The proposed project will combine cross-sectional and longitudinal designs, and employ both task-related and resting-state fMRI techniques, and the data will be collected from Alzheimer's Disease patients (AD), amnesic Mild Cognitive Impairment subjects (aMCI), and elderly normal controls (NC). Based on the previous findings that aMCI and AD demonstrated impaired explicit memory (especially the most impaired associative episodic memory) but intact implicit memory, we will take the interdisciplinary strengths from psychology, neural computation and medicine to investigate their brain activations in specific regions while the subjects are performing these memory tasks, and then will adopt the correlation analysis and Bayesian network learning approach to compute the functional connectivity and effective connectivity among these activated brain regions. Relying on the neural network knowledge derived from task-related fMRI data, we will try to find corresponding memory network during baseline resting-state, and then using this intrinsic connectivity to predict the development of memory impairment within 3 years follow up. We predict there will be a visual memory network beginning from occipital visual cortex going through fusiform gyrus to mesial temporal lobe (MTL), and finally reaching prefrontal cortex (PFC).
修改评论