Gao Peng, Luan Jixin, Yang Aocai, Xu Manxi, Lv Kuan, Hu Pianpian, Yu Hongwei, Yao Zeshan, Ma Guolin
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Developmental Population Neuroscience Research Center, International Data Group/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Sci Data. 2025 Jan 14;12(1):62. doi: 10.1038/s41597-025-04383-4.
The sharing of multimodal magnetic resonance imaging (MRI) data is of utmost importance in the field, as it enables a deeper understanding of facial nerve-related pathologies. However, there is a significant lack of multi-modal neuroimaging databases specifically focused on these conditions, which hampers our comprehensive knowledge of the neural foundations of facial paralysis. To address this critical gap and propel advancements in this area, we have released the Multimodal Neuroimaging Dataset of Meige Syndrome, Facial Paralysis, and Healthy Controls (MND-MFHC). This dataset includes detailed clinical assessments of 53 individuals with facial paralysis (FP), 31 patients with Meige syndrome (MS), and 102 healthy controls (HC). To promote open access, the BIDS-formatted data and associated quality control reports can be accessed through the Science Data Bank (SciDB). By sharing this comprehensive dataset, our aim is to facilitate further research and exploration into the intricate neural mechanisms underlying facial nerve-related pathologies.
在该领域,多模态磁共振成像(MRI)数据的共享至关重要,因为它有助于更深入地了解面神经相关病变。然而,严重缺乏专门针对这些病症的多模态神经影像数据库,这阻碍了我们对面部麻痹神经基础的全面认识。为了填补这一关键空白并推动该领域的进展,我们发布了梅杰综合征、面神经麻痹和健康对照多模态神经影像数据集(MND-MFHC)。该数据集包括对53例面神经麻痹(FP)患者、31例梅杰综合征(MS)患者和102名健康对照(HC)的详细临床评估。为促进开放获取,可通过科学数据银行(SciDB)访问符合BIDS格式的数据及相关质量控制报告。通过共享这个综合数据集,我们的目标是促进对与面神经相关病变背后复杂神经机制的进一步研究和探索。