Evidence map›Paper›PMID 38177341›Full record

ArticleNature neuroscience2024

Behavior-relevant top-down cross-modal predictions in mouse neocortex.

Shuting Han, Fritjof Helmchen

Abstract read
PubMed Publisher
In one paragraph

Article in Nature neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Input-dependent directionality of interactions between cortical areas.bioRxiv : the preprint server for biology · 2026
    Article
  3. Cortical deviance detection represents a canonical difference signal.bioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Parietal cortex is causally required for state-dependent decisions.bioRxiv : the preprint server for biology · 2025
    Article
  8. Article
  9. Article
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  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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

2 authors.

Shuting HanBrain Research Institute, University of Zurich, Zurich, Switzerland. han@hifo.uzh.ch.ORCID http://orcid.org/0000-0001-9315-3089
Fritjof HelmchenBrain Research Institute, University of Zurich, Zurich, Switzerland. helmchen@hifo.uzh.ch.ORCID http://orcid.org/0000-0002-8867-9569

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animals adapt to a constantly changing world by predicting their environment and the consequences of their actions. The predictive coding hypothesis proposes that the brain generates predictions and continuously compares them with sensory inputs to guide behavior. However, how the brain reconciles conflicting top-down predictions and bottom-up sensory information remains unclear. To address this question, we simultaneously imaged neuronal populations in the mouse somatosensory barrel cortex and posterior parietal cortex during an auditory-cued texture discrimination task. In mice that had learned the task with fixed tone-texture matching, the presentation of mismatched pairing induced conflicts between tone-based texture predictions and actual texture inputs. When decisions were based on the predicted rather than the actual texture, top-down information flow was dominant and texture representations in both areas were modified, whereas dominant bottom-up information flow led to correct representations and behavioral choice. Our findings provide evidence for hierarchical predictive coding in the mouse neocortex.

Indexed as

Auditory PerceptionNeocortexAnimalsDiscrimination, PsychologicalMiceParietal LobeSomatosensory Cortex

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.