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Appleton Tower

Lecture Theatre 4

11 Crichton Street

Edinburgh

EH8 9LE

United Kingdom

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Speaker: Professor David Dunson

Arts & Sciences Distinguished Professor, Duke University, USA and Carnegie Centenary Professor 2018, University of Edinburgh

Title: Studying Variation in Human Brain Connectomes: Impact of Substance Use & Education

Date: Tuesday 29th May 2018

Time: 17:15 – 18:15 followed by a Drinks Reception

Location: Lecture: Appleton Tower, Lecture Theatre 4, University of Edinburgh. Drinks Reception: Appleton Tower.

Abstract:

There have been parallel revolutions in recent years in technology for imaging of the human brain and in methods for analyzing high-dimensional and complex data. We are interested in exploiting and building on this technology motivated by interest in studying how people vary in their brain connection structure. White matter tracks in the human brain consist of tightly bundled sets of neurons that are geometrically aligned and act as highways for neural activity and communication across the brain. There are on the order of a million such tracts in a normal human brain, and their locations can be estimated using different types of magnetic resonance imaging (MRI) combined with state-of-the-art image processing. We refer to the set of tracts as the human brain “connectome.” The Human Connectome Project (HCP) collects data on connectomes, along with multiple behaviours and traits of each individual under study. We develop state of the art data science tools to study variation in connectomes, and the relationship with factors, such as substance use (alcohol, marijuana) and education. We find a significant relationship between brain connectivity and multiple factors, with high levels of substance use decreasing connectivity and education increasing connectivity. This talk is designed to be accessible to the general public, focusing on describing these amazing new data resources, analysis tools, and results, with a discussion on ongoing directions.

Biography:

David Dunson is Arts and Sciences Distinguished Professor of Statistical Science, Mathematics, and Electrical & Computer Engineering at Duke University. His research focuses on Bayesian statistical theory and methods motivated by high-dimensional and complex applications. A particular emphasis is on dimensionality reduction, scalable inference algorithms, latent factor models, and nonparametric approaches, particularly for high-dimensional, dynamic and multimodal data, including images, functions, shapes and other complex objects. His work involves inter-disciplinary thinking at the intersection of statistics, mathematics and computer science. Motivation comes from applications in epidemiology, environmental health, neurosciences, genetics, fertility and other settings (music, fine arts, humanities). Professor Dunson is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He is winner of the 2007 Mortimer Spiegelman Award for the top public health statistician under 41, the 2010 Myrto Lefkopoulou Distinguished Lectureship at Harvard University, the 2010 COPSS Presidents' Award for the top statistician under 41, and the 2012 Youden Award for inter-laboratory testing methods.

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Appleton Tower

Lecture Theatre 4

11 Crichton Street

Edinburgh

EH8 9LE

United Kingdom

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