Evidence map›Paper›PMID 27749830›Full record

ReviewNature neuroscience2016

Functional and structural underpinnings of neuronal assembly formation in learning.

Anthony Holtmaat, Pico Caroni

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers.

0numbers the graph read from it
0cells of the map it votes in
115citing 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

115 citing papers in PubMed.

  1. Article
  2. Homeostatic Plasticity Enables Stable yet Tunable Neuronal Assemblies.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies.bioRxiv : the preprint server for biology · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

55 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

2 authors.

Anthony HoltmaatDepartment of Basic Neurosciences, Geneva Neuroscience Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Pico CaroniFriedrich Miescher Institute for Biomedical Research, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning and memory are associated with the formation and modification of neuronal assemblies: populations of neurons that encode what has been learned and mediate memory retrieval upon recall. Functional studies of neuronal assemblies have progressed dramatically thanks to recent technological advances. Here we discuss how a focus on assembly formation and consolidation has provided a powerful conceptual framework to relate mechanistic studies of synaptic and circuit plasticity to behaviorally relevant aspects of learning and memory. Neurons are likely recruited to particular learning-related assemblies as a function of their relative excitabilities and synaptic activation, followed by selective strengthening of pre-existing synapses, formation of new connections and elimination of outcompeted synapses to ensure memory formation. Mechanistically, these processes involve linking transcription to circuit modification. They include the expression of immediate early genes and specific molecular and cellular events, supported by network-wide activities that are shaped and modulated by local inhibitory microcircuits.

Indexed as

AnimalsHumansLearningMemoryMental RecallNeuronal PlasticityNeuronsSynapses

Identifiers

PMID27749830

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.