ArticleJournal of biological physics2011
A database of computational models of a half-center oscillator for analyzing how neuronal parameters influence network activity.
Article in Journal of biological physics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- When can neuronal activity-dependent homeostatic plasticity maintain circuit-level properties?Journal of computational neuroscience · 2026Article
- Dynamics of antiphase bursting modulated by the inhibitory synaptic and hyperpolarization-activated cation currents.Frontiers in computational neuroscience · 2024Article
- Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons.Open biology · 2022Review
- Computational Modeling of Spinal Locomotor Circuitry in the Age of Molecular Genetics.International journal of molecular sciences · 2021Review
- Circuit Stability to Perturbations Reveals Hidden Variability in the Balance of Intrinsic and Synaptic Conductances.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Complex Dynamics in Simplified Neuronal Models: Reproducing Golgi Cell Electroresponsiveness.Frontiers in neuroinformatics · 2018Article
- Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators.Frontiers in computational neuroscience · 2017Article
- Optimizing computer models of corticospinal neurons to replicate in vitro dynamics.Journal of neurophysiology · 2017Article
- The neural control of heartbeat in invertebrates.Current opinion in neurobiology · 2016Review
- From global to local: exploring the relationship between parameters and behaviors in models of electrical excitability.Journal of computational neuroscience · 2016Article
- A positive feedback at the cellular level promotes robustness and modulation at the circuit level.Journal of neurophysiology · 2015Article
- Differential effects of conductances on the phase resetting curve of a bursting neuronal oscillator.Journal of computational neuroscience · 2015Article
- A modeling exploration of how synaptic feedback to descending projection neurons shapes the activity of an oscillatory network.SIAM journal on applied dynamical systems · 2014Article
- Identifying crucial parameter correlations maintaining bursting activity.PLoS computational biology · 2014Article
- The virtual brain integrates computational modeling and multimodal neuroimaging.Brain connectivity · 2013Article
- High prevalence of multistability of rest states and bursting in a database of a model neuron.PLoS computational biology · 2013Article
- morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python.Frontiers in neuroinformatics · 2013Article
- Small is beautiful: models of small neuronal networks.Current opinion in neurobiology · 2012Review
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2 authors.
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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.
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