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OUR RESEARCH

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HUMAN CONNECTOME PROJECT FOR DEPRESSION AND ANXIETY

The Human Connectome Project for Depression and Anxiety is transforming our understanding of depression, anxiety, and mood disorders based on high-resolution imaging of the brain’s connectomes and biotypes.  This study is funded through the NIH Human Connectome Project. It leverages an unparalleled compilation of data to achieve never before realized conclusions about the living human brain and how the brain is disrupted in depression and anxiety.

IRIS NEUROSTUDY

In response to the staggering mental health impact of the COVID-19 pandemic, we have launched the IRIS Neuro study. This study focuses on improving our understanding of the postinfection impact of SARS-CoV-2 on mental health symptoms and accompanying disruptions to concentration and brain function over a 12-month timeframe.  By better understanding the impact, we can also identify and tailor treatment options.

CATALYST

Through Catalyst, we are developing a cutting-edge wearable technology for monitoring stress that is suited to brain health applications. Evidence from our studies connects metrics from the wearable to symptoms and brain imaging biotypes for mental health.

RBRAIN - MDMA

We know little about exactly how MDMA – ‘ecstasy’ – impacts the human brain in real time and how brain changes relate to the experience of MDMA.  In this study, we acquire neuroimaging brain scans immediately following doses of MDMA versus placebo, in a novel mechanistic trial design with healthy individuals. We also acquire detailed information about the individual experiences of each participant so as to connect brain changes to experience. Data from this study is vital to discovering how MDMA works in a more precise way and will inform its safe and personalized therapeutic use in future trials.

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RBRAIN - KETAMINE

Although ketamine has promise as a therapeutic when used at sub-anesthetic doses, we know little about exactly how it impacts the human brain in real-time.  In this study, we acquire neuroimaging brain scans immediately following infusions of ketamine versus placebo, in a novel mechanistic trial design with healthy individuals. We also acquire detailed information about the individual experiences of each participant so as to connect brain changes to experience. Data from this study is vital to discovering how ketamine works in a more precise way and will inform its safe and personalized therapeutic use in future trials.

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PSILOCYBIN

The "ACE-D: Accelerating Cognition-guided signatures to Enhance translation in Depression" study aims to optimize, validate, and deploy a clinical cognitive signature using behavioral measures that have a basis in neural mechanisms, enabling individualized assessment at scale suited to personalized clinical prognostic and treatment selection decisions. We will extend our pioneering work in identifying a cognitive phenotype of depression derived from computerized behavioral ‘WebNeuro’ tasks that align with the RDoC cognitive control construct, to be complemented by a novel, research-based smartphone ‘BiAffect’ application for finer-grained, passively sampled behavioral metrics.​

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TMS - BIOMARKERS TRIAL

A multisite clinical trial that aims to advance a biomarker-driven approach to identifying which patients will benefit from transcranial magnetic stimulation (TMS) and through which mechanisms.

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CLINIC PROJECT

The Stanford Translational Precision Mental Health Clinic Project is a pragmatic project to assess the clinical translation and implementation of neuroscience-based biotyping assessments for diagnosing and subtyping depressive and associated anxiety disorders in the outpatient setting.

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ACE-D

​The "ACE-D: Accelerating Cognition-guided signatures to Enhance translation in Depression" study aims to optimize, validate, and deploy a clinical cognitive signature using behavioral measures that have a basis in neural mechanisms, enabling individualized assessment at scale suited to personalized clinical prognostic and treatment selection decisions. We will extend our pioneering work in identifying a cognitive phenotype of depression derived from computerized behavioral ‘WebNeuro’ tasks that align with the RDoC cognitive control construct, to be complemented by a novel, research-based smartphone ‘BiAffect’ application for finer-grained, passively sampled behavioral metrics.​

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