Evidence map›Paper›PMID 29934400›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Sparse bursts optimize information transmission in a multiplexed neural code.

Richard Naud, Henning Sprekeler

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.

0numbers the graph read from it
0cells of the map it votes in
75citing 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

75 citing papers in PubMed.

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  13. Spontaneous network transitions predict somatosensory perception.Cerebral cortex (New York, N.Y. : 1991) · 2025
    Article
  14. Article
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  16. Nonlinear Dendritic Integration Supports Up-Down States in Single Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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  17. Article
  18. Article
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15 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.

Richard NaudUniversity of Ottawa Brain and Mind Research Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; rnaud@uottawa.ca.ORCID 0000-0001-7383-3095
Henning SprekelerBernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany.ORCID 0000-0003-0690-3553

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.

Indexed as

Models, NeurologicalAnimalsCerebral CortexHumansNeuronsSynaptic Transmissioncerebral cortexdendritic computationmultiplexingneural codingshort-term plasticity

Identifiers

PMID29934400
PMCPMC6142200

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.