The electrical properties of single neurons can be acurately modeled using multicompartmental modeling. Such models are biologically motivated and have a close correspondence with the underlying biophysical properties of neurons and their ion channels. These multicompartment models are also important as building blocks for detailed network models.
Assists users for simulating and developing compartmental models of neurons. Nodus includes a user interface that resembles to biological experiments instead of emphasizing the mathematical aspects. It integrates several required steps in modeling: neuron model conception, model input, translation of the model into simulation parameters, control over experiments, iterating integration of the simulation and graphic output.
Supplies simulation and analysis tools. PyDSTool provides high-level compositional model-building tools involving symbolic expressions and modular component templates for improving users construct large models. Besides, the software supports simulations of ordinary differential equations (ODEs), differential-algebraic equations (DAEs), and discrete mappings and allows users to specify dynamics using evolution equations or explicit functions of time or state.
Facilitates the creation, visualization, and analysis of networks of multicompartmental neurons in 3D space. neuroConstruct provides a graphical user interface (GUI) which allows model generation and modification without programming. Models within neuroConstruct are based on new simulator-independent NeuroML standards, allowing automatic generation of code for NEURON or GENESIS simulators. neuroConstruct was tested by reproducing published models and its simulator independence verified by comparing the same model on two simulators. neuroConstruct can be used for teaching network function in health and disease. The 3D models generated will allow simulations of increased biological realism, enabling more direct comparisons with results from new experimental methods for measuring neural activity in 3D at high spatial and temporal resolution.
Enables generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. PSICS computes the behavior of neurons taking account of the stochastic nature of ion channel gating and the detailed positions of the channels themselves. Moreover, this tool supports representation of ion channels as kinetic schemes involving one or more serial gating complexes.
Enables users to visualize the effect of different hyper-parameters on different Growth Transform (GT) neuron dynamics. GTN model also allows researchers to focus on different population dynamics produced by a network of coupled GT neurons.
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