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Document type:
Zeitschriftenaufsatz
Author(s):
Bade P.-W., Rudnicki M., Hemmert W.
Title:
A model of auditory spiral ganglion neurons.
Abstract:
Our study focuses on biophysical modeling of the auditory periphery and initial stages of neural processing. We examined in detail synaptic excitation between inner hair cells and spiral ganglion type I neurons. Spiral ganglion neurons encode and convey information about sound to the central nervous system in the form of action potentials. For the purpose of our study we utilized a biophysical model of the auditory periphery proposed by Sumner (2002). It consists of outer/middle ear filters, a basilar membrane filter bank, an inner hair cell model coupled with complex vesicle pool dynamics at the presynaptic membrane. Finally, fusion of vesicles, modelled with a probabilistic function, releases neurotransmitter into the synaptic cleft. Response of auditory nerve fibers is modeled with a spike generator. The absolute refractory period is set to 0.75 ms and the relative refractory period is modelled with an exponentially decaying function. In our approach we substituted the artificial spike generation and refraction model with a more realistic spiral ganglion neuron model with Hodgkin-Huxley type ion channels proposed by Negm and Bruce (2008). The model included several channels also found in cochlear nucleus neurons (K_A, K_ht, K_lt). Our model consisted of the postsynaptic bouton (1.5x1.7µ m) from high-spontaneous rate fibers. We coupled the model of the synapse with the spiral ganglion neuron using a synaptic excitation model fitted to results from Glowatzki and Fuchs' (2002) experiments, who conducted patch clamp measurements at the afferent postsynapse. We verified our hybrid model against various experiments, mostly pure tone stimulation. Rate intensity functions fitted experimental data well, rates varied from about 40 spikes/s to a maximum of 260 spikes/s. Adaptation properties were investigated with peri-stimulus time histograms (PSTH). As adaptation is mainly governed by vesicle pool dynamics, only small changes occurred compared with the statistical spike generation model and adaptation was consistent with experiments. Interestingly, Hodgkin-Huxley models of spiral ganglion neurons exhibited a notch visible in the PSTH after rapid adaptation that could also be observed in experiments. This was not revealed by the statistical spike generator. The fiber's refractory period was investigated using inter-spike interval histograms. The refractory period varied with simulus intensity from 1ms (spontaneous activity) to 0.7ms (84dB_SPL). We also analyzed phase locking with the synchronization index. It was slightly lower compared to the statistical spike generator. By varying the density of K_lt and K_A channels, we could replicate heterogenity of auditory nerve fibers as shown by Adamson et al. (2002). In summary, replacing the statistical spike generation model with a more realistic model of the postsynaptic membrane obsoletes the introduction of non-physiologic parameters for absolute and relative refraction. It improves the refractory behaviour and provides more realistic spike trains of the auditory nerve.

Acknowledgments:Supported by within the Munich Bernstein Center for Computational Neuroscience by the German Federal Ministry of Education and Research (reference numbers 01GQ0441 and 01GQ0443).
Keywords:
bccn, ss2010
Journal title:
Frontiers in Computational Neuroscience
Year:
2010
Journal volume:
4
Journal issue:
0
Pages contribution:
5
Reviewed:
ja
Language:
de
Fulltext / DOI:
doi:10.3389/conf.neuro.10.2009.14.131
Semester:
SS 02
Format:
Text
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