Dysfunctional Alpha Modulation as a Mechanism of Working Memory Impairment in Serious Mental Illness.

BACKGROUND: People with psychosis and mood disorders experience disruptions in working memory; however, the underlying mechanism remains unknown. We focused on 2 potential mechanisms: first, poor attentional engagement should be associated with elevated levels of prestimulus alpha-band activity within the electroencephalogram (EEG), whereas impaired working memory encoding should be associated with reduced poststimulus alpha suppression. METHODS: We collected EEG data from 68 people with schizophrenia, 43 people with bipolar disorder with a history of psychosis, 53 people with major depressive disorder, and 90 healthy comparison subjects while they completed a spatial working memory task. We quantified attention lapsing, memory precision, and memory capacity from the behavioral responses, and we quantified alpha using traditional wavelet analysis as well as a novel approach for isolating oscillatory alpha power from aperiodic elements of the EEG signal. RESULTS: We found that 1) greater prestimulus alpha power estimated using traditional wavelet analysis predicted behavioral errors; 2) poststimulus alpha suppression was reduced in the patient groups; and 3) reduced suppression was associated with a lower likelihood of memory storage. However, we also observed that the prestimulus alpha was larger among healthy control participants than patients, and single-trial analyses showed that it was the aperiodic elements of the prestimulus EEG-not oscillatory alpha-that predicted behavioral errors. DISCUSSION: These results suggest that working memory impairments in serious mental illness primarily reflect an impairment in the poststimulus encoding processes rather than reduced attentional engagement prior to stimulus onset.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders.

BACKGROUND AND HYPOTHESIS: The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample. STUDY DESIGN: Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task. STUDY RESULTS: We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well. CONCLUSIONS: These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

A Transdiagnostic Study of Effort-Cost Decision-Making in Psychotic and Mood Disorders.

BACKGROUND: Research suggests that effort-cost decision-making (ECDM), the estimation of work required to obtain reward, may be a relevant framework for understanding motivational impairment in psychotic and mood pathology. Specifically, research has suggested that people with psychotic and mood pathology experience effort as more costly than controls, and thus pursue effortful goals less frequently. This study examined ECDM across psychotic and mood pathology. HYPOTHESIS: We hypothesized that patient groups would show reduced willingness to expend effort compared to controls. STUDY DESIGN: People with schizophrenia (N = 33), schizoaffective disorder (N = 28), bipolar disorder (N = 39), major depressive disorder (N = 40), and controls (N = 70) completed a physical ECDM task. Participants decided between completing a low-effort or high-effort option for small or larger rewards, respectively. Reward magnitude, reward probability, and effort magnitude varied trial-by-trial. Data were analyzed using standard and hierarchical logistic regression analyses to assess the subject-specific contribution of various factors to choice. Negative symptoms were measured with a clinician-rated interview. STUDY RESULTS: There was a significant effect of group, driven by reduced choice of high-effort options in schizophrenia. Hierarchical logistic regression revealed that reduced choice of high-effort options in schizophrenia was driven by weaker contributions of probability information. Use of reward information was inversely associated with motivational impairment in schizophrenia. Surprisingly, individuals with major depressive disorder and bipolar disorder did not differ from controls. CONCLUSIONS: Our results provide support for ECDM deficits in schizophrenia. Additionally, differences between groups in ECDM suggest a seemingly similar behavioral phenotype, reduced motivation, could arise from disparate mechanisms.

Value Representations of Spite Sensitivity in Psychosis on the Minnesota Trust Game.

