Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

BACKGROUND: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of what causes delay/refusal of SARS-CoV-2 vaccination and limited ability to predict who will remain unvaccinated over significant time periods despite vaccine availability. The present study begins to address these barriers by developing a machine learning model that prospectively predicts who will persist in not vaccinating against SARS-CoV-2. METHOD: Unvaccinated individuals (n = 325) who completed a baseline survey were followed over the six-month period when vaccines against SARS-CoV-2 were first widely available (April-October 2021). A random forest model was used to predict who would remain unvaccinated against SARS-CoV-2 from their baseline measures, including demographic information (e.g., age), medical history (e.g., of influenza vaccination), Health-Belief Model constructs (e.g., perceived vaccine dangerousness), conspiracist ideation, and task-based metrics of vulnerability to conspiracist ideation (e.g., tendency toward illusory pattern perception). RESULTS: The resulting model significantly predicted vaccination status (AUC-PR = 0.77, 95%CI [0.56 0.90]). At the optimal probability threshold determined by the Generalized Threshold Shifting Protocol, the model was moderately precise (0.83) when identifying individuals who remained unvaccinated (n = 80), and had a very low rate (0.04) of false-positives (incorrectly suggesting that individuals remained unvaccinated). Permutational importance tests suggested that baseline SARS-CoV-2 vaccine intentions conveyed the most information about future SARS-CoV-2 vaccination status. Conspiracist ideation was the second most informative predictor, suggesting that misinformation influences vaccination behavior. Other important predictors included perceived vaccine dangerousness, as expected under the Health Belief Model, and influenza vaccination history. CONCLUSIONS: The model we developed can accurately and prospectively identify individuals who remain unvaccinated against SARS-CoV-2. It could therefore facilitate empirically-informed allocation of interventions that encourage vaccine uptake. The predictive value of conspiracist ideation, perceived vaccine dangerousness, and vaccine intentions in our model is consistent with potential causal relations between these variables and SARS-CoV-2 vaccine uptake.

Generalized Slowing of Resting State Neural Oscillations in People with Schizophrenia.

BACKGROUND: Recent interest in how neural oscillations reflect the flow of information through the brain has led to partitioning electroencephalography (EEG) recordings into periodic (i.e., oscillatory) and aperiodic (i.e., non-oscillatory) components. While both contribute to conventional measures of power within the frequencies that compose EEG recordings, the periodic aspect characterizes true oscillations - the speed of which is thought to be critical to efficient functioning of neural systems. Given evidence of EEG power abnormalities in schizophrenia, we sought to determine if the periodic aspect of EEG was aberrant in people with schizophrenia (SCZ) and could serve as a general measure of brain efficiency. METHODS: Resting state EEGs were gathered from 104 SCZ and 105 healthy control participants. We used the fitting-oscillations-and-one-over-f (FOOOF) toolbox to remove aperiodic neural activity. We computed the cross-correlation between power spectra for individual participants and the mean power spectrum for all participants to quantify the relative speed of neural oscillations. RESULTS: Periodic activity in SCZ was shifted toward lower frequencies compared to control participants during eyes closed rest. On average SCZ had a 0.55 Hz shift toward oscillatory slowing across the frequency spectrum which predicted worse perceptual reasoning. Slower neural oscillations were associated with weaker perceptual reasoning within SCZ. CONCLUSIONS: Slowed periodic activity at rest is evident in schizophrenia and may represent inefficient functioning of neural circuits as reflected in worse perceptual reasoning. A slower pace of neural oscillations may be a general limitation on the transmission of information within the brain.

Adjustment of Regional Cortical Thickness Measures for Global Cortical Thickness Obscures Deficits Across the Schizophrenia Spectrum: A Cautionary Note About Normative Modeling of Brain Imaging Data.

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Personalized Cognitive Health in Psychiatry: Current State and the Promise of Computational Methods.

