Abstract
Voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of synaptic input patterns. Drosophila and other invertebrates provide valuable model systems for investigating ion channel kinetics and their impact on firing properties. Despite the increasing importance of Drosophila as a model system, few computational models of its ion channel kinetics have been developed. In this study, experimentally observed biophysical properties of voltage gated ion channels from the fruitfly Drosophila melanogaster are used to develop a minimal, conductance based neuron model. We investigate the impact of the densities of these channels on the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from integrator to resonator properties. Further, we analyze the preference to input frequency and how it depends on the channel densities and the resulting bifurcation type the system undergoes. An extension to a three dimensional model demonstrates that the inactivation kinetics of the sodium channels play an important role, allowing for firing patterns with a delayed first spike and subsequent high frequency firing as often observed in invertebrates, without altering the kinetics of the delayed rectifier current.
Highlights
It is well-known that different neuron types exhibit distinct characteristic features under standardized or similar conditions such as constant current injection, due in part to the influence of differing ion channel kinetics and distributions (Shepherd, 2004)
We focus on the identified Drosophila motoneuron 5 (MN5) since its morphology, electrophysiology and certain aspects of its behavior during flight have been well-characterized experimentally
We investigated the influence of A-type channels on Drosophila MN5 firing behavior and found that, in accordance with experimental results, Shal and Shaker can influence the firing patterns and bifurcation structure of a neuron differently (Herrera-Valdez et al, 2009, 2010)
Summary
It is well-known that different neuron types exhibit distinct characteristic features under standardized or similar conditions such as constant current injection, due in part to the influence of differing ion channel kinetics and distributions (Shepherd, 2004). Experimental and theoretical studies show that differences in spiking patterns can be related to different combinations of ion channel densities (Goldman et al, 2001; Zeberg et al, 2010) with different channel kinetics. These differences affect the timing of action potentials (APs) and influence subthreshold integration of synaptic input and the filtering properties of the neuronal structure, resulting in bandpass or highpass filtering properties. Hodgkin classified neurons according to their spiking behavior upon steady current injection, and the resulting frequency–current relationships (f –I curves) generally can be divided into three distinct classes (Hodgkin, 1948). Numerous subsequent studies have analyzed the relationship between this classification and the output properties of a model neuron (Ermentrout, 1996; Rinzel and Ermentrout, 1998; Gutkin et al, 2003; St-Hilaire and Longtin, 2004; Tateno et al, 2004; Tateno and Robinson, 2006, 2007) and, from
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