Analysis of Event-Related fMRI Data Using Diffusion Maps

11 years 7 months ago
Analysis of Event-Related fMRI Data Using Diffusion Maps
The blood oxygen level-dependent (BOLD) signal in response to brief periods of stimulus can be detected using event-related functional magnetic resonance imaging (ER-fMRI). In this paper, we propose a new approach for the analysis of ER-fMRI data. We regard the time series as vectors in a high dimensional space (the dimension is the number of time samples). We believe that all activated times series share a common structure and all belong to a low dimensional manifold. On the other hand, we expect the background time series (after detrending) to form a cloud around the origin. We construct an embedding that reveals the organization of the data into an activated manifold and a cluster of non-activated time series. We use a graph partitioning technique?the normalized cut to find the separation between the activated manifold and the background time series. We have conducted several experiments with synthetic and in-vivo data that demonstrate the performance of our approach.
François G. Meyer, Xilin Shen
Added 16 Nov 2009
Updated 16 Nov 2009
Type Conference
Year 2005
Where IPMI
Authors François G. Meyer, Xilin Shen
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