Associations of alcohol and cannabis use with change in posttraumatic stress disorder and depression symptoms over time in recently trauma-exposed individuals.

BACKGROUND: Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians. METHODS: In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance. RESULTS: Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12. CONCLUSIONS: Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

Sex-dependent differences in vulnerability to early risk factors for posttraumatic stress disorder: results from the AURORA study.

BACKGROUND: Knowledge of sex differences in risk factors for posttraumatic stress disorder (PTSD) can contribute to the development of refined preventive interventions. Therefore, the aim of this study was to examine if women and men differ in their vulnerability to risk factors for PTSD. METHODS: As part of the longitudinal AURORA study, 2924 patients seeking emergency department (ED) treatment in the acute aftermath of trauma provided self-report assessments of pre- peri- and post-traumatic risk factors, as well as 3-month PTSD severity. We systematically examined sex-dependent effects of 16 risk factors that have previously been hypothesized to show different associations with PTSD severity in women and men. RESULTS: Women reported higher PTSD severity at 3-months post-trauma. Z-score comparisons indicated that for five of the 16 examined risk factors the association with 3-month PTSD severity was stronger in men than in women. In multivariable models, interaction effects with sex were observed for pre-traumatic anxiety symptoms, and acute dissociative symptoms; both showed stronger associations with PTSD in men than in women. Subgroup analyses suggested trauma type-conditional effects. CONCLUSIONS: Our findings indicate mechanisms to which men might be particularly vulnerable, demonstrating that known PTSD risk factors might behave differently in women and men. Analyses did not identify any risk factors to which women were more vulnerable than men, pointing toward further mechanisms to explain women's higher PTSD risk. Our study illustrates the need for a more systematic examination of sex differences in contributors to PTSD severity after trauma, which may inform refined preventive interventions.

Structural inequities contribute to racial/ethnic differences in neurophysiological tone, but not threat reactivity, after trauma exposure.

Considerable racial/ethnic disparities persist in exposure to life stressors and socioeconomic resources that can directly affect threat neurocircuitry, particularly the amygdala, that partially mediates susceptibility to adverse posttraumatic outcomes. Limited work to date, however, has investigated potential racial/ethnic variability in amygdala reactivity or connectivity that may in turn be related to outcomes such as post-traumatic stress disorder (PTSD). Participants from the AURORA study (n = 283), a multisite longitudinal study of trauma outcomes, completed functional magnetic resonance imaging and psychophysiology within approximately two-weeks of trauma exposure. Seed-based amygdala connectivity and amygdala reactivity during passive viewing of fearful and neutral faces were assessed during fMRI. Physiological activity was assessed during Pavlovian threat conditioning. Participants also reported the severity of posttraumatic symptoms 3 and 6 months after trauma. Black individuals showed lower baseline skin conductance levels and startle compared to White individuals, but no differences were observed in physiological reactions to threat. Further, Hispanic and Black participants showed greater amygdala connectivity to regions including the dorsolateral prefrontal cortex (PFC), dorsal anterior cingulate cortex, insula, and cerebellum compared to White participants. No differences were observed in amygdala reactivity to threat. Amygdala connectivity was associated with 3-month PTSD symptoms, but the associations differed by racial/ethnic group and were partly driven by group differences in structural inequities. The present findings suggest variability in tonic neurophysiological arousal in the early aftermath of trauma between racial/ethnic groups, driven by structural inequality, impacts neural processes that mediate susceptibility to later PTSD symptoms.

Internal capsule microstructure mediates the relationship between childhood maltreatment and PTSD following adulthood trauma exposure.

