Detecting brain activations by constrained non-negative matrix factorization from task-related BOLD fMRI

Xiaoxiang Wang; Jie Tian; Xingfeng Li; Jianping Dai; Lin Ai

doi:10.1117/12.536186

30 April 2004 Detecting brain activations by constrained non-negative matrix factorization from task-related BOLD fMRI

Xiaoxiang Wang, Jie Tian, Xingfeng Li, Jianping Dai, Lin Ai

Proceedings Volume 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images; (2004) https://doi.org/10.1117/12.536186
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Non-negative Matrix Factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. In this paper, we introduce this new technique to the field of fMRI data analysis. In order to make the representation suitable for task-related brain activation detection, we imposed some additional constraints, and defined an improved contrast function. We deduced the update rules and proved the convergence of the algorithm. In the procedure, the number of factors was determined by visual assessment. We studied 8 healthy right-handed adult volunteers by a 3.0T GE Signa scanner. A block design motor paradigm (bilateral finger tapping) stimulated the blood oxygenation level-dependent (BOLD) response. Gradient Echo EPI sequence was utilized to acquire BOLD contrast functional images. With this constrained NMF (cNMF) we could obtain major activation components and the corresponding time courses, which showed high correlation with the reference function (r>0.7). The results showed that our method would be feasible for detection brain activations from task-related fMRI series.

Citation Download Citation

Xiaoxiang Wang, Jie Tian, Xingfeng Li, Jianping Dai, and Lin Ai "Detecting brain activations by constrained non-negative matrix factorization from task-related BOLD fMRI", Proc. SPIE 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, (30 April 2004); https://doi.org/10.1117/12.536186

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