BACKGROUND: Decades of research have firmly established that cognitive health and cognitive treatment services are a key need for people living with psychosis. However, many current clinical programs do not address this need, despite the essential role that an individual's cognitive and social cognitive capacities play in determining their real-world functioning. Preliminary practice-based research in the Early Psychosis Intervention Network early psychosis intervention network shows that it is possible to develop and implement tools that delineate an individuals' cognitive health profile and that help engage the client and the clinician in shared decision-making and treatment planning that includes cognitive treatments. These findings signify a promising shift toward personalized cognitive health. STUDY DESIGN: Extending upon this early progress, we review the concept of interindividual variability in cognitive domains/processes in psychosis as the basis for offering personalized treatment plans. We present evidence from studies that have used traditional neuropsychological measures as well as findings from emerging computational studies that leverage trial-by-trial behavior data to illuminate the different latent strategies that individuals employ. STUDY RESULT: We posit that these computational techniques, when combined with traditional cognitive assessments, can enrich our understanding of individual differences in treatment needs, which in turn can guide evermore personalized interventions. CONCLUSION: As we find clinically relevant ways to decompose maladaptive behaviors into separate latent cognitive elements captured by model parameters, the ultimate goal is to develop and implement approaches that empower clients and their clinical providers to leverage individual's existing learning capacities to improve their cognitive health and well-being.

Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis.

BACKGROUND AND HYPOTHESIS: Brain development/aging is not uniform across individuals, spawning efforts to characterize brain age from a biological perspective to model the effects of disease and maladaptive life processes on the brain. The brain age gap represents the discrepancy between estimated brain biological age and chronological age (in this case, based on structural magnetic resonance imaging, MRI). Structural MRI studies report an increased brain age gap (biological age > chronological age) in schizophrenia, with a greater brain age gap related to greater negative symptom severity. Less is known regarding the nature of this gap early in schizophrenia (ESZ), if this gap represents a psychosis conversion biomarker in clinical high-risk (CHR-P) individuals, and how altered brain development and/or aging map onto specific symptom facets. STUDY DESIGN: Using structural MRI, we compared the brain age gap among CHR-P (n = 51), ESZ (n = 78), and unaffected comparison participants (UCP; n = 90), and examined associations with CHR-P psychosis conversion (CHR-P converters n = 10; CHR-P non-converters; n = 23) and positive and negative symptoms. STUDY RESULTS: ESZ showed a greater brain age gap relative to UCP and CHR-P (Ps < .010). CHR-P individuals who converted to psychosis showed a greater brain age gap (P = .043) relative to CHR-P non-converters. A larger brain age gap in ESZ was associated with increased experiential (P = .008), but not expressive negative symptom severity. CONCLUSIONS: Consistent with schizophrenia pathophysiological models positing abnormal brain maturation, results suggest abnormal brain development is present early in psychosis. An increased brain age gap may be especially relevant to motivational and functional deficits in schizophrenia.

Putting measurement-based care into action: A mixed methods study of the benefits of integrating routine client feedback in coordinated specialty care programs for early psychosis.

Background: Measurement-based care (MBC) is an effective tool in the delivery of evidence-based practices (EBPs). MBC utilizes feedback loops to share information and drive changes throughout a learning healthcare system. Few studies have demonstrated this practice in team-based care for people with early psychosis. This paper describes the development of a personalized feedback report derived from routine assessments that is shared with clients and clinicians as part of a MBC process. Methods: We used a quasi pre-post comparison design with mixed methods to evaluate the implementation of a personalized feedback report at 5 early psychosis coordinated specialty care programs (CSC). We compared clients enrolled in CSC who did and did not receive a feedback report over the first 6 months of treatment. The sample included 204 clients: 146 who did not receive the feedback report and were enrolled over 2 years, and 58 who received the feedback report. A subset of 67 clients completed measures at both intake and 6-month follow-up, including 42 who received the report and 25 who did not. We compared the two groups with regard to self-reported symptoms, likelihood of completing treatment, and perception of shared decision making. We conducted qualitative interviews with 5 clients and 5 clinicians to identify the benefits and challenges associated with the personalized feedback report. Results: People who received a personalized feedback report reported significant improvements in shared decision-making and had greater improvements over time in their intent to attend future treatment sessions. They engaged in more sessions for Supported Employment and Education (SEE), case management, and peer support, and fewer medication visits over the first 6 months of treatment. Both groups showed significant improvement in symptoms and functioning. Results from the qualitative analysis indicated that the experience of receiving the reports was valuable and validating for both patients and clinicians. Conclusions: A personalized feedback report was integrated into standard of care for early psychosis programs. This process may improve shared decision-making, strengthen the likelihood to stay in treatment, and increase engagement in psychosocial interventions. We posit that this process facilitates strengths-focused discussions, enhances intrinsic motivation, and strengthens the therapeutic alliance.

Trajectories and predictors of response to social cognition training in people with schizophrenia: A proof-of-concept machine learning study.