Childhood trauma is a known risk factor for trauma and stress-related disorders in adulthood. However, limited research has investigated the impact of childhood trauma on brain structure linked to later posttraumatic dysfunction. We investigated the effect of childhood trauma on white matter microstructure after recent trauma and its relationship with future posttraumatic dysfunction among trauma-exposed adult participants (n = 202) recruited from emergency departments as part of the AURORA Study. Participants completed self-report scales assessing prior childhood maltreatment within 2-weeks in addition to assessments of PTSD, depression, anxiety, and dissociation symptoms within 6-months of their traumatic event. Fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI) collected at 2-weeks and 6-months was used to index white matter microstructure. Childhood maltreatment load predicted 6-month PTSD symptoms (b = 1.75, SE = 0.78, 95% CI = [0.20, 3.29]) and inversely varied with FA in the bilateral internal capsule (IC) at 2-weeks (p = 0.0294, FDR corrected) and 6-months (p = 0.0238, FDR corrected). We observed a significant indirect effect of childhood maltreatment load on 6-month PTSD symptoms through 2-week IC microstructure (b = 0.37, Boot SE = 0.18, 95% CI = [0.05, 0.76]) that fully mediated the effect of childhood maltreatment load on PCL-5 scores (b = 1.37, SE = 0.79, 95% CI = [-0.18, 2.93]). IC microstructure did not mediate relationships between childhood maltreatment and depressive, anxiety, or dissociative symptomatology. Our findings suggest a unique role for IC microstructure as a stable neural pathway between childhood trauma and future PTSD symptoms following recent trauma. Notably, our work did not support roles of white matter tracts previously found to vary with PTSD symptoms and childhood trauma exposure, including the cingulum bundle, uncinate fasciculus, and corpus callosum. Given the IC contains sensory fibers linked to perception and motor control, childhood maltreatment might impact the neural circuits that relay and process threat-related inputs and responses to trauma.

Returning Individual Research Results from Digital Phenotyping in Psychiatry.

Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants' locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant's real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas.

Multiracial Reading the Mind in the Eyes Test (MRMET): An inclusive version of an influential measure.

Can an inclusive test of face cognition meet or exceed the psychometric properties of a prominent less inclusive test? Here, we norm and validate an updated version of the influential Reading the Mind in the Eyes Test (RMET), a clinically significant neuropsychiatric paradigm that has long been used to assess theory of mind and social cognition. Unlike the RMET, our Multiracial Reading the Mind in the Eyes Test (MRMET) incorporates racially inclusive stimuli, nongendered answer choices, ground-truth referenced answers, and more accessible vocabulary. We show, via a series of large datasets, that the MRMET meets or exceeds RMET across major psychometric indices. Moreover, the reliable signal captured by the two tests is statistically indistinguishable, evidence for full interchangeability. We thus present the MRMET as a high-quality, inclusive, normed and validated alternative to the RMET, and as a case in point that inclusivity in psychometric tests of face cognition is an achievable aim. The MRMET test and our normative and validation data sets are openly available under a CC-BY-SA 4.0 license at osf.io/ahq6n.

Hippocampal Threat Reactivity Interacts with Physiological Arousal to Predict PTSD Symptoms.

Hippocampal impairments are reliably associated with post-traumatic stress disorder (PTSD); however, little research has characterized how increased threat-sensitivity may interact with arousal responses to alter hippocampal reactivity, and further how these interactions relate to the sequelae of trauma-related symptoms. In a sample of individuals recently exposed to trauma (N=116, 76 Female), we found that PTSD symptoms at 2-weeks were associated with decreased hippocampal responses to threat as assessed with functional magnetic resonance imaging (fMRI). Further, the relationship between hippocampal threat sensitivity and PTSD symptomology only emerged in individuals who showed transient, high threat-related arousal, as assayed by an independently collected measure of Fear Potentiated Startle. Collectively, our finding suggests that development of PTSD is associated with threat-related decreases in hippocampal function, due to increases in fear-potentiated arousal.Significance StatementAlterations in hippocampal function linked to threat-related arousal are reliably associated with post-traumatic stress disorder (PTSD); however, how these alterations relate to the sequelae of trauma-related symptoms is unknown. Prior models based on non-trauma samples suggest that arousal may impact hippocampal neurophysiology leading to maladaptive behavior. Here we show that decreased hippocampal threat sensitivity interacts with fear-potentiated startle to predict PTSD symptoms. Specifically, individuals with high fear-potentiated startle and low, transient hippocampal threat sensitivity showed the greatest PTSD symptomology. These findings bridge literatures of threat-related arousal and hippocampal function to better understand PTSD risk.

Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision.

