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.
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.
Serves for diffusion magnetic resonance imaging (MRI) processing. Camino contains several techniques such as probabilistic tractography, deterministic, diffusion tensor fitting or mapping fractional anisotropy. It enables of processing pipelines thanks to its modular design. It implements a data processing pipeline allowing easy scripting and flexible integration with other software.
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.
Provides a Graphic Processing Unit (GPU)-accelerated library for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. CARLsim allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics on both generic x86 CPUs and standard off-the-shelf GPUs. The simulator provides a PyNN-like programming interface in C/C++, which allows for details and parameters to be specified at the synapse, neuron, and network level.
Aims to support neural simulations conceived under python. NeuroTools intends to supply an additional assistance for tasks which are not provided by simulation engines, for instance into the fields of parameterization, instrumentation or visualization. This package is composed of nine modules encompassing several tools to assist users in plotting and image processing as well as in manipulation and calculation using spike trains.
Consists of a web-based visualization and simulation platform to explore complex biological systems. Geppetto assists users to integrate different data and models and supports different standard formats for both experimental and computational data.
Enables a computational model of an animal’s body to be constructed from simple building blocks. AnimatLab allows users to build neural circuit and biomechanical body models in a virtual physical environment. It supplies features to record time-series of any variable while viewing a 3D animation of the simulated behavior. Moreover, simulations and modules can be readily shared between investigators to allow others to examine and extend a simulation.