Different learning aberrations relate to delusion-like beliefs with different contents.

The prediction error account of delusions has had success. However, its explanation of delusions with different contents has been lacking. Persecutory delusions and paranoia are the common unfounded beliefs that others have harmful intentions towards us. Other delusions include believing that one's thoughts or actions are under external control or that events in the world have specific personal meaning. We compare learning in two different cognitive tasks, probabilistic reversal learning and Kamin blocking, that have relationships to paranoid and non-paranoid delusion-like beliefs, respectively. We find that clinical high-risk status alone does not result in different behavioural results in the probabilistic reversal learning task but that an individual's level of paranoia is associated with excessive switching behaviour. During the Kamin blocking task, paranoid individuals learned inappropriately about the blocked cue. However, they also had decreased learning about the control cue, suggesting more general learning impairments. Non-paranoid delusion-like belief conviction (but not paranoia) was associated with aberrant learning about the blocked cue but intact learning about the control cue, suggesting specific impairments in learning related to cue combination. We fit task-specific computational models separately to behavioural data to explore how latent parameters vary within individuals between tasks and how they can explain symptom-specific effects. We find that paranoia is associated with low learning rates in the probabilistic reversal learning task and the blocking task. Non-paranoid delusion-like belief conviction is instead related to parameters controlling the degree and direction of similarity between cue updating during simultaneous cue presentation. These results suggest that paranoia and other delusion-like beliefs involve dissociable deficits in learning and belief updating, which, given the transdiagnostic status of paranoia, might have differential utility in predicting psychosis.

Randomized controlled trial of the glycine transporter 1 inhibitor PF-03463275 to enhance cognitive training and neuroplasticity in schizophrenia.

N-methyl-d-aspartate glutamate receptor (NMDAR) hypofunction is implicated in the impaired neuroplasticity and cognitive impairments associated with schizophrenia (CIAS). We hypothesized that enhancing NMDAR function by inhibiting the glycine transporter-1 (GLYT1) would improve neuroplasticity and thereby augment benefits of non-pharmacological cognitive training (CT) strategies. This study examined whether co-administration of a GLYT1 inhibitor and computerized CT would have synergistic effects on CIAS. Stable outpatients with schizophrenia participated in this double-blind, placebo-controlled, within-subject, crossover augmentation study. Participants received placebo or GLYT1 inhibitor (PF-03463275) for two 5-week periods separated by 2 weeks of washout. PF-03463275 doses (40 or 60 mg twice daily) were selected to produce high GLYT1 occupancy. To limit pharmacodynamic variability, only cytochrome P450 2D6 extensive metabolizers were included. Medication adherence was confirmed daily. Participants received 4 weeks of CT in each treatment period. Cognitive performance (MATRICS Consensus Cognitive Battery) and psychotic symptoms (Positive and Negative Syndrome Scale) were assessed in each period. 71 participants were randomized. PF-03463275 in combination with CT was feasible, safe, and well-tolerated at the doses prescribed but did not produce greater improvement in CIAS compared to CT alone. PF-03463275 was not associated with improved CT learning parameters. Participation in CT was associated with improvement in MCCB scores.

Relating Glutamate, Conditioned, and Clinical Hallucinations via 1H-MR Spectroscopy.

BACKGROUND AND HYPOTHESIS: Hallucinations may be driven by an excessive influence of prior expectations on current experience. Initial work has supported that contention and implicated the anterior insula in the weighting of prior beliefs. STUDY DESIGN: Here we induce hallucinated tones by associating tones with the presentation of a visual cue. We find that people with schizophrenia who hear voices are more prone to the effect and using computational modeling we show they overweight their prior beliefs. In the same participants, we also measured glutamate levels in anterior insula, anterior cingulate, dorsolateral prefrontal, and auditory cortices, using magnetic resonance spectroscopy. STUDY RESULTS: We found a negative relationship between prior-overweighting and glutamate levels in the insula that was not present for any of the other voxels or parameters. CONCLUSIONS: Through computational psychiatry, we bridge a pathophysiological theory of psychosis (glutamate hypofunction) with a cognitive model of hallucinations (prior-overweighting) with implications for the development of new treatments for hallucinations.

Computerized Assessment of Psychosis Risk.

Early detection and intervention with young people at clinical high risk (CHR) for psychosis is critical for prevention efforts focused on altering the trajectory of psychosis. Early CHR research largely focused on validating clinical interviews for detecting at-risk individuals; however, this approach has limitations related to: (1) specificity (i.e., only 20% of CHR individuals convert to psychosis) and (2) the expertise and training needed to administer these interviews is limited. The purpose of our study is to develop the computerized assessment of psychosis risk (CAPR) battery, consisting of behavioral tasks that require minimal training to administer, can be administered online, and are tied to the neurobiological systems and computational mechanisms implicated in psychosis. The aims of our study are as follows: (1A) to develop a psychosis-risk calculator through the application of machine learning (ML) methods to the measures from the CAPR battery, (1B) evaluate group differences on the risk calculator score and test the hypothesis that the risk calculator score of the CHR group will differ from help-seeking and healthy controls, (1C) evaluate how baseline CAPR battery performance relates to symptomatic outcome two years later (i.e., conversion and symptomatic worsening). These aims will be explored in 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across the study sites. This project will provide a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods that can be used to facilitate the earliest possible detection of psychosis risk.

