Validation of mismatch negativity and P3a for use in multi-site studies of schizophrenia: characterization of demographic, clinical, cognitive, and functional correlates in COGS-2

Bringing Imaging Biomarkers Into Clinical Reality in Psychiatry

Importance

Advancing precision psychiatry, where treatments are based on an individual's biology rather than solely their clinical presentation, requires attention to several key attributes for any candidate biomarker. These include test-retest reliability, sensitivity to relevant neurophysiology, cost-effectiveness, and scalability. Unfortunately, these issues have not been systematically addressed by biomarker development efforts that use common neuroimaging tools like magnetic resonance imaging (MRI) and electroencephalography (EEG). Here, the critical barriers that neuroimaging methods will need to overcome to achieve clinical relevance in the near to intermediate term are examined.

Observations

Reliability is often overlooked, which together with sensitivity to key aspects of neurophysiology and replicated predictive utility, favors EEG-based methods. The principal barrier for EEG has been the lack of large-scale data collection among multisite psychiatric consortia. By contrast, despite its high reliability, structural MRI has not demonstrated clinical utility in psychiatry, which may be due to its limited sensitivity to psychiatry-relevant neurophysiology. Given the prevalence of structural MRIs, establishment of a compelling clinical use case remains its principal barrier. By contrast, low reliability and difficulty in standardizing collection are the principal barriers for functional MRI, along with the need for demonstration that its superior spatial resolution over EEG and ability to directly image subcortical regions in fact provide unique clinical value. Often missing, moreover, is consideration of how these various scientific issues can be balanced against practical economic realities of psychiatric health care delivery today, for which embedding economic modeling into biomarker development efforts may help direct research efforts.

Conclusions and Relevance

EEG seems most ripe for near- to intermediate-term clinical impact, especially considering its scalability and cost-effectiveness. Recent efforts to broaden its collection, as well as development of low-cost turnkey systems, suggest a promising pathway by which neuroimaging can impact clinical care. Continued MRI research focused on its key barriers may hold promise for longer-horizon utility.

Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks

BACKGROUND

Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables.

METHODS

Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants.

RESULTS

Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls.

CONCLUSIONS

Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.

Mismatch Negativity in Schizophrenia, Unaffected First-degree Relatives, and Healthy Controls

BACKGROUND

Mismatch negativity (MMN) amplitude is attenuated in schizophrenia patients (SZ). However, variability in illness course among SZ samples and types of deviant stimuli used in MMN paradigms have contributed to inconsistent findings across studies. Though MMN is suggested to be impaired in schizotypy, the potential link between the two is yet to be systematically examined in unaffected first-degree relatives of schizophrenia patients (FDR).

METHODS

The SZ sample had twenty-two drug-naïve or drug-free patients (dSZ) and thirty chronic/medicated patients (cSZ). dSZ and cSZ patients were compared with thirty-six unaffected FDR and thirty-two healthy controls (HC) using a two-tone passive auditory oddball MMN paradigm in an event-related potential experiment with two conditions (presented as separate blocks)-duration-deviant (duration-MMN) and frequency-deviant (frequency-MMN). Schizotypy scores and MMN indices were examined for correlation in FDR.

RESULTS

Duration-MMN amplitude was significantly attenuated in both dSZ and cSZ compared to other groups. dSZ and cSZ did not differ on MMN indices. Psychopathology scores and features of illness (illness duration, medication dosage, etc.) did not correlate with MMN indices. In FDR, Schizotypal trait measures did not correlate with MMN indices.

CONCLUSIONS

Duration-MMN emerged as a more robust indicator of prediction error signalling deficit in SZ. Frequency-MMN amplitude did not significantly differ among the groups, and MMN indices did not correlate with state and trait measures of schizophrenia-related psychopathology. These findings reiterates that auditory sensory processing captured by MMN is likely reflective of dynamic cognitive functions at the point of testing, and is unlikely to be an expression of enduring symptomatology.

Psychosis superspectrum II: neurobiology, treatment, and implications

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Blocking Src-PSD-95 interaction rescues glutamatergic signaling dysregulation in schizophrenia

The complex and heterogeneous genetic architecture of schizophrenia inspires us to look beyond individual risk genes for therapeutic strategies and target their interactive dynamics and convergence. Postsynaptic NMDA receptor (NMDAR) complexes are a site of such convergence. Src kinase is a molecular hub of NMDAR function, and its protein interaction subnetwork is enriched for risk-genes and altered protein associations in schizophrenia. Previously, Src activity was found to be decreased in post-mortem studies of schizophrenia, contributing to NMDAR hypofunction. PSD-95 suppresses Src via interacting with its SH2 domain. Here, we devised a strategy to suppress the inhibition of Src by PSD-95 via employing a cell penetrating and Src activating PSD-95 inhibitory peptide (TAT-SAPIP). TAT-SAPIP selectively increased post-synaptic Src activity in humans and mice, and enhanced synaptic NMDAR currents in mice. Chronic ICV injection of TAT-SAPIP rescued deficits in trace fear conditioning in Src hypomorphic mice. We propose blockade of the Src-PSD-95 interaction as a proof of concept for the use of interfering peptides as a therapeutic strategy to reverse NMDAR hypofunction in schizophrenia and other illnesses.

P300 in schizophrenia: Then and now

The 1965 discovery of the P300 component of the electroencephalography (EEG)-based event-related potential (ERP), along with the subsequent identification of its alteration in people with schizophrenia, initiated over 50 years of P300 research in schizophrenia. Here, we review what we now know about P300 in schizophrenia after nearly six decades of research. We describe recent efforts to expand our understanding of P300 beyond its sensitivity to schizophrenia itself to its potential role as a biomarker of risk for psychosis or a heritable endophenotype that bridges genetic risk and psychosis phenomenology. We also highlight efforts to move beyond a syndrome-based approach to understand P300 within the context of the clinical, cognitive, and presumed pathophysiological heterogeneity among people diagnosed with schizophrenia. Finally, we describe several recent approaches that extend beyond measuring the traditional P300 ERP component in people with schizophrenia, including time-frequency analyses and pharmacological challenge studies, that may help to clarify specific cognitive mechanisms that are disrupted in schizophrenia. Moreover, we discuss several promising areas for future research, including studies of animal models that can be used for treatment development.

Mismatch negativity and polygenic risk scores for schizophrenia and bipolar disorder

OBJECTIVE

Auditory mismatch negativity (MMN) impairment is a candidate endophenotype in psychotic disorders, yet the genetic underpinnings remain to be clarified. Here, we examined the relationships between auditory MMN and polygenic risk scores (PRS) for individuals with psychotic disorders, including schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) and in healthy controls (HC).

METHODS

Genotyped and clinically well-characterized individuals with psychotic disorders (n = 102), including SSD (n = 43) and BD (n = 59), and HC (n = 397) underwent a roving MMN paradigm. In addition MMN, we measured the memory traces of the repetition positivity (RP) and the deviant negativity (DN), which is believed to reflect prediction encoding and prediction error signals, respectively. SCZ and BD PRS were computed using summary statistics from the latest genome-wide association studies. The relationships between the MMN, RP, and DN and the PRSs were assessed with linear regressions.

