Evidence map›Paper›PMID 42244519›Full record

ArticleNeuroscience of consciousness2026

From self-organizing systems to subjective temporal extension.

Jan Erik Bellingrath

Abstract read
In one paragraph

Article in Neuroscience of consciousness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jan Erik BellingrathUniversité de Toulouse, CerCo, CNRS, Place du Docteur Baylac, Pavillon Baudot, 31059, Toulouse, France.ORCID https://orcid.org/0009-0004-8443-1920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The self-simulational theory of temporal extension (SST) describes an information-theoretically formalized mechanism by which the "width" of subjective temporality emerges from the architecture of self-modeling. In this paper, the perspective of the free energy principle will be assumed to cast the emergence of subjective temporal extension from first principles of the physics of self-organization and to formalize subjective temporal extension using information geometry. Using active inference, a deep parametric generative model of temporal inference is simulated, which realizes the described dynamics on a computational level. Two "biases" (i.e. variations) of time-perception emerge naturally from the simulated computational model. This concerns the intentional binding effect (i.e. the compression of the temporal interval between voluntarily initiated actions and subsequent sensory consequences) and empirically documented alterations of subjective time experience in deep states of meditative absorption (i.e. in minimal phenomenal experience). Generally, numerous systematic and domain-specific alterations of subjective temporal experience are computationally explained in a unified manner, as enabled by integration with current active inference accounts mapping onto the respective domains. This concerns, next to more general attentional and central tendency effects, the temporality-modulating role of valence, impulsivity, boredom, flow-states, near death-experiences, and various psychopathologies, among others. SST, from the perspective of the free energy principle, explains how the "width" of the subjective temporal moment emerges from first principles, accounting for why sometimes, subjective time seems to fly, and sometimes, moments feel like eternities; with the computational mechanism being readily deployable synthetically.

Indexed as

active inferencesubjective temporal extension

Identifiers

PMID42244519
PMCPMC13232630

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.