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Abstract #1351

layerfMRI-toolbox helps to automatize high-resolution whole-brain layer segmentation in volume space with minimum manual editing.

Marco Barilari1,2, Kenshu Koiso3, Paul A. Taylor4, Omer Faruk Gulban3,5, Daniel Glenn4, Peter Bandettini2,6, Olivier Collignon1,7, and Renzo Huber2
1Institute of Neuroscience (IoNS) and Institute of Research in Psychology (IPSY), Universitè Cathoulique de Louvain, Louvain-La-Neuve, Belgium, 2Functional Magnetic Resonance Imaging Facility, NIH, Bethesda, MD, United States, 3Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands, 4Scientific and Statistical Computing Core, NIH, Bethesda, MD, United States, 5Brain Innovation, Maastricht, Netherlands, 6Section of Functional Imaging Methods, NIH, Bethesda, MD, United States, 7HES-SO Valais-Walis, The Sense Innovation and Research Center, Lausanne and Sion, Switzerland

Synopsis

Keywords: Mesoscale: columns and layers, fMRI Analysis, Neuroscience, Data Processing, Brain, High‐Field MRI, Software Tools, layer-fMRI, VASO, UHF, pipeline, open science.

Motivation: The emerging field of layer-fMRI can capture neural information flow across brain areas. However, data analysis in layer-fMRI is challenged by lack of standardization and segmentation quality constraints.

Goal(s): We aim to design, implement, validate, and test a layer-fMRI analysis pipeline toolbox.

Approach: The layerfMRI-toolbox combines a collection of modern layer-fMRI programs to convert raw structural and functional data to high-quality layer profiles.

Results: We find that the layerfMRI-toolbox can be effectively applied on standalone laptops and computing clusters, and we present exemplary results of the toolbox from a few application studies.

Impact: We proposed an easy to use software toolbox that can standardize and streamline layer-fMRI analyses. It is scalable across large N studies with minimal necessity for manual corrections.

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Keywords