Understanding Cognitive Behavioral Therapy for Psychosis Through the Predictive Coding Framework.

Psychological treatments for persecutory delusions, particularly cognitive behavioral therapy for psychosis, are efficacious; however, mechanistic theories explaining why they work rarely bridge to the level of cognitive neuroscience. Predictive coding, a general brain processing theory rooted in cognitive and computational neuroscience, has increasing experimental support for explaining symptoms of psychosis, including the formation and maintenance of delusions. Here, we describe recent advances in cognitive behavioral therapy for psychosis-based psychotherapy for persecutory delusions, which targets specific psychological processes at the computational level of information processing. We outline how Bayesian learning models employed in predictive coding are superior to simple associative learning models for understanding the impact of cognitive behavioral interventions at the algorithmic level. We review hierarchical predictive coding as an account of belief updating rooted in prediction error signaling. We examine how this process is abnormal in psychotic disorders, garnering noisy sensory data that is made sense of through the development of overly strong delusional priors. We argue that effective cognitive behavioral therapy for psychosis systematically targets the way sensory data are selected, experienced, and interpreted, thus allowing for the strengthening of alternative beliefs. Finally, future directions based on these arguments are discussed.

Delusions are distressing and disabling psychiatric symptoms. Cognitive behavioral therapy for psychosis (CBTp) is the leading psychotherapeutic approach for treating delusions. Predictive coding is a contemporary cognitive neuroscience framework that is increasingly being used to explain mechanisms of delusions. In this article, we attempt to integrate CBTp within the predictive coding framework, outlining how effective CBTp techniques impact aspects of the predictive coding model to contribute to cutting-edge treatment and cognitive neuroscience research on delusions and inform recommendations for treatment advancement.

Lesions to the mediodorsal thalamus, but not orbitofrontal cortex, enhance volatility beliefs linked to paranoia.

Beliefs-attitudes toward some state of the environment-guide action selection and should be robust to variability but sensitive to meaningful change. Beliefs about volatility (expectation of change) are associated with paranoia in humans, but the brain regions responsible for volatility beliefs remain unknown. The orbitofrontal cortex (OFC) is central to adaptive behavior, whereas the magnocellular mediodorsal thalamus (MDmc) is essential for arbitrating between perceptions and action policies. We assessed belief updating in a three-choice probabilistic reversal learning task following excitotoxic lesions of the MDmc (n = 3) or OFC (n = 3) and compared performance with that of unoperated monkeys (n = 14). Computational analyses indicated a double dissociation: MDmc, but not OFC, lesions were associated with erratic switching behavior and heightened volatility belief (as in paranoia in humans), whereas OFC, but not MDmc, lesions were associated with increased lose-stay behavior and reward learning rates. Given the consilience across species and models, these results have implications for understanding paranoia.

Belief Updating, Childhood Maltreatment, and Paranoia in Schizophrenia-Spectrum Disorders.

BACKGROUND AND HYPOTHESIS: Exposure to childhood maltreatment-a risk factor for psychosis is associated with paranoia-may impact one's beliefs about the world and how beliefs are updated. We hypothesized that increased exposure to childhood maltreatment is related to volatility-related belief updating, specifically higher expectations of volatility, and that these relationships are strongest for threat-related maltreatment. Additionally, we tested whether belief updating mediates the relationship between maltreatment and paranoia. STUDY DESIGN: Belief updating was measured in 75 patients with schizophrenia-spectrum disorders and 76 nonpsychiatric controls using a 3-option probabilistic reversal learning (3PRL) task. A Hierarchical Gaussian Filter (HGF) was used to estimate computational parameters of belief updating, including prior expectations of volatility (µ03). The Childhood Trauma Questionnaire (CTQ) was used to assess cumulative maltreatment, threat, and deprivation exposure. Paranoia was measured using the Positive and Negative Syndrome Scale (PANSS) and the revised Green et al. Paranoid Thoughts Scale (R-GPTS). RESULTS: Greater exposure to childhood maltreatment is associated with higher prior expectations of volatility in the whole sample and in individuals with schizophrenia-spectrum disorders. This was specific to threat-related maltreatment, rather than deprivation, in schizophrenia-spectrum disorders. Paranoia was associated with both exposure to childhood maltreatment and volatility priors, but we did not observe a significant indirect effect of volatility priors on the relationship between maltreatment and paranoia. CONCLUSIONS: Our study suggests that individuals with schizophrenia-spectrum disorders who were exposed to threatening experiences during childhood expect their environment to be more volatile, potentially facilitating aberrant belief updating and conferring risk for paranoia.

