Professor Thomas Nichols
Thomas Nichols is a Wellcome Trust Senior Research Fellow in Basic Biomedical Science, a Professor and the Head of Neuroimaging Statistics at the Institute for Digital Healthcare, holding a joint position between Warwick Manufacturing Group & the Department of Statistics. Before joining the University of Warwick he was the Director of Modelling & Genetics at the GlaxoSmithKline Clinical Imaging Centre at Hammersmith Hospital in London, where he worked on statistical methods for fMRI in the context of clinical trials, and integrating genetic data into brain image analyses. Before coming to the UK he was an Associate Professor of Biostatistics at the University of Michigan, and in 2001 received his Ph.D. in statistics from Carnegie Mellon University where he also trained in cognitive neuroscience. He has been active in the field of functional neuroimaging since 1992, when he worked at the University of Pittsburgh's PET Center as a programmer and statistician. Dr. Nichols' research focuses on modelling and inference of neuroimaging data, including PET, fMRI & M/EEG.
For a full list of publications please see my CV, my Google Scholar page or my ORCID profile; my research pages have publications in topical groups, or meet my students who do most of the work. My Neuroimaging Tips & Tricks blog has practical tips for neuroimaging researchers.
- I've been named on Thompson-Reuter's Highly Cited Researchers 2014 list! The list is based on how frequently my work was cited in the period 2002-2012. See press release and full report for more details.
- Just out! Random graph mixture models for brain connectivity, validated on C. elegans: Stochastic Blockmodeling of the Modules and Core of the Caenorhabditis elegans Connectome by Pavlovic, Vértes, Bullmore, Schafer, & Nichols, PLoS One 9(7):e97584.
- Also just out! Spatial Bayesian regression modelling of MS lesions: Analysis of Multiple Sclerosis Lesions via Spatial Varying Coefficients by Ge, Müller-Lenke, Bendfeldt, Nichols, & Johnson, The Annals of Applied Statistics 8(2), 1095–1118.
- Statistics and Science: A Report of the London Workshop on the Future of the Statistical Sciences, an interesting white paper produced by a joint committee of six statistical socieities around the globe, in commeration of the 2013 International Year of Statistics.
- Warwick Medical Imaging Network - A group I lead with Joanna Collingwood that hosts seminars and tutorials on all aspects of medical imaging (above the neck and below; in humans and other animals)
- OHBM resources: Imaging Genetics course | Meta-Analysis course | Posters & Talks | Hackathon
- "Inside-Out" is a new EPSRC-funded grant to develop the statistical methods for additive manufacturing (aka 3D printing). This is a joint project between Statistics & WMG, led by Wilfrid Kendall, it funds investigators and post-docs in Statistics & WMG. See the project pages in Stats and WMG for more.
- Threshold-Free Cluster Enhancement and Bayes Net models used to quantify gray matter changes with B-vitamin in elderly at risk for dementia: Douaud et al. (2013). PNAS, 110(23), 9523–8.
- Recent blog posts on FWHM & RESEL details for SPM and FSL, Standardizing DVARS and What are the units in plots in SPM?.
- "Alternative-based thresholding with application to presurgical fMRI." Cognitive, Affective, & Behavioral Neuroscience. doi:10.3758/s13415-013-0185-3, a new thresholding method for presurgical fMRI, or whenever one needs to assert "no activation".
- "Genetics of the Connectome". NeuroImage 80, 475–488., concise overview of the role Imaging Genetics is playing with the Connectome.
- "Preventing Alzheimer’s disease-related gray matter atrophy by B-vitamin treatment." Proceedings of the National Academy of Sciences of the United States of America, 110(23), 9523–8, a voxel-wise analysis of a clinical trial for dimentia.
- "Increasing power for voxel-wise genome-wide association studies: The random field theory, least square kernel machines and fast permutation procedures", NeuroImage 63(2):858–873, fast, accurate and powerful inference for whole-brain, whole-genome imaging genetics studies.
- "A Bayesian non-parametric Potts model with application to pre-surgical FMRI data", Stat Methods Med Res, a spatial mixture model for thresholding unsmoothed data, useful for clinical fMRI.
- Posters and talk slides from my group and collaborators at the Organization for Human Brain Mapping 2014 conference, 8-12 June.
- Slides from the "GlaxoSmithKline - Neurophysics Workshop on Skeptical Neuroimaging", a 1-day event that dug into the thorny issues of reproducibility, data-sharing and meta-analysis in brain imaging.
- I am part of the Washington University - University of Minnesota Human Connectome Project, an ambitious international consortium focused on mapping the structural and functional connections in the human brain. I am working on the imaging genetics component of this study, which will image twins and their siblings, allowing the estimation of heritability of connectivity measures.
- SnPM13, the Statistical Nonparametric Mapping toolbox for SPM has been released, 6 March, 2013. See the SnPM page for more.
Neuroimaging Tips & Tricks
- Visit my blog on Neuroimaging Tips & Tricks, an extension of the John's (SPM software) Gems pages I started almost 10 years ago.
- Term 1 2012/13 Applied Biostatistics, ST416 (I'm teaching the 1st part of this 3-module course)
- Term 2 2012/13 Probabilistic and Statistical Inference, CO902 (Complexity MSc course)
Deptment of Statistics
University of Warwick
Handbook of fMRI Data Analysis by Russ Poldrack, Thomas Nichols and Jeanette Mumford