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

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Psychophysiology

Background:

• The heartbeat evoked potential (HEP) reflects cardiac signal integration in the brain, typically analyzed via EEG time-locked to ECG R-peaks.
• Existing research shows HEP modulation across conditions, but its precise neural underpinnings and components remain unclear, hindering consistent characterization.
• A two-component model proposes an early (100-250ms) task-independent component for primary integration and a late (250-500ms) task-dependent component for elaborative processing.

Purpose of the Study:

• To delineate the early and late components of the HEP and their frequency characteristics at rest.
• To investigate the modulation of these HEP components during an emotion task and a tactile stimulation protocol.
• To ensure reproducibility by using independent datasets and diverse participants.

Main Methods:

• Utilized electroencephalography (EEG) and electrocardiography (ECG) to record brain activity and heartbeats.
• Averaged EEG epochs time-locked to R-peaks to derive HEPs.
• Employed independent datasets for exploratory analysis and reproducibility checks across different tasks and participant groups.

Main Results:

• Identified an early fronto-central negativity (100-250ms) potentially linked to theta phase resetting.
• Observed a subsequent posterior positivity (250-500ms).
• Found no significant intra- or inter-task modulation for the early component, and unexpectedly, no modulation for the late component.

Conclusions:

• The early HEP component appears task-independent, supporting its role in primary cardiac signal integration.
• The late HEP component did not show task-related modulation, challenging the hypothesis of its role in elaborative processing.
• Standardized methodologies are crucial for improving HEP research reproducibility and understanding cardiac-brain interactions.