BACKGROUND: Spite sensitivity provides a valuable construct to understand persecutory ideation and its underlying neural mechanisms. We examined the relationship between persecution and spite sensitivity in psychosis to identify their neural substrates. METHODS: In a 3T magnetic resonance imaging scanner, 49 participants with psychosis played the Minnesota Trust Game, in which they decided whether to take a small amount of money or trust a partner to choose between fair and unfair distributions of money. In some conditions, the partner benefited from the unfair option, while in others, the partner lost money. Participants who were untrusting in the second condition (suspiciousness) showed heightened sensitivity to spite. Behavioral measures included mistrust during the 2 conditions of the game, which were compared with Brief Psychiatric Rating Scale persecution and computational modeling. Functional connectivity and blood oxygen level-dependent analyses were also conducted on a priori regions during spite-sensitive decisions. RESULTS: Behavioral results replicated previous findings; participants who experienced more persecutory ideation trusted less, specifically in the suspiciousness condition. Functional connectivity findings showed that decreased connectivity between the orbitofrontal cortex-insula and the left frontoparietal network was associated with increased persecutory ideation and estimated spite-guilt (a marker of spite sensitivity). Additionally, we found differences between conditions in caudate nucleus, medial prefrontal cortex, and lateral orbitofrontal cortex activation. CONCLUSIONS: These findings provide a new perspective on the origin of positive symptoms by identifying primary brain circuits that are related to both spite sensitivity and persecutory ideation.

Resting-State Functional Connectivity Explained Psychotic-like Experiences in the General Population and Partially Generalized to Patients and Relatives.

Background: Psychotic-like experiences (PLEs) are considered the subclinical portion of the psychosis continuum. Research suggests that there are resting-state functional connectivity (rsFC) substrates of PLEs, yet it is unclear if the same substrates underlie more severe psychosis. Here, to our knowledge, we report the first study to build a cross-validated rsFC model of PLEs in a large community sample and directly test its ability to explain psychosis in an independent sample of patients with psychosis and their relatives. Methods: Resting-state FC of 855 healthy young adults from the WU-Minn Human Connectome Project (HCP) was used to predict PLEs with elastic net. An rsFC composite score based on the resulting model was correlated with psychotic traits and symptoms in 118 patients with psychosis, 71 nonpsychotic first-degree relatives, and 45 healthy control subjects from the psychosis HCP. Results: In the HCP, the cross-validated model explained 3.3% of variance in PLEs. Predictive connections spread primarily across the default, frontoparietal, cingulo-opercular, and dorsal attention networks. The model partially generalized to a younger, but not older, subsample in the psychosis HCP, explaining two measures of positive/disorganized psychotic traits (the Structured Interview for Schizotypy: ß = 0.25, pone-tailed = .027; the Schizotypy Personality Questionnaire positive factor: ß = 0.14, pone-tailed = .041). However, it did not differentiate patients from relatives and control subjects or explain psychotic symptoms in patients. Conclusions: Some rsFC substrates of PLEs are shared across the psychosis continuum. However, explanatory power was modest, and generalization was partial. It is equally important to understand shared versus distinct rsFC variances across the psychosis continuum.

Transdiagnostic Predictors of Everyday Functioning: Examining the Relationships of Depression and Reinforcement Learning.

BACKGROUND AND HYPOTHESIS: Impairments in function (ie, the ability to independently accomplish daily tasks) have been established in psychotic disorders. Identifying factors that contribute to these deficits is essential to developing effective interventions. The current study had several goals: examine potential differential relationships across domains of neurocognition, assess whether reinforcement learning is related to function, identify if predictors of function are transdiagnostic, determine whether depression and positive symptoms contribute to function, and to explore whether the modality of assessment impacts observed relationships. STUDY DESIGN: Data from 274 participants were examined with schizophrenia/schizoaffective disorder (SZ; n = 195) and bipolar disorder (BD; n = 79). To reduce dimensionality, a PCA was completed on neurocognitive tasks which resulted in 3 components. These components and clinical interview data were used to investigate predictors of functional domains across measures of function (self- and informant-report SLOF and UPSA). RESULTS: Two components, working memory/processing speed/episodic memory (ßs = 0.18-0.42), and negative/positive reinforcement learning (ß = -0.04), predicted different functional domains. Predictors of function were largely transdiagnostic with two exceptions: reinforcement learning had a positive association with self-reported interpersonal relationships for SZ and a negative association for BD (ß = 0.34), and the negative association between positive symptoms and self-reported social acceptability was stronger for BD than for SZ (ß = 0.93). Depression robustly predicted self-reported but not informant-reported function, and anhedonia predicted all domains of informant-reported function. CONCLUSIONS: These findings imply that reinforcement learning may differentially relate to function across disorders, traditional domains of neurocognition can be effective transdiagnostic targets for interventions, and positive symptoms and depression play a critical role in self-perceived functional impairments.

