ORTHOGONAL MINIMAL SPANNING TREES (OMSTS) TO ANALYZE FUNCTIONAL NEAR-INFRARED SPECTROSCOPY BASED FUNCTIONAL CONNECTIVITY (FNIRS-FC)
While functional connectivity (FC) has been suggested to reflect brain health, there are significant challenges in defining the survival of connectivity using the current thresholding techniques, especially for the study on functional near-infrared spectroscopy (fNIRS). The current thresholding met...
| Main Author: | CHAN, YEE LING |
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| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.20507 / |
| Published: |
2020
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/20507/1/Chan%20Yee%20Ling_17009922.pdf http://utpedia.utp.edu.my/20507/ |
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| Summary: |
While functional connectivity (FC) has been suggested to reflect brain health, there are significant challenges in defining the survival of connectivity using the current
thresholding techniques, especially for the study on functional near-infrared spectroscopy (fNIRS). The current thresholding methods are inconsistent as they are user-dependent, bias, and have low result reproducibility. A new method that employs wavelet analysis for motion correction and orthogonal minimal spanning trees (OMSTs) to derive brain connectivity was proposed in this study to analyze fNIRSFC. OMSTs thresholding method has been innovated from previous studies on functional magnetic resonance imaging (fMRI) and adapted for the fNIRS study. |
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