STUDY OBJECTIVE: To derive and initially validate a brief bedside clinical decision support tool that identifies emergency department (ED) patients at high risk of substantial, persistent posttraumatic stress symptoms after a motor vehicle collision. METHODS: Derivation (n=1,282, 19 ED sites) and validation (n=282, 11 separate ED sites) data were obtained from adults prospectively enrolled in the Advancing Understanding of RecOvery afteR traumA study who were discharged from the ED after motor vehicle collision-related trauma. The primary outcome was substantial posttraumatic stress symptoms at 3 months (Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 ≥38). Logistic regression derivation models were evaluated for discriminative ability using the area under the curve and the accuracy of predicted risk probabilities (Brier score). Candidate posttraumatic stress predictors assessed in these models (n=265) spanned a range of sociodemographic, baseline health, peritraumatic, and mechanistic domains. The final model selection was based on performance and ease of administration. RESULTS: Significant 3-month posttraumatic stress symptoms were common in the derivation (27%) and validation (26%) cohort. The area under the curve and Brier score of the final 8-question tool were 0.82 and 0.14 in the derivation cohort and 0.76 and 0.17 in the validation cohort. CONCLUSION: This simple 8-question tool demonstrates promise to risk-stratify individuals with substantial posttraumatic stress symptoms who are discharged to home after a motor vehicle collision. Both external validation of this instrument, and work to further develop more accurate tools, are needed. Such tools might benefit public health by enabling the conduct of preventive intervention trials and assisting the growing number of EDs that provide services to trauma survivors aimed at promoting psychological recovery.

Ecological Momentary Assessment of Cognition in Clinical and Community Samples: Reliability and Validity Study.

BACKGROUND: The current methods of evaluating cognitive functioning typically rely on a single time point to assess and characterize an individual's performance. However, cognitive functioning fluctuates within individuals over time in relation to environmental, psychological, and physiological contexts. This limits the generalizability and diagnostic utility of single time point assessments, particularly among individuals who may exhibit large variations in cognition depending on physiological or psychological context (eg, those with type 1 diabetes [T1D], who may have fluctuating glucose concentrations throughout the day). OBJECTIVE: We aimed to report the reliability and validity of cognitive ecological momentary assessment (EMA) as a method for understanding between-person differences and capturing within-person variation in cognition over time in a community sample and sample of adults with T1D. METHODS: Cognitive performance was measured 3 times a day for 15 days in the sample of adults with T1D (n=198, recruited through endocrinology clinics) and for 10 days in the community sample (n=128, recruited from TestMyBrain, a web-based citizen science platform) using ultrabrief cognitive tests developed for cognitive EMA. Our cognitive EMA platform allowed for remote, automated assessment in participants' natural environments, enabling the measurement of within-person cognitive variation without the burden of repeated laboratory or clinic visits. This allowed us to evaluate reliability and validity in samples that differed in their expected degree of cognitive variability as well as the method of recruitment. RESULTS: The results demonstrate excellent between-person reliability (ranging from 0.95 to 0.99) and construct validity of cognitive EMA in both the sample of adults with T1D and community sample. Within-person reliability in both samples (ranging from 0.20 to 0.80) was comparable with that observed in previous studies in healthy older adults. As expected, the full-length baseline and EMA versions of TestMyBrain tests correlated highly with one another and loaded together on the expected cognitive domains when using exploratory factor analysis. Interruptions had higher negative impacts on accuracy-based outcomes (ß=-.34 to -.26; all P values <.001) than on reaction time-based outcomes (ß=-.07 to -.02; P<.001 to P=.40). CONCLUSIONS: We demonstrated that ultrabrief mobile assessments are both reliable and valid across 2 very different clinic versus community samples, despite the conditions in which cognitive EMAs are administered, which are often associated with more noise and variability. The psychometric characteristics described here should be leveraged appropriately depending on the goals of the cognitive assessment (eg, diagnostic vs everyday functioning) and the population being studied.

To BYOD or not: Are device latencies important for bring-your-own-device (BYOD) smartphone cognitive testing?