Managing EEG studies: How to prepare and what to do once data collection has begun.

In this paper, we provide guidance for the organization and implementation of EEG studies. This work was inspired by our experience conducting a large-scale, multi-site study, but many elements could be applied to any EEG project. Section 1 focuses on study activities that take place before data collection begins. Topics covered include: establishing and training study teams, considerations for task design and piloting, setting up equipment and software, development of formal protocol documents, and planning communication strategy with all study team members. Section 2 focuses on what to do once data collection has already begun. Topics covered include: (1) how to effectively monitor and maintain EEG data quality, (2) how to ensure consistent implementation of experimental protocols, and (3) how to develop rigorous preprocessing procedures that are feasible for use in a large-scale study. Links to resources are also provided, including sample protocols, sample equipment and software tracking forms, sample code, and tutorial videos (to access resources, please visit: https://osf.io/wdrj3/).

Theories of psychopathology: Introduction to a special section.

This special section on theories of psychopathology provides an opportunity to collect the emergent, cross-cutting scholarship that is challenging traditional approaches to understanding mental illness. Here, we appraise the state of theory in the field and emphasize the pitfalls of working in the context of overly flexible, unchallenged, and essentially unchallengeable theoretic models, such as the biopsychosocial model, which we argue has become the de facto theoretic model for our field. We further posit that theoretic shortcomings are contributing to the often-referenced pessimism regarding our progress in understanding and treating mental illness, and introduce the charge of the authors of the papers in this section to articulate novel, falsifiable theories of psychopathology. We briefly touch on the intertwined issue of how to define psychopathology and discuss a key issue raised by the array of papers comprising the section, namely how to conceptualize the spatiotemporal boundaries of complex causal systems. We then use this schematic for understanding how these theories relate to each other and to the vanilla biopsychosocial model they are vying to replace. Ultimately, it is our belief and hope that progress in theoretic thinking will catalyze faster progress in research and improvements to and novel developments in clinical prevention and intervention efforts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Shared Neural Activity But Distinct Neural Dynamics for Cognitive Control in Monkey Prefrontal and Parietal Cortex.

To better understand how prefrontal networks mediate forms of cognitive control disrupted in schizophrenia, we translated a variant of the AX continuous performance task that measures specific deficits in the human disease to 2 male monkeys and recorded neurons in PFC and parietal cortex during task performance. In the task, contextual information instructed by cue stimuli determines the response required to a subsequent probe stimulus. We found parietal neurons encoding the behavioral context instructed by cues that exhibited nearly identical activity to their prefrontal counterparts (Blackman et al., 2016). This neural population switched their preference for stimuli over the course of the trial depending on whether the stimuli signaled the need to engage cognitive control to override a prepotent response. Cues evoked visual responses that appeared in parietal neurons first, whereas population activity encoding contextual information instructed by cues was stronger and more persistent in PFC. Increasing cognitive control demand biased the representation of contextual information toward the PFC and augmented the temporal correlation of task-defined information encoded by neurons in the two areas. Oscillatory dynamics in local field potentials differed between cortical areas and carried as much information about task conditions as spike rates. We found that, at the single-neuron level, patterns of activity evoked by the task were nearly identical between the two cortical areas. Nonetheless, distinct population dynamics in PFC and parietal cortex were evident. suggesting differential contributions to cognitive control.SIGNIFICANCE STATEMENT We recorded neural activity in PFC and parietal cortex of monkeys performing a task that measures cognitive control deficits in schizophrenia. This allowed us to characterize computations performed by neurons in the two areas to support forms of cognitive control disrupted in the disease. Subpopulations of neurons in the two areas exhibited parallel modulations in firing rate; and as a result, all patterns of task-evoked activity were distributed between PFC and parietal cortex. This included the presence in both cortical areas of neurons reflecting proactive and reactive cognitive control dissociated from stimuli or responses in the task. However, differences in the timing, strength, synchrony, and correlation of information encoded by neural activity were evident, indicating differential contributions to cognitive control.