BACKGROUND: Social cognition training (SCT) can improve social cognition deficits in schizophrenia. However, little is known about patterns of response to SCT or individual characteristics that predict response. METHODS: 76 adults with schizophrenia randomized to receive 8-12 weeks of remotely-delivered SCT were included in this analysis. Social cognition was measured with a composite of six assessments. Latent class growth analyses identified trajectories of social cognitive response to SCT. Random forest and logistic regression models were trained to predict membership in the trajectory group that showed improvement from baseline measures including symptoms, functioning, motivation, and cognition. RESULTS: Five trajectory groups were identified: Group 1 (29 %) began with slightly above average social cognition, and this ability significantly improved with SCT. Group 2 (9 %) had baseline social cognition approximately one standard deviation above the sample mean and did not improve with training. Groups 3 (18 %) and 4 (36 %) began with average to slightly below-average social cognition and showed non-significant trends toward improvement. Group 5 (8 %) began with social cognition approximately one standard deviation below the sample mean, and experienced significant deterioration in social cognition. The random forest model had the best performance, predicting Group 1 membership with an area under the curve of 0.73 (SD 0.24; 95 % CI [0.51-0.87]). CONCLUSIONS: Findings suggest that there are distinct patterns of response to SCT in schizophrenia and that those with slightly above average social cognition at baseline may be most likely to experience gains. Results may inform future research seeking to individualize SCT treatment for schizophrenia.

The Effects of Remote Cognitive Training Combined With a Mobile App Intervention on Psychosis: Double-Blind Randomized Controlled Trial.

BACKGROUND: Impairments in cognition and motivation are core features of psychosis and strong predictors of social and occupational functioning. Accumulating evidence indicates that cognitive deficits in psychosis can be improved by computer-based cognitive training programs; however, barriers include access and adherence to cognitive training exercises. Limited evidence-based methods have been established to enhance motivated behavior. In this study, we tested the effects of web-based targeted cognitive and social cognitive training (TCT) delivered in conjunction with an innovative digital smartphone app called Personalized Real-Time Intervention for Motivational Enhancement (PRIME). The PRIME app provides users with a motivational coach to set personalized goals and secure social networking for peer support. OBJECTIVE: This study investigated whether deficits in cognition and motivation in people with a psychosis spectrum disorder (N=100) can be successfully addressed with 30 hours of TCT+PRIME as compared with 30 hours of a computer games control condition (CG) plus PRIME (CG+PRIME). Here, we describe our study procedures, the feasibility and acceptability of the intervention, and the results on all primary outcomes. METHODS: In this double-blind randomized controlled trial, English-speaking participants completed all cognitive training, PRIME activities, and assessments remotely. Participants completed a diagnostic interview and remote cognitive, clinical, and self-report measures at baseline, posttraining, and at a 6-month follow-up. RESULTS: This study included participants from 27 states across the United States and 8 countries worldwide. The study population was 58% (58/100) female, with a mean age of 33.77 (SD 10.70) years. On average, participants completed more than half of the cognitive training regimen (mean 18.58, SD 12.47 hours of training), and logged into the PRIME app 4.71 (SD 1.58) times per week. The attrition rate of 22% (22/100) was lower than that reported in our previous studies on remote cognitive training. The total sample showed significant gains in global cognition (P=.03) and attention (P<.001). The TCT+PRIME participants showed significantly greater gains in emotion recognition (P<.001) and global cognition at the trend level (P=.09), although this was not statistically significant, relative to the CG+PRIME participants. The total sample also showed significant improvements on multiple indices of motivation (P=.02-0.05), in depression (P=.04), in positive symptoms (P=.04), and in negative symptoms at a trend level (P=.09), although this was not statistically significant. Satisfaction with the PRIME app was rated at 7.74 (SD 2.05) on a scale of 1 to 10, with higher values indicating more satisfaction. CONCLUSIONS: These results demonstrate the feasibility and acceptability of remote cognitive training combined with the PRIME app and that this intervention can improve cognition, motivation, and symptoms in individuals with psychosis. TCT+PRIME appeared more effective in improving emotion recognition and global cognition than CG+PRIME. Future analyses will test the relationship between hours of cognitive training completed; PRIME use; and changes in cognition, motivation, symptoms, and functioning. TRIAL REGISTRATION: ClinicalTrials.gov NCT02782442; https://clinicaltrials.gov/study/NCT02782442.

Harnessing neuroplasticity.