RESULTS

We found no significant association between the SCZ or BD PRS and grand average MMN in the psychotic disorders group or in the HCs group (all p > 0.05). SCZ PRS and BD PRS were negatively associated with RP in the psychotic disorders group (β = -0.46, t = -2.86, p = 0.005 and β = -0.29, t = -0.21, p = 0.034, respectively). No significant associations were found between DN and PRS.

CONCLUSION

These findings suggest that genetic variants associated with SCZ and BD may be associated with MMN subcomponents linked to predictive coding among patients with psychotic disorders. Larger studies are needed to confirm these findings and further elucidate the genetic underpinnings of MMN impairment in psychotic disorders.

Mismatch negativity in schizophrenia spectrum and bipolar disorders: Group and sex differences and associations with symptom severity

OBJECTIVE

Research increasingly implicates glutamatergic dysfunction in the pathophysiologies of psychotic disorders. Auditory mismatch negativity (MMN) is an electroencephalography (EEG) waveform linked to glutamatergic neurotransmission and is consistently attenuated in schizophrenia (SCZ). MMN consists of two subcomponents, the repetition positivity (RP) and deviant negativity (DN) possibly reflecting different neural mechanisms. However, whether MMN reduction is present across different psychotic disorders, linked to distinct symptom clusters, or related to sex remain to be clarified.

METHODS

Four hundred participants including healthy controls (HCs; n = 296) and individuals with SCZ (n = 39), bipolar disorder (BD) BD typeI (n = 35), or BD type II (n = 30) underwent a roving MMN paradigm and clinical evaluation. MMN, RP and DN as well their memory traces were recorded at the FCZ electrode. Analyses of variance and linear regression models were used both transdiagnostically and within clinical groups.

RESULTS

MMN was reduced in SCZ compared to BD (p = 0.006, d = 0.55) and to HCs (p < 0.001, d = 0.63). There was a significant group × sex interaction (p < 0.003) and the MMN impairment was only detected in males with SCZ. MMN amplitude correlated positively with Positive and Negative Syndrome Scale total score and negatively with Global Assessment of Functioning Scale score. The deviant negativity was impaired in males with SCZ. No group differences in memory trace indices of the MMN, DN, or RP.

CONCLUSION

MMN was attenuated in SCZ and correlated with greater severity of psychotic symptoms and lower level of functioning. Our results may indicate sex-dependent differences of glutamatergic function in SCZ.

Detecting Central Auditory Processing Disorders in Awake Mice

Mice are increasingly used as models of human-acquired neurological or neurodevelopmental conditions, such as autism, schizophrenia, and Alzheimer's disease. All these conditions involve central auditory processing disorders, which have been little investigated despite their potential for providing interesting insights into the mechanisms behind such disorders. Alterations of the auditory steady-state response to 40 Hz click trains are associated with an imbalance between neuronal excitation and inhibition, a mechanism thought to be common to many neurological disorders. Here, we demonstrate the value of presenting click trains at various rates to mice with chronically implanted pins above the inferior colliculus and the auditory cortex for obtaining easy, reliable, and long-lasting access to subcortical and cortical complex auditory processing in awake mice. Using this protocol on a mutant mouse model of autism with a defect of the Shank3 gene, we show that the neural response is impaired at high click rates (above 60 Hz) and that this impairment is visible subcortically-two results that cannot be obtained with classical protocols for cortical EEG recordings in response to stimulation at 40 Hz. These results demonstrate the value and necessity of a more complete investigation of central auditory processing disorders in mouse models of neurological or neurodevelopmental disorders.

Mismatch negativity predicts initial auditory-based targeted cognitive training performance in a heterogeneous population across psychiatric disorders

Auditory-based targeted cognitive training (ATCT) programs are emerging pro-cognitive therapeutic interventions which aim to improve auditory processing to attenuate cognitive impairment in a "bottom up" manner. Biomarkers of early auditory information processing (EAIP) like mismatch negativity (MMN) and P3a have been used successfully to predict gains from a full 40 h course of ATCT in schizophrenia (SZ). Here we investigated the ability of EAIP biomarkers to predict ATCT performance in a group of subjects (n = 26) across SZ, MDD, PTSD and GAD diagnoses. Cognition was assessed via the MATRICS Consensus Cognitive Battery (MCCB) and MMN/P3a were collected prior to completing 1 h of "Sound Sweeps," a representative ATCT exercise. Baseline and final performance over the first two levels of cognitive training served as the primary dependent variables. Groups had similar MMN, but the SZ group had attenuated P3a. MMN and MCCB cognitive domain t-scores, but not P3a, were strongly correlated with most ATCT performance measures, and explained up to 61% of variance in ATCT performance. Diagnosis was not a significant predictor for ATCT performance. These data suggest that MMN can predict ATCT performance in heterogeneous neuropsychiatric populations and should be considered in ATCT studies across diagnostically diverse cohorts.

Evaluating the clinical utility of speech analysis and machine learning in schizophrenia: A pilot study

BACKGROUND

Schizophrenia is a serious mental disorder that significantly impacts social functioning and quality of life. However, current diagnostic methods lack objective biomarker support. While some studies have indicated differences in audio features between patients with schizophrenia and healthy controls, these findings are influenced by demographic information and variations in experimental paradigms. Therefore, it is crucial to explore stable and reliable audio biomarkers for an auxiliary diagnosis and disease severity prediction of schizophrenia.

METHOD

A total of 130 individuals (65 patients with schizophrenia and 65 healthy controls) read three fixed texts containing positive, neutral, and negative emotions, and recorded them. All audio signals were preprocessed and acoustic features were extracted by a librosa-0.9.2 toolkit. Independent sample t-tests were performed on two sets of acoustic features, and Pearson correlation on the acoustic features and Positive and Negative Syndrome Scale (PANSS) scores of the schizophrenia group. Classification algorithms in scikit-learn were used to diagnose schizophrenia and predict the level of negative symptoms.

RESULTS

Significant differences were observed between the two groups in the mfcc_8, mfcc_11, and mfcc_33 of mel-frequency cepstral coefficient (MFCC). Furthermore, a significant correlation was found between mfcc_7 and the negative PANSS scores. Through acoustic features, we could not only differentiate patients with schizophrenia from healthy controls with an accuracy of 0.815 but also predict the grade of the negative symptoms in schizophrenia with an average accuracy of 0.691.

CONCLUSIONS

The results demonstrated the considerable potential of acoustic characteristics as reliable biomarkers for diagnosing schizophrenia and predicting clinical symptoms.

Mismatch negativity and clinical trajectories in psychotic disorders: Five-year stability and predictive utility

BACKGROUND

Mismatch negativity (MMN) amplitude is reduced in psychotic disorders and associated with symptoms and functioning. Due to these robust associations, it is often considered a biomarker for psychotic illness. The relationship between MMN and clinical outcomes has been examined well in early onset psychotic illness; however, its stability and predictive utility in chronic samples are not clear.

METHOD

We examined the five-year stability of MMN amplitude over two timepoints in individuals with established psychotic disorders (cases; N = 132) and never-psychotic participants (NP; N = 170), as well as longitudinal associations with clinical symptoms and functioning.