Comparing the functional neuroanatomy of proactive and reactive control between patients with schizophrenia and healthy controls.

Cognitive control deficits are associated with impaired executive functioning in schizophrenia. The Dual Mechanisms of Control framework suggests that proactive control requires sustained dorsolateral prefrontal activity, whereas reactive control marshals a larger network. However, primate studies suggest these processes are maintained by dual-encoding regions. To distinguish between these theories, we compared the distinctiveness of proactive and reactive control functional neuroanatomy. In a reanalysis of data from a previous study, 47 adults with schizophrenia and 56 controls completed the Dot Pattern Expectancy task during an fMRI scan examining proactive and reactive control in frontoparietal and medial temporal regions. Areas suggesting specialized control or between-group differences were tested for association with symptoms and task performance. Elastic net models additionally explored these areas' predictive abilities regarding performance. Most regions were active in both reactive and proactive control. However, evidence of specialized proactive control was found in the left middle and superior frontal gyri. Control participants showed greater proactive control in the left middle and right inferior frontal gyri. Elastic net models moderately predicted task performance and implicated various frontal gyri regions in control participants, with additional involvement of anterior cingulate and posterior parietal regions for reactive control. Elastic nets for patient participants implicated the inferior and superior frontal gyri, and posterior parietal lobe. Specialized cognitive control was unassociated with either performance or schizophrenia symptomatology. Future work is needed to clarify the distinctiveness of proactive and reactive control, and its role in executive deficits in severe psychopathology.

Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions.

The development of treatments for impaired cognition in schizophrenia has been characterized as the most important challenge facing psychiatry at the beginning of the twenty-first century. The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) project was designed to build on the potential benefits of using tasks and tools from cognitive neuroscience to better understanding and treat cognitive impairments in psychosis. These benefits include: (1) the use of fine-grained tasks that measure discrete cognitive processes; (2) the ability to design tasks that distinguish between specific cognitive domain deficits and poor performance due to generalized deficits resulting from sedation, low motivation, poor test taking skills, etc.; and (3) the ability to link cognitive deficits to specific neural systems, using animal models, neuropsychology, and functional imaging. CNTRICS convened a series of meetings to identify paradigms from cognitive neuroscience that maximize these benefits and identified the steps need for translation into use in clinical populations. The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) Consortium was developed to help carry out these steps. CNTRaCS consists of investigators at five different sites across the country with diverse expertise relevant to a wide range of the cognitive systems identified as critical as part of CNTRICs. This work reports on the progress and current directions in the evaluation and optimization carried out by CNTRaCS of the tasks identified as part of the original CNTRICs process, as well as subsequent extensions into the Positive Valence systems domain of Research Domain Criteria (RDoC). We also describe the current focus of CNTRaCS, which involves taking a computational psychiatry approach to measuring cognitive and motivational function across the spectrum of psychosis. Specifically, the current iteration of CNTRaCS is using computational modeling to isolate parameters reflecting potentially more specific cognitive and visual processes that may provide greater interpretability in understanding shared and distinct impairments across psychiatric disorders.

Psychometric validation and clinical correlates of an experiential foraging task.

