CI]: pooled cases, -1.06 [-1.50 to -0.63]; EP, -0.80 [-1.22 to -0.39]; CP, -1.39 [-2.05 to -0.74]; amplitude: pooled cases, -1.08 [-1.33 to -0.82]; EP, -0.86 [-1.24 to -0.47]; CP, -1.25 [-1.58 to -0.91]; and duration: pooled cases: -1.2 [-1.69 to -0.73]; EP, -0.71 [-1.08 to -0.34]; CP, -1.74 [-2.10 to -1.38]). Individuals with CP had more frequent arousals vs CHR-P (z = 2.24, P = .02) and reduced spindle duration vs EP (z = -3.91, P < .001). Conclusions and Relevance: In this systematic review and meta-analysis, sleep disturbances were found to be prevalent throughout the course of psychosis, and different psychosis stages showed both shared and distinct abnormalities in sleep quality, architecture, and spindles. These findings suggest that sleep should become a core clinical target and research domain from at-risk to early and chronic stages of psychosis.

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.

Less daytime sleepiness and slow wave activity during sleep predict better physical readiness in military personnel.

BACKGROUND: Military personnel must maintain physical performance despite exposure to operational stressors such as sleep loss, caloric restriction and high cognitive load. Habitual sleep and specific sleep features are positively associated with fitness and may contribute to physical performance in operational settings. Further, by affecting muscle recovery, sleep may contribute to the ability to maintain performance across multiple days of exposure to operational stressors. OBJECTIVES: We examined the role of individual differences in baseline sleep on baseline physical performance and on change in physical performance throughout exposure to simulated military operational stress (SMOS). METHODS: Military personnel (36 male, 9 female, 26.3 ± 5.3 years) completed a 5-day SMOS protocol during which they completed a tactical mobility test daily. Sleep questionnaires were administered at intake and sleep was monitored each night with polysomnography. Lasso regressions were used to identify meaningful predictors of physical performance at baseline and of change in physical performance across SMOS. RESULTS: Better aerobic fitness, lower daytime sleepiness (Epworth Sleepiness Scale), and lower absolute slow wave activity (0.5-4 Hz) predicted better physical performance at baseline (66.1% of variance explained), but did not relate to changes in performance. CONCLUSIONS: Collectively, higher daytime sleepiness and slow wave activity may reflect more chronic exposure to insufficient sleep and higher baseline sleep drive, which in turn led to compromised physical performance. The findings suggest that low self-report sleepiness and low objective slow wave activity may reflect two quantifiable markers of healthy sleep behaviors that have implications for operational performance.

Circadian Rhythm Changes in Healthy Aging and Mild Cognitive Impairment.

Disruptions in circadian rhythms can occur in healthy aging; however, these changes are more severe and pervasive in individuals with age-related and neurodegenerative diseases, such as dementia. Circadian rhythm alterations are also present in preclinical stages of dementia, for example, in patients with mild cognitive impairments (MCI); thus, providing a unique window of opportunity for early intervention in neurodegenerative disorders. Nonetheless, there is a lack of studies examining the association between relevant changes in circadian rhythms and their relationship with cognitive dysfunctions in MCI individuals. In this review, circadian system alterations occurring in MCI patients are examined compared to healthy aging individuals while also considering their association with MCI neurocognitive alterations. The main findings are that abnormal circadian changes in rest-activity, core body temperature, melatonin, and cortisol rhythms appear in the MCI stage and that these circadian rhythm disruptions are associated with some of the neurocognitive deficits observed in MCI patients. In addition, preliminary evidence indicates that interventions aimed at restoring regular circadian rhythms may prevent or halt the progress of neurodegenerative diseases and mitigate their related cognitive impairments. Future longitudinal studies with repeated follow-up assessments are needed to establish the translational potential of these findings in clinical practice.

Biological Mechanism-based Neurology and Psychiatry: A BACE1/2 and Downstream Pathway Model.