RESULTS

MMN amplitude exhibited good temporal stability (cases, r = 0.53; never-psychotic, r = 0.52). In cases, structural equation models revealed MMN amplitude to be a significant predictor of worsening auditory hallucinations (β = 0.19), everyday functioning (β = -0.13), and illness severity (β = -0.12) at follow-up. Meanwhile, initial IQ (β = -0.24), negative symptoms (β = 0.23), and illness severity (β = -0.16) were significant predictors of worsening MMN amplitude five years later.

CONCLUSIONS

These results imply that MMN measures a neural deficit that is reasonably stable up to five years. Results support disordered cognition and negative symptoms as preceding reduced MMN, which then may operate as a mechanism driving reductions in everyday functioning and the worsening of auditory hallucinations in chronic psychotic disorders. This pattern may inform models of illness course, clarifying the relationships amongst biological mechanisms of predictive processing and clinical deficits in chronic psychosis and allowing us to better understand the mechanisms driving such impairments over time.

Mismatch negativity generation in subjects at risk for psychosis: source analysis is more sensitive than surface electrodes in risk prediction

Background

Deficits of mismatch negativity (MMN) in patients with schizophrenia have been demonstrated many times and there is growing evidence that alterations of MMN already exist in individuals at risk for psychosis. The present study examines differences in MMN between subjects fulfilling ultra-high risk (UHR) or only basic symptoms criteria and it addresses the question, if MMN source analysis can improve prediction of transition to psychosis.

Methods

The MMN to duration, frequency, and intensity deviants was recorded in 50 healthy controls and 161 individuals at risk for psychosis classified into three subgroups: only basic symptoms (n = 74), only ultra-high risk (n = 13) and persons who fulfill both risk criteria (n = 74). Based on a three-source model of MMN generation, we conducted an MMN source analysis and compared the amplitudes of surface electrodes and sources among the three groups.

Results

Significant differences in MMN generation among the four groups were revealed at surface electrodes Cz and C4 (p < 0.05) and at the frontal source (p < 0.001) for duration deviant stimuli. The 15 subjects from the risk groups who subsequently developed a manifest psychosis had a significantly lower MMN amplitude at frontal source (p = 0.019) without showing significant differences at surface electrodes. Low activity at frontal MMN source increased the risk of transition to manifest disease by the factor 3.12 in UHR subjects.

Conclusion

MMN activity differed significantly between subjects presenting only basic symptoms and subjects which additionally meet UHR criteria. The largest differences between groups as well as between individuals with and without transition were observed at the frontal source. The present results suggest that source analysis is more sensitive than surface electrodes in psychosis risk prediction by MMN.

Deep psychophysiological phenotyping of adolescents and adults with 22q11.2 deletion syndrome: a multilevel approach to defining core disease processes

BACKGROUND

22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol.

METHODS

Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms.

DISCUSSION

Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study's protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS.

Reduced duration mismatch negativity elicited by the multi-feature 'optimal' paradigm in early-phase psychosis

BACKGROUND

MMN and P3a are EEG-derived event related potentials that are thought to be prospective biomarkers for schizophrenia and, potentially, early-phase psychosis (EPP).

METHODS

EPP (n = 12) and healthy control (n = 35) participants listened to a multi-feature optimal paradigm with five deviant types (gap, duration, location, intensity, and frequency).

RESULTS

There was a significant amplitude difference between the EPP and HC group with duration MMN (p =.02). No significant amplitude differences between groups were found for the P3a waveform. There were several correlations for the EPP group with the BNSS, SOFAS, and PANSS-general questionnaires. Length of illness was not associated with MMN or P3a.

CONCLUSIONS

The optimal paradigm is suitable for eliciting multiple deviant types within a short amount of time in both clinical and healthy populations. This study confirms duration MMN deficits within an EPP group and that MMN is related to functional outcomes and positive and negative symptomology.

Validation of a suite of ERP and QEEG biomarkers in a pre-competitive, industry-led study in subjects with schizophrenia and healthy volunteers

OBJECTIVE

Complexity and lack of standardization have mostly limited the use of event-related potentials (ERPs) and quantitative EEG (QEEG) biomarkers in drug development to small early phase trials. We present results from a clinical study on healthy volunteers (HV) and patients with schizophrenia (SZ) that assessed test-retest, group differences, variance, and correlation with functional assessments for ERP and QEEG measures collected at clinical and commercial trial sites with standardized instrumentation and methods, and analyzed through an automated data analysis pipeline.

METHODS

81 HV and 80 SZ were tested at one of four study sites. Subjects were administered two ERP/EEG testing sessions on separate visits. Sessions included a mismatch negativity paradigm, a 40 Hz auditory steady-state response paradigm, an eyes-closed resting state EEG, and an active auditory oddball paradigm. SZ subjects were also tested on the Brief Assessment of Cognition (BAC), Positive and Negative Syndrome Scale (PANSS), and Virtual Reality Functional Capacity Assessment Tool (VRFCAT).

RESULTS

Standardized ERP/EEG instrumentation and methods ensured few test failures. The automated data analysis pipeline allowed for near real-time analysis with no human intervention. Test-retest reliability was fair-to-excellent for most of the outcome measures. SZ subjects showed significant deficits in ERP and QEEG measures consistent with published academic literature. A subset of ERP and QEEG measures correlated with functional assessments administered to the SZ subjects.

CONCLUSIONS

With standardized instrumentation and methods, complex ERP/EEG testing sessions can be reliably performed at clinical and commercial trial sites to produce high-quality data in near real-time.

Mouse mutants in schizophrenia risk genes GRIN2A and AKAP11 show EEG abnormalities in common with schizophrenia patients

Schizophrenia is a heterogeneous psychiatric disorder with a strong genetic basis, whose etiology and pathophysiology remain poorly understood. Exome sequencing studies have uncovered rare, loss-of-function variants that greatly increase risk of schizophrenia [1], including loss-of-function mutations in GRIN2A (aka GluN2A or NR2A, encoding the NMDA receptor subunit 2A) and AKAP11 (A-Kinase Anchoring Protein 11). AKAP11 and GRIN2A mutations are also associated with bipolar disorder [2], and epilepsy and developmental delay/intellectual disability [1, 3, 4], respectively. Accessible in both humans and rodents, electroencephalogram (EEG) recordings offer a window into brain activity and display abnormal features in schizophrenia patients. Does loss of Grin2a or Akap11 in mice also result in EEG abnormalities? We monitored EEG in heterozygous and homozygous knockout Grin2a and Akap11 mutant mice compared with their wild-type littermates, at 3- and 6-months of age, across the sleep/wake cycle and during auditory stimulation protocols. Grin2a and Akap11 mutants exhibited increased resting gamma power, attenuated auditory steady-state responses (ASSR) at gamma frequencies, and reduced responses to unexpected auditory stimuli during mismatch negativity (MMN) tests. Sleep spindle density was reduced in a gene dose-dependent manner in Akap11 mutants, whereas Grin2a mutants showed increased sleep spindle density. The EEG phenotypes of Grin2a and Akap11 mutant mice show a variety of abnormal features that overlap considerably with human schizophrenia patients, reflecting systems-level changes caused by Grin2a and Akap11 deficiency. These neurophysiologic findings further substantiate Grin2a and Akap11 mutants as genetic models of schizophrenia and identify potential biomarkers for stratification of schizophrenia patients.

