Responses to Heartbeats in Ventromedial Prefrontal Cortex Contribute to Subjective Preference-Based Decisions
Bibliographic record
Abstract
Forrest Gump or The Matrix? Preference-based decisions are subjective and entail self-reflection. However, these self-related features are unaccounted for by known neural mechanisms of valuation and choice. Self-related processes have been linked to a basic interoceptive biological mechanism, the neural monitoring of heartbeats, in particular in ventromedial prefrontal cortex (vmPFC), a region also involved in value encoding. We thus hypothesized a functional coupling between the neural monitoring of heartbeats and the precision of value encoding in vmPFC. Human participants of both sexes were presented with pairs of movie titles. They indicated either which movie they preferred or performed a control objective visual discrimination that did not require self-reflection. Using magnetoencephalography, we measured heartbeat-evoked responses (HERs) before option presentation and confirmed that HERs in vmPFC were larger when preparing for the subjective, self-related task. We retrieved the expected cortical value network during choice with time-resolved statistical modeling. Crucially, we show that larger HERs before option presentation are followed by stronger value encoding during choice in vmPFC. This effect is independent of overall vmPFC baseline activity. The neural interaction between HERs and value encoding predicted preference-based choice consistency over time, accounting for both interindividual differences and trial-to-trial fluctuations within individuals. Neither cardiac activity nor arousal fluctuations could account for any of the effects. HERs did not interact with the encoding of perceptual evidence in the discrimination task. Our results show that the self-reflection underlying preference-based decisions involves HERs, and that HER integration to subjective value encoding in vmPFC contributes to preference stability. SIGNIFICANCE STATEMENT Deciding whether you prefer Forrest Gump or The Matrix is based on subjective values, which only you, the decision-maker, can estimate and compare, by asking yourself. Yet, how self-reflection is biologically implemented and its contribution to subjective valuation are not known. We show that in ventromedial prefrontal cortex, the neural response to heartbeats, an interoceptive self-related process, influences the cortical representation of subjective value. The neural interaction between the cortical monitoring of heartbeats and value encoding predicts choice consistency (i.e., whether you consistently prefer Forrest Gump over Matrix over time. Our results pave the way for the quantification of self-related processes in decision-making and may shed new light on the relationship between maladaptive decisions and impaired interoception.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".