Measuring the function of decision-making systems is a central goal of computational psychiatry. Individual measures of decisional function could be used to describe neurocognitive profiles that underpin psychopathology and offer insights into deficits that are shared across traditional diagnostic classes. However, there are few demonstrably reliable and mechanistically relevant metrics of decision making that can accurately capture the complex overlapping domains of cognition whilst also quantifying the heterogeneity of function between individuals. The WebSurf task is a reverse-translational human experiential foraging paradigm which indexes naturalistic and clinically relevant decision-making. To determine its potential clinical utility, we examined the psychometric properties and clinical correlates of behavioural parameters extracted from WebSurf in an initial exploratory experiment and a pre-registered validation experiment. Behaviour was stable over repeated administrations of the task, as were individual differences. The ability to measure decision making consistently supports the potential utility of the task in predicting an individual's propensity for response to psychiatric treatment, in evaluating clinical change during treatment, and in defining neurocognitive profiles that relate to psychopathology. Specific aspects of WebSurf behaviour also correlate with anhedonic and externalising symptoms. Importantly, these behavioural parameters may measure dimensions of psychological variance that are not captured by traditional rating scales. WebSurf and related paradigms might therefore be useful platforms for computational approaches to precision psychiatry.

Sunk cost sensitivity during change-of-mind decisions is informed by both the spent and remaining costs.

Sunk cost sensitivity describes escalating decision commitment with increased spent resources. On neuroeconomic foraging tasks, mice, rats, and humans show similar escalations from sunk costs while quitting an ongoing countdown to reward. In a new analysis taken across computationally parallel foraging tasks across species and laboratories, we find that these behaviors primarily occur on choices that are economically inconsistent with the subject's other choices, and that they reflect not only the time spent, but also the time remaining, suggesting that these are change-of-mind re-evaluation processes. Using a recently proposed change-of-mind drift-diffusion model, we find that the sunk cost sensitivity in this model arises from decision-processes that directly take into account the time spent (costs sunk). Applying these new insights to experimental data, we find that sensitivity to sunk costs during re-evaluation decisions depends on the information provided to the subject about the time spent and the time remaining.

Integrating development into the Research Domain Criteria (RDoC) framework: Introduction to the special section.

The goal of this Special Section is to highlight the generativity of taking a developmental perspective toward the RDoC framework that considers developmental processes and principles and the environmental and contextual processes relevant at different ages and developmental stages. The 9 papers in this Special Section and 2 invited commentaries exemplify and highlight sophisticated efforts to integrate development and principles of developmental psychopathology into the RDoC framework. In so doing, the papers both demonstrate how a developmental perspective can bolster strengths of the RDoC approach and identify notable gaps and shortcomings in how the RDoC framework, assumptions, and constructs are currently conceptualized. There are critical tensions between conducting developmentally informed and informative RDoC research. Our measures and research designs are often outstripped by the challenge of testing our ambitious ideas. Examining the causal transactions between individual differences in RDoC dimensions and normative maturational tasks, supportive and hindering contexts, and the potential moderation of associations by developmental history will produce important information about the development, manifestation, and course of psychopathology. Addressing these gaps holds great potential for identifying preventive-intervention targets, impactful intervention settings, and environmental and contextual supports. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

New titles can give new perspectives: Reflections on language and equity in clinical science.

Rebranding of the Journal of Abnormal Psychology as the Journal of Psychopathology and Clinical Science is insufficient, and will not move the dial on the stigma and discrimination against people suffering from mental illness without a good deal more effort on the part of our community of scholars. In this editorial to inaugurate the new title of this Journal, coauthored by the prompter of this change along with the current editor, we unpack ways in which researchers can be mindful of language, research practices such as representation, and advocacy to promote a healthier science going forward. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Using Computational Modeling to Capture Schizophrenia-Specific Reinforcement Learning Differences and Their Implications on Patient Classification.

