Evidence map›Paper›PMID 34748532›Full record

ArticlePLoS computational biology2021

Self-organization of a doubly asynchronous irregular network state for spikes and bursts.

Filip Vercruysse, Richard Naud, Henning Sprekeler

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Beyond spiking networks: The computational advantages of dendritic amplification and input segregation.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  3. 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

3 authors.

Filip VercruysseDepartment for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany.ORCID 0000-0002-0521-6308
Richard NaudDepartment of Physics, University of Ottawa, Ottawa, Canada.ORCID 0000-0001-7383-3095
Henning SprekelerDepartment for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany.ORCID 0000-0003-0690-3553

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cortical pyramidal cells (PCs) have a specialized dendritic mechanism for the generation of bursts, suggesting that these events play a special role in cortical information processing. In vivo, bursts occur at a low, but consistent rate. Theory suggests that this network state increases the amount of information they convey. However, because burst activity relies on a threshold mechanism, it is rather sensitive to dendritic input levels. In spiking network models, network states in which bursts occur rarely are therefore typically not robust, but require fine-tuning. Here, we show that this issue can be solved by a homeostatic inhibitory plasticity rule in dendrite-targeting interneurons that is consistent with experimental data. The suggested learning rule can be combined with other forms of inhibitory plasticity to self-organize a network state in which both spikes and bursts occur asynchronously and irregularly at low rate. Finally, we show that this network state creates the network conditions for a recently suggested multiplexed code and thereby indeed increases the amount of information encoded in bursts.

Indexed as

Models, NeurologicalAction PotentialsAnimalsComputational BiologyComputer SimulationDendritesHomeostasisInterneuronsNerve NetNeuronal PlasticityPyramidal CellsRats

Identifiers

PMID34748532
PMCPMC8575278

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.