Evidence map›Paper›PMID 25474701›Full record

ArticlePLoS computational biology2014

Intrinsic neuronal properties switch the mode of information transmission in networks.

Julijana Gjorgjieva, Rebecca A Mease, William J Moody, Adrienne L Fairhall

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. EngineeringAPL bioengineering · 2021
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Ion channel degeneracy enables robust and tunable neuronal firing rates.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  15. Temporal dynamics in fMRI resting-state activity.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  16. 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

4 authors.

Julijana GjorgjievaCenter for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.
Rebecca A MeaseInstitute of Neuroscience, Technische Universität München, Munich, Germany.
William J MoodyDepartment of Biology, University of Washington, Seattle, Washington, United States of America.
Adrienne L FairhallDepartment of Physiology and Biophysics and the WRF UW Institute for Neuroengineering, University of Washington, Seattle, Washington, United States of America.

Funding

The computational properties of developing cortical neurons and how they determinR21NS072691 · NINDS · UNIVERSITY OF WASHINGTON · PI FAIRHALL, ADRIENNE L, MOODY, WILLIAM J · 2010 to 2011
$425k
NINDS NIH HHS 1R21NS072691NINDS NIH HHS R21 NS072691
6 · The paper itself

Abstract

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission.

Indexed as

Models, NeurologicalAction PotentialsAnimalsCerebral CortexComputational BiologyIon ChannelsNerve NetNeuronsRatsSynaptic TransmissionIon Channels

Identifiers

PMID25474701
PMCPMC4256072

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.