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 on two different cognitive tasks, probabilistic reversal learning (PRL) 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 behavioral results on the PRL task but that an individual's level of paranoia is associated with excessive switching behavior. 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 behavioral 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 on the PRL task as well as the blocking task. Non-paranoid delusion-like belief conviction was 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 - may have differential utility in predicting psychosis.

Illusory generalizability of clinical prediction models.

It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model's success in one or two datasets or clinical contexts. We scrutinized this optimism by examining how well a machine learning model performed across several independent clinical trials of antipsychotic medication for schizophrenia. Models predicted patient outcomes with high accuracy within the trial in which the model was developed but performed no better than chance when applied out-of-sample. Pooling data across trials to predict outcomes in the trial left out did not improve predictions. These results suggest that models predicting treatment outcomes in schizophrenia are highly context-dependent and may have limited generalizability.

Cognitive behavioral therapy following esketamine for major depression and suicidal ideation for relapse prevention: The CBT-ENDURE randomized clinical trial study protocol.

In 2020, esketamine received a supplemental indication as a therapy for major depression with suicidal ideation (MDSI), based on protocols enrolling hospitalized patients. Given the high risk of suicide following hospital discharge and the high relapse rates following discontinuation of esketamine, the optimal long-term treatment approach remains unclear. Cognitive behavioral therapy (CBT) is highly effective in relapse prevention and has been shown to prevent suicide attempts in high-risk populations. Here we describe the study protocol for the CBT-ENDURE trial: Cognitive Behavioral Therapy Following Esketamine for Major Depression and SUicidal Ideation for RElapse Prevention. Patients with depression (N = 100) who are admitted to hospital or are outpatients with clinically significant suicidal ideation will be enrolled in the study. All patients will receive esketamine (twice weekly for four weeks) and will be randomly assigned (1:1 ratio) to receive a 16-week course of CBT plus treatment as usual (CBT group) or treatment as usual only (TAU only group). Patients are followed for a total of 6 months. Supported under a funding announcement from NIMH to conduct safety and feasibility trials for patients at high risk for suicide, the primary outcome of the CBT-ENDURE study is feasibility (as measured by recruitment and retention), with a key secondary outcome being relapse among those who experience substantial benefit following two weeks of esketamine.

Assessing the impact of a comprehensive mental health program on frontline health service workers.

Mental health issues are a growing concern in the workplace, linked to negative outcomes including reduced productivity, increased absenteeism, and increased turnover. Employer-sponsored mental health benefits that are accessible and proactive may help address these concerns. The aim of this retrospective cohort study was to evaluate the impact of a digital mental health benefit (Spring Health) on frontline healthcare service workers' clinical and workplace outcomes. The benefit was sponsored by a national health services company from 2021-2022 and included mental health screening, care navigation, psychotherapy and/or medication management. We hypothesized program use would be associated with improvements in depression and anxiety symptoms, and increased productivity and retention. Participants were employees enrolled in the benefit program, had at least moderate anxiety or depression, at least 1 treatment appointment, and at least 2 outcome assessments. Clinical improvement measures were PHQ-9 scale (range, 0-27) for depression and GAD-7 scale (range, 0-21) for anxiety; workplace measures were employee retention and the Sheehan Disability Scale (SDS) for functional impairment. A total of 686 participants were included. Participants using the mental health benefit had a 5.60 point (95% CI, 4.40-6.79, d = 1.28) reduction in depression and a 5.48 point (95% CI, 3.88-7.08, d = 1.64) reduction in anxiety across 6 months. 69.9% (95% CI, 61.8%-78.1%) of participants reliably improved (≥5 point change) and 84.1% (95% CI, 78.2%-90.1%) achieved reliable improvement or recovery (<10 points). Participants reported 0.70 (95% CI, 0.26-1.14) fewer workdays per week impacted by mental health issues, corresponding to $3,491 (95% CI, $1305-$5677) salary savings at approximately federal median wage ($50,000). Furthermore, employees using the benefit were retained at 1.58 (95% CI, 1.4-1.76) times the rate of those who did not. Overall, this evaluation suggests that accessible, proactive, and comprehensive mental health benefits for frontline health services workers can lead to positive clinical and workplace outcomes.

