Evidence map›Paper›PMID 39075325›Full record

ArticleNature neuroscience2024

Population-level coding of avoidance learning in medial prefrontal cortex.

Benjamin Ehret, Roman Boehringer, Elizabeth A Amadei, Maria R Cervera, Christian Henning, Aniruddh R Galgali, Valerio Mante, Benjamin F Grewe

Abstract read
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 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Neural basis of social hierarchy across species.Nature reviews. Neuroscience · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Directed cell-type recruitment during consolidation of a remote memory.bioRxiv : the preprint server for biology · 2025
    Article
  13. Article
  14. 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

8 authors.

Benjamin EhretInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland. benjamin.ehret@outlook.com.ORCID http://orcid.org/0000-0002-5059-7947
Roman BoehringerInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Elizabeth A AmadeiInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-1255-9069
Maria R CerveraInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Christian HenningInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Aniruddh R GalgaliGatsby Computational Neuroscience Unit, University College London, London, UK.
Valerio ManteInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-3412-4215
Benjamin F GreweInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland. bgrewe@ethz.ch.ORCID http://orcid.org/0000-0001-8560-2120

Funding

Human Frontier Science Program (HFSP) LT000539Human Frontier Science Program (HFSP) RGY0072/2019Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) CRSII5_173721
6 · The paper itself

Abstract

The medial prefrontal cortex (mPFC) has been proposed to link sensory inputs and behavioral outputs to mediate the execution of learned behaviors. However, how such a link is implemented has remained unclear. To measure prefrontal neural correlates of sensory stimuli and learned behaviors, we performed population calcium imaging during a new tone-signaled active avoidance paradigm in mice. We developed an analysis approach based on dimensionality reduction and decoding that allowed us to identify interpretable task-related population activity patterns. While a large fraction of tone-evoked activity was not informative about behavior execution, we identified an activity pattern that was predictive of tone-induced avoidance actions and did not occur for spontaneous actions with similar motion kinematics. Moreover, this avoidance-specific activity differed between distinct avoidance actions learned in two consecutive tasks. Overall, our results are consistent with a model in which mPFC contributes to the selection of goal-directed actions by transforming sensory inputs into specific behavioral outputs through distributed population-level computations.

Indexed as

Avoidance LearningPrefrontal CortexAnimalsMaleMiceMice, Inbred C57BLNeurons

Identifiers

PMID39075325
PMCPMC11374698

What OpenQuestion holds

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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.