In oncology, comprehensive omics and functional enrichment studies have led to an extensive profiling of (epi)genetic and neurobiological alterations that can be mapped onto a single tumor's clinical phenotype and divergent clinical phenotypes expressing common pathophysiological pathways. Consequently, molecular pathway-based therapeutic interventions for different cancer typologies, namely tumor type- and site-agnostic treatments, have been developed, encouraging the real-world implementation of a paradigm shift in medicine. Given the breakthrough nature of the new-generation translational research and drug development in oncology, there is an increasing rationale to transfertilize this blueprint to other medical fields, including psychiatry and neurology. In order to illustrate the emerging paradigm shift in neuroscience, we provide a state-of-the-art review of translational studies on the ß-site amyloid precursor protein cleaving enzyme (BACE) and its most studied downstream effector, neuregulin, which are molecular orchestrators of distinct biological pathways involved in several neurological and psychiatric diseases. This body of data aligns with the evidence of a shared genetic/biological architecture among Alzheimer's disease, schizoaffective disorder, and autism spectrum disorders. To facilitate a forward-looking discussion about a potential first step towards the adoption of biological pathway-based, clinical symptom-agnostic, categorization models in clinical neurology and psychiatry for precision medicine solutions, we engage in a speculative intellectual exercise gravitating around BACE-related science, which is used as a paradigmatic case here. We draw a perspective whereby pathway-based therapeutic strategies could be catalyzed by highthroughput techniques embedded in systems-scaled biology, neuroscience, and pharmacology approaches that will help overcome the constraints of traditional descriptive clinical symptom and syndrome-focused constructs in neurology and psychiatry.

Dorsolateral Prefrontal Cortex Glutamate/Gamma-Aminobutyric Acid (GABA) Alterations in Clinical High Risk and First-Episode Schizophrenia: A Preliminary 7-T Magnetic Resonance Spectroscopy Imaging Study.

Converging lines of evidence suggest that an imbalance between excitation and inhibition is present in the dorsolateral prefrontal cortex (DLPFC) of schizophrenia (SCZ). Gamma-aminobutyric-acid (GABA) and, to a lesser extent, glutamate (Glu) abnormalities were reported in the DLPFC of SCZ patients, especially on the right hemisphere, by post-mortem studies. However, in vivo evidence of GABA, Glu, and Glu/GABA DLPFC abnormalities, particularly on the right side and the early stages of illness, is limited. In this preliminary study, we utilized 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to investigate bilateral Glu/Creatine (Cre), GABA/Cre, and Glu/GABA in the DLPFC of sixteen first episode schizophrenia (FES), seventeen clinical high risk (CHR), and twenty-six healthy comparison (HC) subjects. FES and CHR had abnormal GABA/Cre and Glu/GABA in the right DLPFC (rDLPFC) compared with HC participants, while no differences were observed in the left DLPFC (lDLPFC) among the three groups. Furthermore, HC had higher Glu/GABA in rDLPFC compared to lDLPFC (R > L), whereas the opposite relationship (R < L) was observed in the DLPFC Glu/GABA of FES patients. Altogether, these findings indicate that GABA/Cre and Glu/GABA DLPFC alterations are present before illness manifestation and worsen in FES patients, thus representing a putative early pathophysiological biomarker for SCZ and related psychotic disorders.

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.

Relationships between rest-activity rhythms, sleep, and clinical symptoms in individuals at clinical high risk for psychosis and healthy comparison subjects.

Sleep-wake disturbances in individuals at clinical high risk (CHR) of psychosis may relate to increased symptom severity and contribute to disease progression. Here, we examined differences in rest-activity rhythms (RAR) measures, derived from actigraphy, and objective sleep outcomes, derived from electroencephalography (EEG), between 12 CHR and 16 healthy comparison (HC) individuals. Further, we examined the relationships between RAR disturbances, objective sleep outcomes and clinical psychosis symptoms (i.e., negative, positive, disorganized, general symptoms). Sleep-wake behaviors were monitored via actigraphy for 3-7 days (CHR: 5.7 ± 1.7 days; HC: 6.3 ± 1.2 days) prior to participants spending a night in the sleep laboratory, which was monitored with EEG. Separate regressions were used to examine the effect of clinical group on RAR measures and objective sleep outcomes after controlling for age and gender. CHR participants were found to be less active, specifically during the evening (17:00-20:00; ß = 1.145, SE = 0.362, p = .004) and nighttime (21:00-24:00; ß = 1.152, SE = 0.326, p = .002) relative to HC. Further, CHR participants had more fragmented sleep (wake after sleep onset: ß = 0.888, SE = 0.395, p = .034) and more hyperarousal during sleep (NREM gamma activity: ß = 1.087, SE = 0.348, p = .005), but these sleep disturbances were not related to reduced activity or clinical symptoms, whereas lower nighttime activity was related to more disorganized symptoms (ρ = -.640, p = .025). Thus, increasing activity through behavioral interventions may have additional beneficial effects on CHR clinical symptoms.