Leveraging human brain connectomes to derive quantitative biomarkers for mood ... (Leonardo Tozzi) скачать в хорошем качестве

Leveraging human brain connectomes to derive quantitative biomarkers for mood ... (Leonardo Tozzi)

Title: Leveraging human brain connectomes to derive quantitative biomarkers for mood and anxiety disorders: methodological advances within the Human Connectome Project for Disordered Emotional States Presenter: Dr. Leonardo Tozzi, MD, PhD, Research Engineer at Stanford University Abstract: Mood and anxiety disorders affect over 400 million people globally and are the leading cause of disability worldwide. The goal of the Human Connectome Project for Disordered Emotional States is to study the structure and function of large scale human brain circuits underpinning these disorders. Our study is grounded in the Research Domain Criteria (RDoC) framework developed by the National Institute of Mental Health, which hypothesizes relations among neural circuits, behavior and self-reported symptoms. In our project, we focus particularly on deriving “human connectomes” from whole-brain magnetic resonance imaging recordings, i.e. representations of the functional connections between all regions of the human brain. During this talk, I will introduce the rationale and protocol of our Human Connectome Project for Disordered Emotional States and then present the results of two methodological studies conducted within it. In the first study, we identified the portions of the human connectome that can be measured most reliably and we determined how analysis choices impact human connectome reliability. In the second study, we developed a new algorithm to link human connectomes and symptoms of disordered emotional states, named “group regularized canonical correlation analysis”. Our algorithm can handle thousands of features efficiently and take into account the correlational structure of human connectomes, thus outperforming existing tools for this application. Bio: Leonardo Tozzi, M.D., Ph.D., graduated as a Medical Doctor from Pisa University and Sant’Anna School of Advanced Studies in 2013. In 2018, he was awarded his Ph.D. from Trinity College Dublin for his research on the impact of genetics, epigenetics and environmental stressors on structural and functional brain changes related to depression. Leonardo joined Stanford University in 2018 as the post-doctoral lead of the Human Connectome Project for Disordered Emotional States. Since 2022, he leads the Computational Neuroscience & Neuroimaging Program at the Stanford Center for Precision Mental Health and Wellness. The goal of Leonardo’s research is to develop quantitative biomarkers for mood disorders that are reliable, interpretable and can be used to guide treatment selection and estimate treatment response. To this end, he integrates large scale recordings of brain structure and function with behavioral measures and symptoms as well as other biological markers.