Comparing a Computerized Digit Symbol Test to a Pen-and-Paper Classic.

Background and Hypothesis: Processing speed dysfunction is a core feature of psychosis and predictive of conversion in individuals at clinical high risk (CHR) for psychosis. Although traditionally measured with pen-and-paper tasks, computerized digit symbol tasks are needed to meet the increasing demand for remote assessments. Therefore we: (1) assessed the relationship between traditional and computerized processing speed measurements; (2) compared effect sizes of impairment for progressive and persistent subgroups of CHR individuals on these tasks; and (3) explored causes contributing to task performance differences. Study Design: Participants included 92 CHR individuals and 60 healthy controls who completed clinical interviews, the Brief Assessment of Cognition in Schizophrenia Symbol Coding test, the computerized TestMyBrain Digit Symbol Matching Test, a finger-tapping task, and a self-reported motor abilities measure. Correlations, Hedges' g, and linear models were utilized, respectively, to achieve the above aims. Study Results: Task performance was strongly correlated (r = 0.505). A similar degree of impairment was seen between progressive (g = -0.541) and persistent (g = -0.417) groups on the paper version. The computerized task uniquely identified impairment for progressive individuals (g = -477), as the persistent group performed similarly to controls (g = -0.184). Motor abilities were related to the computerized version, but the paper version was more related to symptoms and psychosis risk level. Conclusions: The paper symbol coding task measures impairment throughout the CHR state, while the computerized version only identifies impairment in those with worsening symptomatology. These results may be reflective of sensitivity differences, an artifact of existing subgroups, or evidence of mechanistic differences.

Excessive teleological thinking is driven by aberrant associations and not by failure of reasoning.

Teleological thought - the tendency to ascribe purpose to objects and events - is useful in some cases (encouraging explanation-seeking), but harmful in others (fueling delusions and conspiracy theories). What drives excessive and maladaptive teleological thinking? In causal learning, there is a fundamental distinction between associative learning versus learning via propositional mechanisms. Here, we propose that directly contrasting the contributions of these two pathways can elucidate the roots of excess teleology. We modified a causal learning task such that we could encourage associative versus propositional mechanisms in different instances. Across three experiments (total N = 600), teleological tendencies were correlated with delusion-like ideas and uniquely explained by aberrant associative learning, but not by learning via propositional rules. Computational modeling suggested that the relationship between associative learning and teleological thinking can be explained by excessive prediction errors that imbue random events with more significance - providing a new understanding for how humans make meaning of lived events.

Relationships between cognitive biases, decision-making, and delusions.

Multiple measures of decision-making under uncertainty (e.g. jumping to conclusions (JTC), bias against disconfirmatory evidence (BADE), win-switch behavior, random exploration) have been associated with delusional thinking in independent studies. Yet, it is unknown whether these variables explain shared or unique variance in delusional thinking, and whether these relationships are specific to paranoia or delusional ideation more broadly. Additionally, the underlying computational mechanisms require further investigation. To investigate these questions, task and self-report data were collected in 88 individuals (46 healthy controls, 42 schizophrenia-spectrum) and included measures of cognitive biases and behavior on probabilistic reversal learning and explore/exploit tasks. Of those, only win-switch rate significantly differed between groups. In regression, reversal learning performance, random exploration, and poor evidence integration during BADE showed significant, independent associations with paranoia. Only self-reported JTC was associated with delusional ideation, controlling for paranoia. Computational parameters increased the proportion of variance explained in paranoia. Overall, decision-making influenced by strong volatility and variability is specifically associated with paranoia, whereas self-reported hasty decision-making is specifically associated with other themes of delusional ideation. These aspects of decision-making under uncertainty may therefore represent distinct cognitive processes that, together, have the potential to worsen delusional thinking across the psychosis spectrum.