Studies using remote cognitive testing must make a critical decision: whether to allow participants to use their own devices or to provide participants with a study-specific device. Bring-your-own-device (BYOD) studies have several advantages including increased accessibility, potential for larger sample sizes, and reduced participant burden. However, BYOD studies offer little control over device performance characteristics that could potentially influence results. In particular, response times measured by each device not only include the participant's true response time, but also latencies of the device itself. The present study investigated two prominent sources of device latencies that pose significant risks to data quality: device display output latency and touchscreen input latency. We comprehensively tested 26 popular smartphones ranging in price from < $100 to $1000+ running either Android or iOS to determine if hardware and operating system differences led to appreciable device latency variability. To accomplish this, a custom-built device called the Latency and Timing Assessment Robot (LaTARbot) measured device display output and capacitive touchscreen input latencies. We found considerable variability across smartphones in display and touch latencies which, if unaccounted for, could be misattributed as individual or group differences in response times. Specifically, total device (sum of display and touch) latencies ranged from 35 to 140 ms. We offer recommendations to researchers to increase the precision of data collection and analysis in the context of remote BYOD studies.

Socio-demographic and trauma-related predictors of depression within eight weeks of motor vehicle collision in the AURORA study.

BACKGROUND: This is the first report on the association between trauma exposure and depression from the Advancing Understanding of RecOvery afteR traumA(AURORA) multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience. METHODS: We focus on participants presenting at EDs after a motor vehicle collision (MVC), which characterizes most AURORA participants, and examine associations of participant socio-demographics and MVC characteristics with 8-week depression as mediated through peritraumatic symptoms and 2-week depression. RESULTS: Eight-week depression prevalence was relatively high (27.8%) and associated with several MVC characteristics (being passenger v. driver; injuries to other people). Peritraumatic distress was associated with 2-week but not 8-week depression. Most of these associations held when controlling for peritraumatic symptoms and, to a lesser degree, depressive symptoms at 2-weeks post-trauma. CONCLUSIONS: These observations, coupled with substantial variation in the relative strength of the mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated in more in-depth analyses of the rich and evolving AURORA database to find new targets for intervention and new tools for risk-based stratification following trauma exposure.

Socio-demographic and trauma-related predictors of PTSD within 8 weeks of a motor vehicle collision in the AURORA study.

This is the initial report of results from the AURORA multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience. We focus on n = 666 participants presenting to EDs following a motor vehicle collision (MVC) and examine associations of participant socio-demographic and participant-reported MVC characteristics with 8-week posttraumatic stress disorder (PTSD) adjusting for pre-MVC PTSD and mediated by peritraumatic symptoms and 2-week acute stress disorder (ASD). Peritraumatic Symptoms, ASD, and PTSD were assessed with self-report scales. Eight-week PTSD prevalence was relatively high (42.0%) and positively associated with participant sex (female), low socioeconomic status (education and income), and several self-report indicators of MVC severity. Most of these associations were entirely mediated by peritraumatic symptoms and, to a lesser degree, ASD, suggesting that the first 2 weeks after trauma may be a uniquely important time period for intervening to prevent and reduce risk of PTSD. This observation, coupled with substantial variation in the relative strength of mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated with more in-depth analyses of the rich and evolving AURORA data.

Prior histories of posttraumatic stress disorder and major depression and their onset and course in the three months after a motor vehicle collision in the AURORA study.

BACKGROUND: A better understanding of the extent to which prior occurrences of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) predict psychopathological reactions to subsequent traumas might be useful in targeting posttraumatic preventive interventions. METHODS: Data come from 1306 patients presenting to 29 U.S. emergency departments (EDs) after a motor vehicle collision (MVC) in the advancing understanding of recovery after trauma study. Patients completed self-reports in the ED and 2-weeks, 8-weeks, and 3-months post-MVC. Associations of pre-MVC probable PTSD and probable MDE histories with subsequent 3-months post-MVC probable PTSD and probable MDE were examined along with mediation through intervening peritraumatic, 2-, and 8-week disorders. RESULTS: 27.6% of patients had 3-month post-MVC probable PTSD and/or MDE. Pre-MVC lifetime histories of these disorders were not only significant (relative risk = 2.6-7.4) but were dominant (63.1% population attributable risk proportion [PARP]) predictors of this 3-month outcome, with 46.6% prevalence of the outcome among patients with pre-MVC disorder histories versus 9.9% among those without such histories. The associations of pre-MVC lifetime disorders with the 3-month outcome were mediated largely by 2- and 8-week probable PTSD and MDE (PARP decreasing to 22.8% with controls for these intervening disorders). Decomposition showed that pre-MVC lifetime histories predicted both onset and persistence of these intervening disorders as well as the higher conditional prevalence of the 3-month outcome in the presence of these intervening disorders. CONCLUSIONS: Assessments of pre-MVC PTSD and MDE histories and follow-ups at 2 and 8 weeks could help target early interventions for psychopathological reactions to MVCs.

