A database of computational models of a half-center oscillator for analyzing how neuronal parameters influence network activity |
| |
Authors: | Anca Doloc-Mihu Ronald L Calabrese |
| |
Institution: | (1) Department of Biology, Emory University, Atlanta, GA 30322, USA |
| |
Abstract: | A half-center oscillator (HCO) is a common circuit building block of central pattern generator networks that produce rhythmic
motor patterns in animals. Here we constructed an efficient relational database table with the resulting characteristics of
the Hill et al.’s (J Comput Neurosci 10:281–302, 2001) HCO simple conductance-based model. The model consists of two reciprocally inhibitory neurons and replicates the electrical
activity of the oscillator interneurons of the leech heartbeat central pattern generator under a variety of experimental conditions.
Our long-range goal is to understand how this basic circuit building block produces functional activity under a variety of
parameter regimes and how different parameter regimes influence stability and modulatability. By using the latest developments
in computer technology, we simulated and stored large amounts of data (on the order of terabytes). We systematically explored
the parameter space of the HCO and corresponding isolated neuron models using a brute-force approach. We varied a set of selected
parameters (maximal conductance of intrinsic and synaptic currents) in all combinations, resulting in about 10 million simulations.
We classified these HCO and isolated neuron model simulations by their activity characteristics into identifiable groups and
quantified their prevalence. By querying the database, we compared the activity characteristics of the identified groups of
our simulated HCO models with those of our simulated isolated neuron models and found that regularly bursting neurons compose
only a small minority of functional HCO models; the vast majority was composed of spiking neurons. |
| |
Keywords: | Bursting Oscillation Central pattern generator Database Parameter variation Simulation Isolated neuron Automated analysis Large datasets |
本文献已被 PubMed SpringerLink 等数据库收录! |