Our vision for precision psychiatry and neuroscience is to translate insights about the human brain into real world clinical care – to improve the quality of individual lives.

What We Do

Why We Do It

Our current projects focus on depression and anxiety, with research that embraces individual differences in the experience of mental health disorders, and the associated disruptions to social and emotional function. Emotion and cognition are two hallmark features of mental health disorders. Using an integrative approach with MRI, EEG, behavioral testing, genetics, symptoms, and daily functioning data, our research projects aim to:
  • Delineate neural circuitry for emotional and cognitive functions,
  • Examine how this circuitry becomes dysregulated in depression and anxiety,
  • And assess how it is expressed in individual variations in subjective and behavioral symptoms.
Mental health disorders are the leading cause of disability worldwide (depressive disorders account for about 40% of the disability, and anxiety disorders are about 15%). Advances in human neuroscience give us a better understanding for why one treatment works and another does not - but we have not yet bridged the translational divide between the evidence and how to apply this information in the real world. To improve this situation, we need to provide more successful treatment.


Center for Precision Mental Health and Wellness

Dr. Leanne Williams is pioneering the development a Center for Precision Mental Health and Wellness for rapidly translating neuroscience into personalized care.
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We are hiring!
Join our Team 
We have Postdoctoral and Research Positions available. Check out our Opportunities page for more information regarding these opportunites! 
 PanLab News
Click below to learn about recent news in the PanLab. Check out our news page for more.
  1. Dr. Leanne Williams - Key Note Speaker at ASNR Symposium
    JUNE 4, 2018 - Dr. Leanne Williams, key note speaker at the American Society of Neuroradiology (ASNR) symposium in Vancouver, presented her research on ‘Translation of Advanced Neuroimaging for Psychiatric Diseases to the Clinics' during the symposium session ‘Value of Neuroimaging for Psychiatric Disorders.’ This session was co-moderated by collaborator Max Wintermark, MD from Stanford and Jay J. Pillai, MD, Johns Hopkins School of Medicine
  2. Dr. Leanne Williams - Invited Speaker at Stanford's Big Data in Precision Health
    MAY 24, 2018 - Dr. Leanne Williams, Director of the Williams PanLab and Stanford’s Center for Precision Mental Health, was an invited speaker at the Stanford's Big Data in Precision Health conference during the Digital Health and Technology session. Her presentation titled ‘Data Driven Precision Mental Health’ highlighted how deep data about neuroscience connected with big data about day to day function will transform our models of mental health and their translation into real world clinical application.’
  3. Scott Fleming Presents Poster at Stanford's Big Data in Precision Health
    MAY 24, 2018 - Scott Fleming, a graduate student in the PanLab, presented his work during Stanford's Big Data in Precision Health conference poster session, on machine-learning models for disentangling multiple disorders of mental health.
  4. Can precision medicine do for depression what it's done for cancer?
    MAY 9, 2018. Stat News asked the question, 'Can precision medicine do for depression what it's done for cancer?' Dr. Leanne Williams acknowledges that though it might be tricky, it will be worth the effort. Dr. Leanne Williams' goal for the Stanford Center for Precision Mental Health and Wellness is to discover tests that physicians can utilize to guide treatments for depression.
  5. Dr. Leanne Williams - Invited Speaker at the 4th Annual BRAIN Initiative
    APRIL 10, 2018 Dr. Leanne Williams was a featured speaker during a session designed to explore the underlying mechanisms of network modulation and elucidate steps to develop the next generation of brain stimulation devices that can more effectively correct network and circuit dynamics. The title of her presentation was "Quantifying targets for non-invasive network modulation.”
  6. Dr. Tali Manber Ball Awarded K23 Grant by NIH
    APRIL 3, 2018 Dr. Tali Manber Ball, postdoctoral fellow in the PanLab, was awarded K23MH113708 entitled, "Developing a mechanistic neurobiological model of exposure therapy response based on fear extinction theory." Her research aim to build a model to predict which patients with social anxiety will respond to exposure therapy, based on a neuroimaging assessment of individual differences in fear extinction learning.
  7. Adina Fischer, MD, PhD, spoke at the 4th Annual Behavioral Health Symposium
    MAY 24, 2018- PanLab Psychiatry Resident Physician & Postdoctoral Fellow, Adina Fischer, presented on "Understanding the Effects of Marijuana in Psychosis and Schizophrenia at the 4th Annual Behavioral Health Symposium.
  8. Tali Manber Ball, PhD Awarded 2018 NARSAD Young Investigator Grant
    Although occasional mild anxiety is a common human experience, anxiety disorders such as social anxiety disorder have a devastating impact on patients’ lives. A key feature of social anxiety disorder is avoidance of situations in which judgment and evaluation from others might occur, which prevents patients from engaging fully in work, school, and relationships. This maladaptive avoidance is thought to maintain anxiety and is therefore a crucial treatment target. In this project, Tali aims to validate a novel virtual reality paradigm to objectively assess maladaptive avoidance in adults with social anxiety disorder, and to examine how maladaptive avoidance behavior relates to fear and safety learning. The project is funded by the Brain and Behavior Research Foundation’s NARSAD Young Investigator Award. Congratulations, Tali!
  9. PanLab Neuroscience PhD Arielle Keller Tackles inequality in STEM
    JUNE 6, 2018- Check out Arielle Keller's efforts to advocate for underrepresented groups in STEM: https://neuroscience.stanford.edu/news/tackling-inequality-stem-dive-data