Thomas E. Nichols
|Thomas E. Nichols|
|Affiliation:||Department of Statistics, University of Warwick |
Department of Clinical Neurology, University of Oxford
Department of Biostatistics, University of Michigan
University of Pittsburgh
|Databases:||Google Scholar Microsoft Academic Search Scopus|
|Search:||PubMed (first author) PubMed |
Thomas E. Nichols is a statistician developing statistical methods for neuroimaging sequence analysis of data from MRI and PET scanners.
Nichols is a Principal Research Fellow and Head of Neuroimaging Statistics at the Applied Neuroimaging Lab at the Department of Statistics, University of Warwick. He has previously been with Department of Biostatistics, University of Michigan, GlaxoSmithKline and University of Pittsburgh
He has been chair of the educational committtee for the Organization for Human Brain Mapping and given talks at the educational courses at the Annual Meeting of the Organization for Human Brain Mapping, e.g., in connection with neuroimaging genetics.
- Thomas E. Nichols, Jean-Baptiste Poline (2009). "Comment on Vul et al, "puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition". Perspectives on Psychological Science 4(3): 291-293. doi: 10.1111/j.1745-6924.2009.01126.x.
- Controlling the familywise error rate in functional neuroimaging: a comparative review
- Improving heritability estimates with restricted maximum likelihood (ReML)
- Thomas E. Nichols, Andrew P. Holmes (2002). "Nonparametric permutation tests for functional neuroimaging: a primer with examples". Human Brain Mapping 15(1): 1-25. PMID: 11747097.
- Spatiotemporal reconstruction of list-mode PET data
- Valid conjunction inference with the minimum statistic
- Visualizing variance with percent change threshold images
- Association of GSK3β polymorphisms with brain structural changes in major depressive disorder
- Thomas E. Nichols, Becky Inkster(2009). "Comparison of whole brain multiloci association methods". 
- Evaluating the consistency and specificity of neuroimaging data using meta-analysis
- Everything you never wanted to know about circular analysis, but were afraid to ask
- Genetic variation in GOLM1 and prefrontal cortical volume in Alzheimer's disease
- Large-scale automated synthesis of human functional neuroimaging data
- Meta analysis of functional neuroimaging data via Bayesian spatial point processes
- Structural brain changes in patients with recurrent major depressive disorder presenting with anxiety symptoms
- Thresholding of statistical maps in functional neuroimaging using the false discovery rate
 See also
- ↑ Thomas E. Nichols (2009). Association methods for functional and structural MRI