1Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands, 2NIH, Bethesda, MD, United States, 3UCL, London, United Kingdom, 4CMRR, Minneapolis, MN, United States, 5University of Glasgow, Glasgow, United Kingdom, 6Uni Mainz, Mainz, Germany, 7Scannexus, Maastricht, Netherlands, 8Brain Innovation, Maastricht, Netherlands
- LayNii is an open source software toolbox for layer-specific (functional) MRI.
- LayNii performs layerification, columnar distance estimation, cortical unfolding, layer-smoothing, GE-BOLD deveining, fMRI QA, and VASO analyses in the native voxel space of functional data.
Layering metrics generated in LayNii:
The top row shows an application with a synthetic 2D image. The middle row shows the empirical layers from Ding et al. (2016) (0.2 mm iso.). The bottom row shows BigBrain (0.1 mm iso., native space) (Amunts et al. 2013) with cortical borders provided in Wagstyl et al. (2020). The equi-distant metric is shown in the middle column and equi-volume metric is shown in the right column for each image type. The arrows highlight areas where the equi-distant and the equi-volume metric differ considerably.
Estimating columnar units in voxel space with LayNii:
Panel A) describes the algorithm of estimating columnar distances in the example of a cat visual cortex.
Panel B) depicts cortical unfolding in LayNii. The orthogonal coordinates of columnar distances and cortical depths are used to map the signal intensity on a new spatial grid and then LayNii writes it out as NIFTI files.
Panel C) depicts an application for topographic mapping in the human somatosensory system of depicting digit representation in the anterior bank of the central sulcus acros laminar and columnar directions.
