Robert Cox

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Gang ChenScientific and Statistical Computing Core, NIMH Intramural Research Program, National Institutes ofVerified email at mail.nih.gov
Ziad S. SaadSenior Director, Neuroscience Biomarkers and Global Imaging, Johnson & JohnsonVerified email at its.jnj.com
Jeffrey R. BinderProfessor of Neurology and Biophysics, Medical College of WisconsinVerified email at mcw.edu
Stephen RaoDirector of Schey Center for Cognitive Neuroimaging, Cleveland ClinicVerified email at ccf.org
Paul A. TaylorSSCC Director at NIMH, NIH, USA; visiting lecturer at AIMS (African Inst. for Mathematical Sciences)Verified email at nih.gov
Peter A. BandettiniChief, Section on Functional Imaging Methods, National Institute of Mental HealthVerified email at nih.gov
James S. HydeMedical College of WisconsinVerified email at wi.rr.com
Alex MartinNIH Senior Investigator, National Institute of Mental HealthVerified email at mail.nih.gov
Stephen J GottsSenior Associate Scientist, NIMH/NIHVerified email at mail.nih.gov
Hang Joon JoProfessor, Department of Physiology, College of Medicine, Hanyang UniversityVerified email at hanyang.ac.kr
Daniel PineNational Institute of Mental HealthVerified email at Nih.gov
Elliot SteinNIH/NIDA-IRPVerified email at mail.nih.gov
W. Kyle Simmons, Ph.D.Director, Biomedical Imaging Center at Oklahoma State UniversityVerified email at okstate.edu
Ellen LeibenluftVerified email at mail.nih.gov
Jay NeitzProfessor of OphthalmologyVerified email at uw.edu
Luiz PessoaDepartment of Psychology and Maryland Neuroimaging Center, University of Maryland, College ParkVerified email at umd.edu
Andrew R. MayerProfessor, Mind Research NetworkVerified email at mrn.org
Eric C. WongProfessor of Radiology and Psychiatry, University of California, San DiegoVerified email at ucsd.edu
Shruti JapeeNational Institutes of HealthVerified email at mail.nih.gov

Robert Cox

NIMH

Verified email at mail.nih.gov - Homepage

FMRI


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Processing, evaluating and understanding FMRI data with afni_proc. py RC Reynolds, DR Glen, G Chen, ZS Saad, RW Cox, PA Taylor arXiv preprint arXiv:2406.05248, 2024	1	2024
A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth and interactive QC with afni_proc. py and more PA Taylor, DR Glen, G Chen, RW Cox, T Hanayik, C Rorden, DM Nielson, ... bioRxiv, 2024		2024
Hyperbolic trade-off: The importance of balancing trial and subject sample sizes in neuroimaging G Chen, DS Pine, MA Brotman, AR Smith, RW Cox, PA Taylor, SP Haller NeuroImage 247, 118786, 2022	46	2022
Trial and error: A hierarchical modeling approach to test-retest reliability G Chen, DS Pine, MA Brotman, AR Smith, RW Cox, SP Haller NeuroImage 245, 118647, 2021	27	2021
Beyond linearity in neuroimaging: Capturing nonlinear relationships with application to longitudinal studies G Chen, TA Nash, KM Cole, PD Kohn, SM Wei, MD Gregory, ... NeuroImage 233, 117891, 2021	12	2021
Sources of information waste in neuroimaging: mishandling structures, thinking dichotomously, and over-reducing data G Chen, PA Taylor, J Stoddard, RW Cox, PA Bandettini, L Pessoa BioRxiv, 2021.05. 09.443246, 2021	24*	2021
The Haskins pediatric atlas: a magnetic-resonance-imaging-based pediatric template and atlas PJ Molfese, D Glen, L Mesite, RW Cox, F Hoeft, SJ Frost, WE Mencl, ... Pediatric radiology 51, 628-639, 2021	12	2021
To pool or not to pool: Can we ignore cross-trial variability in FMRI? G Chen, S Padmala, Y Chen, PA Taylor, RW Cox, L Pessoa NeuroImage 225, 117496, 2021	27	2021
Beyond the intraclass correlation: A hierarchical modeling approach to test-retest assessment G Chen, DS Pine, MA Brotman, AR Smith, RW Cox, SP Haller bioRxiv, 2021	10	2021
A series of five population‐specific Indian brain templates and atlases spanning ages 6–60 years B Holla, PA Taylor, DR Glen, JA Lee, N Vaidya, UM Mehta, ... Human brain mapping 41 (18), 5164-5175, 2020	21	2020
EPI Distortion Correction is Easy and Useful, and You Should Use It: A case study with toddler data V Roopchansingh, JJ French Jr, DM Nielson, RC Reynolds, DR Glen, ... Biorxiv, 2020.09. 28.306787, 2020	2	2020
Untangling the relatedness among correlations, part III: inter-subject correlation analysis through Bayesian multilevel modeling for naturalistic scanning G Chen, PA Taylor, X Qu, PJ Molfese, PA Bandettini, RW Cox, ES Finn NeuroImage 216, 116474, 2020	26	2020
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	922	2020
Beware (surprisingly common) left-right flips in your MRI data: an efficient and robust method to check MRI dataset consistency using AFNI DR Glen, PA Taylor, BR Buchsbaum, RW Cox, RC Reynolds Frontiers in neuroinformatics, 505994, 2020	18	2020
Variability in the analysis of a single neuroimaging dataset by many teams (Preprint) R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ...	2	2020
Fast detection and reduction of local transient artifacts in resting-state fMRI HJ Jo, RC Reynolds, SJ Gotts, DA Handwerker, I Balzekas, A Martin, ... Computers in biology and medicine 120, 103742, 2020	6	2020
Fighting or embracing multiplicity in neuroimaging? neighborhood leverage versus global calibration G Chen, PA Taylor, RW Cox, L Pessoa NeuroImage 206, 116320, 2020	21	2020
Why de-face when you can re-face? RW Cox, PA Taylor, HI Works 26th Annual Meeting of the Organization for Human Brain Mapping, 2020	3	2020
An integrative Bayesian approach to matrix‐based analysis in neuroimaging G Chen, PC Bürkner, PA Taylor, Z Li, L Yin, DR Glen, J Kinnison, RW Cox, ... Human brain mapping 40 (14), 4072-4090, 2019	24	2019
Handling multiplicity in neuroimaging through Bayesian lenses with multilevel modeling G Chen, Y Xiao, PA Taylor, JK Rajendra, T Riggins, F Geng, E Redcay, ... Neuroinformatics 17, 515-545, 2019	71	2019

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