Methodological approaches to derive the heartbeat evoked potential: past practices and future recommendations

The heartbeat-evoked potential (HEP), a cortical response time-locked to each heartbeat, is suggested as an implicit electrophysiological marker reflecting the cortical processing of heartbeats, and more broadly interoceptive processing. An increasing number of studies suggest that HEP may be a meaningful clinical measure. However, on the scalp, HEP are low amplitude signals that are mixed with direct cardiac field artefacts. Therefore, signal processing pipelines that separate the cortical HEP from cardiac field artefacts are required. With a view to establishing optimal and standardised HEP pipelines, this review aims to evaluate the current approaches to this analysis used within the literature, address gaps and inconsistencies in HEP pipelines, and highlight the impact of crucial parameter choices. To do this, a scoping review investigated current HEP processing methods and parameters used in EEG and MEG studies. Testing these processing methods on Temple University’s normal scalp EEG data (Obeid and Picone, 2016), the effect of different methods/parameters (e.g. HEP window, electrodes, filters, independent component analysis (ICA) and artefact subspace reconstruction (ASR)) on HEP extraction was explored.

EEG studies (N=101) demonstrated greater parameter variability and heterogeneity than MEG studies (N=10), although significantly more studies used EEG. ICA without cardiac field artefact and ASR at threshold 20 exhibit similar results for artefact removal. Statistical analysis revealed that the RR interval, the start and end of the HEP window and the start of the baseline correction window significantly affect HEP values in pre-frontal, frontal and centrotemporal electrodes.

Publications should report critical values for reliable HEP extraction, emphasising the need for standardised methods to enhance study comparison and reproducibility and establish a gold standard in the field.