Models that contain the Modeling Application : Java (Home Page)

(java program)
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    Models   Description
1.  A comparative computer simulation of dendritic morphology (Donohue and Ascoli 2008)
Morphological aspects of dendritic branching such branch lengths, taper rates,ratios of daughter radii, and bifurcation probabilities are measured from real cells. These morphometrics are then resampled to create virtual trees based on the current branch order, radius, path distance to the soma, or combination of the three.
2.  A Method for Prediction of Receptor Activation in the Simulation of Synapses (Montes et al. 2013)
A machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the activation of synaptic receptors, at very low computational cost. The method is designed to learn patterns and general principles from previous Monte Carlo simulations and to predict synapse behavior from them. The resulting procedure is accurate, automatic and can predict synapse behavior under experimental conditions that are different to the ones used during the learning phase. Since our method efficiently reduces the computational costs, it is suitable for the simulation of the vast number of synapses that occur in the mammalian brain.
3.  Alternative time representation in dopamine models (Rivest et al. 2009)
Combines a long short-term memory (LSTM) model of the cortex to a temporal difference learning (TD) model of the basal ganglia. Code to run simulations similar to the published data: Rivest, F, Kalaska, J.F., Bengio, Y. (2009) Alternative time representation in dopamine models. Journal of Computational Neuroscience. See for details.
4.  C elegans pharynx simulation (Avery and Shtonda 2003)
Experimental obervations, measurements, and theoretical analysis of C. elegans pharynx feeding behavior function are reported in the paper. See the paper and the model files for more.
5.  CA1 pyramidal cell receptor dependent cAMP dynamics (Chay et al. 2016)
We use a combination of live cell imaging and stochastic modeling of signaling pathways to investigate how noradrenergic receptor stimulation interacts with calcium to control cAMP, required for synaptic plasticity and memory in the hippocampus. Our simulation results explain the mechanism whereby prior noradrenergic receptor stimulation does not enhance the subsequent NMDA stimulated cAMP elevation. Specifically, our results demonstrate the the negative feedback loop from cAMP, through PKA, to PDE4 cannot explain the results, and that switching of the noradrenergic receptor from Gs to Gi is required.
6.  Compartmental models of growing neurites (Graham and van Ooyen 2004)
Simulator for models of neurite outgrowth. The principle model is a biophysical model of neurite outgrowth described in Graham and van Ooyen (2004). In the model, branching depends on the concentration of a branch-determining substance in each terminal segment. The substance is produced in the cell body and is transported by active transport and diffusion to the terminals. The model reveals that transport-limited effects may give rise to the same modulation of branching as indicated by the stochastic BESTL model. Different limitations arise if transport is dominated by active transport or by diffusion.
7.  Kv4.3, Kv1.4 encoded K channel in heart cells & tachy. (Winslow et al 1999, Greenstein et al 2000)
(1999) We present a model of the canine midmyocardial ventricular action potential and Ca2+ transient. The model is used to estimate the degree of functional upregulation and downregulation of Na/Ca exchanger protein and sarcoplasmic reticulum Ca ATPase in heart failure using data obtained from 2 different experimental protocols. (2000): A model of canine I:(to1) (the Ca(2+)-independent transient outward current) is formulated as the combination of Kv4.3 and Kv1.4 currents and is incorporated into an existing canine ventricular myocyte model. Simulations demonstrate strong coupling between L-type Ca(2+) current and I:(Kv4.3) and predict a bimodal relationship between I:(Kv4.3) density and APD whereby perturbations in I:(Kv4.3) density may produce either prolongation or shortening of APD, depending on baseline I:(to1) current level. See each paper for more and details.
8.  Morphological determinants of dendritic arborization neurons in Drosophila larva (Nanda et al 2018)
"Pairing in vivo imaging and computational modeling of dendritic arborization (da) neurons from the fruit fly larva provides a unique window into neuronal growth and underlying molecular processes. We image, reconstruct, and analyze the morphology of wild-type, RNAi-silenced, and mutant da neurons. We then use local and global rule-based stochastic simulations to generate artificial arbors, and identify the parameters that statistically best approximate the real data. We observe structural homeostasis in all da classes, where an increase in size of one dendritic stem is compensated by a reduction in the other stems of the same neuron. Local rule models show that bifurcation probability is determined by branch order, while branch length depends on path distance from the soma. Global rule simulations suggest that most complex morphologies tend to be constrained by resource optimization, while simpler neuron classes privilege path distance conservation. Genetic manipulations affect both the local and global optimal parameters, demonstrating functional perturbations in growth mechanisms."
9.  Roles of essential kinases in induction of late hippocampal LTP (Smolen et al., 2006)
"… Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. …"

Re-display model names without descriptions