1 - 9 of 9 results


Allows quantitative comparison of biological microscopy methods, quantitative analysis of partially coherent images, and design of phase-retrieval approaches. microlith permits the flexibility of simulating 3D images of a thin specimen under any scalar partially coherent system. It permits users to make simulation of spatially coherent imaging or incoherent imaging as special cases. This tool can be reused to compute effective 3D refractive index distribution from the properties of a thick object and partially coherent illumination.


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.

ANNarchy / Artificial Neural Networks architect

Provides a high-level interface in Python similar to PyNN to facilitate the creation of rate-coded, spike-coded or hybrid neural networks. ANNarchy is a neural simulator designed for distributed rate-coded or spiking neural networks. It brings the flexibility of the Brian interface to rate coded networks, while being compatible with state-of-the-art spiking simulators. It also proposes a default configuration which can be overwritten by the user.

GENESIS / GEneral NEural SImulation System

A general purpose simulation platform that was developed to support the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, simulations of large networks, and systems-level models. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface.


A simulation framework for the developmental generation of 3D large-scale neuronal networks with realistic neuron morphologies. In NETMORPH, neuronal morphogenesis is simulated from the perspective of the individual growth cone. For each growth cone in a growing axonal or dendritic tree, its actions of elongation, branching and turning are described in a stochastic, phenomenological manner. In this way, neurons with realistic axonal and dendritic morphologies, including neurite curvature, can be generated. Synapses are formed as neurons grow out and axonal and dendritic branches come in close proximity of each other. NETMORPH is a flexible tool that can be applied to a wide variety of research questions regarding morphology and connectivity.


A software package for the generation and study of anatomically accurate neuronal analogs. L-Neuron is based on sets of recursive rules that parsimoniously describe dendritic geometry and topology by locally inter-correlating morphological parameters (e.g. branch diameter and length). The L-Neuron algorithm stochastically samples parameter values from experimental statistical distributions, to generate multiple, non-identical virtual neurons within various morphological classes.