Our Research

Anxiety, Mood, Addiction Research Collaborative

Discover More

Identifying Neural Mechanisms of PTSD Symptom Reduction Induced by Combined Estrogen and Prolonged Exposure Therapy

1R61MH111907-01 – National Institute of Mental Health

This study aims to first identify the optimal estradiol (E2) dose that best engages the fear extinction network among healthy women using oral contraceptives. The second objective is to then evaluate the impact of this optimal E2 dose, when administered in conjunction with 5 sessions of Prolonged Exposure therapy, on the functional activity of the fear extinction network of women with clinically significant posttraumatic stress disorder symptoms. This approach will elucidate the neural mechanisms underlying effective exposure treatment for these symptoms, and will document how estradiol could be used as adjunct to enhance the outcome of extinction-based therapies.

How Do Conditioned Drug Associations Promote Drug Taking

5R01AA022961-05 – National Institute on Alcohol Abuse and Alcoholism

This research is relevant to public health because the findings are expected to ultimately inform unique treatment approaches and methods to counteract the powerful effects of alcohol contextual cues on drinking and relapse. Thus, the project is also relevant to the mission of NIAAA which is to support behavioral research on the causes and treatment of alcoholism and alcohol-related problems.

Contextual Conditioning with Drugs in Humans: Causes and Consequences

5R21DA033488-03 – National Institute on Drug Abuse

The proposed research is relevant to public health because the findings are expected to ultimately inform unique treatment approaches and methods to counteract the powerful effects of drug conditioned cues on mood and behavior. Thus, the project is also relevant to the mission of NIDA specifically the component ensuring the effective use of research to significantly improve prevention and treatment of drug abuse and addiction.

Dimensional RDoC Modeling Across the Range of Negative Mood Dysfunction

4R01MH101487-04 – National Institute of Mental Health

Dimensional modeling is a new strategy for helping to resolve how genetics and brain function can be so disparate from current categories of psychiatric illness. The present project uses multimodal, dimensional assessment to capture and subtype, core features across diagnoses, and differentiating biomarkers in all mood disorders, including bipolar, major depressive, mood disorder, adjustment, subthreshold, and NOS categories. Use of these groups and measures from Cognitive and Negative Valence systems provide a full continuum of dimensional data for across modality evaluation of linear, dimensional relationships and determination of construct validity.

Transdiagnostic Brain-Behavior Profiling to Enhance Cognitive Behavioral Therapy Response

1R01MH112705-01A1 – National Institute of Mental Health

Many patients with Major Depressive Disorder (MDD) and generalized Social Anxiety Disorder (gSAD) are treated with cognitive behavioral therapy (CBT) but few have meaningful improvement. MDD and gSAD are diseases of brain dysfunction that manifest as impaired emotion regulation; CBT teaches emotion regulation strategies but how it works remains largely unknown. Individual differences in brain function related to emotion regulation may make some patients better suited for CBT and CBT may remedy the brain dysfunction that underlies these disorders. This project will compare CBT with a placebo psychotherapy (i.e., supportive therapy) in MDD and gSAD and use multiple brain-behavioral units of measure to examine mechanisms of change and predictors of CBT response.

Brain-Behavior Reactivity to Threat and Alcohol Abuse Risk in Young Adults

1K23AA025111-01A1 – National Institute on Alcohol Abuse and Alcoholism

Problematic alcohol use is common, emerges early and leads to enormous personal and societal burden; thus, there is a need to understand who is vulnerable, and why, to facilitate accurate early detection and prevention and develop mechanistically-driven interventions. The current study will combine behavioral and neural measures with a prospective design of progression to escalated alcohol use to test a brain-behavioral phenotype for problematic drinking. Identification of a validated risk model, and better understanding of the brain and behavioral mechanisms that promote excessive alcohol use, will ultimately reduce the number of individuals who develop alcohol use disorder.

