Calvert G A
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, Oxford OX3 9DU, UK.
Cereb Cortex. 2001 Dec;11(12):1110-23. doi: 10.1093/cercor/11.12.1110.
Modern brain imaging techniques have now made it possible to study the neural sites and mechanisms underlying crossmodal processing in the human brain. This paper reviews positron emission tomography, functional magnetic resonance imaging (fMRI), event-related potential and magnetoencephalographic studies of crossmodal matching, the crossmodal integration of content and spatial information, and crossmodal learning. These investigations are beginning to produce some consistent findings regarding the neuronal networks involved in these distinct crossmodal operations. Increasingly, specific roles are being defined for the superior temporal sulcus, the inferior parietal sulcus, regions of frontal cortex, the insula cortex and claustrum. The precise network of brain areas implicated in any one study, however, seems to be heavily dependent on the experimental paradigms used, the nature of the information being combined and the particular combination of modalities under investigation. The different analytic strategies adopted by different groups may also be a significant factor contributing to the variability in findings. In this paper, we demonstrate the impact of computing intersections, conjunctions and interaction effects on the identification of audiovisual integration sites using existing fMRI data from our own laboratory. This exercise highlights the potential value of using statistical interaction effects to model electrophysiological responses to crossmodal stimuli in order to identify possible sites of multisensory integration in the human brain.
现代脑成像技术现已使研究人类大脑中跨模态加工的神经位点和机制成为可能。本文综述了正电子发射断层扫描、功能磁共振成像(fMRI)、事件相关电位和脑磁图对跨模态匹配、内容与空间信息的跨模态整合以及跨模态学习的研究。这些研究开始就参与这些不同跨模态操作的神经网络产生一些一致的发现。颞上沟、顶下沟、额叶皮质区域、岛叶皮质和屏状核的特定作用越来越明确。然而,任何一项研究中涉及的脑区精确网络似乎在很大程度上取决于所使用的实验范式、所组合信息的性质以及所研究的特定模态组合。不同研究团队采用的不同分析策略也可能是导致研究结果变异性的一个重要因素。在本文中,我们利用来自我们自己实验室的现有fMRI数据,展示了计算交集、联合和交互效应在识别视听整合位点方面的影响。这项工作突出了使用统计交互效应来模拟对跨模态刺激的电生理反应以识别人类大脑中多感官整合可能位点的潜在价值。