VISUALIZATION OF TEMPORAL PATTERNS OF COMPLEX BRAIN ACTIVITY

复杂大脑活动时间模式的可视化

• 批准号: 8171154
• 负责人: GREGORY V SIMPSON
• 金额: $ 0.61万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171154
• 关键词: Area; Brain; Brain region; Complex; Computer Retrieval of Information on Scientific Projects Database; Data; Dependency; Functional Magnetic Resonance Imaging; Funding; Grant; Hybrids; Imagery; Imaging Techniques; Institution; Mental Processes; Methods; Multimodal Imaging; Nature; Neurons; Pattern; Positron-Emission Tomography; Research; Research Personnel; Resolution; Resources; Source; Structure; Study models; United States National Institutes of Health; interest; neurophysiology; operation; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project is aimed at developing optimal methods for visualizing spatial and temporal features of complex brain activity. The hybrid nature of brain networks (i.e. combinations of serial, parallel, local independent operations and hierarchical dependencies within a network) is expected to result in very complicated spatial?temporal patterns of activity underlying mental processes. Anatomical studies have demonstrated modular organization in the brain with extensive interconnectivity consistent with network structures. Neurophysiological studies have uncovered the tremendous range of temporal activity patterns possible in ensembles of neurons within a brain area and modeling studies suggest that such patterns can encode a variety of functions (e.g. Steriade et al., 1996; Samsonovich & McNaughton, 1997). An even larger range of temporal patterns can be expected when one considers activity across brain areas. Explorations of temporal patterns between small numbers of neurons (e.g. 2 or 3), or brain areas, have shown interesting correlations in activity (e.g. McClurkin & Optican, 1996; Engel et al., 1997). It is likely that much more will be revealed as we look at the spatial temporal patterns between all the interconnected areas underlying a given mental process (Simpson et al., 1995). Methods that examine correlations between activation in different brain regions have been applied initially to PET and fMRI data (Friston et al., 1996). Our group will expand upon this approach by taking advantage of the high resolution temporal patterns within and between active regions provided by our integrated multimodal imaging techniques. However, the spatial temporal patterns will be an order of magnitude more complex than those currently being studied with other methods, requiring the new tools provided by this Center for visualization and analysis.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 中心，不一定是研究者的机构。 该项目旨在开发可视化复杂大脑活动的空间和时间特征的最佳方法。 大脑网络的混合性质（即网络内串行、并行、局部独立操作和层次依赖性的组合）预计将导致心理过程中非常复杂的时空活动模式。 解剖学研究表明，大脑中的模块化组织具有与网络结构一致的广泛互连性。 神经生理学研究揭示了大脑区域内神经元群可能存在的巨大范围的时间活动模式，并且建模研究表明这种模式可以编码多种功能（例如，Seriade 等人，1996 年；Samsonovich 和 McNaughton，1997 年）。 当考虑跨大脑区域的活动时，可以预期更大范围的时间模式。对少量神经元（例如 2 或 3 个）或大脑区域之间时间模式的探索显示出有趣的活动相关性（例如 McClurkin & Optican，1996；Engel 等，1997）。 当我们观察给定心理过程中所有相互关联的区域之间的时空模式时，很可能会揭示更多的内容（Simpson 等人，1995）。检查不同大脑区域激活之间相关性的方法最初已应用于 PET 和 fMRI 数据（Friston 等，1996）。 我们的团队将利用我们的集成多模态成像技术提供的活动区域内和活动区域之间的高分辨率时间模式来扩展这种方法。 然而，时空模式将比目前使用其他方法研究的时空模式复杂一个数量级，需要该中心提供的新工具进行可视化和分析。