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Abstract #4289

On false positive control in Fixel-Based Analysis

Robert Smith1,2, Daan Christiaens3,4, Ben Jeurissen5, Maximillian Pietsch3, David Vaughan1,2,6, Graeme Jackson1,2,6, and J-Donald Tournier3
1Florey Institute of Neuroscience & Mental Health, Melbourne, Australia, 2Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia, 3School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, 4Department of Electrical Engineering, KU Leuven, Leuven, Belgium, 5Department of Physics, University of Antwerp, Antwerp, Belgium, 6Department of Neurology, Austin Health, Melbourne, Australia

While the Fixel-Based Analysis (FBA) framework provides familywise error control across a whole-brain template accounting for the presence of crossing fibres in the white matter, its typical usage fails to correct for multiple hypothesis tests due to the utilisation of multiple quantitative metrics. We demonstrate different methods that can be employed to provide more comprehensive false positive control in this context.

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