Mismatch negativity as an early biomarker of cognitive impairment in schizophrenia

Background

Due to its disturbance in schizophrenic patients, mismatch negativity (MMN) generation is believed to be a potential biomarker for recognizing primary impairments in auditory sensory processing during the course of the disease. However, great controversy exists regarding the type and onset of MMN-related impairments, with the deficits to frequency deviants is more debatable. This cross-sectional, case–control study was conducted to assess the cognitive functions among 33 eligible Egyptian schizophrenics (15 early and 18 chronic), and 30 matched healthy controls by assessing their psychometric tests and correlating them to the coexisting frequency deviant MMN responses (using both tone and speech stimuli).

Results

Deficits in frequency MMN and neuropsychological tests were evident among early and chronic schizophrenics compared to their matched control counterparts, and also between early versus chronic schizophrenia in favor of the later. MMN deficits to speech stimuli were more elicited than tone stimuli among schizophrenics. Moreover, significant correlations were identified between MMN parameters and the results of psychiatric cognitive scales.

Conclusions

We demonstrated that frequency-deviant MMN deficits are evident feature among the enrolled Egyptian schizophrenics. The cognitive functions as indexed by MMN seem affected early, with the striking decrease of MMN amplitude and delay of latency point towards the progression of the illness. The normal lateralization of MMN was absent in chronic schizophrenia. These findings could be helpful in using the MMN as an additional objective tool for confirming cognitive impairments among schizophrenics and to differentiate between early- and chronic-schizophrenic patients for medico-legal purposes and clinical implication for medications.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

Cholinergic Functioning, Cognition, and Anticholinergic Medication Burden in Schizophrenia

Acetylcholine (ACh) signaling is critical for central nervous function and is known to be abnormal in schizophrenia (SZ), a chronic neuropsychiatric disorder in which cognitive deficits persist, despite treatment. This review provides a summary of the clinical evidence linking ACh abnormalities to SZ-associated cognitive deficits, an overview of ACh-based pro-cognitive strategies attempted in SZ, and a survey of recent studies that describe the impact of anticholinergic medication burden on cognitive outcomes in SZ. Methodological challenges that currently limit more substantial investigation of ACh in SZ patients and future directions are also discussed.

Atypical prediction error learning is associated with prodromal symptoms in individuals at clinical high risk for psychosis

Reductions in the auditory mismatch negativity (MMN) have been well-demonstrated in schizophrenia rendering it a promising biomarker for understanding the emergence of psychosis. According to the predictive coding theory of psychosis, MMN impairments may reflect disturbances in hierarchical information processing driven by maladaptive precision-weighted prediction errors (pwPEs) and enhanced belief updating. We applied a hierarchical Bayesian model of learning to single-trial EEG data from an auditory oddball paradigm in 31 help-seeking antipsychotic-naive high-risk individuals and 23 healthy controls to understand the computational mechanisms underlying the auditory MMN. We found that low-level sensory and high-level volatility pwPE expression correlated with EEG amplitudes, coinciding with the timing of the MMN. Furthermore, we found that prodromal positive symptom severity was associated with increased expression of sensory pwPEs and higher-level belief uncertainty. Our findings provide support for the role of pwPEs in auditory MMN generation, and suggest that increased sensory pwPEs driven by changes in belief uncertainty may render the environment seemingly unpredictable. This may predispose high-risk individuals to delusion-like ideation to explain this experience. These results highlight the value of computational models for understanding the pathophysiological mechanisms of psychosis.

Documentation of Peripheral Auditory Function in Studies of the Auditory P300 Response

Abstract. A critical review was conducted to examine whether the peripheral hearing status of participants with neurological and psychological disorders was documented in published clinical studies of the auditory P300 response. Literature searches were conducted with three databases: PubMed, PsycINFO, and Scopus. Studies of participants with seven neurological or psychological disorders were included in the study. Each disorder was coupled with the main search phrase in separate searches on each database. Of the total 102 papers which met the inclusion criteria, the majority (64%) did not describe the peripheral hearing sensitivity of participants. In this review with studies that included participants at risk for hearing impairment, particularly age-related hearing loss, only a single publication adequately described formal hearing evaluation. Peripheral hearing status is rarely defined in studies of the P300 response. The inclusion of participants with a hearing loss likely affects the validity of findings for these studies. We recommend formal hearing assessment prior to inclusion of participants in studies of the auditory P300 response. The findings of this study may increase the awareness among researchers outside the field of audiology of the effects of peripheral hearing loss on the auditory P300.

A narrative review of treatment interventions to improve cognitive performance in schizophrenia, with an emphasis on at-risk and early course stages

Cognitive dysfunction is a core feature of schizophrenia (SCZ), which unfavorably affects SCZ patients' daily functioning and overall clinical outcome. An increasing body of evidence has shown that cognitive deficits are present not only at the beginning of the illness but also several years before the onset of psychosis. Nonetheless, the majority of treatment interventions targeting cognitive dysfunction in SCZ, using both pharmacological and nonpharmacological approaches, have focused on chronic patients rather than individuals at high risk or in the early stages of the disease. In this article, we provide a narrative review of cognitive interventions in SCZ patients, with a particular focus on pre-emptive interventions in at-risk/early course individuals when available. Furthermore, we discuss current challenges for these pre-emptive treatment interventions and provide some suggestions on how future work may ameliorate cognitive dysfunction in these individuals.

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.

The viability of the frequency following response characteristics for use as biomarkers of cognitive therapeutics in schizophrenia

Deficits in early auditory information processing contribute to cognitive and psychosocial disability; this has prompted development of interventions that target low-level auditory processing, which may alleviate these disabilities. The frequency following response (FFR) is a constellation of event-related potential and frequency characteristics that reflect the processing of acoustic stimuli at the level of the brainstem and ascending portions of the auditory pathway. While FFR is a promising candidate biomarker of response to auditory-based cognitive training interventions, the psychometric properties of FFR in schizophrenia patients have not been studied. Here we assessed the psychometric reliability and magnitude of group differences across 18 different FFR parameters to determine which of these parameters demonstrate adequate internal consistency. Electroencephalography from 40 schizophrenia patients and 40 nonpsychiatric comparison subjects was recorded during rapid presentation of an auditory speech stimulus (6000 trials). Patients showed normal response amplitudes but longer latencies for most FFR peaks and lower signal-to-noise ratios (SNRs) than healthy subjects. Analysis of amplitude and latency estimates of peaks, however, indicated a need for a substantial increase in task length to obtain internal consistency estimates above 0.80. In contrast, excellent internal consistency (>0.95) was shown for FFR sustained responses. Only SNR scores reflecting the FFR sustained response yielded significant group differences and excellent internal consistency, suggesting that this measure is a viable candidate for use in clinical treatment studies. The present study highlights the use of internal consistency estimates to select FFR characteristics for use in future intervention studies interested in individual differences among patients.

