Evidence map›Paper›PMID 17440801›Full record

ArticleJournal of computational neuroscience2007

Capturing the bursting dynamics of a two-cell inhibitory network using a one-dimensional map.

Victor Matveev, Amitabha Bose, Farzan Nadim

Abstract read
In one paragraph

Article in Journal of computational neuroscience, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Linking dynamics of the inhibitory network to the input structure.Journal of computational neuroscience · 2016
    Article
  4. Article
  5. Frequency separation by an excitatory-inhibitory network.Journal of computational neuroscience · 2013
    Article
  6. Article
  7. Article
  8. 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

3 authors.

Victor MatveevDepartment of Mathematical Sciences, New Jersey Institute of Technology, Cullimore Hall, University Heights, Newark, NJ 07102-1982, USA matveev@njit.edu
Amitabha Bose
Farzan Nadim

Funding

REGULATION OF NEURONAL OSCILLATIONS BY SYNAPTIC DYNAMICSR01MH060605 · NIMH · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI Dirk Martin Bucher, Farzan Nadim · 2001 to 2026
$6.6M
NIMH NIH HHS MH-60605NIMH NIH HHS R01 MH060605
6 · The paper itself

Abstract

Out-of-phase bursting is a functionally important behavior displayed by central pattern generators and other neural circuits. Understanding this complex activity requires the knowledge of the interplay between the intrinsic cell properties and the properties of synaptic coupling between the cells. Here we describe a simple method that allows us to investigate the existence and stability of anti-phase bursting solutions in a network of two spiking neurons, each possessing a T-type calcium current and coupled by reciprocal inhibition. We derive a one-dimensional map which fully characterizes the genesis and regulation of anti-phase bursting arising from the interaction of the T-current properties with the properties of synaptic inhibition. This map is the burst length return map formed as the composition of two distinct one-dimensional maps that are each regulated by a different set of model parameters. Although each map is constructed using the properties of a single isolated model neuron, the composition of the two maps accurately captures the behavior of the full network. We analyze the parameter sensitivity of these maps to determine the influence of both the intrinsic cell properties and the synaptic properties on the burst length, and to find the conditions under which multistability of several bursting solutions is achieved. Although the derivation of the map relies on a number of simplifying assumptions, we discuss how the principle features of this dimensional reduction method could be extended to more realistic model networks.

Indexed as

Models, NeurologicalNonlinear DynamicsAction PotentialsAnimalsCell CommunicationNerve NetNeural InhibitionNeural Networks, ComputerNeurons

Identifiers

PMID17440801
PMCPMC2606977

What OpenQuestion holds

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Registered trials

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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.