Suppr超能文献

全自动区域性人类脑影像行为分析

Automated regional behavioral analysis for human brain images.

机构信息

Research Imaging Institute, The University of Texas Health Science Center at San Antonio San Antonio, TX, USA.

出版信息

Front Neuroinform. 2012 Aug 28;6:23. doi: 10.3389/fninf.2012.00023. eCollection 2012.

Abstract

Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score ≥ 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of 100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten "major representative" functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions.

摘要

行为类别和功能成像实验相关的激活的标准化脑坐标被用于开发一种自动分析人类大脑图像的区域行为的方法。行为和坐标数据取自 BrainMap 数据库(http://www.brainmap.org/),该数据库记录了 20 多年来发表的功能脑成像研究。如果图像空间归一化为 MNI 或 Talairach 标准,可以在功能图像、解剖图像或脑图谱中定义行为分析的感兴趣脑区(ROI)。为跨越五个行为领域(行动、认知、情感、内感受和感知)的 BrainMap 的 51 个行为子领域中的每一个呈现行为分析的结果。对于每个行为子领域,计算落在 ROI 内的坐标的分数,并将其与行为坐标未聚类时(即均匀分布)的分数进行比较。如果这些分数之间的差异较大,则表示存在行为关联。使用 z 分数≥3.0 来指定具有统计学意义的行为关联。通过半球、叶和行为子领域评估了约 10 万个激活焦点的左右对称性。结果突出了语言的经典左侧优势,而大多数子领域(约 75%)的不对称性没有统计学意义。为哈佛-牛津皮质(HOC)脑图谱的解剖 ROI、TMS-PET 研究中的统计参数图的功能 ROI、基于任务的 fMRI 研究中的功能 ROI 以及之前发表的静息状态 fMRI 研究中的十个“主要代表性”功能网络的 ROI 呈现了使用场景。这些使用场景的统计学显著行为发现与相关解剖和功能区域的已发表行为一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27a2/3428588/483d59887909/fninf-06-00023-g0001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验