Is sensor space analysis good enough? Spatial patterns as a tool for assessing spatial mixing of EEG/MEG rhythms

Analyzing non-invasive recordings of electroencephalography (EEG) and magnetoencephalography (MEG) directly in sensor space, using the signal from individual sensors, is a convenient and standard way of working with this type of data. However, volume conduction introduces considerable challenges for sensor space analysis. While the general idea of signal mixing due to volume conduction in EEG/MEG is recognized, the implications have not yet been clearly exemplified. Here, we illustrate how different types of activity overlap on the level of individual sensors. We show spatial mixing in the context of alpha rhythms, which are known to have generators in different areas of the brain. Using simulations with a realistic 3D head model and lead field and data analysis of a large resting-state EEG dataset, we show that electrode signals can be differentially affected by spatial mixing by computing a sensor complexity measure. While prominent occipital alpha rhythms result in less heterogeneous spatial mixing on posterior electrodes, central electrodes show a diversity of rhythms present. This makes the individual contributions, such as the sensorimotor mu-rhythm and temporal alpha rhythms, hard to disentangle from the dominant occipital alpha. Additionally, we show how strong occipital rhythms can contribute the majority of activity to frontal channels, potentially compromising analyses that are solely conducted in sensor space. We also outline specific consequences of signal mixing for frequently used assessment of power, power ratios and connectivity profiles in basic research and for neurofeedback application. With this work, we hope to illustrate the effects of volume conduction in a concrete way, such that the provided practical illustrations may be of use to EEG researchers to in order to evaluate whether sensor space is an appropriate choice for their topic of investigation.

From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach

Deep learning techniques have been applied to electroencephalogram (EEG) signals, with promising applications in the field of psychiatry. Schizophrenia is one of the most disabling neuropsychiatric disorders, often characterized by the presence of auditory hallucinations. Auditory processing impairments have been studied using EEG-derived event-related potentials and have been associated with clinical symptoms and cognitive dysfunction in schizophrenia. Due to consistent changes in the amplitude of ERP components, such as the auditory N100, some have been proposed as biomarkers of schizophrenia. In this paper, we examine altered patterns in electrical brain activity during auditory processing and their potential to discriminate schizophrenia and healthy subjects. Using deep convolutional neural networks, we propose an architecture to perform the classification based on multi-channels auditory-related EEG single-trials, recorded during a passive listening task. We analyzed the effect of the number of electrodes used, as well as the laterality and distribution of the electrical activity over the scalp. Results show that the proposed model is able to classify schizophrenia and healthy subjects with an average accuracy of 78% using only 5 midline channels (Fz, FCz, Cz, CPz, and Pz). The present study shows the potential of deep learning methods in the study of impaired auditory processing in schizophrenia with implications for diagnosis. The proposed design can provide a base model for future developments in schizophrenia research.

Mismatch negativity as an index of target engagement for excitation/inhibition-based treatment development: a double-blind, placebo-controlled, randomized, single-dose cross-over study of the serotonin type-3 receptor antagonist CVN058

Serotonin type-3 receptor (5-HT₃R) antagonists show potential as a treatment for cognitive deficits in schizophrenia. CVN058, a brain-penetrant, potent and selective 5-HT₃R antagonist, shows efficacy in rodent models of cognition and was well-tolerated in Phase-1 studies. We evaluated the target engagement of CVN058 using mismatch negativity (MMN) in a randomized, double-blind, placebo-controlled, cross-over study. Subjects were stable outpatients with schizophrenia or schizoaffective disorder treated with antipsychotics. Subjects were not permitted to use other 5-HT₃R modulators or serotonin reuptake inhibitors. Each subject received a high (150 mg) and low (15 mg or 75 mg) oral dose of CVN058 and placebo in a randomized order across 3 single-day treatment visits separated by at least 1 week. The primary pre-registered outcome was amplitude of duration MMN. Amplitude of other MMN deviants (frequency, intensity, frequency modulation, and location), P50, P300 and auditory steady-state response (ASSR) were exploratory endpoints. 19 of 22 randomized subjects (86.4%) completed the study. Baseline PANSS scores indicated moderate impairment. CVN058 150 mg led to significant improvement vs. placebo on the primary outcome of duration MMN (p = 0.02, Cohen's d = 0.48). A significant treatment effect was also seen in a combined analysis across all MMN deviants (p < 0.001, d = 0.57). Effects on location MMN were independently significant (p < 0.007, d = 0.46). No other significant effects were seen for other deviants, doses or EEG measures. There were no clinically significant treatment related adverse effects. These results show MMN to be a sensitive target engagement biomarker for 5-HT₃R, and support the potential utility of CVN058 in correcting the excitatory/inhibitory imbalance in schizophrenia.

Test-retest reliability of mismatch negativity and gamma-band auditory steady-state response in patients with schizophrenia

Patients with schizophrenia show widespread impairments in clinical, cognitive and psychosocial functioning. Mismatch negativity (MMN) and gamma-band auditory steady-state response (ASSR) are two neurophysiological biomarkers widely used to inform diagnosis, guide treatments and track response to interventions in schizophrenia. However, evidence for the test-retest reliability of these indices across multiple sessions in schizophrenia patients remains scarce. In the present study, we included 34 schizophrenia patients (17 females) and obtained duration MMN (dMMN), frequency MMN (fMMN) and 40-Hz ASSR data across three sessions with intervals of 2 days. Event-related spectrum perturbation (ERSP) and inter-trial coherence (ITC) were calculated following Morlet wavelet time-frequency decomposition of ASSR data. The intra-class correlation coefficient (ICC) was used to quantify the reliability of MMN and ASSR measures among the three sessions. We found fair to good reliability for dMMN amplitudes but poor reliability for fMMN amplitudes. For the ASSR measures, ERSP showed good to excellent test-retest reliability while ITC had poor to fair test-retest reliability. In addition, the average of dMMN amplitudes was significantly correlated with that of ERSP across the three sessions. In summary, we established for the first time the short-term test-retest reliability of MMN and ASSR measures in schizophrenia patients. These findings demonstrate that dMMN amplitudes and ERSP of ASSR are reliable indices which may be used in longitudinal observational studies.

Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response

Precision medicine has been considered a promising approach to diagnosis, treatment, and various interventions, considering the individual clinical and biological characteristics. Recent advances in biomarker development hold promise for guiding a new era of precision medicine style trials for psychiatric illnesses, including psychosis. Electroencephalography (EEG) can directly measure the full spatiotemporal dynamics of neural activation associated with a wide variety of cognitive processes. This manuscript reviews three aspects: prediction of diagnosis, prognostic aspects of disease progression and outcome, and prediction of treatment response that might be helpful in understanding the current status of electrophysiological biomarkers in precision medicine for patients with psychosis. Although previous EEG analysis could not be a powerful method for the diagnosis of psychiatric illness, recent methodological advances have shown the possibility of classifying and detecting mental illness. Some event-related potentials, such as mismatch negativity, have been associated with neurocognition, functioning, and illness progression in schizophrenia. Resting state studies, sophisticated ERP measures, and machine-learning approaches could make technical progress and provide important knowledge regarding neurophysiology, disease progression, and treatment response in patients with schizophrenia. Identifying potential biomarkers for the diagnosis and treatment response in schizophrenia is the first step towards precision medicine.

