How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study
September 8th, 2021
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 fu
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.
For the default parameters, use the Morlet mother wavelet to transform each time series into the time and frequency domain by the continuous wavelet transformation. Next, to choose the frequency band of interest, select an average the coherent values of the frequency band between 0.5 to one Hertz. According to the frequency band used in the finger motion task of the F N I R S Hyper-scanning study.
Obtain one column of coherent values for each pair. Then, select an average the coherent values of the time window during the resting stage. And for each experimental condition, using the information of mark, obtain five coherent values for each dyad for the task session, only select the duration during which participants tapped to reproduce the auditory stimulus, which is about 12 seconds for each trial resulting in a total of 180 seconds for each experimental condition.
Then, subtract the resting coherent value from the task related coherent value. Since the coherence value during the resting state is used as a baseline in this experiment. Next, using the paired samples permutation T test with the malt underscore comp underscore perm T1 function of drops work.
Compare the subtracted coherent values with zero at each channel for each experimental condition. Then, using the a FDR function of the MATLAB toolbox, correct the P values by the false discovery rate method. Next, using the paired samples permutation T test with the malt underscore comp underscore perm underscore T1 function of drops work, compare the coherence values between different task conditions at the channel where IBS existed.
For validating the IBS, use the rant perm function a MATLAB to randomize the label of trials in the meter coordination condition for one dyad at each channel. Follow the demonstrated pipeline for calculating the IBS and statistics for the randomized trial label, excluding the sensitivity analysis for the frequency band of interest. Conduct the permutation 1000 times, then plot the distribution of statistical Z values generated within dyad permutation.
Next, follow the pipeline to calculate the IBS and statistics after randomizing the pairing of the participants of the same trial, in the meter coordination condition. Finally, follow the pipeline again after randomizing the condition labels for the same members of one dyad in the same trial. The results showed the presence of IBS at channel five in the meter coordination condition.
Whereas no IBS was detected in the other conditions. At channel five, the IBS and the meter coordination condition was significantly higher than the coherent values in the non meter coordination and meter independence condition. Permutation analysis showed that the observed IBS probably presented in two individuals of one dyad who tried to synchronize with each other in the matched time, but not in the time partner or condition of random pairing.
Ensure that, the IBS is specific for rare interaction. So, calculating IBS in the task, correlated frequency band and per mutating trust conditions and interviews. Computing the IBS of all channels within the simple reach, or across different channels and the regions, would enrich the IBS calculation partner.
Analyzing the Inter-Brain network for large groups of participates in natural interactions will benefit is the qualification of social interaction.
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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.
