Spatial independent component analysis of functional brain optical imaging

Yong Li; Pengcheng Li; Yadong Liu; Weihua Luo; Dewen Hu; Qingming Luo

doi:10.1117/12.546140

8 December 2003 Spatial independent component analysis of functional brain optical imaging

Yong Li, Pengcheng Li, Yadong Liu, Weihua Luo, Dewen Hu, Qingming Luo

Proceedings Volume 5254, Third International Conference on Photonics and Imaging in Biology and Medicine; (2003) https://doi.org/10.1117/12.546140
Event: Third International Conference on Photonics and Imaging in Biology and Medicine, 2003, Wuhan, China

Abstract

This paper introduces the algorithm and the basic theory of Independent Component Analysis (ICA), and discusses how to choose the proper ICA model of the data by the characteristics of the underlying signals to be estimated. The Spatial ICA (SICA) is applied to model and analysis of the data in the experiment when the signals and noises are spatially dependent. The data acquired from the intrinsic optical signals which are caused by electricity stimulation to sciatic nerve of rat are analyzed by SICA. In the result, the active-related component of the signals and its time course can be separate, and the signals of heartbeat and respiration also can be separated.

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Yong Li, Pengcheng Li, Yadong Liu, Weihua Luo, Dewen Hu, and Qingming Luo "Spatial independent component analysis of functional brain optical imaging", Proc. SPIE 5254, Third International Conference on Photonics and Imaging in Biology and Medicine, (8 December 2003); https://doi.org/10.1117/12.546140

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KEYWORDS

Independent component analysis

Data modeling

Optical imaging

Brain

Neuroimaging

Interference (communication)

Nerve

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