Hosted by the MRC Integrative Epidemiology Unit

Summary: Steve will give a brief introduction to brain imaging in UK Biobank: what imaging is included, and what biology does it reflect. He will then describe the processing carried out on behalf of UKB, which results in thousands of distinct "IDPs" - imaging-derived phenotypes - making the imaging easier to use for non-imaging-experts. He will finish with a few of our studies using UKB data, including GWAS and COVID studies.

Tom will talk about some more advanced modelling of relevance to UKB brain imaging. He will start by covering our work on confound modelling specific to imaging. He will then describe his group's work on computationally-practical genetic analyses of voxelwise imaging data. He will finish by covering our initial work on applying causal methods to UKB brain imaging, primarily with Mendelian Randomisation.

Biography: Steve Smith is head the Analysis Group at the Wellcome Centre for Integrative Neuroimaging. We carry out research into new methodologies for the analysis of functional and structural brain imaging data. Our research is also turned into software tools that are available in the FSL package, which is free to all academic and non-profit institutions. https://www.win.ox.ac.uk/people/stephen-smith

Tom Nichols is the Professor of Neuroimaging Statistics and a Wellcome Trust Senior Research Fellow in Basic Biomedical Science. He is a statistician with a solitary focus on modelling and inference methods for brain imaging research. He has a unique background, with both industrial and academic experience, and diverse training including computer science, cognitive neuroscience and statistics. After serving on the faculty of University of Michigan's Department of Biostatistics he became the Director Modelling and Genetics at GlaxoSmithKline's Clinical Imaging Centre, London.  He returned to academia in 2009 moving to the University of Warwick, taking a joint position between the Department of Statistics and the Warwick Manufacturing Group.  He joined the BDI in 2017.

The focus of Dr. Nichols work is developing modelling and inference methods for brain image data.  He has worked with a variety of types of data, including Positron Emission Tomography and Magneto- and Electroencephalography, though most of his methods are motivated by Magnetic Resonance Imaging (MRI) and functional MRI (fMRI) in particular.  He has extensive experience in modelling large, complex data, particularly known for his contributions to multiple testing inference for brain imaging.  He has developed methods for clinical trials with imaging, as well as methods for integrating genetic and imaging data.  His current research involves meta-analysis of neuroimaging studies and informatics tools to make data sharing easy and pervasive https://www.bdi.ox.ac.uk/Team/t-e-nichols.

All welcome Zoom link