Key result
The OptoNet MATLAB toolbox was developed to provide a simple and intuitive graphical user interface for analyzing cortical networks using functional near-infrared spectroscopy signals.
Why the study?
Existing analysis toolboxes for functional near-infrared spectroscopy are difficult to use due to numerous steps, coefficients, and related files.
OptoNet provides a simple and intuitive graphical user interface for analyzing cortical networks using fNIRS signals.
Should not yet influence clinical decisions; leaves open enhanced fNIRS network analysis in research.
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.
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Lee et al. (2019) studied this question. OptoNet toolbox was evaluated on Efficacy of the developed toolbox in analyzing cortical networks during a finger tapping task. The OptoNet MATLAB toolbox was developed to provide a simple and intuitive graphical user interface for analyzing cortical networks using functional near-infrared spectroscopy signals.
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