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Minimal Conductance-Based Model of Auditory Coincidence Detector Neurons
Author(s) -
Go Ashida,
Kazuo Funabiki,
Jutta Kretzberg
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0122796
Subject(s) - coincidence detection in neurobiology , computer science , computational model , biological system , mathematical model , robustness (evolution) , nonlinear system , sound localization , auditory system , detector , coincidence , neuroscience , physics , algorithm , biology , medicine , telecommunications , biochemistry , alternative medicine , pathology , quantum mechanics , gene
Sound localization is a fundamental sensory function of a wide variety of animals. The interaural time difference (ITD), an important cue for sound localization, is computed in the auditory brainstem. In our previous modeling study, we introduced a two-compartment Hodgkin-Huxley type model to investigate how cellular and synaptic specializations may contribute to precise ITD computation of the barn owl's auditory coincidence detector neuron. Although our model successfully reproduced fundamental physiological properties observed in vivo , it was unsuitable for mathematical analyses and large scale simulations because of a number of nonlinear variables. In the present study, we reduce our former model into three types of conductance-based integrate-and-fire (IF) models. We test their electrophysiological properties using data from published in vivo and in vitro studies. Their robustness to parameter changes and computational efficiencies are also examined. Our numerical results suggest that the single-compartment active IF model is superior to other reduced models in terms of physiological reproducibility and computational performance. This model will allow future theoretical studies that use more rigorous mathematical analysis and network simulations.

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