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Thomas E. Nichols
Thomas E. Nichols
University of Oxford
Verifierad e-postadress på bdi.ox.ac.uk - Startsida
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Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data
SM Smith, M Jenkinson, H Johansen-Berg, D Rueckert, TE Nichols, ...
Neuroimage 31 (4), 1487-1505, 2006
75502006
Nonparametric permutation tests for functional neuroimaging: a primer with examples
TE Nichols, AP Holmes
Human brain mapping 15 (1), 1-25, 2002
69502002
Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference
SM Smith, TE Nichols
Neuroimage 44 (1), 83-98, 2009
55672009
Statistical parametric mapping: the analysis of functional brain images
WD Penny, KJ Friston, JT Ashburner, SJ Kiebel, TE Nichols
Elsevier, 2011
54832011
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
CR Genovese, NA Lazar, T Nichols
Neuroimage 15 (4), 870-878, 2002
54292002
Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
A Eklund, TE Nichols, H Knutsson
Proceedings of the national academy of sciences 113 (28), 7900-7905, 2016
38572016
Large-scale automated synthesis of human functional neuroimaging data
T Yarkoni, RA Poldrack, TE Nichols, DC Van Essen, TD Wager
Nature methods 8 (8), 665-670, 2011
38472011
Permutation inference for the general linear model
AM Winkler, GR Ridgway, MA Webster, SM Smith, TE Nichols
Neuroimage 92, 381-397, 2014
37642014
Network modelling methods for FMRI
SM Smith, KL Miller, G Salimi-Khorshidi, M Webster, CF Beckmann, ...
Neuroimage 54 (2), 875-891, 2011
22092011
Valid conjunction inference with the minimum statistic
T Nichols, M Brett, J Andersson, T Wager, JB Poline
Neuroimage 25 (3), 653-660, 2005
20312005
The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments
KJ Gorgolewski, T Auer, VD Calhoun, RC Craddock, S Das, EP Duff, ...
Scientific data 3 (1), 1-9, 2016
16502016
Reproducible brain-wide association studies require thousands of individuals
S Marek, B Tervo-Clemmens, FJ Calabro, DF Montez, BP Kay, ...
Nature 603 (7902), 654-660, 2022
15542022
Controlling the familywise error rate in functional neuroimaging: a comparative review
T Nichols, S Hayasaka
Statistical Methods in Medical Research 12 (5), 419-446, 2003
14342003
SARS-CoV-2 is associated with changes in brain structure in UK Biobank
G Douaud, S Lee, F Alfaro-Almagro, C Arthofer, C Wang, P McCarthy, ...
Nature 604 (7907), 697-707, 2022
14192022
Scanning the horizon: towards transparent and reproducible neuroimaging research
RA Poldrack, CI Baker, J Durnez, KJ Gorgolewski, PM Matthews, ...
Nature reviews neuroscience 18 (2), 115-126, 2017
13962017
Functional connectomics from resting-state fMRI
SM Smith, D Vidaurre, CF Beckmann, MF Glasser, M Jenkinson, KL Miller, ...
Trends in cognitive sciences 17 (12), 666-682, 2013
11082013
Handbook of functional MRI data analysis
RA Poldrack, JA Mumford, TE Nichols
Cambridge University Press, 2024
10992024
Variability in the analysis of a single neuroimaging dataset by many teams
R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ...
Nature 582 (7810), 84-88, 2020
10872020
Placebo effects mediated by endogenous opioid activity on µ-opioid receptors
JK Zubieta, JA Bueller, LR Jackson, DJ Scott, Y Xu, RA Koeppe, ...
The Journal of neuroscience 25 (34), 7754, 2005
10632005
Common genetic variants influence human subcortical brain structures
DP Hibar, JL Stein, ME Renteria, A Arias-Vasquez, S Desrivières, ...
Nature 520 (7546), 224-229, 2015
9042015
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Artiklar 1–20