Phenomenological and Cognitive Features Associated With Auditory Hallucinations in Clinical and Nonclinical Voice Hearers.

BACKGROUND AND HYPOTHESES: Auditory verbal hallucinations (AVH) are central features of schizophrenia (SZ). However, AVH also occur in a small percentage of the general population who do not have a need for care, termed nonclinical voice hearers (NCVH). We sought to determine the degree to which the experience of AVH was similar in NCVH and in people with schizophrenia (PSZ) and evaluate the degree to which NCVH shared other features of SZ such as delusional beliefs, cognitive impairment, and negative symptoms. STUDY DESIGN: We recruited 76 people with a DSM-V diagnosis of SZ/schizoaffective disorder (PSZ; 49 with current AVH, 27 without), 48 NCVH, and 51 healthy controls. Participants received a broad battery of clinician-administered and self-report symptom assessments and a focused cognitive assessment. STUDY RESULTS: The AVH of NCVH and PSZ shared very similar sensory features. NCVH experienced less distress, had greater control over their AVH, and, unlike PSZ, rarely heard 2 voices speaking to each other. NCVH demonstrated a wide range of deeply held unusual beliefs, but reported less paranoia, and fewer first-rank symptoms such as passivity and alterations in self-experience. NCVH showed no evidence of cognitive deficits or negative symptoms. CONCLUSIONS: The AVH in NCVH and PSZ demonstrate important similarities as well as clear differences. Specific features, rather than the presence, of AVH appear to determine the need for care. NCVH do not share the cognitive and motivational deficits seen in PSZ. These results suggest that AVH and unusual beliefs can be separated from the broader phenotype of SZ.

The association between evening social media use and delayed sleep may be causal: Suggestive evidence from 120 million Reddit timestamps.

Public health officials and clinicians routinely advise social media users to avoid nighttime social media use due to the perception that this delays the onset of sleep and predisposes to the health risks of insufficient sleep. With some exceptions, the evidence behind this advice mostly derives from surveys identifying an association between self-reported social media usage and self-reported sleep patterns. In principle, these associations could alternatively be explained by users turning to social media to pass the time when they are otherwise having difficulty sleeping, or by individual differences that draw some people to frequent social media use, or by offline activities that overlap with both social media use and delayed sleep. To attempt to distinguish among these explanations, we leveraged estimated bedtimes from 44,000 Reddit users reported in a recent study and their 120 million posts to test whether the relationship between sleep and social media has properties suggestive of a causal relationship. We find that users are especially likely to be active on Reddit after their bedtime (and therefore awake) on nights that they posted to Reddit shortly before bedtime, especially if they posted multiple times or in high-engagement forums that night. Overall, this study lends additional support to the notion that there likely is some causal effect of evening social media use on delayed sleep onset.

Assumed shared belief about conspiracy theories in social networks protects paranoid individuals against distress.

Paranoia is the belief that others intend you harm. It is related to conspiracy theories, wherein those others represent an organized faction, coordinating the harm against self and others, and violating societal norms. Current psychological studies of paranoid conspiracy theorizing focus either on the individual or their broader social network. Likewise, theories of belief formation and updating often contain individual level processes as well as broader interpersonal and organizational factors. Here we examine paranoia and conspiracy theorizing in terms of individual behavioral predictors (performance on a probabilistic reversal learning task which assays belief updating) as well as social sensing: we ask participants to report the features of their social network, including whether their friends and acquaintances share their paranoid conspiratorial beliefs. We find that people who believe paranoid conspiracy theories expect more volatility during the task. They also assume that members of their social network share their paranoid beliefs. Critically, those participants with larger social networks and greater assumed shared belief tend to harbor their conspiratorial beliefs with less emotional distress and expect less volatility in the task. This is evidence that, like political and religious beliefs, conspiracy theories may flourish under a sacred canopy of belief consensus. These data suggest that friends and acquaintances may serve as sources of credulity and moving between them may sustain conspiracy beliefs when there is detraction. This hybrid individual/social account may shed light on clinical paranoia and persecutory delusion, wherein disability is defined normatively, and social supports are fewer.

