Active Projects
PRIORI Ambient
This collaborative project uses digital phenotyping methods to measure emotion, mood, and functional outcomes within the context of Prechter Longitudinal Study of Bipolar Disorder. It integrates two technologies – our proprietary PRIORI (Predicting Individiual Outcomes for Rapid Intervention) app and an ecological momentary assessment (EMA) protocol. The PRIORI app was developed by Dr.Emily Mower Provost in Engineering and Computer Sciences and Dr. Melvin McInnis, and uses machine algorithms to detect emotion activation and valence from speech collected passively on participants smartphones. Initial validation was completed on clinical interview telephone calls and has been expanded to capture ambient speech and noise as participants go about their normal daily lives. In our new deployment, the EMA protocol that will assess participants self-perceptions of their emotional valence and arousal as well as their social and physical location contexts. We will use anomaly detection methods to identify whether changes in passively detected speech are associated with self-reported emotional valence and arousal, and whether this differs as a function of context (e.g., socialization, location).
COLLABORATORS: Dr. Emily Mower Provost & Dr. Melvin McInnis
FUNDING: NIMH R01MH130411, Bazucki Brain Research Fund, Heinz C. Prechter Bipolar Research Fund
Modeling Mood Instability in Bipolar Disorder
As a first step towards precision medicine approaches in bipolar disorder, this project aims to (1) model longitudinal patterns of mood in bipolar disorder, identifying illness phenotypes based on intraindividual mood dynamics, and (2) discover biopsychosocial predictors of such illness phenotypes. We will do so in a unique cohort of patients with bipolar disorder that have been followed for approximately 10 years, integrating repeated and extensive clinical, biological, neurocognitive, personality, and functional assessments with electronic health records to maximize a data-driven approach to identify clinically relevant phenotypes. Results from this study have the potential to inform individualized treatment planning and better risk prognostication in those with bipolar disorder. For example, if an individual has a set of risk factors that are associated with a more severe and turbulent longitudinal course of mood, those risk factors may be targeted first via psychopharmacology, novel intervention approaches (e.g., neuromodulation), and cognitive and behavioral interventions.
FUNDING: Brain and Behavior Research Foundation Young Investigator Award (NARSAD)
Neurophysiological Indicators of Emotion-Based Impulsivity
Individuals with bipolar disorder (BD) experience severe and persistent difficulties with impulsivity, especially in the context of experiencing strong emotions. Emotion-based impulsivity is associated with increased hospitalizations, lost relationships, substance use, and suicide. Yet, mechanisms underlying emotion-based impulsivity are not well understood, limiting the design of effective interventions. This project uses multimodal assessments to identify candidate mechanisms of emotion-based impulsivity in the lab and daily life. This study will recruit 90 individuals across the entire bipolar spectrum (30 healthy individuals, 30 with subclinical BD, and 30 with diagnosed BD). Participants will complete trait measures of emotion-based impulsivity and undergo an EEG recording while completing a affective inhibition task. Following the EEG, participants will complete a 28-day ecological momentary assessment protocol which assesses emotions, their regulation, and impulsive behaviors. The specific aims are to: 1) Identify neurophysiological components of response inhibition that are associated with trait and lab-based emotion-based impulsivity, and 2) evaluate the extent to which these components are associated with emotion-based impulsivity in real-world settings.
COLLABORATORS: Dr. Ivy Tso
FUNDING: NIMH K23MH131601, Eisenberg Family Depression Center Eisenberg Scholar Award
Emotion Regulation and Mania Risk
The Hypomanic Attitudes and Positive Predictions Inventory (HAPPI) was developed in tandem with an Integrative Cognitive Model of mood swings (ICM; Mansell et al., 2007), to measure extreme appraisals of internal states. According to the ICM, when people vulnerable to mood swings appraise changes to internal states (such as increased/decreased energy, feeling happier or feeling sadder) in extreme ways this drives attempts to change internal states in line with the nature of that appraisal. For example, a positive appraisal (‘When I feel full of energy, the world is full of unlimited opportunities for me’) might lead to attempts to upregulate energy levels, whereas a negative appraisal (‘When I feel full of energy, this means I am about to have a breakdown’) might lead to attempts to downregulate energy levels. This the leads to further internal state changes, which might again be appraised in an extreme positive or negative way, proposed to lead to the mood dysregulation characteristic of conditions such as bipolar disorder. However, despite theory and evidence supporting its pertinence for mood difficulties (e.g., Dodd et al., 2011), the HAPPI has 61 items and this makes leads to practical limitations in its use in both research and clinical practice. Additionally, although the ICM proposes an interaction between appraisals and regulatory attempts, no research has directly investigated whether such attempts (e.g., emotion regulation strategies) moderate the association between appraisals and affective outcomes (emotion and mood). In this project we will: 1) determine the factor structure of the HAPPI-61, 2) Reduce the number of items on the HAPPI-61, 3) Assess the validity of the short version of the HAPPI, 4) Investigate whether emotion regulation strategies moderate the association between the HAPPI and affective outcomes.
COLLABORATORS: Dr. Alysson Dodd & Dr. Tamsyn Van Rheenen
FUNDING: Investigator contributions
Rhythm and Blues: Changing the Clock to Breakthrough in
Bipolar Disorder
Circadian rhythm disruption, as marked by circadian rhythm variability, eveningness (i.e., preference for later sleep timing), and delayed sleep-wake phase disorder (DSPD, characterized by eveningness) are common among adults with bipolar disorder. Importantly, DSPD, eveningness, and circadian rhythm variability are the most robust predictors of a poorer clinical course in bipolar disorder, including greater functional impairment and relapse to mood episodes across 1-5 years. Efficacious therapies such as Interpersonal and Social Rhythms Therapy (IPSRT) seek to improve outcomes in BD by indirectly targeting the circadian system through stabilization of social rhythms. In this project, we build vertically upon IPSRT by testing the mechanisms of a strategic intervention that directly targets the circadian system disruptions observed in BD—low-dose afternoon supplemental melatonin plus time in bed scheduling. With demonstrated efficacy for DSPD, this strategic intervention is low-burden to person, stabilizes dysregulated sleep patterns, improves sleep, increases morningness, and normalizes circadian timing. We will complete a randomized controlled trial of low-dose afternoon melatonin plus time in bed scheduling relative to control (sleep hygiene education plus placebo pill) for DSPD in adults with bipolar disorder and clinically significant depressive symptoms to determine its engagement of the novel mechanistic target of circadian timing. Specific aims are as follows: AIM 1: Determine the effect of low-dose afternoon melatonin plus time in bed scheduling vs. sleep hygiene education plus placebo pill on the primary mechanistic probe of circadian timing as measured by the gold-standard biomarker, dim light melatonin onset (DLMO); AIM 2: Evaluate DLMO advance as a predictor of change in depression symptoms (self-reported and Ecological Momentary Assessment, EMA); Evaluate exploratory mechanisms (increase in morningness and reduction in sleep variability) as predictors of reduction in depression symptoms (self-reported and EMA); AIM 3. Evaluate DLMO advance as a predictor of exploratory outcomes (total sleep time, sleep-related impairment, mania symptoms).
COLLABORATORS: Leslie Swanson & Helen Burgess
FUNDING: NIMH R21MH132901, Eisenberg Family Depression Center Breakthrough Innovation Award
