Evidence map›Paper›PMID 23055965›Full record

ArticleFrontiers in computational neuroscience2012

Self-repair in a bidirectionally coupled astrocyte-neuron (AN) system based on retrograde signaling.

John Wade, Liam McDaid, Jim Harkin, Vincenzo Crunelli, Scott Kelso

Abstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2012. 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. Article
  5. The computational power of the human brain.Frontiers in cellular neuroscience · 2023
    Review
  6. Neuron-Glia Interactions and Brain Circuits.Advances in experimental medicine and biology · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Computational Models for Calcium-Mediated Astrocyte Functions.Frontiers in computational neuroscience · 2018
    Review
  14. Article
  15. 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

5 authors.

John WadeIntelligent Systems Research Center, School of Computing and Intelligent Systems, University of Ulster Derry, Northern Ireland, UK.
Liam McDaid
Jim Harkin
Vincenzo Crunelli
Scott Kelso

Funding

Wellcome Trust
6 · The paper itself

Abstract

In this paper we demonstrate that retrograde signaling via astrocytes may underpin self-repair in the brain. Faults manifest themselves in silent or near silent neurons caused by low transmission probability (PR) synapses; the enhancement of the transmission PR of a healthy neighboring synapse by retrograde signaling can enhance the transmission PR of the "faulty" synapse (repair). Our model of self-repair is based on recent research showing that retrograde signaling via astrocytes can increase the PR of neurotransmitter release at damaged or low transmission PR synapses. The model demonstrates that astrocytes are capable of bidirectional communication with neurons which leads to modulation of synaptic activity, and that indirect signaling through retrograde messengers such as endocannabinoids leads to modulation of synaptic transmission PR. Although our model operates at the level of cells, it provides a new research direction on brain-like self-repair which can be extended to networks of astrocytes and neurons. It also provides a biologically inspired basis for developing highly adaptive, distributed computing systems that can, at fine levels of granularity, fault detect, diagnose and self-repair autonomously, without the traditional constraint of a central fault detect/repair unit.

Indexed as

astrocytecalcium waveendocannabinoidIP3neuronself-repairsynapse

Identifiers

PMID23055965
PMCPMC3458420

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.