McIntosh A R, Grady C L, Ungerleider L G, Haxby J V, Rapoport S I, Horwitz B
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
J Neurosci. 1994 Feb;14(2):655-66. doi: 10.1523/JNEUROSCI.14-02-00655.1994.
Brain metabolic mapping techniques, such as positron emission tomography (PET), can provide information about the functional interactions within entire neural systems. With the large quantity of data that can accumulate from a mapping study, a network analysis, which makes sense of the complex interactions among neural elements, is necessary. A network analysis was performed on data obtained from a PET study that examined both the changes in regional cerebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot-location matching) task. Brain areas for the network were selected based on regions showing significant rCBF or interregional correlations between tasks. Anterior temporal and frontal lobe regions were added to the network using a principal components analysis. Interactions among selected regions were quantified with structural equation modeling. In the structural equation models, connections between brain areas were based on known neuroanatomy and the interregional correlations were used to calculate path coefficients representing the magnitude of the influence of each directional path. The combination of the anatomical network and interregional correlations created a functional network for each task. The functional network for the right hemisphere showed that in the object vision task, dominant path influences were among occipitotemporal areas, while in the spatial vision task, occipitoparietal interactions were stronger. The network for the spatial vision task also had a strong feedback path from area 46 to occipital cortex, an effect that was absent in the object vision task. There were strong interactions between dorsal and ventral pathways in both networks. Functional networks for the left hemisphere did not differ between tasks. Networks for the interhemispheric interactions showed that the dominant pathway in the right hemisphere also had stronger effects on homologous left hemisphere areas and are consistent with a hypothesis that intrahemispheric interactions were greater in the right hemisphere in both tasks, and that these influences were transmitted callosally to the left hemisphere.
脑代谢图谱技术,如正电子发射断层扫描(PET),可以提供有关整个神经系统内功能相互作用的信息。由于图谱研究可能积累大量数据,因此需要进行网络分析,以理解神经元件之间的复杂相互作用。对从一项PET研究中获得的数据进行了网络分析,该研究在执行物体视觉(面部匹配)和空间视觉(点位置匹配)任务期间,检查了局部脑血流量(rCBF)的变化以及人类皮质区域之间的区域间相关性。基于显示出显著rCBF或任务之间区域间相关性的区域来选择网络的脑区。使用主成分分析将颞叶前部和额叶区域添加到网络中。用结构方程模型对选定区域之间的相互作用进行量化。在结构方程模型中,脑区之间的连接基于已知的神经解剖学,区域间相关性用于计算表示每个定向路径影响大小的路径系数。解剖网络和区域间相关性的结合为每个任务创建了一个功能网络。右半球的功能网络表明,在物体视觉任务中,主要的路径影响发生在枕颞区域之间,而在空间视觉任务中,枕顶叶相互作用更强。空间视觉任务的网络还具有从46区到枕叶皮质的强反馈路径,这一效应在物体视觉任务中不存在。两个网络中背侧和腹侧通路之间都存在强相互作用。左半球的功能网络在不同任务之间没有差异。半球间相互作用的网络表明,右半球的主要通路对同源的左半球区域也有更强的影响,这与一个假设一致,即在两个任务中,右半球的半球内相互作用更大,并且这些影响通过胼胝体传递到左半球。