Intracortical brain‐heart interplay: An EEG model source study of sympathovagal changes

Abstract

The interplay between cerebral and cardiovascular activity, known as the functional brain‐heart interplay (BHI), and its temporal dynamics, have been linked to a plethora of physiological and pathological processes. Various computational models of the brain‐heart axis have been proposed to estimate BHI non‐invasively by taking advantage of the time resolution offered by electroencephalograph (EEG) signals. However, investigations into the specific intracortical sources responsible for this interplay have been limited, which significantly hampers existing BHI studies. This study proposes an analytical modeling framework for estimating the BHI at the source‐brain level. This analysis relies on the low‐resolution electromagnetic tomography sources localization from scalp electrophysiological recordings. BHI is then quantified as the functional correlation between the intracortical sources and cardiovascular dynamics. Using this approach, we aimed to evaluate the reliability of BHI estimates derived from source‐localized EEG signals as compared with prior findings from neuroimaging methods. The proposed approach is validated using an experimental dataset gathered from 32 healthy individuals who underwent standard sympathovagal elicitation using a cold pressor test. Additional resting state data from 34 healthy individuals has been analysed to assess robustness and reproducibility of the methodology. Experimental results not only confirmed previous findings on activation of brain structures affecting cardiac dynamics (e.g., insula, amygdala, hippocampus, and anterior and mid‐cingulate cortices) but also provided insights into the anatomical bases of brain‐heart axis. In particular, we show that the bidirectional activity of electrophysiological pathways of functional brain‐heart communication increases during cold pressure with respect to resting state, mainly targeting neural oscillations in the , , and bands. The proposed approach offers new perspectives for the investigation of functional BHI that could also shed light on various pathophysiological conditions.

Unraveling emotional regulation through multimodal neuroimaging techniques

“…This capability is crucial for capturing the fleeting and complex sequences of neural events that underlie emotional processing and regulation. However, while EEG excels in temporal resolution, it has notable limitations in spatial resolution (Catrambone et al, 2024;Tang et al, 2024). The electrical signals recorded by EEG are subject to volume conduction, meaning that the signals spread out and are picked up by multiple electrodes, making it challenging to pinpoint the exact origin of the activity within the brain (Li et al, 2020).…”