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Record W4411721650 · doi:10.1101/2025.06.25.660685

Interoception vs. Exteroception: Cardiac interoception competes with tactile perception, yet also facilitates self-relevance encoding

2025· preprint· en· W4411721650 on OpenAlexfundno aff
Marie Loescher, Patrick Haggard, Catherine Tallon‐Baudry

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersAgence Nationale de la RechercheCanadian Institute for Advanced ResearchAlexander von Humboldt-Stiftung
KeywordsInteroceptionRelevance (law)Encoding (memory)PerceptionPsychologyCognitive psychologySensory systemCommunicationNeurosciencePolitical science

Abstract

fetched live from OpenAlex

Abstract Internal bodily signals, notably the heartbeat, influence our perception of the external world – but the nature of this influence remains unclear. Different frameworks, originating in opposing views of the function of interoception, have developed largely in parallel. One line of evidence (Internal/External Competition) indicates that interoceptive and exteroceptive inputs compete for neural resources. Another line (Self-related Facilitation) shows a link between interoceptive and self-related processing, which might include computing the self-relevance of exteroceptive inputs. We contrasted these accounts within a single experimental task for which they yielded distinct predictions. We measured heartbeat-evoked potentials (HEPs, a measure of cardiac interoception) with EEG, and manipulated the self-relevance of an audio-tactile stimulus by placing the audio source either inside or outside the peripersonal space immediately around the body. On one hand, pre-stimulus HEP amplitudes over somatosensory cortex were linked to slower reaction times, and affected audio-tactile stimulus-evoked responses in the same area, indicating competition for shared neural resources. On the other hand, pre-stimulus HEPs over integrative sensorimotor and default-mode network regions facilitated stimulus self-relevance encoding, both in reaction times and audio-tactile evoked responses. Importantly, Competition and Facilitation effects were spatially and statistically independent from each other. We therefore reconcile the two views by showing the co-existence of two independent mechanisms: one that allocates neural resources to either internal bodily signals or the external world, and another by which interoception and exteroception are combined to determine the self-relevance of external signals. Our results highlight the multi-dimensionality of HEPs, and of internal states more generally. Significance Statement Do internal bodily signals distract us from the external world (Internal/External Competition account)? Or do internal signals contribute to conscious perception, by situating the perceived external world relative to the organism (Self-related Facilitation account)? So far, both accounts – reflecting fundamentally different views of brain-body interactions – received experimental support, but have never been compared directly. We measured neural responses to heartbeats, and tested how they influenced perception in an audio-tactile reaction time task where self-relevance was manipulated. We found evidence for both accounts, reflecting independent mechanisms in distinct brain regions. Our results reconcile two hitherto independent and seemingly contradictory research programmes on the relationship between interoception and exteroception. They further highlight the multi-dimensionality of cardiac-brain interactions, and hence of internal state.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.237
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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