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

• Type of Material: Article
• Authors: Cengiz Gunay, Emory University; Astrid A Prinz, Emory University
• Language: English
• Date: 2010-02-03
• Publisher: Lippincott, Williams & Wilkins
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2010 the authors
• Final Published Version (URL): http://www.jneurosci.org/content/30/5/1686
• Title of Journal or Parent Work: Journal of Neuroscience Nursing
• ISSN: 0888-0395
• Volume: 30
• Issue: 5
• Start Page: 1686
• End Page: 1698
• Grant/Funding Information: This work is supported by 1 R01 NS054911-01A1 from NINDS and a Career Award at the Scientific Interface from the Burroughs Wellcome Fund awarded to author AAP. R.M. Hooper and K.R. Hammett contributed to preliminary results.; National Institute of Neurological Disorders and Stroke : NINDS
• Keywords: calcium sensor; lobster; neuronal network model; pyloric network; stomatogastric ganglion; activity-dependent homeostatic regulation
• Research Categories: Biology, Neuroscience

Abstract

In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intra-cellular Ca2+ concentration is a good candidate for sensing activity levels because it is correlated with the cell's electrical activity. Previous ADHR models, developed with abstract activity sensors for model pyloric neurons and networks of the crustacean stomatogastric ganglion (STG), showed that functional activity can be maintained by a regulation mechanism that senses activity levels solely from Ca2+. At the same time, several intracellular pathways have been discovered for Ca2+-dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca2+ 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 millisecond and that inactivates within 1 second. 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 non-linearly. Specific to this pyloric network model, the follower pyloric constrictor cell's sensor 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.