Paranoia and belief updating during the COVID-19 crisis.

The COVID-19 pandemic has made the world seem less predictable. Such crises can lead people to feel that others are a threat. Here, we show that the initial phase of the pandemic in 2020 increased individuals' paranoia and made their belief updating more erratic. A proactive lockdown made people's belief updating less capricious. However, state-mandated mask-wearing increased paranoia and induced more erratic behaviour. This was most evident in states where adherence to mask-wearing rules was poor but where rule following is typically more common. Computational analyses of participant behaviour suggested that people with higher paranoia expected the task to be more unstable. People who were more paranoid endorsed conspiracies about mask-wearing and potential vaccines and the QAnon conspiracy theories. These beliefs were associated with erratic task behaviour and changed priors. Taken together, we found that real-world uncertainty increases paranoia and influences laboratory task behaviour.

Increased face detection responses on the mooney faces test in people at clinical high risk for psychosis.

Identifying state-sensitive measures of perceptual and cognitive processes implicated in psychosis may allow for objective, earlier, and better monitoring of changes in mental status that are predictive of an impending psychotic episode, relative to traditional self-report-based clinical measures. To determine whether a measure of visual perception that has demonstrated sensitivity to the clinical state of schizophrenia in multiple prior studies is sensitive to features of the at-risk mental state, we examined differences between young people identified as being at clinical high risk for psychosis (CHR; n = 37) and non-psychiatric matched controls (n = 29) on the Mooney Faces Test (MFT). On each trial of the MFT, participants report whether they perceive a face in a degraded face image. The CHR group reported perceiving a greater number of faces in both upright and inverted MFT stimuli. Consistent with prior work, males reported more faces on the MFT than females in both conditions. However, the finding of greater reported face perception among CHR subjects was robustly observed in the female CHR group relative to the female control group. Among male CHR participants, greater reported face perception was related to increased perceptual abnormalities. These preliminary results are consistent with a small but growing literature suggesting that heightened perceptual sensitivity may characterize individuals at increased clinical risk for psychosis. Further studies are needed to determine the contributions of specific perceptual, cognitive, and motivational mechanisms to the findings.

Paranoia and belief updating during a crisis.

The 2019 coronavirus (COVID-19) pandemic has made the world seem unpredictable. During such crises we can experience concerns that others might be against us, culminating perhaps in paranoid conspiracy theories. Here, we investigate paranoia and belief updating in an online sample (N=1,010) in the United States of America (U.S.A). We demonstrate the pandemic increased individuals' self-rated paranoia and rendered their task-based belief updating more erratic. Local lockdown and reopening policies, as well as culture more broadly, markedly influenced participants' belief-updating: an early and sustained lockdown rendered people's belief updating less capricious. Masks are clearly an effective public health measure against COVID-19. However, state-mandated mask wearing increased paranoia and induced more erratic behaviour. Remarkably, this was most evident in those states where adherence to mask wearing rules was poor but where rule following is typically more common. This paranoia may explain the lack of compliance with this simple and effective countermeasure. Computational analyses of participant behaviour suggested that people with higher paranoia expected the task to be more unstable, but at the same time predicted more rewards. In a follow-up study we found people who were more paranoid endorsed conspiracies about mask-wearing and potential vaccines - again, mask attitude and conspiratorial beliefs were associated with erratic task behaviour and changed priors. Future public health responses to the pandemic might leverage these observations, mollifying paranoia and increasing adherence by tempering people's expectations of other's behaviour, and the environment more broadly, and reinforcing compliance.

Stability of mismatch negativity event-related potentials in a multisite study.

OBJECTIVES: Mismatch negativity (MMN), an auditory event-related potential sensitive to deviance detection, is smaller in schizophrenia and psychosis risk. In a multisite study, a regression approach to account for effects of site and age (12-35 years) was evaluated alongside the one-year stability of MMN. METHODS: Stability of frequency, duration, and frequency + duration (double) deviant MMN was assessed in 167 healthy subjects, tested on two occasions, separated by 52 weeks, at one of eight sites. Linear regression models predicting MMN with age and site were validated and used to derive standardized MMN z-scores. Variance components estimated for MMN amplitude and latency measures were used to calculate Generalizability (G) coefficients within each site to assess MMN stability. Trait-like aspects of MMN were captured by averaging across occasions and correlated with subject traits. RESULTS: Age and site accounted for less than 7% of MMN variance. G-coefficients calculated at electrode Fz were stable (G = 0.63) across deviants and sites for amplitude measured in a fixed window, but not for latency (G = 0.37). Frequency deviant MMN z-scores averaged across tests negatively correlated with averaged global assessment of functioning. CONCLUSION: MMN amplitude is stable and can be standardized to facilitate longitudinal multisite studies of patients and clinical features.

One-Month Stability of Cyberball Post-Exclusion Ostracism Distress in Adolescents.

