Estimation of brain activity sources of sympathovagal dynamics

IF 4.5 2区医学 Q1 NEUROIMAGING

NeuroImage Pub Date : 2025-10-06 DOI:10.1016/j.neuroimage.2025.121501

Dario Milea, Vincenzo Catrambone, Gaetano Valenza

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引用次数: 0

Abstract

Characterizing source brain activity in relation to peripheral neural-autonomic function is crucial in neuroscience research. Despite recent advances for estimating brain-heart interplay (BHI), the specific intracortical sources underlying this interaction remain poorly understood, and especially a non-invasive model to localize the brain source of cardiac autonomic functions is lacking. In an effort to estimate the joint intrinsic activity of central and autonomic systems, this study extends canonical EEG source localization by introducing a framework for brain source reconstruction of sympathovagal and vagal components. The proposed method integrates EEG and ECG-derived heart rate variability series within a low-resolution electromagnetic tomography framework and was validated using data from 26 healthy subjects undergoing a well-known sympathovagal elicitation paradigm – the cold pressor test – compared to the resting state. Experimental results demonstrate that accounting for heartbeat dynamics significantly alters source activation patterns, aligning coherently with current knowledge on central autonomic networks and BHI dynamics. The proposed method opens new avenues for research into the neural sources of autonomic functions.

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交感迷走神经动力学脑活动源的估计。

表征与周围神经-自主神经功能相关的源脑活动在神经科学研究中至关重要。尽管最近在估计脑-心相互作用（BHI）方面取得了进展，但这种相互作用的特定皮质内来源仍然知之甚少，特别是缺乏一种定位心脏自主神经功能的大脑来源的非侵入性模型。为了估计中枢和自主神经系统的联合内在活动，本研究通过引入交感神经迷走神经和迷走神经成分的脑源重建框架，扩展了典型的EEG源定位。所提出的方法在低分辨率电磁断层扫描框架内整合了EEG和ecg衍生的心率变异性系列，并使用来自26名健康受试者的数据进行了验证，这些受试者正在进行众所周知的交感迷走神经激发范式-冷压试验-与静息状态进行比较。实验结果表明，考虑心跳动态会显著改变源激活模式，这与目前关于中枢自主神经网络和BHI动态的知识一致。该方法为研究自主神经功能的神经来源开辟了新的途径。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

NeuroImage 医学-核医学

CiteScore

11.30

自引率

10.50%

发文量

809

审稿时长

63 days

期刊介绍： NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.