Spatiotemporal Imaging of Human Visual System Processing

描述（由申请人提供）：我们研究项目的总体目标是开发一个全面的实验和分析框架，用于感知，认知和行动的神经基础的时空成像和建模。根据我们的一般模型，复杂行为源于空间分布的神经系统的协调活动，而不是特定的解剖部位，从而产生了在空间和时间上分布的脑-行为关系。迄今为止，我们已经开发了一系列时空成像方法，使创新的，非侵入性的人类视觉系统的研究在更高的空间和时间分辨率比以前实现。我们现在建议通过探索以更高的采样率获取功能性脑成像数据的方法，探索大脑远程空间同步的机制，并通过建立一个强大的因果建模框架来更好地理解感知和视觉运动处理过程中的信息流，从而推进我们的时空成像方法的发展。为此，我们开发了结合功能磁共振成像（fMRI）和脑磁图/脑电图（MEG/EEG）数据的新方法，以获得高时间（毫秒）和空间（毫米）分辨率的无创大脑活动时空图。我们建议继续并扩大这项技术发展。具体而言，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大脑振荡活动的机制，从而提高脑时空成像方法的准确性和灵敏度。此外，我们将继续发展因果建模方法，允许研究大规模分布式神经元相互作用如何产生感知和认知。最后，我们将把这些技术进步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，我们将多种成像模式的信息结合起来的方法应该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，例如与中风、脑肿瘤、阿尔茨海默病和发育障碍相关的异常。

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.