Activation detection in functional near-infrared spectroscopy by wavelet coherence

Zhang, Xin, Yu, Jian, Zhao, Ruirui, Xu, Wenting, Niu, Haijing, Zhang, Yujin, Zuo, Nianming and Jiang, Tianzi (2015) Activation detection in functional near-infrared spectroscopy by wavelet coherence. Journal of Biomedical Optics, 20 1: 016004-1-016004-9. doi:10.1117/1.JBO.20.1.016004

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Author Zhang, Xin
Yu, Jian
Zhao, Ruirui
Xu, Wenting
Niu, Haijing
Zhang, Yujin
Zuo, Nianming
Jiang, Tianzi
Title Activation detection in functional near-infrared spectroscopy by wavelet coherence
Journal name Journal of Biomedical Optics   Check publisher's open access policy
ISSN 1560-2281
Publication date 2015-01-06
Year available 2015
Sub-type Article (original research)
DOI 10.1117/1.JBO.20.1.016004
Open Access Status File (Publisher version)
Volume 20
Issue 1
Start page 016004-1
End page 016004-9
Total pages 9
Place of publication Bellingham, WA, United States
Publisher S P I E - International Society for Optical Engineering
Collection year 2016
Language eng
Abstract Functional near-infrared spectroscopy (fNIRS) detects hemodynamic responses in the cerebral cortex by transcranial spectroscopy. However, measurements recorded by fNIRS not only consist of the desired hemodynamic response but also consist of a number of physiological noises. Because of these noises, accurately detecting the regions that have an activated hemodynamic response while performing a task is a challenge when analyzing functional activity by fNIRS. In order to better detect the activation, we designed a multiscale analysis based on wavelet coherence. In this method, the experimental paradigm was expressed as a binary signal obtained while either performing or not performing a task. We convolved the signal with the canonical hemodynamic response function to predict a possible response. The wavelet coherence was used to investigate the relationship between the response and the data obtained by fNIRS at each channel. Subsequently, the coherence within a region of interest in the time-frequency domain was summed to evaluate the activation level at each channel. Experiments on both simulated and experimental data demonstrated that the method was effective for detecting activated channels hidden in fNIRS data.
Keyword Functional monitoring and imaging
Image analysis
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2016 Collection
Centre for Advanced Imaging Publications
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