차 의과학대학교 | 최근연구논문
Quick

자주찾는 메뉴

산학‧연구

 

HyperOptoNet: a MATLAB-based toolbox for inter-brain neuronal synchrony analysis using fNIRS hyperscanning

개제 일
2023-06-13
주 저자
공동 저자
신세영: 분당차병원 재활의학과
학술지 명
Neurophotonics
인용 지수
5.3

Abstract



Significance

We developed a MATLAB-based toolbox for the analysis of inter-brain synchrony (IBS) and performed an experimental study to confirm its performance. To the best of our knowledge, this is the first toolbox for IBS based on functional near-infrared spectroscopy (fNIRS) hyperscanning data that visually shows the results on two three-dimensional (3D) head models.

Aim

Research on IBS using fNIRS hyperscanning is a nascent but expanding field. Although various analysis toolboxes for fNIRS exist, none can show inter-brain neuronal synchrony on a 3D head model. In 2019 and 2020, we released two MATLAB toolboxes named OptoNet I and II, which have helped researchers to analyze functional brain networks using fNIRS. We developed a MATLAB-based toolbox named HyperOptoNet to overcome the limitation of the previous OptoNet series.

Approach

The developed HyperOptoNet can easily analyze inter-brain cortical connectivity using fNIRS hyperscanning signals simultaneously measured from two people at the same time. The connectivity results can be easily recognized by representing inter-brain neuronal synchrony with colored lines that are visually expressed on two standard head models.

Results

To evaluate the performance of the developed toolbox, we conducted an fNIRS hyperscanning study of 32 healthy adults. The fNIRS hyperscanning data were measured while the subjects performed traditional, paper-and-pencil-based, cognitive tasks or interactive, computer-assisted, cognitive tasks (ICT). The results visualized different inter-brain synchronization patterns according to the interactive nature of the given tasks; a more extensive inter-brain network was seen with the ICT.

Conclusions

The developed toolbox has good performance of IBS analysis and helps even unskilled researchers to easily analyze fNIRS hyperscanning data.

PMID 37325778