Systematic review and meta-analysis of the relationship between the heartbeat-evoked potential and interoception.
Bibliographic record
Abstract
The Heartbeat Evoked Potential (HEP) has been proposed as a neurophysiological marker of interoceptive processing. Despite its use to validate interoceptive measures and to assess interoceptive functioning in clinical groups, the empirical evidence for a relationship between HEP amplitude and interoceptive processing, including measures of such processing, is scattered across several studies with varied designs. The aim of this systematic review and meta-analysis was to examine the body of HEP-interoception research, and consider the associations the HEP shows with various direct and indirect measures of interoception, and how it is affected by manipulations of interoceptive processing. Specifically, we assessed the effect on HEP amplitude of manipulating attention to the heartbeat; manipulating participants’ arousal; the association between the HEP and behavioural measures of cardiac interoception; and comparisons between healthy and clinical groups. Following database searches and screening, 45 studies were included in the systematic review and 42 in the meta-analyses. We noted variations in the ways individual studies have attempted to address key confounds, particularly the cardiac field artefact. Meta-analytic summaries indicated there were moderate to large effects of attention, arousal, and clinical status on the HEP, and a moderate association between HEP amplitude and behavioural measures of interoception. Problematically, the reliability of the meta-analytic effects documented here remain unknown, given the lack of standardised protocols for measuring the HEP. Thus, it is possible effects are driven by confounds such as cardiac factors or somatosensory effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".