Spatiotemporal Imaging of Human Visual System Processing

描述(由申请人提供)：我们研究计划的总体目标是开发一个全面的实验和分析框架，用于时空成像和感知、认知和行动的神经基础的建模。根据我们的一般模型，复杂的行为是空间分布的神经系统协调活动的结果，而不是特定解剖位置的协调活动，从而产生在空间和时间上分布的大脑-行为关系。到目前为止，我们已经开发了一系列时空成像方法，使得对人类视觉系统的创新、非侵入性研究能够以比以前更高的空间和时间分辨率进行。我们现在建议通过探索以更高的采样率获取功能脑成像数据的方法来推进时空成像方法的发展，探索远程空间同步的大脑机制，并通过建立稳健的因果建模框架来实现对知觉和视觉运动处理过程中的信息流的更好理解。为此，我们开发了结合功能磁共振成像(FMRI)和脑磁图/脑电(MEG/EEG)数据的新方法，以获得高时间(毫秒)和空间(毫米)分辨率的无创脑活动时空图。我们建议继续并扩大这一技术开发。具体地说，我们将进一步改进fMRI和MEG/EEG数据采集和分析方法，并结合fMRI、MEG和EEG数据源开发新的方法来探索脑活动振荡的机制，从而提高时空脑成像方法的准确性和灵敏度。此外，我们将继续开发因果建模方法，允许研究大规模分布的神经元相互作用如何引起感知和认知。最后，我们将把这些技术进展应用于人类高级视觉和视觉运动加工的研究，包括基于特征的注意和大脑半球间信息传递的神经机制的研究。鉴于MRI和EEG/MEG的可用性越来越高，我们将来自多种成像模式的信息结合在一起的方法应该会对促进对复杂行为的神经基础的理解产生重大影响。在我们的研究过程中开发的神经成像技术可能有助于调查各种临床异常，如与中风、脑瘤、阿尔茨海默病和发育障碍有关的异常。

DESCRIPTION (provided by applicant): The overall goal of our research program is the development of a comprehensive experimental and analytical framework for spatiotemporal imaging and modeling of the neural basis of perception, cognition and action. According to our general model, complex behavior results from the coordinated activity of spatially distributed neural systems rather than specific anatomical sites, giving rise to brain-behavior relationships that are distributed in space and time. To date, we have developed a range of spatiotemporal imaging methods that have enabled innovative, non-invasive studies of the human visual system at higher spatial and temporal resolution than previously achieved. We now propose to carry forward the development of our spatiotemporal imaging approach by exploring methods for acquiring functional brain imaging data at ever higher sampling rates, probing the brain mechanisms for long-range spatial synchronization and achieving a better understanding of information flow during perceptual and visuomotor processing by establishing a robust framework for causal modeling. To these ends we have developed novel methods combining functional MRI (fMRI) and magnetoencephalography / electroencephalography (MEG/EEG) data to obtain noninvasive spatiotemporal maps of cerebral activity with both high temporal (millisecond) and spatial (millimeter) resolution. We propose to continue and extend this technical development. Specifically, we will further improve fMRI and MEG/EEG data acquisition and analysis methods and develop new methods to explore mechanisms of oscillatory brain activity by combining fMRI, MEG and EEG data sources, thereby increasing the accuracy and sensitivity of the spatiotemporal brain imaging approach. Further, we will continue development of causal modeling approaches, allowing for the study of how large-scale distributed neuronal interactions give rise to perception and cognition. Finally, we will apply these technical advances to studies of human higher visual and visuomotor processing, including studies of the neural mechanisms of feature-based attention and interhemispheric information transfer. Given the increasing availability of both MRI and EEG/MEG, our approach of combining information from multiple imaging modalities should have significant impact on advancing the understanding of the neural bases of complex behavior. The neuroimaging techniques developed during the course of our research may help the investigation of a variety of clinical abnormalities, such as those associated with stroke, brain tumors, Alzheimer's disease, and developmental disorders.