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.

Mismatch negativity amplitude in first-degree relatives of individuals with psychotic disorders: Links with cognition and schizotypy

Mismatch negativity (MMN) amplitude is reliably reduced in psychotic disorders. While several studies have examined this effect in first-degree relatives of individuals with schizophrenia, few have sought to quantify deficits in relatives of individuals with other psychotic disorders. While some conclude that, compared to healthy subjects, first-degree relatives of schizophrenia show reduced MMN, others contradict this finding. Furthermore, though MMN is often shown to be associated with cognitive impairments and clinical symptoms in psychotic disorders, to our knowledge no studies have sought to fully examine these relationships in studies of first-degree relatives. The present study sought to clarify the extent of MMN amplitude reductions in a large sample of siblings of individuals with diverse psychotic disorders (n = 67), compared to probands with psychosis (n = 221) and never psychotic comparison subjects (n = 251). We further examined associations of MMN amplitude with cognition and schizotypal symptoms across these groups. We found that MMN amplitude was intact in siblings compared to probands. MMN amplitude was associated with cognition and schizotypal symptoms dimensionally across levels of familial risk. The present results imply that MMN reductions do not reflect genetic risk for psychotic disorders per se, and instead emerge as a result of, or in conjunction with, clinical features associated with psychosis. Such findings carry important implications for the utility of MMN amplitude as an indicator of inherited risk, and suggest that this component may be best conceptualized as an endophenotype for clinical symptoms and cognitive impairments, rather than risk for psychosis per se.

Duration Mismatch Negativity Predicts Remission in First-Episode Schizophrenia Patients

Objective: Remission in schizophrenia patients is associated with neurocognitive, social, and role functioning during both the early and chronic stages of schizophrenia. It is well-established that the amplitudes of duration mismatch negativity (dMMN) and frequency MMN (fMMN) are reduced in schizophrenia patients. However, the potential link between MMN and remission has not been established. In this study, we investigated the relationship between MMNs and remission in first-episode schizophrenia (FES) and their association with neurocognitive and social functioning. Method: dMMN and fMMN were measured in 30 patients with FES and 22 healthy controls at baseline and after a mean of 3 years. Clinical symptoms and cognitive and social functioning in the patients were assessed at the time of MMN measurements by using the Positive and Negative Syndrome Scale (PANSS), modified Global Assessment of Functioning (mGAF), Schizophrenia Cognition Rating Scale (SCoRS), and the Brief Assessment of Cognition in Schizophrenia (BACS). Remission of the patients was defined using the criteria by the Remission in Schizophrenia Working Group; of the 30 patients with FES, 14 achieved remission and 16 did not. Results: Baseline dMMN amplitude was reduced in FES compared to healthy controls. Further, baseline dMMN in the non-remitters had decreased amplitude and prolonged latency compared to the remitters. MMN did not change during follow-up period regardless of parameters, diagnosis, or remission status. Baseline dMMN amplitude in FES was correlated with future SCoRS and PANSS total scores. Logistic regression analysis revealed that dMMN amplitude at baseline was a significant predictor of remission. Conclusions: Our findings suggest that dMMN amplitude may be a useful biomarker for predicting symptomatic remission and improvement of cognitive and social functions in FES.

Evaluation of the frequency following response as a predictive biomarker of response to cognitive training in schizophrenia

Neurophysiological biomarkers of auditory processing show promise predicting outcomes following auditory-based targeted cognitive training (TCT) in schizophrenia, but the viability of the frequency following response (FFR) as a biomarker has yet to be examined, despite its ecological and face validity for auditory-based interventions. FFR is an event-related potential (ERP) that reflects early auditory processing. We predicted that schizophrenia patients would show acute- and longer-term FFR malleability in the context of TCT. Patients were randomized to either TCT (n = 30) or treatment as usual (TAU; n = 22), and electroencephalography was recorded during rapid presentation of an auditory speech stimulus before treatment, after one hour of training, and after 30 h of training. Whereas patients in the TCT group did not show changes in FFR after training, amplitude reductions were observed in the TAU. FFR was positively associated with performance on a measure of single word-in-noise perception in the TCT group, and with a measure of sentence-in-noise perception in both groups. Psychometric reliability analyses of FFR scores indicated high internal consistency but low one-hour and 12-week test-rest reliability. These findings support the dissociation between measures of speech discriminability along the hierarchy of cortical and subcortical early auditory information processing in schizophrenia.

Central auditory processing deficits in schizophrenia: Effects of auditory-based cognitive training

BACKGROUND

Sensory processing abnormalities are common in schizophrenia (SZ) and impact everyday functions, such as speech perception in noisy environments. Auditory-based targeted cognitive training (TCT) is a "bottom up" cognitive remediation intervention designed to enhance the speed and accuracy of low-level auditory information processing. However, the effects of TCT on behavioral measures of central auditory processing (CAP) and the role of CAP function on verbal learning outcomes in SZ are unknown.

METHODS

SZ (n = 42) and healthy subjects (CTL; n = 18) underwent comprehensive clinical, neurocognitive, and auditory assessments, including tests of hearing sensitivity and speech recognition (Words-in-Noise (WIN), Quick Speech-in-Noise (SIN)). SZ patients were randomized to receive either treatment-as-usual (TAU); or 30-h of TCT + TAU using a stratified, parallel design. SZ patients repeated assessments ~10-12 weeks later.

RESULTS

Patients exhibited deficits in both WIN (p < 0.05, d = 0.50) and SIN (p < 0.01, d = 0.63). A treatment × time interaction on WIN (p < 0.05, d = 0.74), but not SIN discriminability, was seen in the TCT group relative to TAU. Specific enhancements in the 4-dB over background range drove gains in WIN performance. Moreover, SZ patients with greater CAP deficits experienced robust gains in verbal learning after 30-h of TCT relative to SZ patients without CAP impairment (p < 0.01, d = 1.28).

CONCLUSION

Findings demonstrate that intensive auditory training enhances the fidelity of auditory processing and perception, such that specific CAP deficits were 'normalized' and were predictive of gains in verbal learning after TCT. It is conceivable that patients with deficiencies in CAP measures may benefit most from TCT and other interventions targeting auditory dysfunction in SZ.

Predicting Long-Term Outcomes in First-Admission Psychosis: Does the Hierarchical Taxonomy of Psychopathology Aid DSM in Prognostication?

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical, dimensional model of psychological symptoms and functioning. Its goals are to augment the use and address the limitations of traditional diagnoses, such as arbitrary thresholds of severity, within-disorder heterogeneity, and low reliability. HiTOP has made inroads to addressing these problems, but its prognostic validity is uncertain. The present study sought to test the prediction of long-term outcomes in psychotic disorders was improved when the HiTOP dimensional approach was considered along with traditional (ie, DSM) diagnoses. We analyzed data from the Suffolk County Mental Health Project (N = 316), an epidemiologic study of a first-admission psychosis cohort followed for 20 years. We compared 5 diagnostic groups (schizophrenia/schizoaffective, bipolar disorder with psychosis, major depressive disorder with psychosis, substance-induced psychosis, and other psychoses) and 5 dimensions derived from the HiTOP thought disorder spectrum (reality distortion, disorganization, inexpressivity, avolition, and functional impairment). Both nosologies predicted a significant amount of variance in most outcomes. However, except for cognitive functioning, HiTOP showed consistently greater predictive power across outcomes-it explained 1.7-fold more variance than diagnoses in psychiatric and physical health outcomes, 2.1-fold more variance in community functioning, and 3.4-fold more variance in neural responses. Even when controlling for diagnosis, HiTOP dimensions incrementally predicted almost all outcomes. These findings support a shift away from the exclusive use of categorical diagnoses and toward the incorporation of HiTOP dimensions for better prognostication and linkage with neurobiology.

Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification

Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software with allowable thresholds to make deterministic approximate conclusions. In comparison to traditional technologies in healthcare, artificial intelligence enhances the process of data analysis without the need for human input, producing nearly equally reliable, well defined output. Schizophrenia is a chronic mental health condition that affects millions worldwide, with impairment in thinking and behaviour that may be significantly disabling to daily living. Multiple artificial intelligence and machine learning algorithms have been utilized to analyze the different components of schizophrenia, such as in prediction of disease, and assessment of current prevention methods. These are carried out in hope of assisting with diagnosis and provision of viable options for individuals affected. In this paper, we review the progress of the use of artificial intelligence in schizophrenia.

Mismatch negativity as EEG biomarker supporting CNS drug development: a transnosographic and translational study

The lack of translation from basic research into new medicines is a major challenge in CNS drug development. The need to use novel approaches relying on (i) patient clustering based on neurobiology irrespective to symptomatology and (ii) quantitative biomarkers focusing on evolutionarily preserved neurobiological systems allowing back-translation from clinical to nonclinical research has been highlighted. Here we sought to evaluate the mismatch negativity (MMN) response in schizophrenic (SZ) patients, Alzheimer's disease (AD) patients, and age-matched healthy controls. To evaluate back-translation of the MMN response, we developed EEG-based procedures allowing the measurement of MMN-like responses in a rat model of schizophrenia and a mouse model of AD. Our results indicate a significant MMN attenuation in SZ but not in AD patients. Consistently with the clinical findings, we observed a significant attenuation of deviance detection (~104.7%) in rats subchronically exposed to phencyclidine, while no change was observed in APP/PS1 transgenic mice when compared to wild type. This study provides new insight into the cross-disease evaluation of the MMN response. Our findings suggest further investigations to support the identification of neurobehavioral subtypes that may help patients clustering for precision medicine intervention. Furthermore, we provide evidence that MMN could be used as a quantitative/objective efficacy biomarker during both preclinical and clinical stages of SZ drug development.

Hierarchical Pathways from Sensory Processing to Cognitive, Clinical, and Functional Impairments in Schizophrenia

Cognitive impairment is a hallmark of schizophrenia and a robust predictor of functional outcomes. Impairments are found in all phases of the illness and are only moderately attenuated by currently approved therapeutics. Neurophysiological indices of sensory discrimination (ie, mismatch negativity (MMN) and P3a amplitudes) and gamma-band auditory steady-state response (ASSR; power and phase locking) are translational biomarkers widely used in the development of novel therapeutics for neuropsychiatric disorders. It is unclear whether laboratory-based EEG measures add explanatory power to well-established models that use only cognitive, clinical, and functional outcome measures. Moreover, it is unclear if measures of sensory discrimination and gamma-band ASSR uniquely contribute to putative causal pathways linking sensory discrimination, neurocognition, negative symptoms, and functional outcomes in schizophrenia. To answer these questions, hierarchical associations among sensory processing, neurocognition, clinical symptoms, and functional outcomes were assessed via structural equation modeling in a large sample of schizophrenia patients (n = 695) and healthy comparison subjects (n = 503). The results showed that the neurophysiologic indices of sensory discrimination and gamma-band ASSR both significantly contribute to and yield unique hierarchical, "bottom-up" effects on neurocognition, symptoms, and functioning. Measures of sensory discrimination showed direct effects on neurocognition and negative symptoms, while gamma-band ASSR had a direct effect on neurocognition in patients. Continued investigation of the neural mechanisms underlying abnormal networks of MMN/P3a and gamma-band ASSR is needed to clarify the pathophysiology of schizophrenia and the development of novel therapeutic interventions.

Unique contributions of sensory discrimination and gamma synchronization deficits to cognitive, clinical, and psychosocial functional impairments in schizophrenia

BACKGROUND

Schizophrenia patients show widespread deficits in neurocognitive, clinical, and psychosocial functioning. Mismatch negativity (MMN) and gamma-band auditory steady-state response (ASSR) are robust translational biomarkers associated with schizophrenia and associated with cognitive dysfunction, negative symptom severity, and psychosocial disability. Although these biomarkers are conceptually linked as measures of early auditory information processing, it is unclear whether MMN and gamma-band ASSR account for shared vs. non-shared variance in cognitive, clinical, and psychosocial functioning.

METHODS

Multiple regression analyses with MMN, gamma-band ASSR, and clinical measures were performed in large cohorts of schizophrenia outpatients (N = 428) and healthy comparison subjects (N = 283).

RESULTS

Reduced MMN (d = 0.67), gamma-band ASSR (d = -0.40), and lower cognitive function were confirmed in schizophrenia patients. Regression analyses revealed that reduced MMN amplitude showed unique associations with lower verbal learning and negative symptoms, reduced gamma-band ASSR showed a unique association with working memory deficits, and both reduced MMN amplitude and reduced gamma-band ASSR showed an association with daily functioning impairment in schizophrenia patients.

CONCLUSION

MMN and ASSR measures are non-redundant and complementary measures of early auditory information processing that are associated with important domains of functioning. Studies are needed to clarify the neural substrates of MMN and gamma-band ASSR to improve our understanding of the pathophysiology of schizophrenia and accelerate their use in the development of novel therapeutic interventions.

Sources of the frontocentral mismatch negativity and P3a responses in schizophrenia patients and healthy comparison subjects

BACKGROUND

Mismatch negativity (MMN) and P3a are event-related potential measures of early auditory information processing that are increasingly used as translational biomarkers in the development of treatments for neuropsychiatric disorders. These responses are reduced in schizophrenia patients over the frontocentral scalp electrodes and are associated with important domains of cognitive and psychosocial functioning. While MMN and P3a responses are generated by a dynamic network of cortical sources distributed across the temporal and frontal brain regions, it is not clear how these sources independently contribute to MMN and P3a at the primary frontocentral scalp electrode or to abnormalities observed in schizophrenia. This study aimed to determine the independent source contributions and characterize the magnitude of impairment in source-level MMN and P3a responses in schizophrenia patients.

METHODS

A novel method was applied to back-project the contributions of 11 independent cortical source components to Fz, the primary scalp sensor that is used in clinical studies, in n = 589 schizophrenia patients and n = 449 healthy comparison subjects.

RESULTS

The groups showed comparable individual source contributions underlying both MMN and P3a responses at Fz. Source-level responses revealed an increasing magnitude of impairment in schizophrenia patients from the temporal to more frontal sources.