Associations Between Childhood Trauma Characteristics and Theory of Mind in Adults: Results From a Large, Diverse Sample.

Theory of mind (ToM) is an essential social cognitive process encompassing abilities to represent and understand others' mental states. Although previous reports linked childhood trauma to social cognitive deficits, how characteristics of trauma exposure, such as subtype or timing, affect ToM remains unaddressed. Using data from a diverse adult sample (n = 2200), we tested whether exposure type and first exposure timing of common childhood trauma associated with ToM. Neither interpersonal loss (ß = - 0.25, p = 0.170, [- 0.61, 0.10]) nor child maltreatment (ß = - 0.21, p = 0.369, [- 0.66, 0.25]) was associated with lower ToM. There was no effect of timing of age at which trauma was experienced (F = 2.19, p = 0.087). While we did not identify age-dependent effects, future studies should examine links between timing or chronicity of prospectively reported childhood trauma and social cognition. Understanding of how childhood experiences shape ToM could reveal mechanisms underlying social cognition development and inform prevention efforts.

Social cognition or social class and culture? On the interpretation of differences in social cognitive performance.

BACKGROUND: The ability to understand others' mental states carries profound consequences for mental and physical health, making efforts at validly and reliably assessing mental state understanding (MSU) of utmost importance. However, the most widely used and current NIMH-recommended task for assessing MSU - the Reading the Mind in the Eyes Task (RMET) - suffers from potential assessment issues, including reliance on a participant's vocabulary/intelligence and the use of culturally biased stimuli. Here, we evaluate the impact of demographic and sociocultural factors (age, gender, education, ethnicity, race) on the RMET and other social and non-social cognitive tasks in an effort to determine the extent to which the RMET may be unduly influenced by participant characteristics. METHODS: In total, 40 248 international, native-/primarily English-speaking participants between the ages of 10 and 70 completed one of five measures on TestMyBrain.org: RMET, a shortened version of RMET, a multiracial emotion identification task, an emotion discrimination task, and a non-social/non-verbal processing speed task (digit symbol matching). RESULTS: Contrary to other tasks, performance on the RMET increased across the lifespan. Education, race, and ethnicity explained more variance in RMET performance than the other tasks, and differences between levels of education, race, and ethnicity were more pronounced for the RMET than the other tasks such that more highly educated, non-Hispanic, and White/Caucasian individuals performed best. CONCLUSIONS: These data suggest that the RMET may be unduly influenced by social class and culture, posing a serious challenge to assessing MSU in clinical populations given shared variance between social status and psychiatric illness.

When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span.

Understanding how and when cognitive change occurs over the life span is a prerequisite for understanding normal and abnormal development and aging. Most studies of cognitive change are constrained, however, in their ability to detect subtle, but theoretically informative life-span changes, as they rely on either comparing broad age groups or sparse sampling across the age range. Here, we present convergent evidence from 48,537 online participants and a comprehensive analysis of normative data from standardized IQ and memory tests. Our results reveal considerable heterogeneity in when cognitive abilities peak: Some abilities peak and begin to decline around high school graduation; some abilities plateau in early adulthood, beginning to decline in subjects' 30s; and still others do not peak until subjects reach their 40s or later. These findings motivate a nuanced theory of maturation and age-related decline, in which multiple, dissociable factors differentially affect different domains of cognition.

Face recognition's practical relevance: Social bonds, not social butterflies.

Research on individual differences in face recognition has provided important foundational insights: their broad range, cognitive specificity, strong heritability, and resilience to change. Elusive, however, has been the key issue of practical relevance: do these individual differences correlate with aspects of life that go beyond the recognition of faces, per se? Though often assumed, especially in social realms, such correlates remain largely theoretical, without empirical support. Here, we investigate an array of potential social correlates of face recognition. We establish social relationship quality as a reproducible correlate. This link generalises across face recognition tasks and across independent samples. In contrast, we detect no robust association with the sheer quantity of social connections, whether measured directly via number of social contacts or indirectly via extraversion-related personality indices. These findings document the existence of a key social correlate of face recognition and provide some of the first evidence to support its practical relevance. At the same time, they challenge the naive assumption that face recognition relates equally to all social outcomes. In contrast, they suggest a focused link of face recognition to the quality, not quantity, of one's social connections.

