Mapping brain activity in gradient-echo functional MRI using principal component analysis

Deepak Khosla; Manbir Singh; Manuel Don

doi:10.1117/12.274035

9 May 1997 Mapping brain activity in gradient-echo functional MRI using principal component analysis

Deepak Khosla, Manbir Singh, Manuel Don

Proceedings Volume 3033, Medical Imaging 1997: Physiology and Function from Multidimensional Images; (1997) https://doi.org/10.1117/12.274035
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.

Citation Download Citation

Deepak Khosla, Manbir Singh, and Manuel Don "Mapping brain activity in gradient-echo functional MRI using principal component analysis", Proc. SPIE 3033, Medical Imaging 1997: Physiology and Function from Multidimensional Images, (9 May 1997); https://doi.org/10.1117/12.274035

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