Twenty years ago, cognitive impairments were recognized as an unmet treatment need in schizophrenia. Basic science discoveries in neuroplasticity had led to cognitive training approaches for dyslexia. We wondered whether a similar approach could target working memory deficits in schizophrenia by harnessing plasticity in the auditory cortex. Our per protocol experimental therapeutics studies tested the hypothesis that sharpening auditory cortical representations would result in better verbal learning and memory. We also later studied the effects of intensive training of basic social cognitive operations. Our training protocols were deliberately focused, effortful and intensive, since participants were often up against decades of cortical dysplasticity. In studies in different stages of illness, we demonstrated that neuroscience-informed cognitive training was associated with: (1) proximal psychophysical as well as distal cognitive improvements; (2) increases in serum BDNF levels; (3) negative effects of serum anticholinergic burden; (4) electrophysiologic responses and brain activation patterns consistent with restorative neuroplastic changes in cortex; (5) positive cortical and thalamic volumetric changes suggestive of neuroprotection; (6) better 6-month clinical functioning in those with a positive initial response. Taken together, this work indicates how much the field of psychiatry could benefit from a deep understanding of the basic science of cortical neuroplasticity processes and of how they can be deliberately and efficiently harnessed for therapeutic purposes.

Social interpretation inflexibility moderates emotional reactions to social situations in children and adolescents.

Interpretation biases and inflexibility (i.e., difficulties revising interpretations) have been linked to increased internalizing symptoms. Although adolescence is a developmental period characterized by novel social situations and increased vulnerability to internalizing disorders, no studies have examined interpretation inflexibility in adolescents. Additionally, no studies (on adolescents or adults) have examined interpretation flexibility as a protective factor against adverse outcomes of interpersonal events. Using a novel task and a 28-day diary we examined relations among interpretation bias and inflexibility, internalizing symptoms, and negative interpersonal events in a sample of children and adolescents (N = 159, ages 9-18). At baseline, negative interpretation bias was positively correlated with social anxiety symptoms, and positive interpretation bias negatively correlated with social anxiety and depressive symptoms. Inflexible positive interpretations were correlated with higher social anxiety and depressive symptoms, while inflexible negative interpretations were correlated with higher social anxiety. Finally, interpretation inflexibility moderated daily associations between negative interpersonal events and depressive symptoms in daily life, such that higher inflexibility was associated with stronger associations between interpersonal events and subsequent depressive symptoms, potentially increasing depressive symptom instability. These results suggest that interpretation biases and inflexibility may act as both risk and protective factors for adolescent anxiety and depression.

Causal pathways to social and occupational functioning in the first episode of schizophrenia: uncovering unmet treatment needs.

BACKGROUND: We aimed to identify unmet treatment needs for improving social and occupational functioning in early schizophrenia using a data-driven causal discovery analysis. METHODS: Demographic, clinical, and psychosocial measures were obtained for 276 participants from the Recovery After an Initial Schizophrenia Episode Early Treatment Program (RAISE-ETP) trial at baseline and 6-months, along with measures of social and occupational functioning from the Quality of Life Scale. The Greedy Fast Causal Inference algorithm was used to learn a partial ancestral graph modeling causal relationships across baseline variables and 6-month functioning. Effect sizes were estimated using a structural equation model. Results were validated in an independent dataset (N = 187). RESULTS: In the data-generated model, greater baseline socio-affective capacity was a cause of greater baseline motivation [Effect size (ES) = 0.77], and motivation was a cause of greater baseline social and occupational functioning (ES = 1.5 and 0.96, respectively), which in turn were causes of their own 6-month outcomes. Six-month motivation was also identified as a cause of occupational functioning (ES = 0.92). Cognitive impairment and duration of untreated psychosis were not direct causes of functioning at either timepoint. The graph for the validation dataset was less determinate, but otherwise supported the findings. CONCLUSIONS: In our data-generated model, baseline socio-affective capacity and motivation are the most direct causes of occupational and social functioning 6 months after entering treatment in early schizophrenia. These findings indicate that socio-affective abilities and motivation are specific high-impact treatment needs that must be addressed in order to promote optimal social and occupational recovery.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia.

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

Rich-club connectivity and structural connectome organization in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia.

