Evidence map›Paper›PMID 40397746›Full record

ArticleScience advances2025

Communication of perceptual predictions from the hippocampus to the deep layers of the parahippocampal cortex.

Oliver Warrington, Nadine N Graedel, Martina F Callaghan, Peter Kok

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Multisensory coding of audiovisual movies in the human hippocampus.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
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  4. Review
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

4 authors.

Oliver WarringtonDepartment of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0002-3592-7071
Nadine N GraedelDepartment of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0001-7473-4363
Martina F CallaghanDepartment of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-0374-1659
Peter KokDepartment of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0001-5153-4959

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current evidence suggests that the hippocampus is essential for exploiting predictive relationships during perception. However, it remains unclear whether the hippocampus drives the communication of predictions to sensory cortex or receives prediction signals from elsewhere. We collected 7-tesla fMRI data in the medial temporal lobe (MTL) while auditory cues predicted abstract shapes. Strikingly, neural patterns evoked by predicted shapes in CA2/3, pre/parasubiculum, and the parahippocampal cortex (PHC) were negatively correlated to patterns evoked by the same shapes when actually presented. Using layer-specific analyses, we ask: In which direction are predictions communicated between the hippocampus and neocortex? Superficial layers of the MTL cortex project to the hippocampus, while the deep layers receive feedback projections. Informational connectivity analyses revealed that communication between CA2/3 and PHC was specific to the deep layers of PHC. These findings suggest that the hippocampus generates predictions through pattern completion in CA2/3 and feeds these predictions back to the neocortex.

Indexed as

HippocampusParahippocampal GyrusAdultBrain MappingFemaleHumansMagnetic Resonance ImagingMaleNeocortexTemporal LobeYoung Adult

Identifiers

PMID40397746
PMCPMC12094225

What OpenQuestion holds

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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.