CONCLUSIONS

Schizophrenia patients have a normal architecture of source contributions that are accompanied by widespread abnormalities in source resolved mismatch and P3a responses, with more prominent deficits detected from the frontal sources. Quantification of source contributions and source-level responses accelerates clarification of the neural networks underlying MMN reduction at Fz in schizophrenia patients.

Deficits in auditory predictive coding in individuals with the psychosis risk syndrome: Prediction of conversion to psychosis

The mismatch negativity (MMN) event-related potential (ERP) component is increasingly viewed as a prediction error signal elicited when a deviant sound violates the prediction that a frequent "standard" sound will repeat. Support for this predictive coding framework emerged with the identification of the repetition positivity (RP), a standard stimulus ERP component that increases with standard repetition and is thought to reflect strengthening of the standard's memory trace and associated predictive code. Using electroencephalographic recordings, we examined the RP elicited by repeating standard tones presented during a traditional "constant standard" MMN paradigm in individuals with the psychosis risk syndrome (PRS; n = 579) and healthy controls (HC; n = 241). Clinical follow-up assessments identified PRS participants who converted to a psychotic disorder (n = 77) and PRS nonconverters who were followed for the entire 24-month clinical follow-up period and either remained symptomatic (n = 144) or remitted from the PRS (n = 94). In HC, RP linearly increased from early- to late-appearing standards within local trains of repeating standards (p < .0001), consistent with auditory predictive code/memory trace strengthening. Relative to HC, PRS participants showed a reduced RP across standards (p = .0056). PRS converters showed a relatively small RP deficit for early appearing standards relative to HC (p = .0.0107) and a more prominent deficit for late-appearing standards (p = .0006) relative to both HC and PRS-remitted groups. Moreover, greater RP deficits predicted shorter time to conversion in a subsample of unmedicated PRS individuals (p = .02). Thus, auditory predictive coding/memory trace deficits precede psychosis onset and predict future psychosis risk in PRS individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The effects of roflumilast, a phosphodiesterase type-4 inhibitor, on EEG biomarkers in schizophrenia: A randomised controlled trial

BACKGROUND

Patients with schizophrenia have significant cognitive deficits, which may profoundly impair quality of life. These deficits are also evident at the neurophysiological level with patients demonstrating altered event-related potential in several stages of cognitive processing compared to healthy controls; within the auditory domain, for example, there are replicated alterations in Mismatch Negativity, P300 and Auditory Steady State Response. However, there are no approved pharmacological treatments for cognitive deficits in schizophrenia.

AIMS

Here we examine whether the phosphodiesterase-4 inhibitor, roflumilast, can improve neurophysiological deficits in schizophrenia.

METHODS

Using a randomised, double-blind, placebo-controlled, crossover design study in 18 patients with schizophrenia, the effect of the phosphodiesterase-4 inhibitor, roflumilast (100 µg and 250 µg) on auditory steady state response (early stage), mismatch negativity and theta (intermediate stage) and P300 (late stage) was examined using electroencephalogram. A total of 18 subjects were randomised and included in the analysis.

RESULTS

Roflumilast 250 µg significantly enhanced the amplitude of both the mismatch negativity (p=0.04) and working memory-related theta oscillations (p=0.02) compared to placebo but not in the other (early- or late-stage) cognitive markers.

CONCLUSIONS

The results suggest that phosphodiesterase-4 inhibition, with roflumilast, can improve electroencephalogram cognitive markers, which are impaired in schizophrenia, and that phosphodiesterase-4 inhibition acts at an intermediate rather than early or late cognitive processing stage. This study also underlines the use of neurophysiological measures as cognitive biomarkers in experimental medicine.

Abnormally Large Baseline P300 Amplitude Is Associated With Conversion to Psychosis in Clinical High Risk Individuals With a History of Autism: A Pilot Study

Psychosis rates in autism spectrum disorder (ASD) are 5-35% higher than in the general population. The overlap in sensory and attentional processing abnormalities highlights the possibility of related neurobiological substrates. Previous research has shown that several electroencephalography (EEG)-derived event-related potential (ERP) components that are abnormal in schizophrenia, including P300, are also abnormal in individuals at Clinical High Risk (CHR) for psychosis and predict conversion to psychosis. Yet, it is unclear whether P300 is similarly sensitive to psychosis risk in help-seeking CHR individuals with ASD history. In this exploratory study, we leveraged data from the North American Prodrome Longitudinal Study (NAPLS2) to probe for the first time EEG markers of longitudinal psychosis profiles in ASD. Specifically, we investigated the P300 ERP component and its sensitivity to psychosis conversion across CHR groups with (ASD+) and without (ASD-) comorbid ASD. Baseline EEG data were analyzed from 304 CHR patients (14 ASD+; 290 ASD-) from the NAPLS2 cohort who were followed longitudinally over two years. We examined P300 amplitude to infrequent Target (10%; P3b) and Novel distractor (10%; P3a) stimuli from visual and auditory oddball tasks. Whereas P300 amplitude attenuation is typically characteristic of CHR and predictive of conversion to psychosis in non-ASD sample, in our sample, history of ASD moderated this relationship such that, in CHR/ASD+ individuals, enhanced - rather than attenuated - visual P300 (regardless of stimulus type) was associated with psychosis conversion. This pattern was also seen for auditory P3b amplitude to Target stimuli. Though drawn from a small sample of CHR individuals with ASD, these preliminary results point to a paradoxical effect, wherein those with both CHR and ASD history who go on to develop psychosis have a unique pattern of enhanced neural response during attention orienting to both visual and target stimuli. Such a pattern stands out from the usual finding of P300 amplitude reductions predicting psychosis in non-ASD CHR populations and warrants follow up in larger scale, targeted, longitudinal studies of those with ASD at clinical high risk for psychosis.

CDP-choline and galantamine, a personalized α7 nicotinic acetylcholine receptor targeted treatment for the modulation of speech MMN indexed deviance detection in healthy volunteers: a pilot study

RATIONALE

The combination of CDP-choline, an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist, with galantamine, a positive allosteric modulator of nAChRs, is believed to counter the fast desensitization rate of the α7 nAChRs and may be of interest for schizophrenia (SCZ) patients. Beyond the positive and negative clinical symptoms, deficits in early auditory prediction-error processes are also observed in SCZ. Regularity violations activate these mechanisms that are indexed by electroencephalography-derived mismatch negativity (MMN) event-related potentials (ERPs) in response to auditory deviance.

OBJECTIVES/METHODS

This pilot study in thirty-three healthy humans assessed the effects of an optimized α7 nAChR strategy combining CDP-choline (500 mg) with galantamine (16 mg) on speech-elicited MMN amplitude and latency measures. The randomized, double-blinded, placebo-controlled, and counterbalanced design with a baseline stratification method allowed for assessment of individual response differences.

RESULTS

Increases in MMN generation mediated by the acute CDP-choline/galantamine treatment in individuals with low baseline MMN amplitude for frequency, intensity, duration, and vowel deviants were revealed.

CONCLUSIONS

These results, observed primarily at temporal recording sites overlying the auditory cortex, implicate α7 nAChRs in the enhancement of speech deviance detection and warrant further examination with respect to dysfunctional auditory deviance processing in individuals with SCZ.