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.