TY  - CONF
PB  - Institute of Electrical and Electronics Engineers Inc.
AV  - none
ID  - scholars12930
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091007847&doi=10.1109%2fEMBC44109.2020.9175241&partnerID=40&md5=c7896216e8ccb5ad1405a5a8e5be0043
KW  - Correlation methods; Cost effectiveness; Efficiency; Extraction; Infrared devices; Near infrared spectroscopy; Neurons; Small-world networks
KW  -  Analytical method; Brain connectivity; Functional connectivity; Functional near-infrared spectroscopy (fnirs); Healthy subjects; Minimal spanning tree; Neuronal networks; Oxygenated hemoglobin
KW  -  Cost benefit analysis
EP  - 2904
SP  - 2901
N2  - This paper reported data-driven functional connectivity (FC) analytical method to investigate functional near infrared spectroscopy (fNIRS)-based connectivity. We evaluated the synchronization of oxygenated hemoglobin using Pearson's correlation and employed orthogonal minimal spanning trees (OMSTs) in characterizing brain connectivity. Then we compared the resultant global cost efficiency and robustness with those generated by non-human i.e. lattice and random networks. We also further benchmarked our method using proportional threshold. Results from 59 healthy subjects demonstrated global cost efficiency and assortativity varied in lattice and random network significantly (p < 0.05), highlighting the potential of OMSTs in extracting true neuronal network. Moreover, the inadequate of proportional threshold in extracting small world network from the same dataset supported that the OMSTs might be the better alternative in FC analysis especially in evaluating cost-efficiency and robustness of network. © 2020 IEEE.
A1  - Chan, Y.L.
A1  - Boon Tang, T.
N1  - cited By 0; Conference of 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 ; Conference Date: 20 July 2020 Through 24 July 2020; Conference Code:162693
Y1  - 2020///
SN  - 1557170X
TI  - Characterizing Functional Near Infrared Spectroscopy (fNIRS)-based Connectivity as Cost-effective Small World Network using Orthogonal Minimal Spanning Trees (OMSTs)
VL  - 2020-J
ER  -