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Exploratory analysis of nonlinear coupling between EEG global field power and end-tidal carbon dioxide in free breathing and breath-hold tasks

机译:在自由呼吸和屏气任务中脑电图全局场功率与潮气中二氧化碳之间非线性耦合的探索性分析

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Brain activations underlying control of breathing are not completely known. Furthermore, the coupling between neural and respiratory dynamics is usually estimated through linear correlation measures, thus totally disregarding possible underlying nonlinear interactions. To overcome these limitations, in this preliminary study we propose a nonlinear coupling analysis of simultaneous recordings of electroencephalographic (EEG) and respiratory signals at rest and after variation of carbon dioxide (CO2) level. Specifically, a CO2 increase was induced by a voluntary breath hold task. EEG global field power (GFP) in different frequency bands and end-tidal CO2 (PETCO2) were estimated in both conditions. The maximum information coefficient (MIC) and MIC-ρ2 (where ρ represents the Pearson's correlation coefficient) between the two signals were calculated to identify generic associations (i.e. linear and nonlinear correlations) and nonlinear correlations, respectively. With respect to a free breathing state, our results suggest that a breath hold state is characterized by an increased coupling between respiration activity and specific EEG oscillations, mainly involving linear and nonlinear interactions in the delta band (1-4 Hz), and prevalent nonlinear interactions in the alpha band (8-13 Hz).
机译:呼吸控制基础的大脑激活尚不完全清楚。此外,神经动力学和呼吸动力学之间的耦合通常通过线性相关度量来估计,因此完全忽略了潜在的潜在非线性相互作用。为了克服这些限制,在这项初步研究中,我们提出了在静息时以及二氧化碳(CO2)水平变化后同时记录脑电图(EEG)和呼吸信号的非线性耦合分析。具体来说,二氧化碳的增加是由自主屏气任务引起的。在这两种情况下,均估算了不同频段的EEG全球场强(GFP)和潮气末CO2(PETCO2)。计算两个信号之间的最大信息系数(MIC)和MIC-ρ2(其中ρ表示皮尔逊相关系数),分别识别泛型关联(即线性和非线性相关)和非线性相关。关于自由呼吸状态,我们的结果表明,屏气状态的特征是呼吸活动与特定EEG振荡之间的耦合增加,主要涉及三角带(1-4 Hz)中的线性和非线性相互作用,以及普遍存在的非线性在Alpha波段(8-13 Hz)中的相互作用。

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