Neuronal Chronometry of Target Detection: Fusion of Hemodynamic and Event-Related Potential Data

V. Calhoun,T. Adalı,G. Pearlson,K. Kiehl

Published 2005 in IEEE Workshop on Machine Learning for Signal Processing

ABSTRACT

Functional magnetic resonance imaging (fMRI) data provides spatially localized subcentimeter information about blood flow and oxygenation secondary to neuronal activation, but with temporal resolution on the order of seconds. Event-related potential (ERP) studies provide millimeter resolution measurements of the electric changes induced by neuronal activity, but spatial information is not well localized and suffers from an ill-posed inverse problem since there are much fewer sensors than solutions. Combining or fusing these two techniques thus has the potential to provide simultaneous higher temporal and high spatial resolution. Localization of the brain's response to infrequent, task-relevant target 'oddball' stimuli in humans has remained challenging due to the lack of a single imaging technique with good spatial and temporal resolution. Here we use independent component analysis to fuse ERP and fMRI modalities to identify, for the first time in humans, the dynamics of the auditory oddball response with high spatiotemporal resolution across the entire brain. The results illuminate a new era of brain research utilizing the precise temporal information in ERPs and the high spatial resolution of fMRI

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