Characterizing the Heartbeat‐Evoked Potential: A Two‐Component Model of Cardiac Signal Processing?

The heartbeat evoked potential (HEP) is a potential marker of cardiac signal integration at the cerebral level, obtained by averaging epochs time-locked to the ECG R-peaks. The HEP is modulated across different experimental conditions with amplitude differences arising between 200 and 600 ms post-R-peak over fronto-central sites. However, substantial heterogeneity exists, and to date there is no clear characterization of the HEP. Here, we propose a two-component model of the HEP consisting of first, an early (100-250 ms) component presumed to index primary cardiac signal integration, thus being task independent; and second a late (250-500 ms) component thought to index elaborative processes, supposed to be modulated both within and between tasks. We aimed to first delineate these components together with their frequency characteristics at rest before exploring their modulation during an emotion task and a tactile stimulation protocol, using independent datasets for exploratory and reproducibility purposes, totaling 104 participants from different cultures. Our results revealed an early (100-250 ms) fronto-central negativity potentially associated with theta phase resetting, followed by a posterior positivity (250-500 ms). As expected, we did not observe any intra or inter-task modulation of the early component. However, contrary to our hypothesis, the late component was not modulated by task neither. This lack of task-related modulation in the late component contrasts with previous literature but appears robust given that our study design used multiple datasets, participants and experimental protocols. Our findings highlight the need for standardized methodologies in HEP research to improve reproducibility and enhance our understanding of cardiac-related neural processing.

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Publication Details

Journal
Psychophysiology
Published
2025-12-01
DOI
https://doi.org/10.1111/psyp.70206
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

Characterizing the Heartbeat‐Evoked Potential: A Two‐Component Model of Cardiac Signal Processing?

Raphael H. Gautier, Marianne Latinus, Frédéric Briend
Psychophysiology
EEG and Brain-Computer Interfaces
article

Characterizing the Heartbeat‐Evoked Potential: A Two‐Component Model of Cardiac Signal Processing?

Raphael H. Gautier, Marianne Latinus, Frédéric Briend
article en

Abstract

The heartbeat evoked potential (HEP) is a potential marker of cardiac signal integration at the cerebral level, obtained by averaging epochs time-locked to the ECG R-peaks. The HEP is modulated across different experimental conditions with amplitude differences arising between 200 and 600 ms post-R-peak over fronto-central sites. However, substantial heterogeneity exists, and to date there is no clear characterization of the HEP. Here, we propose a two-component model of the HEP consisting of first, an early (100-250 ms) component presumed to index primary cardiac signal integration, thus being task independent; and second a late (250-500 ms) component thought to index elaborative processes, supposed to be modulated both within and between tasks. We aimed to first delineate these components together with their frequency characteristics at rest before exploring their modulation during an emotion task and a tactile stimulation protocol, using independent datasets for exploratory and reproducibility purposes, totaling 104 participants from different cultures. Our results revealed an early (100-250 ms) fronto-central negativity potentially associated with theta phase resetting, followed by a posterior positivity (250-500 ms). As expected, we did not observe any intra or inter-task modulation of the early component. However, contrary to our hypothesis, the late component was not modulated by task neither. This lack of task-related modulation in the late component contrasts with previous literature but appears robust given that our study design used multiple datasets, participants and experimental protocols. Our findings highlight the need for standardized methodologies in HEP research to improve reproducibility and enhance our understanding of cardiac-related neural processing.

PsychophysiologyVol. 62(12)
Université de Tours (FR), Inserm (FR)
Openalex Percentile: Top 61%
EEG and Brain-Computer Interfaces
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