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8 October 2019 OptoNet: a MATLAB-based toolbox for cortical network analyses using functional near-infrared spectroscopy
Gihyoun Lee, Ji-Su Park, Young-Jin Jung
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Abstract

Functional brain network analysis is important for understanding the causes of neurological disorders and relevant brain mechanisms. Lately, functional near-infrared spectroscopy (fNIRS) yields outputs similar to the blood-oxygen-level-dependent signals of functional magnetic resonance imaging (fMRI), and numerous studies have been conducted on functional connectivity and causality using fMRI and fNIRS. Despite the existence of numerous analysis toolboxes for fNIRS, most of them are difficult to use because they involve numerous steps, coefficients, and related files. In this study, we developed a MATLAB toolbox called OptoNet, to analyze cortical networks in the brain for fNIRS. Given that OptoNet consists of a simple and intuitive graphical user interface, users can readily analyze the cortical networks of the brain for fNIRS signals. To evaluate the efficacy of the developed toolbox, the finger tapping task experiment—extensively used in brain functional activities and causal connectivity studies—was employed. The experiment was performed using the right and left hands, and both hands simultaneously, and the consequently elicited brain cortical network activity was analyzed using developed OptoNet.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Gihyoun Lee, Ji-Su Park, and Young-Jin Jung "OptoNet: a MATLAB-based toolbox for cortical network analyses using functional near-infrared spectroscopy," Optical Engineering 59(6), 061602 (8 October 2019). https://doi.org/10.1117/1.OE.59.6.061602
Received: 8 July 2019; Accepted: 14 August 2019; Published: 8 October 2019
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Brain

Network security

Hemodynamics

Functional magnetic resonance imaging

Data modeling

MATLAB

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