Adapting behavior to dynamic stimulus-reward contingences is a core feature of reversal learning and a capacity thought to be critical to socio-emotional behavior. Impairment in reversal learning has been linked to multiple psychiatric outcomes, including depression, Parkinson's disorder, and substance abuse. A recent influential study introduced an innovative laboratory reversal-learning paradigm capable of disentangling the roles of feedback valence and expectancy. Here, we sought to use this paradigm in order to examine the time-course of reward and punishment learning using event-related potentials among a large, representative sample (N = 101). Three distinct phases of processing were examined: initial feedback evaluation (reward positivity, or RewP), allocation of attention (P3), and sustained processing (late positive potential, or LPP). Results indicate a differential pattern of valence and expectancy across these processing stages: the RewP was uniquely related to valence (i.e., positive vs. negative feedback), the P3 was uniquely associated with expectancy (i.e., unexpected vs. expected feedback), and the LPP was sensitive to both valence and expectancy (i.e., main effects of each, but no interaction). The link between ERP amplitudes and behavioral performance was strongest for the P3, and this association was valencespecific. Overall, these findings highlight the potential utility of the P3 as a neural marker for feedback processing in reversal-based learning and establish a foundation for future research in clinical populations.

The COVID-19 global pandemic has left many feeling a sense of profound uncertainty about their world, safety, and livelihood. Sources espousing misinformation and conspiracy theories frequently offer information that can help make sense of this uncertainty. Individuals high in intolerance of uncertainty (IU) may be particularly impacted by the impoverished epistemic environment and may thus be more drawn to conspiratorial thinking (CT). In the present work, we show across 2 studies (N = 519) that COVID-19-specific CT is associated with higher levels of IU as well as delusion-proneness, and paranoia. Furthermore, delusion-proneness and paranoia explained the relationship between IU and CT and emerged as independent partial correlates of CT even when controlling for other facets of schizotypy. In contrast, anxiety did not explain the relationship between IU and CT. Overall, our findings highlight the importance of individual differences in IU, delusion-proneness and paranoia in the development of CT in the context of the acute uncertainty of a global crisis, in which conspiracy theories are more prevalent and salient. Informational intervention designs may benefit from leveraging the body of work demonstrating the efficacy of targeting IU to incite meaningful changes in thinking.

The COVID-19 global pandemic has left many feeling a sense of profound uncertainty about their world, safety, and livelihood. Explanatory frameworks to make sense of this uncertainty are offered by both official health-organizations as well as sources espousing misinformation and conspiracy theories. Individual differences that predispose towards conspiratorial thinking (CT) have been investigated by past work, but never in the context of the acute uncertainty of a global pandemic. In the present study we show that endorsement of COVID-19-specific conspiracy theories is associated with higher levels of intolerance of uncertainty, delusion-proneness, and paranoid ideation. Furthermore, delusion-proneness and paranoia mediated the relationship between intolerance to uncertainty and CT, and emerged as independent partial predictors of CT even when controlling for other facets of schizotypy. Overall, our findings highlight the importance of individual differences in intolerance to uncertainty, delusion-proneness and paranoia in the development of CT in the context of crisis and uncertainty due to the COVID-19 pandemic. These findings provide evidence that specific individual differences can create susceptibility to misinformation and may have implications for message framing strategies when designing informational interventions.

Mismatch negativity (MMN) amplitude has been widely shown to be diminished in schizophrenia and, more recently, in other psychotic disorders. Although there is considerable evidence linking MMN reduction to cognitive and functional deficits in schizophrenia, there is little evidence of associations with specific psychotic symptoms. Further, it is unclear if MMN reductions relate to specific symptoms, cognitive, and functional deficits transdiagnostically across different psychotic disorders. The present study examines MMN amplitude in a large cohort of cases diagnosed with psychotic disorders including schizophrenia and schizoaffective disorder (N = 116); bipolar disorder and major depressive disorder (N = 75); and other psychotic disorders (N = 25), as well as individuals with no psychotic disorder diagnoses (N = 248). Furthermore, we examined the association of MMN with symptoms, cognitive functioning, and real-world functioning to determine whether these relationships differ by diagnosis. Results showed that MMN amplitude was reduced in cases overall compared to never-psychotic individuals, with no differences between psychotic disorders. Furthermore, there were transdiagnostic associations of reduced duration MMN (MMN-D) with worse auditory hallucinations (r = .14) and disorganization (r = .14), frequency MMN (MMN-F) with real-word functioning (r = .20) and episodic memory (r = −.22), and both components with executive functioning (MMN-D: r = −.17; MMN-F: r = −.15). Our findings relating MMN reductions with cognitive and real-world functioning replicate earlier research in schizophrenia and extend these relationships to other psychotic disorders. Furthermore, our correlations with MMN-D are consistent with computational modeling research and theoretical proposals that view MMN reduction, cognitive dysfunction, and psychotic symptoms as reflecting underlying predictive coding deficits. However, differences in relationships with MMN-F suggest that additional work is warranted on this topic.

Response inhibition (RI) is a component of the cognitive control systems that support optimal cognition. Cognitive control deficits are well-described in schizophrenia, but are not well characterized in individuals at clinical high risk (CHR) for developing psychosis. Functional magnetic resonance imaging during Go/NoGo task performance was collected from 30 CHR youth, 23 early illness schizophrenia patients (ESZ), and 72 healthy adolescents and young adults (HC). Voxelwise main effects of group were examined (P < .005 height threshold, family-wise error-corrected cluster threshold, P < .05) for correct NoGo-Go contrast values and task-based functional connectivity. CHR and ESZ groups had slower and more variable reaction times (RT) on Go trials compared to HCs. Significant main effects of group in bilateral dorsal anterior cingulate (dACC) and right inferior frontal cortex stemmed from CHR and ESZ groups showing significantly less NoGo-Go activation, relative to HCs. Faster responding HCs had less functional coupling between dACC and medial prefrontal cortex, a default mode network (DMN) region during NoGo vs Go trials. This functional connectivity-performance relationship was not present in ESZ or CHR groups. The pattern of findings suggests CHR and ESZ groups were deficient in developing strong and consistent prepotent responding, based on their slow and variable motor responses and decreased engagement of dACC and right inferior frontal regions implicated in inhibitory control. Furthermore, only the control group showed a functional connectivity relationship consistent with greater response prepotency requiring more decoupling of inhibitory control regions from DMN regions during RI.

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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.