BACKGROUND: Psychiatric diagnosis and treatment have historically taken a symptom-based approach, with less attention on identifying underlying symptom-producing mechanisms. Recent efforts have illuminated the extent to which different underlying circuitry can produce phenotypically similar symptomatology (e.g., psychosis in bipolar disorder vs. schizophrenia). Computational modeling makes it possible to identify and mathematically differentiate behaviorally unobservable, specific reinforcement learning differences in patients with schizophrenia versus other disorders, likely owing to a higher reliance on prediction error-driven learning associated with basal ganglia and underreliance on explicit value representations associated with orbitofrontal cortex. METHODS: We used a well-established probabilistic reinforcement learning task to replicate those findings in individuals with schizophrenia both on (n = 120) and off (n = 44) antipsychotic medications and included a patient comparison group of bipolar patients with psychosis (n = 60) and healthy control subjects (n = 72). RESULTS: Using accuracy, there was a main effect of group (F3,279 = 7.87, p < .001), such that all patient groups were less accurate than control subjects. Using computationally derived parameters, both medicated and unmediated individuals with schizophrenia, but not patients with bipolar disorder, demonstrated a reduced mixing parameter (F3,295 = 13.91, p < .001), indicating less dependence on learning explicit value representations as well as greater learning decay between training and test (F1,289 = 12.81, p < .001). Unmedicated patients with schizophrenia also showed greater decision noise (F3,295 = 2.67, p = .04). CONCLUSIONS: Both medicated and unmedicated patients showed overreliance on prediction error-driven learning as well as significantly higher noise and value-related memory decay, compared with the healthy control subjects and the patients with bipolar disorder. Additionally, the computational model parameters capturing these processes can significantly improve patient/control classification, potentially providing useful diagnosis insight.

Both unmedicated and medicated individuals with schizophrenia show impairments across a wide array of cognitive and reinforcement learning tasks.

BACKGROUND: Schizophrenia is a disorder characterized by pervasive deficits in cognitive functioning. However, few well-powered studies have examined the degree to which cognitive performance is impaired even among individuals with schizophrenia not currently on antipsychotic medications using a wide range of cognitive and reinforcement learning measures derived from cognitive neuroscience. Such research is particularly needed in the domain of reinforcement learning, given the central role of dopamine in reinforcement learning, and the potential impact of antipsychotic medications on dopamine function. METHODS: The present study sought to fill this gap by examining healthy controls (N = 75), unmedicated (N = 48) and medicated (N = 148) individuals with schizophrenia. Participants were recruited across five sites as part of the CNTRaCS Consortium to complete tasks assessing processing speed, cognitive control, working memory, verbal learning, relational encoding and retrieval, visual integration and reinforcement learning. RESULTS: Individuals with schizophrenia who were not taking antipsychotic medications, as well as those taking antipsychotic medications, showed pervasive deficits across cognitive domains including reinforcement learning, processing speed, cognitive control, working memory, verbal learning and relational encoding and retrieval. Further, we found that chlorpromazine equivalency rates were significantly related to processing speed and working memory, while there were no significant relationships between anticholinergic load and performance on other tasks. CONCLUSIONS: These findings add to a body of literature suggesting that cognitive deficits are an enduring aspect of schizophrenia, present in those off antipsychotic medications as well as those taking antipsychotic medications.

A Computational Model of Non-optimal Suspiciousness in the Minnesota Trust Game.