We examined one-month reliability, internal consistency, and validity of ostracism distress (Need Threat Scale) to simulated social exclusion during Cyberball. Thirty adolescents (13-18 yrs.) completed the Cyberball task, ostracism distress ratings, and measures of related clinical symptoms, repeated over one month. Need Threat Scale ratings of ostracism distress showed adequate test-retest reliability and internal consistency at both occasions. Construct validity was demonstrated via relationships with closely related constructs of anxiety, anxiety sensitivity, and emotion dysregulation, and weaker associations with more distal constructs of state paranoia and subclinical psychosis-like experiences. While ratings of ostracism distress and anxiety were significantly attenuated at retest, most participants continued to experience post-Cyberball ostracism distress at one-month follow-up, which indicates that the social exclusion induction of Cyberball persisted despite participants' familiarity with the paradigm. Overall, results suggest that the primary construct of ostracism distress is preserved over repeated administration of Cyberball, with reliability sufficient for usage in longitudinal research. These findings have important implications for translating this laboratory simulation of social distress into developmental and clinical intervention studies.

A translational approach for NMDA receptor profiling as a vulnerability biomarker for depression and schizophrenia.

NEW FINDINGS: What is the central question of this study? Can the change in plasma arginine vasopressin concentration (P[AVP] ) in response to osmotic stimulation (POsm ) serve as a biomarker for NMDA receptor signalling in schizophrenia and depression and thereby distinguish between these mental illnesses? What is the main finding and its importance? In response to hyperosmotic challenge, depressed subjects showed increased P[AVP] response compared with healthy control and schizophrenic subjects. However, schizophrenic subjects were not different from healthy control subjects in this small sample. The 'P[AVP] response to POsm ' is a suitable biomarker to distinguish depressed versus schizophrenic patients when used with psychiatric screening. This is the first objective physiological measure for schizophrenia or depression. Altered NMDA receptor activity and glutamate signalling might underlie the pathogenesis of both schizophrenia and depression in subgroups of patients. In schizophrenia, pharmacological modelling, post-mortem and imaging data suggest reduced NMDA signalling. In contrast, recent clinical trials demonstrating the efficacy of the NMDA antagonist ketamine in severely depressed patients suggest increased NMDA receptor signalling. We conducted a proof-of-concept study to assess whether there is any in vivo evidence for an inverse association in depression and schizophrenia with respect to the NMDA receptor function. For this purpose, we used a translational approach, based on findings from animal studies that NMDA receptor is a key mediator of arginine vasopressin (AVP) release into the bloodstream. Using hypertonic saline to increase plasma osmolality (POsm ) and thereby induce AVP release, as done in animal studies, we found that in depressed patients the NMDA receptor-mediated AVP release induced by hypertonic saline infusion was significantly increased [0.24 (0.15) pg ml-1  mosmol-1 , P < 0.05] compared with schizophrenia patients [0.07 (0.07) pg ml-1  mosmol-1 ]. Slopes for healthy control subjects were 0.11 (0.09) pg ml-1  mosmol-1 which was less than the depressed group. These findings are consistent with implicated NMDA receptor-related abnormalities in depression and schizophrenia in subgroups of patients and provide the first in vivo evidence of this dichotomy.

Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults.

BACKGROUND: With millisecond-level resolution, electroencephalographic (EEG) recording provides a sensitive tool to assay neural dynamics of human cognition. However, selection of EEG features used to answer experimental questions is typically determined a priori. The utility of machine learning was investigated as a computational framework for extracting the most relevant features from EEG data empirically. METHODS: Schizophrenia (SZ; n = 40) and healthy community (HC; n = 12) subjects completed a Sternberg Working Memory Task (SWMT) during EEG recording. EEG was analyzed to extract 5 frequency components (theta1, theta2, alpha, beta, gamma) at 4 processing stages (baseline, encoding, retention, retrieval) and 3 scalp sites (frontal-Fz, central-Cz, occipital-Oz) separately for correctly and incorrectly answered trials. The 1-norm support vector machine (SVM) method was used to build EEG classifiers of SWMT trial accuracy (correct vs. incorrect; Model 1) and diagnosis (HC vs. SZ; Model 2). External validity of SVM models was examined in relation to neuropsychological test performance and diagnostic classification using conventional regression-based analyses. RESULTS: SWMT performance was significantly reduced in SZ (p < .001). Model 1 correctly classified trial accuracy at 84 % in HC, and at 74 % when cross-validated in SZ data. Frontal gamma at encoding and central theta at retention provided highest weightings, accounting for 76 % of variance in SWMT scores and 42 % variance in neuropsychological test performance across samples. Model 2 identified frontal theta at baseline and frontal alpha during retrieval as primary classifiers of diagnosis, providing 87 % classification accuracy as a discriminant function. CONCLUSIONS: EEG features derived by SVM are consistent with literature reports of gamma's role in memory encoding, engagement of theta during memory retention, and elevated resting low-frequency activity in schizophrenia. Tests of model performance and cross-validation support the stability and generalizability of results, and utility of SVM as an analytic approach for EEG feature selection.