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fMRI-based decoding of the modified default-mode network in mild cognitive impairment
This video was recorded at NIPS Workshop on New Directions on Decoding Mental States from fMRI Data, Whistler 2006. The diagnostic tool to detect early stages of Alzheimer's Disease, a progressive neurodegenerative disease, is lacking until today. FDG-PET (Fluorodeoxyglucose-Positron Emission Tomography) shows hypometabolic areas in the brains of pre-demented, i.e. patients suffering from mild cognitive impairment (MCI). The reduced activity may be attributed to disrupted connectivity of the resting-, or default-mode network of the brain [1]. In this contribution, we study the detection of such a network using the framework of blind signal processing, a technique to identify hidden sources within a multivariate mixture using source characteristics such as statistical independence or sparseness. The results are compared to FDG-PET data.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
