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Optimization of wavelet coherence analysis as a measure of neural synchrony during hyperscanning using functional near-infrared spectroscopy.
Neurophotonics ( IF 4.8 ) Pub Date : 2020-02-28 , DOI: 10.1117/1.nph.7.1.015010
Xian Zhang 1 , J Adam Noah 2 , Swethasri Dravida 3, 4 , Joy Hirsch 1, 4, 5, 6
Affiliation  

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.

中文翻译:

优化小波相干分析,作为使用功能近红外光谱的超扫描过程中神经同步性的一种度量。

意义:功能性近红外光谱(fNIRS)可以扩大人类社交互动的范围,该功能在实时的两人互动中获取血液动力学信号。这些进步要求开发量化交互过程的方法。目的:小波相干分析已应用于跨脑神经耦合。但是,尚未探索fNIRS特定的计算。这项研究确定了整体均值去除,小波方程以及氧合血红蛋白与脱氧血红蛋白信号选择的影响。方法:我们将具有已知相干性的信号与获取的信号进行比较,以确定最佳的计算方法。已知的相干性是使用反演棋盘的三个视觉刺激序列与经典血液动力学响应函数卷积来计算的。将该标准与使用相同序列的视觉皮层内获得的人fNIRS反应进行比较。结果:在10到20 s的波长范围内,观察到的相干性与已知相干性具有最高的相关性。不管小波相干的具体公式如何,整体均值的去除都会改善相关性,并且氧合血红蛋白信号具有边际相关性优势。结论:这些发现提供了方法学和计算指导,从而增强了在社交互动中获取的fNIRS信号的小波相干分析的有效性和可解释性。在10到20 s的波长范围内,观测到的相干与已知相干具有最高的相关性。不管小波相干的具体公式如何,整体均值的去除都会改善相关性,并且氧合血红蛋白信号具有边际相关性优势。结论:这些发现提供了方法学和计算指导,从而增强了在社交互动中获取的fNIRS信号的小波相干分析的有效性和可解释性。在10到20 s的波长范围内,观察到的相干与已知相干具有最高的相关性。不管小波相干的具体公式如何,整体均值的去除都会改善相关性,并且氧合血红蛋白信号具有边际相关性优势。结论:这些发现提供了方法学和计算指导,从而增强了在社交互动中获取的fNIRS信号的小波相干分析的有效性和可解释性。
更新日期:2020-02-28
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