Modeling recovery of rhythmic activity: Hypothesis for the role of a calcium pump

Yili Zhang, Jorge Golowasch

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The pyloric network of crustaceans is a model system for the study of the recovery of function after perturbation/injury of a central pattern-generating network. The network is well characterized anatomically and functionally, yet the cellular mechanism underlying the stabilization or recovery of its activity is not known. In a previous theoretical study long-term activity-dependent regulation of ionic conductances was shown to be sufficient to explain the recovery of rhythmic activity after it is lost due to removal of central input. This model, however, did not capture the complex temporal activity dynamics (bouting) that follows decentralization and that precedes the final stable recovery. Here we build a model of a conditional pacemaker neuron whose ionic conductance levels depend on activity as before, but also includes a slow activity-dependent regulation of Ca2+ uptake (and release). Intracellular Ca2+ sensors, representing enzymatic pathways, regulate the Ca2+ pump activity as well as Ca2+ and K+ conductances. Our model suggests that the activity-dependent regulation of Ca2+ uptake as well as ionic currents interact to generate the complex changes in pyloric activity that follows decentralization. Supported by NIMH 64711 and NSF IBN-0090250.

Original languageEnglish (US)
Pages (from-to)1657-1662
Number of pages6
JournalNeurocomputing
Volume70
Issue number10-12
DOIs
StatePublished - Jun 2007

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Keywords

  • Activity-dependent regulation
  • Bursting
  • Decentralization
  • Feedback
  • Intracellular signaling
  • Stomatogastric

Fingerprint

Dive into the research topics of 'Modeling recovery of rhythmic activity: Hypothesis for the role of a calcium pump'. Together they form a unique fingerprint.

Cite this