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

N2 Responses in Youths With Psychosis Risk Syndrome and Their Association With Clinical Outcomes: A Cohort Follow-Up Study Based on the Three-Stimulus Visual Oddball Paradigm

OBJECTIVE

Schizophrenia often occurs during youth, and psychosis risk syndrome occurs before the onset of psychosis. The aim of this study was to determine whether the visual event-related potential responses in youths with psychosis risk syndrome were defective in the presence of interference stimuli and associated with their clinical outcomes.

METHODS

A total of 223 participants, including 122 patients with psychosis risk syndrome, 50 patients with emotional disorders, and 51 healthy control subjects, were assessed. Baseline EEG was recorded during the three-stimulus visual oddball task. The event-related potentials induced by square pictures with different colors were measured. Almost all patients with psychosis risk syndrome were followed up for 12 months and were reclassified into three subgroups: conversion, symptomatic, and remission. The differences in baseline event-related potential responses were compared among the clinical outcome subgroups.

RESULTS

The average N2 amplitude of the psychosis risk syndrome group was significantly less negative than that in the healthy control group (d=0.53). The baseline average N2 amplitude in the conversion subgroup was significantly less negative than that in the symptomatic (d=0.58) and remission (d=0.50) subgroups and in the healthy control group (d=0.97). The average N2 amplitude did not differ significantly between the symptomatic and remission subgroups (d=0.02). However, it was significantly less negative in the symptomatic and remission subgroups than in the healthy control group (d=0.46 and d=0.38). No statistically significant results were found in the P3 response.

CONCLUSIONS

Youths with psychosis risk syndrome had significant N2 amplitude defects in attention processing with interference stimuli. N2 amplitude shows potential as a prognostic biomarker of clinical outcome in the psychosis risk syndrome.

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.

Aberrant Hierarchical Prediction Errors Are Associated With Transition to Psychosis: A Computational Single-Trial Analysis of the Mismatch Negativity

BACKGROUND

Mismatch negativity reductions are among the most reliable biomarkers for schizophrenia and have been associated with increased risk for conversion to psychosis in individuals who are at clinical high risk for psychosis (CHR-P). Here, we adopted a computational approach to develop a mechanistic model of mismatch negativity reductions in CHR-P individuals and patients early in the course of schizophrenia.

METHODS

Electroencephalography was recorded in 38 CHR-P individuals (15 converters), 19 patients early in the course of schizophrenia (≤5 years), and 44 healthy control participants during three different auditory oddball mismatch negativity paradigms including 10% duration, frequency, or double deviants, respectively. We modeled sensory learning with the hierarchical Gaussian filter and extracted precision-weighted prediction error trajectories from the model to assess how the expression of hierarchical prediction errors modulated electroencephalography amplitudes over sensor space and time.

RESULTS

Both low-level sensory and high-level volatility precision-weighted prediction errors were altered in CHR-P individuals and patients early in the course of schizophrenia compared with healthy control participants. Moreover, low-level precision-weighted prediction errors were significantly different in CHR-P individuals who later converted to psychosis compared with nonconverters.

CONCLUSIONS

Our results implicate altered processing of hierarchical prediction errors as a computational mechanism in early psychosis consistent with predictive coding accounts of psychosis. This computational model seems to capture pathophysiological mechanisms that are relevant to early psychosis and the risk for future psychosis in CHR-P individuals and may serve as predictive biomarkers and mechanistic targets for the development of novel treatments.

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.

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

PURPOSE OF REVIEW

This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis.

RECENT FINDINGS

Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.

Habituation, Adaptation and Prediction Processes in Neurodevelopmental Disorders: A Comprehensive Review

Habituation, the simplest form of learning preserved across species and evolution, is characterized by a response decrease as a stimulus is repeated. This adaptive function has been shown to be altered in some psychiatric and neurodevelopmental disorders such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or schizophrenia. At the brain level, habituation is characterized by a decrease in neural activity as a stimulation is repeated, referred to as neural adaptation. This phenomenon influences the ability to make predictions and to detect change, two processes altered in some neurodevelopmental and psychiatric disorders. In this comprehensive review, the objectives are to characterize habituation, neural adaptation, and prediction throughout typical development and in neurodevelopmental disorders; and to evaluate their implication in symptomatology, specifically in sensitivity to change or need for sameness. A summary of the different approaches to investigate adaptation will be proposed, in which we report the contribution of animal studies as well as electrophysiological studies in humans to understanding of underlying neuronal mechanisms.