Depression Risk in Young Adults: Sensitivity to Uncertainty and Reward

Brain & Behavior Research Foundation (NARSAD)

Major depressive disorder (MDD) emerges early in life and poses tremendous burden. There is an urgent need to understand who is vulnerable, and why, to facilitate accurate detection, prevention, and treatment. To address this critical issue, a more precise mechanistic understanding of risk is needed. New, emerging data suggests that one source of risk for depression is an inability to tolerate uncertainty in ones’ environment, labeled as high intolerance of uncertainty (IU). To date, however, very little research has directly tested whether high IU functions as a risk factor and prospectively predicts onset and escalation of depressive symptoms in young adults. The mechanisms that mediate this potential source of risk are also unknown; although, preliminary data suggests that individuals with high IU may display blunted neural and psychophysiological reward processing, which could contribute to the development of depressive symptoms. Given that establishing a validated biobehavioral risk model, and elucidating mechanisms underlying MDD, has the potential to significantly improve clinical efforts, this study combines psychophysiology and neural measures, with a prospective design, to test whether high IU is a risk factor for depression that is mediated by aberrant reward processing.

Behavioral-Brain-Epigenetic Model of Alcohol Use Disorder in Humans

5P50AA022538-03 Pilot Project – National Institute on Alcohol Abuse and Alcoholism

Alcohol is known to cause neuroadaptations in affective neural circuits, it is also unclear the extent to which ongoing vs. prior alcohol use impacts the Anticipatory Anxiety Network (AAN) structure and function. Clarifying these questions is necessary to validate the proposed behavioral-brain model and facilitate the development of targeted, mechanistic AUD interventions. The overarching aim of the study is to test the proposed model of AUD using structural and functional MRI with simultaneous startle collection in young adults with current (n=30) and remitted (n=30) AUD, and a sample of matched healthy controls/HC (n=30). The study will examine whether compared with controls, individuals with AUD display exaggerated behavioral reactivity, structural AAN abnormalities, and aberrant AAN circuit functioning during U-threat. We will also examine whether individuals with current AUD (cAUD) exhibit more pronounced hypersensitivities and abnormalities compared to those with remitted AUD (rAUD). The secondary aim of the study is to generate pilot data uncovering new hypotheses and refine understanding of how reactivity to U-threat contributes to AUD at multiple layers of neurobiology including epigenetics.

From Networks to the Real World: Integrating Neural and Autonomic Processes of Loss

1K23MH112769-01A1 – National Institute of Mental Health

Major depressive disorder (MDD) is the most common lifetime mental disorder and is associated with tremendous personal, economic and societal costs; thus, there is a need to better understand the processes underlying MDD to facilitate the development of mechanistically-driven interventions. The proposed research will link neural circuitry underlying cognitive control and affective processing to autonomic and behavioral measures of affect regulation in the laboratory and in daily life, among individuals with remitted MDD and healthy controls. An improved mechanistic understanding of cognitive-affective risk phenotypes for depression will inform the timely prevention, early detection, and advancement of novel treatments for affect dysregulation in depression.

Probing Autonomic and Network Mechanisms of Emotion Regulation in Major Depressive Disorder

Brain and Behavior Research Foundation (NARSAD Young Investigator Award)

Major depressive disorder (MDD) is a prevalent and debilitating disorder that places a heavy burden on society through healthcare service use, loss of productivity, and loss of life to suicide.  To develop more effective treatments and reduce risk for recurrence, there is an urgent need for a more precise mechanistic understanding of depression risk phenotypes. Despite having a greater need for effective emotion regulation, individuals with MDD experience less benefit from attempts to regulate than individuals without MDD, leading to prolonged negative emotion and suppressed parasympathetic nervous system activity. By identifying biomarkers of problematic responses to sadness, treatments can be developed that allow for regulatory intervention earlier than when relying exclusively on individuals’ self-reports of these processes. The proposed study aims to identify (a) brain networks important in disrupted emotion regulation that can be targeted to improve regulatory success, and (b) parasympathetic indicators of disrupted network functioning that are less invasive and more cost-effective to evaluate than fMRI. This study has important implications for the identification of neural and psychophysiological mechanisms of emotion regulation that have strong potential for translation to novel interventions. Parasympathetic activity (respiratory sinus arrhythmia [RSA], a plausible parasympathetic biomarker of depression risk) and regulatory effectiveness will be assessed during a laboratory-based sadness paradigm. This design will bridge key gaps in the field and build upon the candidate’s existing strengths in the experimental and longitudinal assessment of cognitive-affective vulnerabilities for depression in two new areas: neural network modeling and multimodal data integration. We hypothesize that maladaptive patterns of activation in neural networks supporting emotion processing (elevated) and cognitive control (diminished) will be associated with poorer regulation, indexed by poorer parasympathetic and emotional recovery from sadness. Given that RSA is a brief, inexpensive, and noninvasive measure that can be collected in any lab, we expect results to suggest that RSA can provide a remote window into brain networks underlying emotion regulation. This study has the potential to contribute to new tools (e.g., neuromodulation, biofeedback, behavioral techniques) to improve the detection and treatment of emotion dysregulation in depression.

