Evidence map›Paper›PMID 32101169›Full record

ArticleeLife2020

Experience shapes activity dynamics and stimulus coding of VIP inhibitory cells.

Marina Garrett, Sahar Manavi, Kate Roll, Douglas R Ollerenshaw, Peter A Groblewski, Nicholas D Ponvert, Justin T Kiggins, Linzy Casal, Kyla Mace, Ali Williford and 7 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
7.3field-weighted citation impact, top 2% of its field
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

62 citing papers in PubMed, 116 citations in OpenAlex.

  1. Article
  2. Cell-Type-Specific Synaptic Scaling Mechanisms Differentially Contribute to Associative Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Environmental enrichment accelerates cortical memory consolidation.bioRxiv : the preprint server for biology · 2025
    Article
  15. Article
  16. Learning predictive signals within a local recurrent circuit.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  17. Review
  18. Article
  19. Article
  20. Review

2 more citing papers are in PubMed but not listed here.

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

17 authors at 1 institution in 1 country.

Marina GarrettAllen Institute for Brain Science, Seattle, United States.ORCID 0000-0002-5271-2291
Sahar ManaviAllen Institute for Brain Science, Seattle, United States.
Kate RollAllen Institute for Brain Science, Seattle, United States.
Douglas R OllerenshawAllen Institute for Brain Science, Seattle, United States.
Peter A GroblewskiAllen Institute for Brain Science, Seattle, United States.ORCID 0000-0002-8415-1118
Nicholas D PonvertAllen Institute for Brain Science, Seattle, United States.
Justin T KigginsAllen Institute for Brain Science, Seattle, United States.
Linzy CasalAllen Institute for Brain Science, Seattle, United States.
Kyla MaceAllen Institute for Brain Science, Seattle, United States.
Ali WillifordAllen Institute for Brain Science, Seattle, United States.
Arielle LeonAllen Institute for Brain Science, Seattle, United States.
Xiaoxuan JiaAllen Institute for Brain Science, Seattle, United States.
Peter LedochowitschAllen Institute for Brain Science, Seattle, United States.
Michael A BuiceAllen Institute for Brain Science, Seattle, United States.
Wayne WakemanAllen Institute for Brain Science, Seattle, United States.
Stefan MihalasAllen Institute for Brain Science, Seattle, United States.ORCID 0000-0002-2629-7100
Shawn R OlsenAllen Institute for Brain Science, Seattle, United States.ORCID 0000-0002-9568-7057
Allen Institute for Brain Science · US

Funding

Models and Methods for Calcium Imaging Data with Application to the Allen Brain ObservatoryR01EB026908 · NIBIB · UNIVERSITY OF WASHINGTON · PI BUICE, MICHAEL, WITTEN, DANIELA · 2018 to 2020
$1.1M
NIBIB NIH HHS R01 EB026908
6 · The paper itself

Abstract

Cortical circuits can flexibly change with experience and learning, but the effects on specific cell types, including distinct inhibitory types, are not well understood. Here we investigated how excitatory and VIP inhibitory cells in layer 2/3 of mouse visual cortex were impacted by visual experience in the context of a behavioral task. Mice learned a visual change detection task with a set of eight natural scene images. Subsequently, during 2-photon imaging experiments, mice performed the task with these familiar images and three sets of novel images. Strikingly, the temporal dynamics of VIP activity differed markedly between novel and familiar images: VIP cells were stimulus-driven by novel images but were suppressed by familiar stimuli and showed ramping activity when expected stimuli were omitted from a temporally predictable sequence. This prominent change in VIP activity suggests that these cells may adopt different modes of processing under novel versus familiar conditions.

Indexed as

AnimalsMiceTask Performance and AnalysisVasoactive Intestinal PeptideVisual CortexVasoactive Intestinal Peptidebehaviorlearningmouseneurosciencevisual system

Identifiers

PMID32101169
PMCPMC7043888
OpenAlexW3008923542

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.