Studying Healthy Psychosislike Experiences to Improve Illness Prediction.

Importance: Distinguishing delusions and hallucinations from unusual beliefs and experiences has proven challenging. Observations: The advent of neural network and generative modeling approaches to big data offers a challenge and an opportunity; healthy individuals with unusual beliefs and experiences who are not ill may raise false alarms and serve as adversarial examples to such networks. Conclusions and Relevance: Explicitly training predictive models with adversarial examples should provide clearer focus on the features most relevant to casehood, which will empower clinical research and ultimately diagnosis and treatment.

Self-reported Gesture Interpretation and Performance Deficits in Individuals at Clinical High Risk for Psychosis.

BACKGROUND AND HYPOTHESIS: Deficits in performing and interpreting communicative nonverbal behaviors, such as gesture, have been linked to varied psychopathology and dysfunction. Some evidence suggests that individuals at risk for psychosis have deficits in gesture interpretation and performance; however, individuals with internalizing disorders (eg, depression) may have similar deficits. No previous studies have examined whether gesture deficits in performance and interpretation are specific to those at risk for psychosis. Additionally, the underlying mechanisms (eg, cognition) and consequences (eg, functioning) of these deficits are poorly understood. STUDY DESIGN: This study examined self-reported gesture interpretation (SRGI) and performance (SRGP) in those at clinical high risk for psychosis (CHR; N = 88), those with internalizing disorders (INT; N = 51), and healthy controls (HC; N = 53). Participants completed questionnaires, clinical interviews, and neurocognitive tasks. STUDY RESULTS: Results indicated that the CHR group was characterized by significantly lower SRGI scores than the HC or INT groups (d = 0.41); there were no differences among groups in SRGP. Within CHR participants, greater deficits in SRGP were associated with lower verbal learning and memory (r = -.33), but not general intelligence or processing speed. Furthermore, gesture deficits were associated with higher cross-sectional risk for conversion to a full psychotic disorder in the CHR group. CONCLUSIONS: Overall, these findings suggest that specific subdomains of gesture may reflect unique vulnerability for psychosis, self-report may be a viable assessment tool in understanding these phenomena, and gesture dysfunction may signal risk for transition to psychosis.

The reliability and validity of the revised Green et al. paranoid thoughts scale in individuals at clinical high-risk for psychosis.

INTRODUCTION: Paranoia is a common and impairing psychosis symptom, which exists along a severity continuum that extends into the general population. Individuals at clinical high-risk for psychosis (CHR) frequently experience paranoia and this may elevate their risk for developing full psychosis. Nonetheless, limited work has examined the efficient measurement of paranoia in CHR individuals. The present study aimed to validate an often-used self-report measure, the revised green paranoid thoughts scale (RGPTS), in this critical population. METHOD: Participants were CHR individuals (n = 103), mixed clinical controls (n = 80), and healthy controls (n = 71) who completed self-report and interview measures. Confirmatory factor analysis (CFA), psychometric indices, group differences, and relations to external measures were used to evaluate the reliability and validity of the RGPTS. RESULTS: CFA replicated a two-factor structure for the RGPTS and the associated reference and persecution scales were reliable. CHR individuals scored significantly higher on both reference and persecution, relative to both healthy (ds = 1.03, 0.86) and clinical controls (ds = 0.64, 0.73). In CHR participants, correlations between reference and persecution and external measures were smaller than expected, though showed evidence of discriminant validity (e.g., interviewer-rated paranoia, r = 0.24). When examined in the full sample, correlation magnitude was larger and follow-up analyses indicated that reference related most specifically to paranoia (ß = 0.32), whereas persecution uniquely related to poor social functioning (ß = -0.29). CONCLUSION: These results demonstrate the reliability and validity of the RGPTS, though its scales related more weakly to severity in CHR individuals. The RGPTS may be useful in future work aiming to develop symptom-specific models of emerging paranoia in CHR individuals.

Using dimensionality-reduction techniques to understand the organization of psychotic symptoms in persistent psychotic illness and first episode psychosis.

