Can computation validate the final scientific claim?

No. Active-inference models are explanatory frameworks and simulations, not personal validation tests. Computation can prioritize and eliminate directions; final validation remains with the appropriate domain methods and accountable specialists.

When should the project stop or reframe?

Stop or reframe when the internal signal cannot be translated into a prediction made before the answer is known, when performance does not survive blinded or held-out scoring, when confidence is not calibrated, or when the claim requires medical, clinical, or physiological interpretation outside the available evidence.

Research

Interoceptive Inference: How Priors and Body Signals Shape Perception

Published 2026-08-24 · Updated 2026-08-24

Answer in brief

Interoceptive Inference can shorten the search only by eliminating weak directions early. Start with whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction; compare mechanisms against formal generative models, arousal priors, visceral prediction errors, uncertainty, behavior, and alternative model fits; and try to break the ranking with this challenge: vary priors and sensory precision to identify which mechanism best predicts the observed pattern. A negative result is valuable when it prevents the wrong validation cycle.

Evidence status: Decision-method guide; not a completed investigation or final validation.

The decision this guide supports

whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction

Why the problem is difficult

The article-specific identification challenge is whether the question “whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction” can be resolved using formal generative models, arousal priors, visceral prediction errors, uncertainty, behavior, and alternative model fits, rather than merely restated in new language.

A falsifier-first workflow

Define the decision precisely: whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction.
Build a source and data ledger around formal generative models, arousal priors, visceral prediction errors, uncertainty, behavior, and alternative model fits.
Compare the inherited route with a mechanistically distinct alternative and a constraint-based null.
Actively search for the strongest counterevidence relevant to this decision, including boundary cases and prior failures.
Run the lowest-cost discriminating challenge: vary priors and sensory precision to identify which mechanism best predicts the observed pattern.
Record pursue, reframe, or stop, the confidence level, the evidence ceiling, and who owns downstream validation.

Decision criteria

Decision impact: would the result materially change the choice about whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction?
Evidence fit: does the available evidence—formal generative models, arousal priors, visceral prediction errors, uncertainty, behavior, and alternative model fits—directly address the decision rather than merely correlate with it?
Discrimination: does the preferred route predict an outcome a credible alternative does not?
Robustness: does the ranking survive the challenge “vary priors and sensory precision to identify which mechanism best predicts the observed pattern”?
Validation boundary: is the conclusion no stronger than the available sources, data and computation?

Supporting evidence

formal generative models, arousal priors, visceral prediction errors, uncertainty, behavior, and alternative model fits

Counterevidence

For this decision, a result from “vary priors and sensory precision to identify which mechanism best predicts the observed pattern” that reverses or flattens the ranking must remain visible even when it is commercially inconvenient.

Computation

Here computation earns its place only if it changes the choice about whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction or exposes why the available evidence cannot resolve it.

Fastest falsifier

vary priors and sensory precision to identify which mechanism best predicts the observed pattern

When to stop or reframe

A decision-specific stop trigger is failure of the challenge “vary priors and sensory precision to identify which mechanism best predicts the observed pattern” without an independently supported alternative mechanism.

Evidence ceiling

Active-inference models are explanatory frameworks and simulations, not personal validation tests.

Sources and starting points

Khalsa et al.: Interoception and Mental Health, A Roadmap — A multidisciplinary roadmap that separates interoceptive sensing, interpretation, integration, and measurement rather than treating interoception as one simple ability.
Critchley and Garfinkel: Interoception and Emotion — A review of afferent bodily signalling, central representation, predictive coding, emotion, and the distinct psychological dimensions of interoception.
Allen et al.: In the Body's Eye — A formal active-inference model showing how cardiac signals, priors, prediction errors, arousal, and perceptual uncertainty can interact.
Beissner et al.: The Central Autonomic System Revisited — A neuroimaging meta-analysis identifying convergent roles for dorsal anterior insula and midcingulate cortex in autonomic regulation.
Van Den Houte et al.: Respiratory Occlusion Discrimination Task — A psychophysical respiratory task developed because cardiac-only measures cannot represent every interoceptive channel.
Cochrane Handbook — Additional authoritative starting point selected for this decision area; applicability must be checked against the precise question.
Crossref REST API — Additional authoritative starting point selected for this decision area; applicability must be checked against the precise question.

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Frequently asked questions

What decision does “Interoceptive Inference: How Priors and Body Signals Shape Perception” help make?: It supports a bounded decision about whether a felt signal reflects incoming physiology, prior expectation, prediction error, or their interaction. The framework keeps alternatives, evidence, counterevidence, uncertainty, and the fastest falsification test visible.
What is the fastest useful test?: vary priors and sensory precision to identify which mechanism best predicts the observed pattern
Can computation validate the final scientific claim?: No. Active-inference models are explanatory frameworks and simulations, not personal validation tests. Computation can prioritize and eliminate directions; final validation remains with the appropriate domain methods and accountable specialists.
When should the project stop or reframe?: Stop or reframe when the internal signal cannot be translated into a prediction made before the answer is known, when performance does not survive blinded or held-out scoring, when confidence is not calibrated, or when the claim requires medical, clinical, or physiological interpretation outside the available evidence.