Barriers and solutions to the adoption of translational tools for computational psychiatry

Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. There has been significant progress in the development of tasks and how to model them, presenting an opportunity to incorporate computational psychiatry methodologies into large- scale research projects or into clinical practice. In this viewpoint, we explore some of the barriers to incorporation of computational psychiatry tasks and models into wider mainstream research directions. These barriers include the time required for participants to complete tasks, test-retest reliability, limited ecological validity, as well as practical concerns, such as lack of computational expertise and the expense and large sample sizes traditionally required to validate tasks and models. We then discuss solutions, such as the redesigning of tasks with a view toward feasibility, and the integration of tasks into more ecologically valid and standardized game platforms that can be more easily disseminated. Finally, we provide an example of how one task, the conditioned hallucinations task, might be translated into such a game. It is our hope that interest in the creation of more accessible and feasible computational tasks will help computational methods make more positive impacts on research as well as, eventually, clinical practice.

Candidate biomarkers in psychiatric disorders: state of the field

The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.

Predictive encoding of pure tones and FM-sweeps in the human auditory cortex

Expectations substantially influence perception, but the neural mechanisms underlying this influence are not fully understood. A prominent view is that sensory neurons encode prediction error with respect to expectations on upcoming sensory input. Although the encoding of prediction error has been previously demonstrated in the human auditory cortex (AC), previous studies often induced expectations using stimulus repetition, potentially confounding prediction error with neural habituation. These studies also measured AC as a single population, failing to consider possible predictive specializations of different AC fields. Moreover, the few studies that considered prediction error to stimuli other than pure tones yielded conflicting results. Here, we used functional magnetic resonance imaging (fMRI) to systematically investigate prediction error to subjective expectations in auditory cortical fields Te1.0, Te1.1, Te1.2, and Te3, and two types of stimuli: pure tones and frequency modulated (FM) sweeps. Our results show that prediction error is elicited with respect to the participants' expectations independently of stimulus repetition and similarly expressed across auditory fields. Moreover, despite the radically different strategies underlying the decoding of pure tones and FM-sweeps, both stimulus modalities were encoded as prediction error in most fields of AC. Altogether, our results provide unequivocal evidence that predictive coding is the general encoding mechanism in AC.

Mismatch Negativity in Response to Auditory Deviance and Risk for Future Psychosis in Youth at Clinical High Risk for Psychosis

Importance

Although clinical criteria for identifying youth at risk for psychosis have been validated, they are not sufficiently accurate for predicting outcomes to inform major treatment decisions. The identification of biomarkers may improve outcome prediction among individuals at clinical high risk for psychosis (CHR-P).

Objective

To examine whether mismatch negativity (MMN) event-related potential amplitude, which is deficient in schizophrenia, is reduced in young people with the CHR-P syndrome and associated with outcomes, accounting for effects of antipsychotic medication use.

Design, Setting, and Participants

MMN data were collected as part of the multisite case-control North American Prodrome Longitudinal Study (NAPLS-2) from 8 university-based outpatient research programs. Baseline MMN data were collected from June 2009 through April 2013. Clinical outcomes were assessed throughout 24 months. Participants were individuals with the CHR-P syndrome and healthy controls with MMN data. Participants with the CHR-P syndrome who developed psychosis (ie, converters) were compared with those who did not develop psychosis (ie, nonconverters) who were followed up for 24 months. Analysis took place between December 2019 and December 2021.

Main Outcomes and Measures

Electroencephalography was recorded during a passive auditory oddball paradigm. MMN elicited by duration-, pitch-, and duration + pitch double-deviant tones was measured.

Results

The CHR-P group (n = 580; mean [SD] age, 19.24 [4.39] years) included 247 female individuals (42.6%) and the healthy control group (n = 241; mean age, 20.33 [4.74] years) included 114 female individuals (47.3%). In the CHR-P group, 450 (77.6%) were not taking antipsychotic medication at baseline. Baseline MMN amplitudes, irrespective of deviant type, were deficient in future CHR-P converters to psychosis (n = 77, unmedicated n = 54) compared with nonconverters (n = 238, unmedicated n = 190) in both the full sample (d = 0.27) and the unmedicated subsample (d = 0.33). In the full sample, baseline medication status interacted with group and deviant type indicating that double-deviant MMN, compared with single deviants, was reduced in unmedicated converters compared with nonconverters (d = 0.43). Further, within the unmedicated subsample, deficits in double-deviant MMN were most strongly associated with earlier conversion to psychosis (hazard ratio, 1.40 [95% CI, 1.03-1.90]; P = .03], which persisted over and above positive symptom severity.

Conclusions and Relevance

This study found that MMN amplitude deficits were sensitive to future psychosis conversion among individuals at risk of CHR-P, particularly those not taking antipsychotic medication at baseline, although associations were modest. While MMN shows limited promise as a biomarker of psychosis onset on its own, it may contribute novel risk information to multivariate prediction algorithms and serve as a translational neurophysiological target for novel treatment development in a subgroup of at-risk individuals.

