Foit Niels Alexander, Yung Seles, Lee Hyo Min, Bernasconi Andrea, Bernasconi Neda, Hong Seok-Jun
Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada.
Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany.
Data Brief. 2023 Feb 20;47:108999. doi: 10.1016/j.dib.2023.108999. eCollection 2023 Apr.
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 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 MRI studies.
获得人类大脑精确而详细的脑区划分一直是神经科学研究的主要焦点。在此，我们展示了一个多模态数据集MYATLAS，它基于组织学衍生的髓鞘构筑脑区划分，可用于当代神经成像分析软件。MYATLAS的核心是一个新颖的基于表面的三维新皮质图谱，源自传统的髓鞘构筑组织学研究。此外，我们提供了从死后光度数据得出的皮质内髓鞘含量的数字化定量分层剖面图，并与通过定量MRI映射获得的髓鞘构筑特征进行了交叉关联。此外，还提供了汇总、数字化且质量得到提升的沃格特 - 沃格特传统组织学数据。最后，为了实现跨模态关联，还纳入了定量髓鞘估计图以及相应的冯·埃科诺莫 - 科斯金纳斯细胞构筑特征图。我们共享所有必要的基于表面和体积的配准文件以及外壳脚本，以促进将MYATLAS应用于未来的MRI研究。
