Models that contain the Neuron : Cochlear nucleus bushy GLU cell

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	Models	Description
1.	CN bushy, stellate neurons (Rothman, Manis 2003)
		Using kinetic data from three different K+ currents in acutely isolated neurons, a single electrical compartment model representing the soma of a ventral cochlear nucleus (VCN) neuron was created. The K+ currents include a fast transient current (IA), a slow-inactivating low-threshold current (ILT), and a noninactivating high-threshold current (IHT). The model also includes a fast-inactivating Na+ current, a hyperpolarization-activated cation current (Ih), and 1-50 auditory nerve synapses. With this model, the role IA, ILT, and IHT play in shaping the discharge patterns of VCN cells is explored. Simulation results indicate these currents have specific roles in shaping the firing patterns of stellate and bushy CN cells. (see readme.txt and the papers, esp 2003c, for details). Any questions regarding these implementations should be directed to: pmanis@med.unc.edu 2 April 2004 Paul B Manis, Ph.D.
2.	CN bushy, stellate neurons (Rothman, Manis 2003) (Brian 2)
		This model is an updated version of Romain Brette's adaptation of Rothman & Manis (2003). The model now uses Brian 2 instead of Brian 1 and can be configured to use n cells instead of a single cell. The included figure shows that Brian 2 is more efficient than Brian 1 once the number of cells exceeds 1,000.
3.	CN bushy, stellate neurons (Rothman, Manis 2003) (Brian)
		Cochlear neuron model of Rothman & Manis (2003). Adapted from the Neuron implementation.
4.	High entrainment constrains synaptic depression in a globular bushy cell (Rudnicki & Hemmert 2017)
		" ... Here we show how different levels of synaptic depression shape firing properties of GBCs in in vivo-like conditions using computer simulations. We analyzed how an interplay of synaptic depression (0 % to 70 %) and the number of auditory nerve fiber inputs (10 to 70) contributes to the variability of the experimental data from previous studies. ... Overall, this study helps to understand how synaptic properties shape temporal processing in the auditory system. It also integrates, compares, and reconciles results of various experimental studies."
5.	Human auditory periphery model: cochlea, IHC-AN, auditory brainstem responses (Verhulst et al 2018)
		The human auditory periphery model can simulate single-unit response of basilar-membrane vibration, IHC receptor potential, instantaneous AN/CN/IC firing rates, as well as population responses such as otoacoustic emissions, auditory brainstem responses. The neuron models (IHC, AN,CN,IC) can be run independently to relate their responses to electrophysiology, or be simulated as part of the human auditory periphery.
6.	Modelling platform of the cochlear nucleus and other auditory circuits (Manis & Compagnola 2018)
		"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, bio-physically 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. ..."
7.	Simulating ion channel noise in an auditory brainstem neuron model (Schmerl & McDonnell 2013)
		" ... Here we demonstrate that biophysical models of channel noise can give rise to two kinds of recently discovered stochastic facilitation effects in a Hodgkin-Huxley-like model of auditory brainstem neurons. The first, known as slope-based stochastic resonance (SBSR), enables phasic neurons to emit action potentials that can encode the slope of inputs that vary slowly relative to key time constants in the model. The second, known as inverse stochastic resonance (ISR), occurs in tonically firing neurons when small levels of noise inhibit tonic firing and replace it with burstlike dynamics. ..." Preprint available at http://arxiv.org/abs/1311.2643

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