Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century
Niels Alexander Foit,
Seles Yung,
Hyo Min Lee,
Andrea Bernasconi,
Neda Bernasconi,
Seok-Jun Hong
Affiliations
Niels Alexander Foit
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Corresponding author at: Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada.
Seles Yung
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
Hyo Min Lee
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
Andrea Bernasconi
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
Neda Bernasconi
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
Seok-Jun Hong
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Center for the Developing Brain, Child Mind Institute, NY, USA; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea
Obtaining precise and detailed parcellations of the human brain has been a major focus of neuroscience research. Here, we present a multimodal dataset, MYATLAS, based on histology-derived myeloarchitectonic parcellations for use with contemporary neuroimaging analyses software. The core of MYATLAS is a novel 3D neocortical, surface-based atlas derived from legacy myeloarchitectonic histology studies. Additionally, we provide digitized quantitative laminar profiles of intracortical myelin content derived from postmortem photometric data, cross-correlated with in vivo myeloarchitectonic features obtained by quantitative MRI mapping. Moreover, congregated, digitized and quality-improved Vogt-Vogt legacy histology data is made available. Finally, to allow for cross-modality correlations, maps of quantitative myelin estimates and corresponding von Economo-Koskinas’ cytoarchitectonic features are also included. We share all necessary surface and volume-based registration files as well as shell scripts to facilitate applications of MYATLAS to future in vivo MRI studies.
