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Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
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Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

DOI:
10.3791/62927-v

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08:42 min

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September 03, 2021

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, ,
1State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research,Beijing Normal University, 2Institute of Developmental Psychology, Faculty of Psychology,Beijing Normal University

Capitoli

  • 00:04Introduction
  • 00:54Functional Near-Infrared Spectroscopy (fNIRS) Data Preprocessing
  • 01:47First-Level Functional Near-Infrared Spectroscopy (fNIRS) Data Processing
  • 04:04Second-Level Functional Near-Infrared Spectroscopy (fNIRS) Data Processing
  • 05:56Results: Findings of the Simulation and Empirical Experiment
  • 07:50Conclusion

Summary

Traduzione automatica

Traduzione automatica

This protocol describes partial wavelet transform coherence (pWTC) for calculating the time-lagged pattern of interpersonal neural synchronization (INS) to infer the direction and temporal pattern of information flow during social interaction. The effectiveness of pWTC in removing the confounds of signal autocorrelation on INS was proved by two experiments.

Tags

Keywords: FNIRS-hyperscanningPartial Wavelet Transform CoherenceInformation FlowNeural SynchronizationTime-lagged AnalysisAutocorrelationMotion Artifact CorrectionPCA Denoising

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