Models that contain the Receptor : Glycine

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    Models   Description
1.  A model for interaural time difference sensitivity in the medial superior olive (Zhou et al 2005)
This model simulates responses of neurons to interaural time difference (ITD) in the medial superior olive (MSO) of the mammalian brainstem. The model has a bipolar cell structure and incorporates two anatomic observations in the MSO: (1) the axon arises from the dendrite that receives ipsilateral inputs and (2) inhibitory synapses are located primarily on the soma in adult animals. Fine adjustment of the best ITD is achieved by the interplay of somatic sodium currents and synaptic inhibitory currents. The model suggests a mechanism for dynamically "fine-tuning" the ITD sensitivity of MSO cells by the opponency between depolarizing sodium currents and hyperpolarizing inhibitory currents.
2.  Application of a common kinetic formalism for synaptic models (Destexhe et al 1994)
Application to AMPA, NMDA, GABAA, and GABAB receptors is given in a book chapter. The reference paper synthesizes a comprehensive general description of synaptic transmission with Markov kinetic models. This framework is applicable to modeling ion channels, synaptic release, and all receptors. Please see the references for more details. A simple introduction to this method is given in a seperate paper Destexhe et al Neural Comput 6:14-18 , 1994). More information and papers at http://cns.iaf.cnrs-gif.fr/Main.html and through email: Destexhe@iaf.cnrs-gif.fr
3.  Central Nervous System tadpole model in Matlab and NEURON-Python (Ferrario et al, accepted)
This is the source code for three compuational models used for generating connectivity and swimming dynamics of spinal cord and hindbrain neurons in the Xenopus tadpoles using biological data. The model reproduces the initiation, continuation, termination and accelaration of forward swimming.
4.  Effects of spinal cord stimulation on WDR dorsal horn network (Zhang et al 2014)
" ... To study the mechanisms underlying SCS (Spinal cord stimulation), we constructed a biophysically-based network model of the dorsal horn circuit consisting of interconnected dorsal horn interneurons and a wide dynamic range (WDR) projection neuron and representations of both local and surround receptive field inhibition. We validated the network model by reproducing cellular and network responses relevant to pain processing including wind-up, A-fiber mediated inhibition, and surround receptive field inhibition. ..." See paper for more.
5.  Gating of steering signals through phasic modulation of reticulospinal neurons (Kozlov et al. 2014)
" ... We use the lamprey as a model for investigating the role of this phasic modulation of the reticulospinal activity, because the brainstem–spinal cord networks are known down to the cellular level in this phylogenetically oldest extant vertebrate. We describe how the phasic modulation of reticulospinal activity from the spinal CPG ensures reliable steering/turning commands without the need for a very precise timing of on- or offset, by using a biophysically detailed large-scale (19,600 model neurons and 646,800 synapses) computational model of the lamprey brainstem–spinal cord network. To verify that the simulated neural network can control body movements, including turning, the spinal activity is fed to a mechanical model of lamprey swimming. ..."
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.  Proximal inhibition of Renshaw cells (Bui et al 2005)
Inhibitory synaptic inputs to Renshaw cells are concentrated on the soma and the juxtasomatic dendrites. In the present study, we investigated whether this proximal bias leads to more effective inhibition under different neuronal operating conditions. Using compartmental models based on detailed anatomical measurements of intracellularly stained Renshaw cells, we compared the inhibition produced by GABAA synapses when distributed with a proximal bias to the inhibition produced when the same synapses were distributed uniformly. See paper for more and details.
8.  Respiratory central pattern generator including Kolliker-Fuse nucleus (Wittman et al 2019)
We present three highly reduced conductance-based models for the core of the respiratory CPG. All successfully simulate respiratory outputs across eupnoeic and vagotomized conditions and show that loss of inhibition to the pontine Kolliker-Fuse nucleus reproduces the key respiratory alterations associated with Rett syndrome.
9.  Superior paraolivary nucleus neuron (Kopp-Scheinpflug et al. 2011)
This is a model of neurons in the brainstem superior paraolivary nucleus (SPN), which produce very salient offset firing during sound stimulation. Rebound offset firing is triggered by IPSPs coming from the medial nucleus of the trapezoid body (MNTB). This model shows that AP firing can emerge from inhibition through integration of large IPSPs, driven by an extremely negative chloride reversal potential, combined with a large hyperpolarization- activated non-specific cationic current (IH), with a secondary contribution from a T-type calcium conductance (ITCa). As a result, tiny gaps in sound stimuli of just 3-4ms can elicit reliable APs that signal such brief offsets.

Re-display model names without descriptions