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About the Cognitive Dynamics Lab


Mission Statement

Our mission is to advance the field of digital brain research and identify targets for precision-medicine to enhance the lives of people with serious mental illness across the lifespan. Furthermore, we aim to provide resources and education for clinical researchers looking to integrate in-the-wild digital health technologies into their studies.


Research Focus

The Cognitive Dynamics Lab leverages advances in computational capabilities, coupled with burst and just-in-time study designs, to answer questions such as:

  • What are the complex and dynamic effects of mood on real-time cognition in bipolar disorder?
  • Can GPS mobility data serve as a digital biomarker for symptoms and cognition in serious mental illness?
  • What are the near-term changes in behavior prior to onset of suicidal ideation?
  • How can we use active and passive smartphone data to better measure self-awareness and promote enhanced daily functioning in serious mental illness?

Ongoing Research Projects

Social Cognition and Suicide in Psychotic Disorders (2019–2023)

This study uses a measurement burst design to evaluate the impact of social cognitive biases on risk for suicidal ideation and attempt in people with psychosis.

R01MH116902 (NIH/NIMH)

PI: Colin Depp

Introspective Accuracy, Bias, and Everyday Functioning in Severe Mental Illness (2018–2022)

The proposed study aims to: 1) learn how impaired introspective accuracy contributes to difficulties in real world functioning, 2) understand how introspective accuracy differs from other types of self-awareness, and 3) discover how clinical symptoms affect the amount and direction of introspective accuracy impairments.

R01MH112620 (NIH/NIMH)

PI: Amy Pinkham
Site PI: Colin Depp

Real-Time Mobile Cognitive Tests for Bipolar Disorder Research (2018–2020)

Project will validate frequently repeated mobile cognitive tests against standard neuropsychological assessments, to understand how the real-time effects of mood relate to real-world cognition, and to discover how real-world cognition relates to real-time daily functioning.

R21MH116104 (NIMH)

PI: Raeanne Moore

Development of a Mobile Health Augmented Brief Suicide Prevention Intervention for People with SMI Accessing Community Care (2017–2020)

This study is aimed at developing, implementing and evaluating a novel intervention that employs in-person and mobile intervention augmentation to improve transition from urgent care to ongoing outpatient care in people with schizophrenia or bipolar disorder.

R34MH113613-02 (NIH/NIMH)

PI: Colin Depp

The Mobile Toolbox for Monitoring Cognitive Function (2018–2022)

To develop a set of app-based, validated cognitive assessment tools, the MobileToolbox, to help identify normal from abnormal cognitive change in adults aged 20 to 85.

U2C AG060426 (NIA)

PI: Gershon, Richard
Site PI: Raeanne Moore 

Rapid Referral to Suicide Specific Intervention in Psychiatric Emergency Care

This study will evaluate the impact on suicide prevention and operational efficiency of Collaborative Assessment and Management of Suicidality versus Telephone Outreach to Veterans at high risk for suicide.

I01HX002468-01 (VA ORD)

PI: Colin Depp

DETECT: A novel device to assess how HIV affects neurocognitive decline and postural instability in older adults at risk for Alzheimer's Disease (2019–2024)

To use a novel, portable and automated virtual reality assessment tool to differentiate patterns of neurocognitive decline, and associated risk factors, to distinguish HIV-associated neurocognitive disorders from those related to the Mild Cognitive Impairment stage of AD.

R01AG062387 (NIA)

PI: Raeanne Moore

Remote Sensing Technology to Improve Community-Based Fall Risk Assessment and Prevention Among Older Adults Living with HIV (2018–2020)

To validate a novel, technology-based comprehensive fall risk assessment system for use in research and community-based geriatric HIV clinics.

ePD#6892 (Gilead)

PI: Raeanne Moore

Digital Phenotyping Risk of Alzheimer's disease: Supplement to NIMH K23 (2018–2019)

To determine whether we can identify a digital phenotype of older person's living with HIV who are at-risk for Alzheimer's disease using a combination of multiple smartphone-based data sources, obtained via active and passive data collection methods.

Administrative Suppl to K23MH107260 (NIA)

PI: Raeanne Moore

Real-Time Mobile Assessment of Daily Functioning Among Older HIV-Infected Adults (2015–2019)

This career development award is to increase the PIs capacity to conduct mHealth assessments for older adults with HIV.

K23MH107260 (NIMH)

PI: Raeanne Moore