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Hear Res. 2018 Mar;360:76-91. doi: 10.1016/j.heares.2017.12.017. Epub 2017 Dec 28.

A biophysical modelling platform of the cochlear nucleus and other auditory circuits: From channels to networks.

Author information

1
Dept. of Otolaryngology/Head and Neck Surgery, B027 Marsico Hall, 125 Mason Farm Road, UNC Chapel Hill, Chapel Hill, NC 27599-7070, USA. Electronic address: pmanis@med.unc.edu.
2
Dept. of Otolaryngology/Head and Neck Surgery, B027 Marsico Hall, 125 Mason Farm Road, UNC Chapel Hill, Chapel Hill, NC 27599-7070, USA.

Abstract

Models of the auditory brainstem have been an invaluable tool for testing hypotheses about auditory information processing and for highlighting the most important gaps in the experimental literature. Due to the complexity of the auditory brainstem, and indeed most brain circuits, the dynamic behavior of the system may be difficult to predict without a detailed, biologically realistic computational model. Despite the sensitivity of models to their exact construction and parameters, most prior models of the cochlear nucleus have incorporated only a small subset of the known biological properties. This confounds the interpretation of modelling results and also limits the potential future uses of these models, which require a large effort to develop. To address these issues, we have developed a general purpose, biophysically detailed model of the cochlear nucleus for use both in testing hypotheses about cochlear nucleus function and also as an input to models of downstream auditory nuclei. The model implements conductance-based Hodgkin-Huxley representations of cells using a Python-based interface to the NEURON simulator. Our model incorporates most of the quantitatively characterized intrinsic cell properties, synaptic properties, and connectivity available in the literature, and also aims to reproduce the known response properties of the canonical cochlear nucleus cell types. Although we currently lack the empirical data to completely constrain this model, our intent is for the model to continue to incorporate new experimental results as they become available.

PMID:
29331233
PMCID:
PMC6053909
[Available on 2019-03-01]
DOI:
10.1016/j.heares.2017.12.017
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