Brain dysconnectivity has been posited as a biological marker of schizophrenia. Emerging schizophrenia connectome research has focused on rich-club organization, a tendency for brain hubs to be highly-interconnected but disproportionately vulnerable to dysconnectivity. However, less is known about rich-club organization in individuals at clinical high-risk for psychosis (CHR-P) and how it compares with abnormalities early in schizophrenia (ESZ). Combining diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), we examined rich-club and global network organization in CHR-P (n = 41) and ESZ (n = 70) relative to healthy controls (HC; n = 74) after accounting for normal aging. To characterize rich-club regions, we examined rich-club MRI morphometry (thickness, surface area). We also examined connectome metric associations with symptom severity, antipsychotic dosage, and in CHR-P specifically, transition to a full-blown psychotic disorder. ESZ had fewer connections among rich-club regions (ps < .024) relative to HC and CHR-P, with this reduction specific to the rich-club even after accounting for other connections in ESZ relative to HC (ps < .048). There was also cortical thinning of rich-club regions in ESZ (ps < .013). In contrast, there was no strong evidence of global network organization differences among the three groups. Although connectome abnormalities were not present in CHR-P overall, CHR-P converters to psychosis (n = 9) had fewer connections among rich-club regions (ps < .037) and greater modularity (ps < .037) compared to CHR-P non-converters (n = 19). Lastly, symptom severity and antipsychotic dosage were not significantly associated with connectome metrics (ps < .012). Findings suggest that rich-club and connectome organization abnormalities are present early in schizophrenia and in CHR-P individuals who subsequently transition to psychosis.

Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity.

Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.

Auditory discrimination and frequency modulation learning in schizophrenia patients: amphetamine within-subject dose response and time course.

BACKGROUND: Auditory frequency modulation learning ('auditory learning') is a key component of targeted cognitive training (TCT) for schizophrenia. TCT can be effective in enhancing neurocognition and function in schizophrenia, but such gains require significant time and effort and elude many patients. METHODS: As a strategy to increase and/or accelerate TCT-induced clinical gains, we tested the dose- and time-course effects of the pro-attentional drug, amphetamine (AMPH; placebo, 2.5, 5 or 10 mg po; within-subject double-blind, order balanced) on auditory learning in schizophrenia patients [n = 32; M:F = 19:13; age 42.0 years (24-55)]. To understand predictors and/or mechanisms of AMPH-enhanced TCT, we also measured auditory fidelity (words-in-noise (WIN), quick speech-in-noise (QuickSIN)) and neurocognition (MATRICS comprehensive cognitive battery (MCCB)). Some measures were also acquired from age-matched healthy subjects (drug free; n = 10; M:F = 5:5). RESULTS: Patients exhibited expected deficits in neurocognition. WIN and QuickSIN performance at low signal intensities was impaired in patients with low v. high MCCB attention/vigilance (A/V) scores; these deficits were corrected by AMPH, maximally at 2.5-5 mg (d's = 0.79-1.29). AMPH also enhanced auditory learning, with maximal effects at 5 mg (d = 0.93), and comparable effects 60 and 210 min post pill. 'Pro-learning' effects of AMPH and AMPH-induced gains in auditory fidelity were most evident in patients with low MCCB A/V scores. CONCLUSIONS: These findings advance our understanding of the impact of pro-attentional interventions on auditory information processing and suggest dose- and time-course parameters for studies that assess the ability of AMPH to enhance the clinical benefits of TCT in schizophrenia patients.

Predictive models for social functioning in healthy young adults: A machine learning study integrating neuroanatomical, cognitive, and behavioral data.

Poor social functioning is an emerging public health problem associated with physical and mental health consequences. Developing prognostic tools is critical to identify individuals at risk for poor social functioning and guide interventions. We aimed to inform prediction models of social functioning by evaluating models relying on bio-behavioral data using machine learning. With data from the Human Connectome Project Healthy Young Adult sample (age 22-35, N = 1,101), we built Support Vector Regression models to estimate social functioning from variable sets of brain morphology to behavior with increasing complexity: 1) brain-only model, 2) brain-cognition model, 3) cognition-behavioral model, and 4) combined brain-cognition-behavioral model. Predictive accuracy of each model was assessed and the importance of individual variables for model performance was determined. The combined and cognition-behavioral models significantly predicted social functioning, whereas the brain-only and brain-cognition models did not. Negative affect, psychological wellbeing, extraversion, withdrawal, and cortical thickness of the rostral middle-frontal and superior-temporal regions were the most important predictors in the combined model. Results demonstrate that social functioning can be accurately predicted using machine learning methods. Behavioral markers may be more significant predictors of social functioning than brain measures for healthy young adults and may represent important leverage points for preventative intervention.

Abnormal Information Flow in Schizophrenia Is Linked to Psychosis.

