LayNii: A software suite for layer-fMRI

Abstract

Highlights• A new software toolbox is introduced for layer-specific functional MRI: LAYNII.• LAYNII is a suite of command-line executable C++ programs for Linux, Windows, and macOS.• LAYNII is designed for layer-fMRI data that suffer from SNR and coverage constraints.• LAYNII performs layerification in the native voxel space of functional data.• LAYNII performs layer-smoothing, GE-BOLD vein removal, QA, and VASO analysis. AbstractHigh-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient performance accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LAYNII. This toolbox is a collection of commandline executable programs written in C/C++ and is distributed open-source and as pre-compiled binaries for Linux, Windows, and macOS. LAYNII is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analysed in alternative software packages. Some of the most popular programs of LAYNII contain 'layerification' and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layerspecific smoothing, vein-removal of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data. layer-fMRI | layer fmri | laminar fMRI | columnar fMRI | submillimeter fMRI | fMRI QA | cortical depth-dependent fMRI Correspondence: renzohuber@gmail.com Graphical abstract Huber et al. | bioRχiv | June 12, 2020 | 1-20

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7 Tesla: Challenges and capabilities

“…Starting from a protocol that was previously successfully used (Huber et al, 2021b), the location and vascular physiology of the auditory cortex resulted in several artifacts. This required us to reconsider acquisition parameters and approaches that have helped to improve layer-fMRI applications but whose proof of generalizability across brain areas is still limited.…”

Cortical Surface-Informed Volumetric Spatial Smoothing of fMRI Data via Graph Signal Processing

“…We proposed a method that enables volumetric spatial smoothing of functional data in such way that filtering is informed by the morphological structure of the cerebral cortex, as defined by extracted cortical surfaces. In future work, we will compare the proposed method with spatial smoothing performed on cortical surface [10], [14], and will also explore the benefits of the proposed method for processing high spatial resolution fMRI data [32], [33].…”

“…[7], [8], [9], [10], [11]-and volume-based-see e.g. [12], [13], [14], [15]-methods, which differ from methods such as [16], [17], [18], [19] in that they leverage an independent contrast image-different from the data to be smoothedthat confines the spatial profile of the filters.…”

Fine-scale computations for adaptive processing in the human brain

“…For the 3D GRASE control experiment, we used the LAYNII tools ( Huber et al, 2020 ), as they provided better segmentation for images with a limited field of view.…”