401-03-009 ISMRM Abstract

Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation

Primary: Analysis Methods - Visualization

Secondary: Analysis Methods - Software Tools

401-03-009 · End-to-End Software Innovation · Tuesday, 12 May, 1:40 PM–3:30 PM · Hall 1A

Keywords: Visualization Reproducibility Meta-analysis Context Quality control

Accepted

Paul A Taylor ¹, Himanshu Aggarwal², Peter A Bandettini¹, Marco Barilari³, Molly Bright⁴, César Caballero-Gaudes^5,6, Vince D Calhoun^7,8,9, Mallar Chakravarty^10,11, Gabriel A Devenyi^10,11, Jennifer W Evans¹², Eduardo Garza-Villarreal¹³, Jalil Rasgado-Toledo¹³, Remi Gau², Daniel Glen¹⁴, Rainer Goebel^15,16, Javier Gonzalez-Castillo¹², Omer Faruk Gulban^15,16, Yaroslav Halchenko¹⁷, Daniel Handwerker¹², Taylor Hanayik¹⁸, Peter D Lauren¹², David Leopold¹², Jason Lerch^18,19, Christian Mathys²⁰, Paul McCarthy¹⁸, Anke McLeod²¹, Amanda Mejia²², Stefano Moia²³, Thomas Nichols²⁴, Cyril Pernet²⁵, Luiz Pessoa²⁶, Bettina Pfleiderer²⁷, Justin K Rajendra¹², Laura Reyes²⁸, Richard C Reynolds¹², Vinai Roopchansingh¹², Chris Rorden²⁹, Brian E Russ^30,31, Benedikt Sundermann^20,32, Bertrand Thirion², Salvatore Torrisi^33,34, Gang Chen¹²

¹National Institute of Mental Health, Bethesda, United States of America

²Inria, Saclay, France

³Crossmodal Perception and Plasticity Lab, Institute of Neuroscience (IoNS) and Institute of Research in Psychology (IPSY), Université Catholique de Louvain, Belgium

⁴Northwestern University, Chicago, United States of America

⁵Ikerbasque, Basque Foundation for Science, Bilbao, Spain

⁶Basque Center on Cognition, Brain and Language, San Sebastian - Donostia, Spain

⁷Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Atlanta, United States of America

⁸Georgia State University, Atlanta, United States of America

⁹Emory/Georgia Tech, Atlanta, United States of America

¹⁰Douglas Mental Health University Institute, Montreal, Canada

¹¹McGill University, Montreal, Canada

¹²National Institute of Mental Health (NIMH), Bethesda, United States of America

¹³Universidad Nacional Autónoma de México campus Juriquilla, Mexico

¹⁴Scientific and Statistical Computing Core, National Institute of Mental Health (NIMH), Bethesda, United States of America

¹⁵Brain innovation B.V., Maastricht, Netherlands

¹⁶Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands

¹⁷Dartmouth College, Hanover, United States of America

¹⁸Wellcome Centre for Integrative Neuroimaging, Oxford, United Kingdom

¹⁹University of Toronto, Toronto, Canada

²⁰Universitätsmedizin Oldenburg, Germany

²¹Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany

²²Indiana University, Bloomington, United States of America

²³Department of Cognitive Neuroscience, FPN, Maastricht University, Netherlands

²⁴Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, Oxford, United Kingdom

²⁵Neurobiology Research Unit, Rigshospitalet, Denmark, Denmark

²⁶University of Maryland, College Park, United States of America

²⁷University of Münster, Münster, Germany

²⁸National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, United States of America

²⁹McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, United States of America

³⁰Nathan Kline Institute, Orangeburg, United States of America

³¹Icahn School of Medicine at Mount Sinai, New York, United States of America

³²University Muenster, Münster, Germany

³³University Of California, San Francisco (UCSF), United States of America

³⁴San Francisco Veteran Affairs Health Care System, San Francisco, United States of America

Presenting Author: Paul A Taylor

Synopsis

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References

1. [1] Allen EA, Erhardt EB, Calhoun VD (2012). Data Visualization in the Neurosciences: overcoming the Curse of Dimensionality. Neuron 74:603-608. PMID: 22632718, DOI: 10.1016/j.neuron.2012.05.001 [doi] [pmid]

2. [2] Taylor PA, Reynolds RC, Calhoun V, Gonzalez-Castillo J, Handwerker DA, Bandettini PA, Mejia AF, Chen G (2023). Highlight Results, Don’t Hide Them: Enhance interpretation, reduce biases and improve reproducibility. Neuroimage 274:120138. PMID: 37116766, DOI: 10.1016/j.neuroimage.2023.120138 [doi] [pmid]

3. [3] Chen G, Pine DS, Brotman MA, Smith AR, Cox RW, Taylor PA, Haller SP (2022). Hyperbolic trade-off: the importance of balancing trial and subject sample sizes in neuroimaging. NeuroImage 247:118786. PMID: 34906711, DOI: 10.1016/j.neuroimage.2021.118786 [doi] [pmid]

4. [4] Cox RW (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 29(3):162-173. PMID: 8812068, DOI: 10.1006/cbmr.1996.0014 [doi] [pmid]

5. [5] Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, et al. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature 582(7810):84-88. PMID: 32483374, DOI: 10.1038/s41586-020-2314-9 [doi] [pmid]

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http://echo.ismrm.org/p/ISMRM2026/401-03-009