Evidence map›Paper›PMID 20130178›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2010

Model calcium sensors for network homeostasis: sensor and readout parameter analysis from a database of model neuronal networks.

Cengiz Günay, Astrid A Prinz

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.1field-weighted citation impact, top 28% 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

14 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Article
  3. Intrinsic plasticity and birdsong learning.Neurobiology of learning and memory · 2021
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Pumilio-2 regulates translation of Nav1.6 to mediate homeostasis of membrane excitability.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2013
    Article
  9. Article
  10. Article
  11. Article
  12. Neuronal homeostasis: time for a change?The Journal of physiology · 2011
    Review
  13. Compensation for variable intrinsic neuronal excitability by circuit-synaptic interactions.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2010
    Article
  14. 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

2 authors at 1 institution in 1 country.

Cengiz GünayDepartment of Biology, Emory University, Atlanta, Georgia 30322, USA. cgunay@emory.edu
Astrid A Prinz
Emory University · US

Funding

Atlanta Clinical and Translational Science Institute (ACTSI) RenewalUL1TR000454 · NCATS · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2012 to 2016
$25.8M
Activity-dependent homeostatic regulation in neural networksR01NS054911 · NINDS · EMORY UNIVERSITY · PI PRINZ, ASTRID ANTONIA · 2007 to 2011
$1.2M
NCATS NIH HHS UL1 TR000454NINDS NIH HHS 1 R01 NS054911-01A1NINDS NIH HHS R01 NS054911
6 · The paper itself

Abstract

In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intracellular Ca(2+) concentration is a good candidate for sensing activity levels because it is correlated with the electrical activity of the cell. Previous ADHR models, developed with abstract activity sensors for model pyloric neurons and networks of the crustacean stomatogastric ganglion, showed that functional activity can be maintained by a regulation mechanism that senses activity levels solely from Ca(2+). At the same time, several intracellular pathways have been discovered for Ca(2+)-dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca(2+) sensors across thousands of model pyloric networks. We found that an optimal regulation signal can be generated for 86% of model networks with a sensing mechanism that activates with a time constant of 1 ms and that inactivates within 1 s. The sensor performed robustly around this optimal point and did not need to be specific to the role of the cell. When multiple sensors with different time constants were used, coverage extended to 88% of the networks. Without changing the sensors, it extended to 95% of the networks by letting the sensors affect the readout nonlinearly. Specific to this pyloric network model, the sensor of the follower pyloric constrictor cell was more informative than the pacemaker anterior burster cell for producing a regulatory signal. Conversely, a global signal indicating network activity that was generated by summing the sensors in individual cells was less informative for regulation.

Indexed as

Models, NeurologicalNeural Networks, ComputerBiosensing TechniquesCalciumCalcium SignalingFeedback, PhysiologicalHomeostasisLinear ModelsNeural PathwaysNonlinear DynamicsPylorusReceptors, Calcium-SensingSynapsesCalciumReceptors, Calcium-Sensing

Identifiers

PMID20130178
PMCPMC2851246
OpenAlexW1983184768

What OpenQuestion holds

Textmetadata
LicenceTDM
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.