Recovery of rhythmic activity in a central pattern generator: Analysis of the role of neuromodulator and activity-dependent mechanisms

Document Type

Article

Publication Date

1-1-2011

Abstract

The pyloric network of decapods crustaceans can undergo dramatic rhythmic activity changes. Under normal conditions the network generates low frequency rhythmic activity that depends obligatorily on the presence of neuromodulatory input from the central nervous system. When this input is removed (decentralization) the rhythmic activity ceases. In the continued absence of this input, periodic activity resumes after a few hours in the form of episodic bursting across the entire network that later turns into stable rhythmic activity that is nearly indistinguishable from control (recovery). It has been proposed that an activity-dependent modification of ionic conductance levels in the pyloric pacemaker neuron drives the process of recovery of activity. Previous modeling attempts have captured some aspects of the temporal changes observed experimentally, but key features could not be reproduced. Here we examined a model in which slow activity-dependent regulation of ionic conductances and slower neuromodulator-dependent regulation of intracellular Ca2+ concentration reproduce all the temporal features of this recovery. Key aspects of these two regulatory mechanisms are their independence and their different kinetics. We also examined the role of variability (noise) in the activity-dependent regulation pathway and observe that it can help to reduce unrealistic constraints that were otherwise required on the neuromodulator-dependent pathway. We conclude that small variations in intracellular Ca2+ concentration, a Ca2+ uptake regulation mechanism that is directly targeted by neuromodulator-activated signaling pathways, and variability in the Ca2+ concentration sensing signaling pathway can account for the observed changes in neuronal activity. Our conclusions are all amenable to experimental analysis. © 2011 Springer Science+Business Media, LLC.

Identifier

83055194742 (Scopus)

Publication Title

Journal of Computational Neuroscience

External Full Text Location

https://doi.org/10.1007/s10827-011-0338-8

e-ISSN

15736873

ISSN

09295313

PubMed ID

21573963

First Page

685

Last Page

699

Issue

3

Volume

31

Grant

R01MH064711

Fund Ref

National Institutes of Health

This document is currently not available here.

Share

COinS