Linking heartbeats with the cortical network dynamics involved in self-social touch distinction

Figures

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  Fig. 1. Brain connectivity-Cardiac Coupling under touch. A The framework aims to quantify the brain-heart coupling under three modalities of touch: social, self-, and object-touch. B The framework involved the computation of brain connectivity from EEG and C the estimation of cardiac sympathetic and parasympathetic/vagal activities are computed from the successive changes in interbeat intervals (IBI) gathered from the Poincaré plot (for an in depth description of this method see ref.107). D The coupling quantification is achieved by assessing the similarities between two time series, using the Maximal Information Coefficient (MIC) method, which evaluates the similarities between distinct segments individually, using an adjusted grid as depicted in the figure. The overall measure combines the similarities observed throughout the entire time-course. From the brain-heart coupling matrices, the networks are identified by grouping neighboring links using a nonparametric permutation test.

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  Fig. 2. Summary of the results on the identification of brain networks whose couplings with cardiac sympathetic or parasympathetic activity differentiate between modalities of touch. The comparisons encompass social vs. self-touch, social vs. object-touch, and self vs. object touch. The statistical analyses are based on the cluster permutation test to identify the brain networks that showed an increased or decreased coupling with respect to the touch modalities compared, as specified in the legend. The histograms display the network size, which indicate the number of EEG connectivity links that presented a significant change in their coupling with cardiac activity, between the two touch modalities compared.

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  Fig. 3. Brain-heart coupling distinguishing social vs self-touch at the early stage (0–60 s). The main distinctions were found in the coupling between alpha, beta, and gamma brain networks with cardiac parasympathetic activity. Main brain networks were defined as network size >10 connections. The arrows indicate the directed EEG connectivity links pertaining to the identified network. The right column displays the average coupling across all links pertaining to the identified network. Coupling ranges between 0–1, indicating the degree of co-fluctuations between brain and heart signals. Each data point corresponds to one participant.

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  Fig. 4. Brain-heart coupling distinguishing social vs self-touch at the late stage (120–180 s). The main distinctions were found in the coupling between delta, theta, alpha, and gamma brain networks with cardiac sympathetic activity. Main brain networks were defined as network size >10 connections. The arrows indicate the directed EEG connectivity links pertaining to the identified network. The right column displays the average coupling across all links pertaining to the identified network. Coupling ranges between 0–1, indicating the degree of co-fluctuations between brain and heart signals. Each data point corresponds to one participant.

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  Fig. 5. Control analysis on EEG connectivity. A Results on the identification of brain networks whose connectivity amplitude differentiate between modalities of touch. The comparisons encompass social vs. self-touch, social vs. object-touch, and self- vs. object touch. The statistical analyses are based on the cluster permutation test to identify the brain networks that showed an increased or decreased amplitude with respect to the touch modalities compared, as specified in the legend. The histograms display the network size, which indicate the number of EEG connectivity links that presented a significant change in their amplitude, between the two touch modalities compared. B, C EEG connectivity amplitude change distinguishing social vs self-touch. The main distinctions were found in the EEG connectivity in alpha and gamma brain networks (0–60 s and 120–180 s). Data points display the average EEG connectivity amplitude across all links pertaining to the identified network. Each data point corresponds to one participant. D Alpha and gamma networks distinguishing self- vs. social touch at 120–180 s. The arrows indicate the directed EEG connectivity links pertaining to the identified network.