This study modelled spite sensitivity, the worry that others are willing to incur a loss to hurt you, which is thought to undergird suspiciousness and persecutory ideation. Two samples performed a parametric, non-iterative trust game known as the Minnesota Trust Game (MTG). The MTG distinguishes suspicious decision-making from otherwise rational mistrust by incentivizing the player to trust in certain situations but not others. In Sample 1, 243 undergraduates who completed the MTG showed less trust as the amount of money they could lose increased. However, only for choices where partners had a financial disincentive to betray the player was variation in the willingness to trust associated with suspicious beliefs. We modified the Fehr-Schmidt (1999) inequity aversion model, which compares unequal outcomes in social decision-making tasks, to include the possibility for spite sensitivity. An anticipated partner's dislike of advantageous inequity (i.e., guilt) parameter included negative values, with negative guilt indicating spite. We hypothesized that the anticipated guilt parameter would be strongly related to suspicious beliefs. Our modification of the Fehr-Schmidt model improved estimation of MTG behavior. Furthermore, the estimation of partner's spite-guilt was highly correlated with choices associated with beliefs in persecution. We replicated our findings in a second sample. This parameter was weakly correlated with a self-reported measure of persecutory ideation in Sample 2. The "Suspiciousness" condition, unique to the MTG, can be modeled to isolate spite sensitivity, suggesting differentiation from inequity aversion or risk aversion. The MTG offers promise for future studies to quantify persecutory beliefs in clinical populations.

Resting-State Networks Associated with Behavioral and Self-Reported Measures of Persecutory Ideation in Psychosis.

Persecutory ideations are self-referential delusions of being the target of malevolence despite a lack of evidence. Wisner et al. (2021) found that reduced connectivity between the left frontoparietal (lFP) network and parts of the orbitofrontal cortex (OFC) correlated with increased persecutory behaviors among psychotic patients performing in an economic social decision-making task that can measure the anticipation of a partner's spiteful behavior. If this pattern could be observed in the resting state, it would suggest a functional-structural prior predisposing individuals to persecutory ideation. Forty-four patients in the early course of a psychotic disorder provided data for resting-state functional connectivity magnetic resonance imaging across nine brain networks that included the FP network and a similar OFC region. As predicted, we found a significant and negative correlation between the lFP-OFC at rest and the level of suspicious mistrust on the decision-making task using a within-group correlational design. Additionally, self-reported persecutory ideation correlated significantly with the connectivity between the right frontoparietal (rFP) network and the OFC. We extended the previous finding of reduced connectivity between the lFP network and the OFC in psychosis patients to the resting state, and observed a possible hemispheric difference, such that greater rFP-OFC connectivity predicted elevated self-reported persecutory ideation, suggesting potential differences between the lFP and rFP roles in persecutory social interactions.

Task-related neural mechanisms of persecutory ideation in schizophrenia and community monozygotic twin-pairs.

Perceptions of spiteful behavior are common, distinct from rational fear, and may undergird persecutory ideation. To test this hypothesis and investigate neural mechanisms of persecutory ideation, we employed a novel economic social decision-making task, the Minnesota Trust Game (MTG), during neuroimaging in patients with schizophrenia (n = 30) and community monozygotic (MZ) twins (n = 38; 19 pairs). We examined distinct forms of mistrust, task-related brain activation and connectivity, and investigated relationships with persecutory ideation. We tested whether co-twin discordance on these measurements was correlated to reflect a common source of underlying variance. Across samples persecutory ideation was associated with reduced trust only during the suspiciousness condition, which assessed spite sensitivity given partners had no monetary incentive to betray. Task-based activation contrasts for specific forms of mistrust were limited and unrelated to persecutory ideation. However, task-based connectivity contrasts revealed a dorsal cingulate anterior insula network sensitive to suspicious mistrust, a left frontal-parietal (lF-P) network sensitive to rational mistrust, and a ventral medial/orbital prefrontal (vmPFC/OFC) network that was sensitive to the difference between these forms of mistrust (all p < .005). Higher persecutory ideation was predicted only by reduced connectivity between the vmPFC/OFC and lF-P networks (p = .005), which was only observed when the intentions of the other player were relevant. Moreover, co-twin differences in persecutory ideation predicted co-twin differences in both spite sensitivity and in vmPFC/OFC-lF-P connectivity. This work found that interconnectivity may be particularly important to the complex neurobiology underlying persecutory ideation, and that unique environmental variance causally linked persecutory ideation, decision-making, and brain connectivity.