Research Overview
The Translational Research on Affective Disorders and Suicide Laboratory utilizes a multimodal and multidisciplinary approach (e.g., laboratory-based experiments, EEG/ERPs, fMRI) to determine why depressive symptoms unfold, how self-injurious and suicidal behaviors develop, and what predicts treatment response. As a whole, the research aims to better understand the putative mechanisms that may improve early identification of and treatment for adolescent depression and suicidal behaviors.
Director: Randy P. Auerbach, Ph.D., ABPP
Major Depressive disorder
Mindful Brain Project
Adolescent major depressive disorder (MDD) is common and debilitating. Presently, gold-standard treatments are only effective for approximately half of patients, underscoring the need to develop novel interventions. Rumination, the tendency to perseverate about depressive symptoms, contributes to MDD onset and predicts treatment non-response and relapse. Mindfulness meditation, which trains attentional focus to the present moment, reduces perseverative thinking, ruminative tendencies, and depression symptoms. However, MDD symptoms, including reduced motivation, inattention, and lack of self-efficacy, may impede a patient’s ability to successfully acquire and utilize mindfulness strategies to mitigate rumination. We will use real-time fMRI neurofeedback to enhance the acquisition and utilization of mindfulness skills better to target neural activity (e.g., DMN hyperconnectivity), rumination, and depressive symptoms. This project is supported through funds received from the National Institute of Mental Health and Tommy Fuss Fund (MPIs: Dr. Randy P. Auerbach and Dr. Susan Whitfield-Gabrieli).
Socioemotional Predictors of Adolescent Depression
Adolescence is a period of heightened risk for major depressive disorder (MDD). During the transition from childhood to adolescence, there is increased autonomy from parents and greater reliance on peer relationships. The overarching aim of this multisite study (Columbia University and Northwestern University) is to identify socioemotional processes across different units of analysis—clinical, behavioral, real-time monitoring (e.g., passive sensor, EMA), and neural markers (e.g., eye tracking, EEG/ERPs, MRI)—that lead to the escalation of depression symptoms and MDD. This research is supported though funding from the National Institute of Mental Health awarded to Dr. Randy P. Auerbach, Dr. Stewart Shankman, and Dr. David Pagliaccio.
Suicidal Thoughts and Behaviors
Developing a Digitally Assisted Risk Reduction Platform for High-Risk, Suicidal Youth
Despite efforts to prevent suicide, rates continue to surge. Personal smartphones provide a unique understanding of risk factors among high-risk individuals, and thus, this project aims to enhance the effectiveness of preventative health care delivery to youth at risk for suicide by developing a comprehensive digital platform that allows practitioners to integrate mobile sensing data and client communication tools for management of their patients. This two-part project first involves using a rapid, iterative human-centered design to enhance the accessibility of Vira—the digital interface for practitioners and youth patients. Then, high-risk adolescents within an intensive outpatient setting will participate in a randomized control trial to test whether Vira accelerates skill acquisition and reduces suicidal thoughts and behaviors. This research is supported by funding from the National Institute of Mental Health awarded to Dr. Randy P. Auerbach and Dr. Nicholas B. Allen.
Extracting Positive Valence System Constructs from Electronic Health Records to Predict Suicide in Youth
Despite efforts to identify sociodemographic and diagnostic risk factors that predict suicide and suicidal thoughts and behaviors (STB) remains difficult. Recent studies suggest that electronic health record (EHR) data analytics can help predict suicidal behaviors. Accordingly, our study will use deep learning-based natural language processing to identify Positive Valence System constructs from EHR and innovative machine learning approaches to predict suicidal behaviors in youth. This research is supported by funding from the National Institute of Mental Health awarded to Dr. Fu-Chiang (Rich) Tsui, Dr. Neal Ryan, and & Dr. Randy P. Auerbach.
GET ActivE
Suicide rates among Black and Hispanic adolescents are increasing faster than among White youth in the United States. Thus, there is a need for culturally appropriate interventions that target risk factors for suicidal thoughts and behaviors (STB) among a growing population of racially diverse youth. Anhedonia, defined as the loss of interest or pleasure, is a core feature of depression and an independent risk factor for STB in youth. Anhedonia can be effectively treated using Behavioral Activation (BA) therapy, an intervention that uses positive reinforcement to increase engagement in valued activities and experiences of reward. The BA model is well suited for adaptation to digital platforms, which can provide objective data on activity patterns. This study will tailor and test a health coach-supported, digital BA intervention to target anhedonia in a diverse sample of youth. If successful, this study has the potential to offer a low-cost and scalable behavioral intervention that may decrease the risk of suicide among at-risk youth. This research is supported by the Center of Excellence (P50) grant funded through the National Institute of Mental Health.
Identifying Children at Suicide Risk Following Emergency Department Discharge
Rates of suicide have been increasing among children ages 8-12-years-old, however, risk factors facilitating the transition from suicidal ideation to action remain unclear. The current study aims to delineate developmental, environmental, and internal factors that may confer increased risk for suicide following discharge from the pediatric Emergency Department. Additionally, within a subset of these children, MRI data will be acquired to probe neural activation within the context of reward processing as well as dopamine levels through neuromelanin scans. These data may help to understand specific neural indicators of prior and future suicide risk. This research is supported through funding from the Tommy Fuss Fund and Bender-Fishbein Foundation.
Mobile Assessment for the Prediction of Suicide (MAPS)
Suicide is the second leading cause of death among adolescents, and despite this pressing public health crisis, little is known about factors that confer imminent risk for suicide. However, recent advancements in mobile technologies afford the capacity to monitor known risk factors—including emotional distress, social dysfunction, and sleep disturbance—which has the potential to revolutionize our insight and clinical management of short-term risk for suicidal thoughts and behaviors. This multisite study—data collection at Columbia University and the University of Pittsburgh—will leverage adolescents’ naturalistic use of smartphone technology, along with advanced signal processing and computational modeling approaches, to identify promising short-term predictors of suicide among high-risk adolescents, which ultimately, may reduce needless loss of life. This research is supported though funding from the National Institute of Mental Health award to Dr. Randy P. Auerbach and Dr. Nicholas B. Allen.
Smartphones and the Brain: Predicting Adolescent Suicide
Suicide is a major public health crisis and is the second leading cause of death among 10-24-year-olds. It remains unclear, however, why certain depressed adolescents engage in suicidal behaviors. Accordingly, the current study uses a multimodal approach—including neuroimaging, passive smartphone sensing, ecological momentary assessment, and clinical interviewing methods—to clarify factors that may facilitate the transition from ideation to action among adolescent discharged from the pediatric department. This research is supported though funding awarded to Dr. David Pagliaccio from the National Institute of Mental Health and the American Foundation for Suicide Prevention.
College Mental Health
WHO World Mental Health International College student initiative
The WHO World Mental Health International College Student (WMH-ICS) Initiative aims to obtain accurate longitudinal cross-national information about the prevalence and correlates of mental, substance, and behavioral disorders among college students worldwide. The main goals of the project include: assessing unmet need for treatment, targeting students in need of outreach, and evaluating model preventive and clinical interventions. The initial phase of the project consists of the implementation of an online survey framework with representative samples of college students to estimate the prevalence of mental disorders, associated impairments, adverse social and academic consequences, and patterns of help-seeking. During the second phase of the project, the initiative will use the protocol developed for implementing these surveys to target students in need of outreach and will evaluate the effects of interventions implemented based on this targeting.