Abstract #4289

On false positive control in Fixel-Based Analysis

Robert Smith^1,2, Daan Christiaens^3,4, Ben Jeurissen⁵, Maximillian Pietsch³, David Vaughan^1,2,6, Graeme Jackson^1,2,6, 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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