At the PanLab, we are currently recruiting post-doctoral fellows and graduate students. Learn more about opportunities in the lab here.

The vision for personalized neuroscience is to translate insights about the human brain into real world clinical care, to improve the quality of individual lives.

Mental and substance use disorders are the leading cause of years lived with disability worldwide. Depressive disorders account for around 40% of the disability, and anxiety disorders account for around 15%. Under health care reform, approximately 62 million more Americans will gain access to expanded mental health care services. To improve this situation, we need to provide more successful treatment. 

Advances in human neuroscience and genomics give us new markers for understanding 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. 

In the PanLab, our current projects focus on depression and anxiety. We are also working on collaborative projects investigating psychosis and ADHD with anxiety as a cross disorder. 

Our research embraces the study of heterogeneity and individual differences in the experience of mental disorder, and the associated disruptions to social and emotional function. 

Emotion and cognition are two hallmark features of mental disorder. Our research projects aim to delineate neural circuitry for emotional and cognitive functions, how this circuitry becomes dysregulated in depression and anxiety, and how it is expressed in individual variations in subjective and behavioral symptoms. To delineate emotional and cognitive circuitry we use multiple sources of information:  MRI,  EEG, behavioral testing, and genetics.  These sources of information are then integrated with subjective reports about symptoms and daily functioning.

Components of the PanLab research program include:

  • Identifying "biomarkers" for new ways to classify mental illnesses based on sources of brain information 
  • New designs for real world pragmatic trials that are coupled with measures of brain circuits and genetics, to identify biomarkers for predicting which individual will respond best to which treatment 
  • Harnessing new technology and neuroinformatics, with the goal of translating the findings to real world practice, on scale