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

(The R Project for Statistical Computing)
Re-display model names without descriptions
    Models   Description
1.  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.
2.  Adjusted regularization of cortical covariance (Vinci et al 2018)
Graphical Lasso with Adjusted Regularization (GAR) useful to estimate functional connectivity.
3.  DRG neuron models investigate how ion channel levels regulate firing properties (Zheng et al 2019)
We present computational models for an Abeta-LTMR (low-threshold mechanoreceptor) and a C-LTMR expressing four Na channels and four K channels to investigate how the expression level of Kv1 and Kv4 regulate number of spikes (repetitive firing) and onset latency to action potentials in Abeta-LTMRs and C-LTMRs, respectively.
4.  Paranoia and belief updating during a crisis (Suthaharan et al., 2021)
Perceptual model with three hierarchical layers defined by probability distributions: (1) reward belief, (2) contingency beliefs, (3) volatility beliefs used to investigate the relationship between real-world uncertainty, paranoia, and laboratory task behavior.
5.  Paranoia as a deficit in non-social belief updating (Reed et al 2020)
Model fit to human and rodent data showing effects of paranoia and methamphetamine on behavior and model parameters.
6.  Squid axon (Hodgkin, Huxley 1952) used in (Chen et al 2010) (R language)
"... Previous work showed that magnetic electrical field-induced antinoceptive action is mediated by activation of capsaicin-sensitive sensory afferents. In this study, a modified Hodgkin-Huxley model, in which TRP-like current (I-TRP) was incorporated, was implemented to predict the firing behavior of action potentials (APs), as the model neuron was exposed to sinusoidal changes in externally-applied voltage. ... Our simulation results suggest that modulation of TRP-like channels functionally expressed in small-diameter peripheral sensory neurons should be an important mechanism through which it can contribute to the firing pattern of APs."

Re-display model names without descriptions