BACKGROUND AND HYPOTHESIS: Prior research has shown that patients with schizophrenia (SZ) show disruption in brain network connectivity that is thought to underlie their cognitive and psychotic symptoms. However, most studies examining functional network disruption in schizophrenia have focused on the temporally correlated coupling of the strength of network connections. Here, we move beyond correlative metrics to assay causal computations of connectivity changes in directed neural information flow, assayed from a neural source to a target in SZ. STUDY DESIGN: This study describes a whole-brain magnetoencephalography-imaging approach to examine causal computations of connectivity changes in directed neural information flow between brain regions during resting states, quantified by phase-transfer entropy (PTE) metrics, assayed from a neural source to an endpoint, in 21 SZ compared with 21 healthy controls (HC), and associations with cognitive and clinical psychotic symptoms in SZ. STUDY RESULTS: We found that SZ showed significant disruption in information flow in alpha (8-12 Hz) and beta (12-30 Hz) frequencies, compared to HC. Reduced information flow in alpha frequencies from the precuneus to the medio-ventral occipital cortex was associated with more severe clinical psychopathology (ie, positive psychotic symptoms), while reduced information flow between insula and middle temporal gyrus was associated with worsening cognitive symptoms. CONCLUSIONS: The present findings highlight the importance of delineating dysfunction in neural information flow in specific oscillatory frequencies between distinct regions that underlie the cognitive and psychotic symptoms in SZ, and provide potential neural biomarkers that could lead to innovations in future neuromodulation treatment development.

Etiopathogenic Models of Psychosis Spectrum Illnesses Must Resolve Four Key Features.

Etiopathogenic models for psychosis spectrum illnesses are converging on a number of key processes, such as the influence of specific genes on the synthesis of proteins important in synaptic functioning, alterations in how neurons respond to synaptic inputs and engage in synaptic pruning, and microcircuit dysfunction that leads to more global cortical information processing vulnerabilities. Disruptions in prefrontal operations then accumulate and propagate over time, interacting with environmental factors, developmental processes, and homeostatic mechanisms, eventually resulting in symptoms of psychosis and disability. However, there are 4 key features of psychosis spectrum illnesses that are of primary clinical relevance but have been difficult to assimilate into a single model and have thus far received little direct attention: 1) the bidirectionality of the causal influences for the emergence of psychosis, 2) the catastrophic clinical threshold seen in first episodes of psychosis and why it is irreversible in some individuals, 3) observed biotypes that are neurophysiologically distinct but clinically both convergent and divergent, and 4) a reconciliation of the role of striatal dopaminergic dysfunction with models of prefrontal cortical state instability. In this selective review, we briefly describe these 4 hallmark features and we argue that theoretically driven computational perspectives making use of both algorithmic and neurophysiologic models are needed to reduce this complexity and variability of psychosis spectrum illnesses in a principled manner.

Changes in emotion processing and social cognition with auditory versus visual neuroscience-informed cognitive training in individuals with schizophrenia.

BACKGROUND: Neuroscience-informed cognitive training has been used to remediate cognitive deficits in schizophrenia, but their effect on emotion processing and social cognition deficits, which may involve auditory and visual impairments, remain relatively unknown. In this study, we compared the efficacy of auditory versus visual neuroscience-informed cognitive training on emotion processing and social cognition in individuals with schizophrenia. METHODS: In this randomised, double-blind clinical trial, 79 participants with chronic schizophrenia performed 40-hours auditory or visual dynamically equivalent computerised cognitive training. We assessed emotion processing and social cognition using Emotion Recognition, Affective Go-NoGo, Mayer-Salovey-Caruso Emotional-Intelligence, Theory of mind, and Hinting tests before and after 20 h and 40 h of training. RESULTS: After training, participants from both groups decreased their reaction time for facial emotion recognition (p = 3 × 10-6, d = 0.9). This was more remarkable for the auditory group when analysing individual emotions. Both groups also reduced omissions in the affective go-no go (p = 0.01, d = 0.6), which was also attributed, post hoc, to the auditory group. Trends for improvement were observed in theory of mind (p = 0.06, d = 0.6) for both groups. Improvement in emotion processing was associated with improvement in reasoning and problem solving and global cognition and improvement in theory of mind was associated with improvement in attention and global cognition. CONCLUSIONS: Both the auditory and the visual neuroscience-informed cognitive training were efficacious at improving emotion processing and social cognition in individuals with schizophrenia, although improvement was more remarkable for the auditory training group. These improvements were related to cognitive - but not symptom - improvement.