Abstract
.Significance: The expanding field of human social interaction is enabled by functional near-infrared spectroscopy (fNIRS) that acquires hemodynamic signals during live two-person interactions. These advances call for development of methods to quantify interactive processes.Aim: Wavelet coherence analysis has been applied to cross-brain neural coupling. However, fNIRS-specific computations have not been explored. This investigation determines the effects of global mean removal, wavelet equation, and choice of oxyhemoglobin versus deoxyhemoglobin signals.Approach: We compare signals with a known coherence with acquired signals to determine optimal computational approaches. The known coherence was calculated using three visual stimulation sequences of a contrast-reversing checkerboard convolved with the canonical hemodynamic response function. This standard was compared with acquired human fNIRS responses within visual cortex using the same sequences.Results: Observed coherence was consistent with known coherence with highest correlations within the wavelength range between 10 and 20 s. Removal of the global mean improved the correlation irrespective of the specific equation for wavelet coherence, and the oxyhemoglobin signal was associated with a marginal correlation advantage.Conclusions: These findings provide both methodological and computational guidance that enhances the validity and interpretability of wavelet coherence analysis for fNIRS signals acquired during live social interactions.
Highlights
Emerging theoretical frameworks in neuroscience focus on interpersonal interactions and the challenge to understand communicating brains
Hyperscanning with functional near-infrared spectroscopy (fNIRS) is a rapidly advancing field focused on pivotal neural topics for investigation including eye-to-eye contact, dynamic facial expressions, and responsive gestures that occur spontaneously in real-time communications
An upward trend along the wavelength dimension is observed. This phenomenon is related to the noise and the mathematic nature of the wavelet coherence analysis
Summary
Emerging theoretical frameworks in neuroscience focus on interpersonal interactions and the challenge to understand communicating brains. Human brain processes and organization are conventionally studied using functional magnetic resonance imaging (fMRI), where subjects are studied one at a time in noninteractive conditions due to the constraints of the imaging technology. The technique of hyperscanning was pioneered using fMRI by chaining together two scanners and setting up conditions with limited interactions between participants.[1] The research goal was to interrogate neural systems engaged during the processing of spontaneous and reciprocal social interactive cues. This technology does not permit imaging within natural conditions where two individuals share information in real time, including face-to-face interactions and spoken communications. The neurophysiology that underlies interpersonal communication and dynamic interactions between humans has emerged as an active neuroscience research topic opening many new areas of investigation including competition and cooperation, coordination of movements, group musical performances, mother-child interactions, joint decision-making and attention, theory of mind, spoken dialogue, and group interactions
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