Psychotic disorders are highly heterogeneous. Understanding relationships between symptoms will be relevant to their underlying pathophysiology. We apply dimensionality-reduction methods across two unique samples to characterize the patterns of symptom organization. We analyzed publicly-available data from 153 participants diagnosed with schizophrenia or schizoaffective disorder (fBIRN Data Repository and the Consortium for Neuropsychiatric Phenomics), as well as 636 first-episode psychosis (FEP) participants from the Prevention and Early Intervention Program for Psychosis (PEPP-Montreal). In all participants, the Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were collected. Multidimensional scaling (MDS) combined with cluster analysis was applied to SAPS and SANS scores across these two groups of participants. MDS revealed relationships between items of SAPS and SANS. Our application of cluster analysis to these results identified: 1 cluster of disorganization symptoms, 2 clusters of hallucinations/delusions, and 2 SANS clusters (asocial and apathy, speech and affect). Those reality distortion items which were furthest from auditory hallucinations had very weak to no relationship with hallucination severity. Despite being at an earlier stage of illness, symptoms in FEP presentations were similarly organized. While hallucinations and delusions commonly co-occur, we found that their specific themes and content sometimes travel together and sometimes do not. This has important implications, not only for treatment, but also for research-particularly efforts to understand the neurocomputational and pathophysiological mechanism underlying delusions and hallucinations.

Learning to Discern the Voices of Gods, Spirits, Tulpas, and the Dead.

There are communities in which hearing voices frequently is common and expected, and in which participants are not expected to have a need for care. This paper compares the ideas and practices of these communities. We observe that these communities utilize cultural models to identify and to explain voice-like events-and that there are some common features to these models across communities. All communities teach participants to "discern," or identify accurately, the legitimate voice of the spirit or being who speaks. We also observe that there are roughly two methods taught to participants to enable them to experience spirits (or other invisible beings): trained attention to inner experience, and repeated speech to the invisible other. We also observe that all of these communities model a learning process in which the ability to hear spirit (or invisible others) becomes more skilled with practice, and in which what they hear becomes clearer over time. Practice-including the practice of discernment-is presumed to change experience. We also note that despite these shared cultural ideas and practices, there is considerable individual variation in experience-some of which may reflect psychotic process, and some perhaps not. We suggest that voice-like events in this context may be shaped by cognitive expectation and trained practice as well as an experiential pathway. We also suggest that researchers could explore these common features both as a way to help those struggling with psychosis, and to consider the possibility that expectations and practice may affect the voice-hearing experience.

A pilot randomized controlled trial of ketamine in Borderline Personality Disorder.

This study is the first randomized controlled trial to test the effects of ketamine in Borderline Personality Disorder (BPD). BPD remains undertreated in the community and no medication has FDA approval for this indication. People with BPD experience chronic mood disturbances with depressed mood, suicidal ideation, and severe social difficulties. In this double-blind, randomized controlled pilot study, we tested the effects of one infusion of ketamine (0.5 mg/kg, n = 10) or the psychoactive comparator drug midazolam (0.04 mg/kg, n = 12) in adults with BPD. Infusions were well tolerated in both groups. Dissociative symptoms during infusion were more intense with ketamine than midazolam (t(12.3) = 3.61, p = 0.01), but they resolved by 40 min after infusion in both groups. Post-infusion adverse events were at the expected low levels in both groups. For our primary outcome measure of suicidal ideation and our secondary outcome measure of depression, we found numerical reduction but not significant group or group x timepoint difference (p > 0.05). For our secondary outcome measures of anxiety and BPD symptoms, we did not observe group or group x timepoint differences. There was a group x timepoint effect for socio-occupational functioning (F(1,20.12) = 5.16, p = 0.03, at Day 14, ketamine group showed more improvement than midazolam group). An exploratory analysis revealed that improvement in socio-occupational functioning was correlated with improvement in depression in the ketamine group (r(8) = 0.65, p = 0.04) but not midazolam group (r(9) = 0.41, p = 0.216). This pilot study provides the first randomized controlled evidence of the effects of antidepressant-dosed ketamine in people with BPD. Our results provide reason for optimism that antidepressant-dosed ketamine will be well-tolerated in larger studies and may provide clinical benefit for mood symptoms and related impairments in people with BPD.