Large-scale citizen science reveals predictors of sensorimotor adaptation.

Sensorimotor adaptation is essential for keeping our movements well calibrated in response to changes in the body and environment. For over a century, researchers have studied sensorimotor adaptation in laboratory settings that typically involve small sample sizes. While this approach has proved useful for characterizing different learning processes, laboratory studies are not well suited for exploring the myriad of factors that may modulate human performance. Here, using a citizen science website, we collected over 2,000 sessions of data on a visuomotor rotation task. This unique dataset has allowed us to replicate, reconcile and challenge classic findings in the learning and memory literature, as well as discover unappreciated demographic constraints associated with implicit and explicit processes that support sensorimotor adaptation. More generally, this study exemplifies how a large-scale exploratory approach can complement traditional hypothesis-driven laboratory research in advancing sensorimotor neuroscience.

Avoidant/restrictive food intake disorder differs from anorexia nervosa in delay discounting.

BACKGROUND: Avoidant/restrictive food intake disorder (ARFID) and anorexia nervosa (AN) are the two primary restrictive eating disorders; however, they are driven by differing motives for inadequate dietary intake. Despite overlap in restrictive eating behaviors and subsequent malnutrition, it remains unknown if ARFID and AN also share commonalities in their cognitive profiles, with cognitive alterations being a key identifier of AN. Discounting the present value of future outcomes with increasing delay to their expected receipt represents a core cognitive process guiding human decision-making. A hallmark cognitive characteristic of individuals with AN (vs. healthy controls [HC]) is reduced discounting of future outcomes, resulting in reduced impulsivity and higher likelihood of favoring delayed gratification. Whether individuals with ARFID display a similar reduction in delay discounting as those with AN (vs. an opposing bias towards increased delay discounting or no bias) is important in informing transdiagnostic versus disorder-specific cognitive characteristics and optimizing future intervention strategies. METHOD: To address this research question, 104 participants (ARFID: n = 57, AN: n = 28, HC: n = 19) completed a computerized Delay Discounting Task. Groups were compared by their delay discounting parameter (ln)k. RESULTS: Individuals with ARFID displayed a larger delay discounting parameter than those with AN, indicating steeper delay discounting (M ± SD = -6.10 ± 2.00 vs. -7.26 ± 1.73, p = 0.026 [age-adjusted], Hedges' g = 0.59), with no difference from HC (p = 0.514, Hedges' g = -0.35). CONCLUSION: Our findings provide a first indication of distinct cognitive profiles among the two primary restrictive eating disorders. The present results, together with future research spanning additional cognitive domains and including larger and more diverse samples of individuals with ARFID (vs. AN), will contribute to identifying maintenance mechanisms that are unique to each disorder as well as contribute to the optimization and tailoring of treatment strategies across the spectrum of restrictive eating disorders.

Avoidant/restrictive food intake disorder (ARFID) and anorexia nervosa (AN) are both restrictive eating disorders. However, the reasons for restricting food intake differ between the two diagnoses. A key question in further understanding similarities and differences between ARFID and AN is to understand whether individuals with these disorders process information and make decisions in similar or distinct ways. When humans decide between two different outcomes (e.g., a smaller immediate or a larger delayed reward), outcomes decrease in their value the farther in the future we expect to receive them (delay discounting). Individuals with AN exhibit a reduced discounting of future outcomes, which makes them more likely to forego immediate gratification for later rewards. However, whether this holds true for individuals with ARFID too (or whether they show the opposite or no bias) is unknown. Our investigation is the first to compare delay discounting between individuals with ARFID, AN, and healthy controls (HC). Our results show that individuals with ARFID show more delay discounting than those with AN, with no difference from HC. Knowing how rewards are being chosen and decisions made (and knowing differences between diagnoses) will be helpful in further optimizing and tailoring treatments for restrictive eating disorders.

The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry.

An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.