Models that contain the Neuron : Retina ganglion GLU cell

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    Models   Description
1.  A Model Circuit of Thalamocortical Convergence (Behuret et al. 2013)
“… Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. … The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. …”
2.  A network model of the vertebrate retina (Publio et al. 2009)
In this work, we use a minimal conductance-based model of the ON rod pathways in the vertebrate retina to study the effects of electrical synaptic coupling via gap junctions among rods and among AII amacrine cells on the dynamic range of the retina. The model is also used to study the effects of the maximum conductance of rod hyperpolarization activated current Ih on the dynamic range of the retina, allowing a study of the interrelations between this intrinsic membrane parameter with those two retina connectivity characteristics.
3.  Availability of low-threshold Ca2+ current in retinal ganglion cells (Lee SC et al. 2003)
"... we measured T-type current of isolated goldfish retinal ganglion cells with perforated-patch voltageclamp methods in solutions containing a normal extracellular Ca2+ concentration. The voltage sensitivities and rates of current activation, inactivation, deactivation, and recovery from inactivation were similar to those of expressed +1G (CaV3.1) Ca2+ channel clones, except that the rate of deactivation was significantly faster. We reproduced the amplitude and kinetics of measured T currents with a numerical simulation based on a kinetic model developed for an +1G Ca2+ channel. Finally, we show that this model predicts the increase of T-type current made available between resting potential and spike threshold by repetitive hyperpolarizations presented at rates that are within the bandwidth of signals processed in situ by these neurons."
4.  COREM: configurable retina simulator (Martínez-Cañada et al., 2016)
COREM is a configurable simulator for retina modeling that has been implemented within the framework of the Human Brain Project (HBP). The software platform can be interfaced with neural simulators (e.g., NEST) to connect with models of higher visual areas and with the Neurorobotics Platform of the HBP. The code is implemented in C++ and computations of spatiotemporal equations are optimized by means of recursive filtering techniques and multithreading. Most retina simulators are more focused on fitting specific retina functions. By contrast, the versatility of COREM allows the configuration of different retina models using a set of basic retina computational primitives. We implemented a series of retina models by combining these primitives to characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The code has been extensively tested in Linux. The software can be also adapted to Mac OS. Installation instructions as well as the user manual can be found in the Github repository: https://github.com/pablomc88/COREM
5.  Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
We show that microsaccades (MS) enable efficient synchrony-based coding among the primate retinal ganglion cells (RGC). We find that each MS causes certain RGCs to fire synchronously, namely those whose receptive fields contain contrast edges after the MS. The emitted synchronous spike volley thus rapidly transmits the most salient edges of the stimulus. We demonstrate that the readout could be done rapidly by simple coincidence-detector neurons, and that the required connectivity could emerge spontaneously with spike timing-dependent plasticity.
6.  Multiplication by NMDA receptors in Direction Selective Ganglion cells (Poleg-Polsky & Diamond 2016)
The model demonstrates how signal amplification with NMDARs depends on the synaptic environment. When direction selectivity (DS) detection is mediated by DS inhibition, NMDARs multiply other synaptic conductances. In the case of DS tuned excitation, NMDARs contribute additively.
7.  Nonlinear neuronal computation based on physiologically plausible inputs (McFarland et al. 2013)
"... Here we present an approach for modeling sensory processing, termed the Nonlinear Input Model (NIM), which is based on the hypothesis that the dominant nonlinearities imposed by physiological mechanisms arise from rectification of a neuron’s inputs. Incorporating such ‘upstream nonlinearities’ within the standard linear-nonlinear (LN) cascade modeling structure implicitly allows for the identification of multiple stimulus features driving a neuron’s response, which become directly interpretable as either excitatory or inhibitory. Because its form is analogous to an integrate-and-fire neuron receiving excitatory and inhibitory inputs, model fitting can be guided by prior knowledge about the inputs to a given neuron, and elements of the resulting model can often result in specific physiological predictions. Furthermore, by providing an explicit probabilistic model with a relatively simple nonlinear structure, its parameters can be efficiently optimized and appropriately regularized. ... ”
8.  Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
Phenomenological spiking model of the cat early visual system. We show how natural vision can drive spike time correlations on sufficiently fast time scales to lead to the acquisition of orientation-selective V1 neurons through STDP. This is possible without reference times such as stimulus onsets, or saccade landing times. But even when such reference times are available, we demonstrate that the relative spike times encode the images more robustly than the absolute ones.
9.  Retinal Ganglion Cell: I-A (Benison et al 2001)
NEURON mod files for the K-A current from the papers: (model) Benison G, Keizer J, Chalupa LM, Robinson DW. Modeling temporal behavior of postnatal cat retinal ganglion cells. J.Theor.Biol. 210:187-199 (2001) and (experiment) Skaliora I, Robinson DW, Scobey RP, Chalupa LM., Properties of K+ conductances in cat retinal ganglion cells during the period of activity-mediated refinements in retinofugal pathways. Eur.J.Neurosci. 7:1558-1568 (1995).
10.  Retinal Ganglion Cell: I-CaN and I-CaL (Benison et al. 2001)
NEURON mod files for the CaN and CaL currents from the papers: Huang, S.-J. & Robinson, D.W. (1998). Activation and Inactivation properties of voltage-gated calcium currents in developing cat retinal ganglion cells. Neuroscience 85:239-247 (experimental) and Benison G. Keizer J., Chalupa L.M., Robinson D.W., (2001) J. theor. Biol. 210:187-199 (theoretical).
11.  Retinal Ganglion Cell: I-K (Skaliora et al 1995)
NEURON mod files for the K-DR current from the paper: Skaliora I, Robinson DW, Scobey RP, Chalupa LM. Properties of K+ conductances in cat retinal ganglion cells during the period of activity-mediated refinements in retinofugal pathways. Eur J Neurosci 1995 7(7):1558-1568. See the readme.txt file below for more information.
12.  Retinal Ganglion Cell: I-Na,t (Benison et al 2001)
NEURON mod files for the Na current from the papers: (model) Benison G, Keizer J, Chalupa LM, Robinson DW. Modeling temporal behavior of postnatal cat retinal ganglion cells. J Theor Biol. 2001 210:187-99 and a reference from this paper: (experimental) Skaliora I, Scobey RP, Chalupa LM. Prenatal development of excitability in cat retinal ganglion cells: action potentials and sodium currents. J Neurosci 1993 13:313-23. See the readme.txt file below for more information.
13.  Ribbon Synapse (Sikora et al 2005)
A model of the ribbon synapse was developed to replicate both pre- and postsynaptic functions of this glutamatergic juncture. The presynaptic portion of the model is rich in anatomical and physiological detail and includes multiple release sites for each ribbon based on anatomical studies of presynaptic terminals, presynaptic voltage at the terminal, the activation of voltage-gated calcium channels and a calcium-dependent release mechanism whose rate varies as a function of the calcium concentration that is monitored at two different sites which control both an ultrafast, docked pool of vesicles and a release ready pool of tethered vesicles. See paper for more and details.
14.  Salamander retinal ganglian cells: morphology influences firing (Sheasby, Fohlmeister 1999)
Nerve impulse entrainment and other excitation and passive phenomena are analyzed for a morphologically diverse and exhaustive data set (n=57) of realistic (3-dimensional computer traced) soma-dendritic tree structures of ganglion cells in the tiger salamander (Ambystoma tigrinum) retina.
15.  Salamander retinal ganglion cell: ion channels (Fohlmeister, Miller 1997)
A realistic five (5) channel spiking model reproduces the bursting behavior of tiger salamander ganglion cells in the retina. Please see the readme for more information.

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