How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

Yinying Hu; Zixuan Wang; Bei Song; Yafeng Pan; Xiaojun Cheng; Yi Zhu; Yi Hu

doi:10.3791/62801

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

JoVE Journal
Neuroscience

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JoVE Journal Neuroscience

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

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05:33 min

September 8, 2021

DOI: 10.3791/62801-v

Yinying Hu¹, Zixuan Wang¹, Bei Song², Yafeng Pan³, Xiaojun Cheng⁴, Yi Zhu¹, Yi Hu¹

¹Institute of Brain and Education Innovation, School of Psychology and Cognitive Science,East China Normal University, ²Department of Musicology,Harbin Conservatory of Music, ³Department of Clinical Neuroscience,Karolinska Institutet, ⁴School of Psychology,Shenzhen University

Overview

This study focuses on inter-brain synchronization (IBS) among individuals during coordinated tasks, utilizing functional near-infrared spectroscopy (fNIRS) in a hyperscanning setup. It employs wavelet transform coherence (WTC) for assessing IBS and validates results through permutation-based methods. Critical methodological considerations are discussed to enhance reproducibility and reliability in these studies.

Key Study Components

Area of Science

Neuroscience
Brain Imaging
Interpersonal Coordination

Background

Inter-brain synchronization (IBS) reflects coordination between individuals’ brain activity.
Hyperscanning allows simultaneous recording of brain signals from multiple participants.
Wavelet transform coherence (WTC) is utilized to analyze time-frequency characteristics.
Permutation methods help validate IBS findings by controlling for chance occurrences.

Purpose of Study

To present a protocol for analyzing IBS using fNIRS hyperscanning studies.
To detail how to calculate and validate IBS effectively.
To identify critical methodological considerations for improved analyses.

Methods Used

The study uses functional near-infrared spectroscopy (fNIRS) for brain signal acquisition.
It assesses coordination using the wavelet transform coherent function with MATLAB software.
Data preprocessing includes techniques like principal component analysis and using the NPCA filter.
The procedure involves testing coherence values across experimental conditions and using permutation tests for validation.

Main Results

IBS was observed during specific conditions, indicating synchronization efforts between participants.
The presence of IBS was confirmed through statistical testing and permutation analyses.
The results imply that IBS detection is specific to certain tasks and conditions, enhancing understanding of social interaction dynamics.

Conclusions

This study provides a methodological framework for assessing IBS, aiding future research in interpersonal neuroscience.
It enhances reproducibility and reliability in analyzing neural synchrony between individuals.
The findings contribute valuable insights into the neural basis of social interactions.

Frequently Asked Questions

What is inter-brain synchronization (IBS)?

IBS refers to the synchronization of brain activity between individuals during social interactions or coordinated tasks, highlighting relational dynamics.

How is functional near-infrared spectroscopy (fNIRS) utilized in this study?

fNIRS is employed to record brain signals from multiple participants simultaneously, facilitating the analysis of brain synchronization during tasks.

What role does wavelet transform coherence (WTC) play in the analysis?

WTC is used to evaluate the time-frequency properties of brain oscillations, allowing for a nuanced assessment of IBS over time.

What preprocessing steps are necessary for the fNIRS data?

Key preprocessing steps include removing global physiological noise and correcting for head motion artifacts to enhance data quality.

How are the results validated in this study?

Validation is achieved through permutation-based methods, comparing observed IBS with randomized conditions to ensure results are significant and reliable.

What implications do the findings have for understanding social interactions?

The findings provide insights into the neural mechanisms underlying coordination and social engagement, showcasing how brain activity synchronizes during interactions.

The dynamics between coupled brains of individuals have been increasingly represented by inter-brain synchronization (IBS) when they coordinate with each other, mostly using simultaneous-recording signals of brains (namely hyperscanning) with fNIRS. In fNIRS hyperscanning studies, IBS has been commonly assessed through the wavelet transform coherence (WTC) method because of its advantage on expanding time series into time-frequency space where oscillations can be seen in a highly intuitive way. The observed IBS can be further validated via the permutation-based random pairing of the trial, partner, and condition. Here, a protocol is presented to describe how to obtain brain signals via fNIRS technology, calculate IBS through the WTC method, and validate IBS by permutation in a hyperscanning study. Further, we discuss the critical issues when using the above methods, including the choice of fNIRS signals, methods of data preprocessing, and optional parameters of computations. In summary, using the WTC method and permutation is a potentially standard pipeline for analyzing IBS in fNIRS hyperscanning studies, contributing to both the reproducibility and reliability of IBS.

This protocol provides a potentially standard pipeline of analyzing Inter-Brain synchronization in fNIRS Hyper-scanning Study. The main advantage of this technique is that it allows calculating Inter-Brain synchronization law which will transform coherent method and validate Inter-Brain synchronization ways, permutation based toward empowering of chest conditions and participates. Perform all data analysis using the MATLAB software with appropriate toolboxes.

During data pre-processing, specifically using the principle component analysis and correlation based signal improvement method, remove the F N I R S global physiological noise using the NPCA filter. And the head motion artifacts using the HMR motion correct underscore CBSI of Homer two. Next, for calculating Inter-Brain synchronization or IBS, adopt the wavelet transform coherent function of cross wavelet and wavelet coherent toolbox with default parameters, and compute the coherent values at each time in frequency point to obtain a two axis matrix of coherent values.

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