Deficits in Pre-attentive Processing of Spatial Location and Negative Symptoms in Subjects at Clinical High Risk for Schizophrenia

Deficits in mismatch negativity (MMN) generation are among the best-established biomarkers for cognitive dysfunction in schizophrenia and predict conversion to schizophrenia (Sz) among individuals at symptomatic clinical high risk (CHR). Impairments in MMN index dysfunction at both subcortical and cortical components of the early auditory system. To date, the large majority of studies have been conducted using deviants that differ from preceding standards in either tonal frequency (pitch) or duration. By contrast, MMN to sound location deviation has been studied to only a limited degree in Sz and has not previously been examined in CHR populations. Here, we evaluated location MMN across Sz and CHR using an optimized, multi-deviant pattern that included a location-deviant, as defined using interaural time delay (ITD) stimuli along with pitch, duration, frequency modulation (FM) and intensity deviants in a sample of 42 Sz, 33 CHR and 28 healthy control (HC) subjects. In addition, we obtained resting state functional connectivity (rsfMRI) on CHR subjects. Sz showed impaired MMN performance across all deviant types, along with strong correlation between MMN deficits and impaired neurocognitive function. In this sample of largely non-converting CHR subjects, no deficits were observed in either pitch or duration MMN. By contrast, CHR subjects showed significant impairments in location MMN generation particularly over right hemisphere and significant correlation between impaired location MMN and negative symptoms including deterioration of role function. In addition, significant correlations were observed between location MMN and rsfMRI involving brainstem circuits. In general, location detection using ITD stimuli depends upon precise processing within midbrain regions and provides a rapid and robust reorientation of attention. Present findings reinforce the utility of MMN as a pre-attentive index of auditory cognitive dysfunction in Sz and suggest that location MMN may index brain circuits distinct from those indexed by other deviant types.

Computational Mechanism for the Effect of Psychosis Community Treatment: A Conceptual Review From Neurobiology to Social Interaction

The computational underpinnings of positive psychotic symptoms have recently received significant attention. Candidate mechanisms include some combination of maladaptive priors and reduced updating of these priors during perception. A potential benefit of models with such mechanisms is their ability to link multiple levels of explanation, from the neurobiological to the social, allowing us to provide an information processing-based account of how specific alterations in self-self and self-environment interactions result in the experience of positive symptoms. This is key to improving how we understand the experience of psychosis. Moreover, it points us toward more comprehensive avenues for therapeutic research by providing a putative mechanism that could allow for the generation of new treatments from first principles. In order to demonstrate this, our conceptual paper will discuss the application of the insights from previous computational models to an important and complex set of evidence-based clinical interventions with strong social elements, such as coordinated specialty care clinics (CSC) in early psychosis and assertive community treatment (ACT). These interventions may include but also go beyond psychopharmacology, providing, we argue, structure and predictability for patients experiencing psychosis. We develop the argument that this structure and predictability directly counteract the relatively low precision afforded to sensory information in psychosis, while also providing the patient more access to external cognitive resources in the form of providers and the structure of the programs themselves. We discuss how computational models explain the resulting reduction in symptoms, as well as the predictions these models make about potential responses of patients to modifications or to different variations of these interventions. We also link, via the framework of computational models, the patient's experiences and response to interventions to putative neurobiology.

Reliability of mismatch negativity event-related potentials in a multisite, traveling subjects study

OBJECTIVE

To determine the optimal methods for measuring mismatch negativity (MMN), an auditory event-related potential (ERP), and quantify sources of MMN variance in a multisite setting.

METHODS

Reliability of frequency, duration, and double (frequency + duration) MMN was determined from eight traveling subjects, tested on two occasions at eight laboratory sites. Deviant-specific variance components were estimated for MMN peak amplitude and latency measures using different ERP processing methods. Generalizability (G) coefficients were calculated using two-facet (site and occasion), fully-crossed models and single-facet (occasion) models within each laboratory to assess MMN reliability.

RESULTS

G-coefficients calculated from two-facet models indicated fair (0.4 < G<=0.6) duration MMN reliability at electrode Fz, but poor (G < 0.4) double and frequency MMN reliability. Single-facet G-coefficients averaged across laboratory resulted in improved reliability (G > 0.5). MMN amplitude reliability was greater than latency reliability, and reliability with mastoid referencing significantly outperformed nose-referencing.

CONCLUSIONS

EEG preprocessing methods have an impact on the reliability of MMN amplitude. Within site MMN reliability can be excellent, consistent with prior single site studies.

SIGNIFICANCE

With standardized data collection and ERP processing, MMN can be reliably obtained in multisite studies, providing larger samples sizeswithin rare patient groups.