Whole Brain Layer-fMRI Connectome: An Open Dataset

Autor: Müller, Anna Katharina, Huber, Laurentius
Rok vydání: 2020
DOI: 10.5281/zenodo.6860807
Popis: Background – With the first layer-dependent Vascular-Space Occupancy (VASO) studies in humans in 2014/15, a huge breakthrough has been made. Since then, layer-functional magnetic resonance imaging (fMRI) is an emerging method, permanently challenging cutting edge of technology in the neuroimaging field. Purpose – Here, we provide an exemplary layer-dependent whole-brain fMRI connectome acquired at ultra-high magnetic field of 7 Tesla (T), coming along with a quality assessment comprising metrics of skew, kurtosis, temporal Signal-to-Noise Ratio (tSNR) and sharpness. This dataset demonstrates consistency and reproducibility of a whole brain layer-fMRI connectome paving the way for novel research questions in the neuroscientific field. The purpose of this dataset is to 1.) characterize the prospects and challenges of whole brain layer-fMRI acquisition sequences in a test-retest setting and 2.) to provide a test bed for developing and benchmarking new layer-dependent analysis tools. Data Accessibility –This is an initial release of an ongoing study, published in line with the Brian Imaging Data Structure (BIDS) standard on OpenNeuro, a free and open platform for sharing research data. We are happy to share the data via SIEMENS C2P.
Databáze: OpenAIRE