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
Exploring Childhood irritability and mood
Irritability—operationalized as an increased proneness to anger and frustration (for one’s age and out of proportion to the situation)—is among the most common reasons that youth receive psychiatric evaluation and care. Despite this and an association between irritability and increased risk for depression, the cognitive and neural processes underlying irritability are not well understood. Thus, the current study will use electroencephalography (EEG) to examine the unique and interacting roles of reward processing, emotional reactivity, and inhibitory control processes across a range of irritability severity in 7-12-year-old children. Further, the study will test whether alterations in these processes predict worsening of irritability and depression over time.
Parsing Anhedonia in Adolescents: An ERP Study
Among adolescents, anhedonia—the reduced ability to experience pleasure or reduced reactivity to pleasurable cues — is a transdiagnostic risk factor implicated in psychiatric illness, treatment non-response, and suicidal behaviors. However, anhedonia is not a monolithic entity, as it reflects deficits in how rewards are ‘wanted’ (anticipatory behavior), ‘liked’ (consummatory behavior), and/or ‘learned’ (reinforcement learning processes). Therefore, the present study will: (1) classify individuals from a large sample of adolescents into different anhedonia biotypes based on their neurophysiological response to these different reward - related processes, (2) determine clinical links with these biotypes, and (3) examine whether these separate biotypes of individuals exhibit a different course and progression of psychiatric and psychosocial dysfunction over time.
Towards Identification of Neural Predictors of Adolescent Depression
Children of depressed parents are two- to three- times more likely to develop depression than children of never-depressed parents. In the current study, healthy low-risk and high-risk (i.e., with a maternal history of MDD) adolescents aged 12-14 years complete a multimodal assessment using state-of-the-art neuroimaging techniques (EEG, fMRI, MRS) to identify neural markers that prospectively predict depression over a 2-year period. Results from this project may contribute to the development of a biobehavioral model of depression in adolescents. This work is funded by the Klingenstein Third Generation Foundation, Dana Foundation: Clinical Neuroscience Research Grant, and Tommy Fuss Fund.
Boston Adolescent Neuroimaging of Depression and Anxiety
The Human Connectome Project is a multi-institutional project seeking to build a comprehensive map of neural connections in the human brain, and the project goal is to determine whether we can identify reliable biomarkers for depression and anxiety disorders in adolescents, which then can then be used to more accurately predict clinical outcomes. The study is supported through funding from the National Institute of Mental Health.
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. Therefore, the present study 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.
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.
Predicting Internet-Based Treatment Response for Major Depressive Disorder
As many as 53% of students report experiencing depression during college, and these depressive episodes are associated with a higher frequency of academic problems, comorbidity, and suicide. Although there are effective options for treatment, the majority of individuals (>70%) do not pursue services, and even for those who do, response rates remain modest (~40-50%). As a means of increasing accessibility to treatment, internet-based interventions for depression have been developed and tested. Despite increased availability, response to internet-based interventions continues to vary substantially, and failed treatment often contributes to persistence and worsening of symptoms. Therefore, identifying individuals with a high likelihood of responding to internet-based treatment would represent a major advance and address a critical unmet need. This research is supported through funding from the National Institute of Mental Health.