Identifying Mechanisms of Proximal Suicide Risk Using Ambulatory Assessment

Portes Foundation and Institute of Medicine of Chicago

Suicide is the second leading cause of death among young adults in the United States and often occurs within the context of major depressive disorder.  Difficulties with regulating strong negative emotions is a candidate mechanism by which numerous risk factors may lead to suicidal behavior.  However, existing models of suicide risk have had only modest success, suggesting the need to go beyond traditional laboratory-based methods by measuring emotional processes in real-world contexts that are closer in time to the occurrence of suicidal ideation, and that have greater ecological validity.  The present study will use ambulatory assessment, involving wearable technology to measure physiological and behavioral components of emotion regulation in participants’ daily lives, among N=40 individuals with major depressive disorder who have experienced suicidal ideation within the past month (n=20 of whom have a past suicide attempt).  Participants will complete seven days of ambulatory assessment during which putative biological mechanisms of emotion regulation (sleep quality and parasympathetic activity), behavioral factors (emotions, regulation strategies), and environmental factors (activity, stressors, substance use) are assessed across the day.  By using an innovative, person-centered approach, this study will detect contexts when individuals are at particular risk for suicidal ideation, and will evaluate which individuals with ideation may be at risk for suicide attempts. These data have important implications for the development of personalized suicide prevention interventions to identify possible periods of suicide risk in real time, and intervene to improve affect regulation and related factors in ways that affect daily functioning, thereby reducing risk.

Brain-Behavior Markers of Emotion in Depressed Mothers and Their Daughters

Daughters of mothers with a history of depression are at extremely high risk for developing depression themselves and thus, there is a need to identify specific mechanisms of risk in order to develop targeted, prevention efforts. The MADS study combines behavioral, neural (EEG and fMRI), and ecological momentary assessment (EMA) measures with a prospective design to test whether disrupted social-emotional and motivational processing styles are direct, familial mechanisms implicated in the intergenerational transmission of depression. We believe this work will ultimately contribute to a better understanding of brain and behavioral measures underlying youth depression risk and promote the development of targeted, prevention efforts for this population.

Targeting Biomarkers of Risk among Offspring of Depressed Parents through a Cognitive Behavioral Preventive Intervention

The PODS study leverages a well-developed evidence-based family group cognitive-behavioral prevention program (developed by Bruce Compas – Vanderbilt University) to examine whether biological markers (ERPs) implicated in emotion processing can be altered in children of depressed parents to reduce depression risk.  This project is also examining whether ERPs can predict which offspring of depressed parents respond to the intervention program. Findings from the study have the potential to improve clinical outcomes and optimize limited resources for high risk families.

Brain Mechanisms of Cognitive Behavioral Therapy for Social Anxiety Disorder

K23MH093679 – National Institute of Mental Health

Cognitive behavioral treatment (CBT) is a widely used first-line treatment for social anxiety disorder (SAD), a prevalent, debilitating disorder. Although many do not fully recover from SAD with CBT, the specific mechanisms by which CBT exerts its therapeutic effects are unknown. The primary goal of this research is to discover the effects of CBT on brain function, particularly in relation to specific emotion regulation strategies implicated in CBT-namely, increased attentional control over threat stimuli and higher-order cognitive regulation of emotions evoked by threat-relevant stimuli. A better understanding of the brain mechanisms of CBT and of individual differences in treatment response in patients with SAD will improve our understanding of CBT mechanisms thereby optimizing current therapies and contributing to the advancement of improved therapies to increase the probability of therapeutic success.