Evidence map›Paper›PMID 19759328›Full record

ArticleJournal of neurophysiology2009

Locally balanced dendritic integration by short-term synaptic plasticity and active dendritic conductances.

Vladislav Volman, Herbert Levine, Eshel Ben-Jacob, Terrence J Sejnowski

Open access · greenAbstract read
In one paragraph

Article in Journal of neurophysiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Cellular biomechanics of central nervous system injury.Handbook of clinical neurology · 2015
    Review
  3. An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2014
    Article
  4. Review
  5. 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 at 3 institutions in 2 countries.

Vladislav VolmanCenter for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92093, USA. volman@salk.edu
Herbert Levine
Eshel Ben-Jacob
Terrence J Sejnowski
Salk Institute for Biological Studies · USCenter for Theoretical Biological Physics · USTel Aviv University · IL

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

The high degree of variability observed in spike trains and membrane potentials of pyramidal neurons in vivo is thought to be a consequence of a balance between excitatory and inhibitory inputs, which depends on the dynamics of the network. We simulated synaptic currents and ion channels in a reconstructed hippocampal CA1 pyramidal cell and show here that a local balance can be achieved on a dendritic branch with a different mechanism, based on presynaptic depression of quantal release interacting with active dendritic conductances. This mechanism, which does not require synaptic inhibition, allows each dendritic branch to remain sensitive to correlated synaptic inputs, induces a high degree of variability in the output spike train, and can be combined with other balance mechanisms based on network dynamics. This hypothesis makes a testable prediction for the cause of the observed variability in the firing of hippocampal place cells.

Indexed as

Action PotentialsAnimalsBiophysicsCA1 Region, HippocampalCalciumCalcium ChannelsComputer SimulationDendritesElectric StimulationModels, NeurologicalNeural ConductionNeuronal PlasticityProbabilityPyramidal CellsSynapsesCalciumCalcium Channels

Identifiers

PMID19759328
PMCPMC2804429
OpenAlexW2166027557

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.