An efficient simulation environment for modeling large-scale cortical processing

Frontiers in Neuroinformatics

Nikil eDutt¹  Jeffrey L Krichmar¹  Micah eRichert¹  Jayram Moorkanikara Nageswaran¹ 

[1] University of California, Irvine;

关键词: Software;    Visual Cortex;    short-term plasticity;    simulation;    STDP;    spiking neurons;   

DOI  :  10.3389/fninf.2011.00019

来源: DOAJ

【 摘 要 】

We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models.The simulator implements current or conductance based Izhikevich neuron networks, having Spike-Timing Dependent Plasticity (STDP) and Short-Term Plasticity (STP). It uses a standard network construction interface. The simulator allows for execution on either GPUs or CPUs.The simulator, which is written in C/C++, allows for both fine grain and coarse grain specificity of a host of parameters.We demonstrate the ease of use and computational efficiency of this model by implementing a large-scale model of cortical areas V1, V4 and area MT.The complete model, which has 138,240 neurons and approximately 30 million synapses, runs in real-time on an off-the-shelf GPU. The simulator source code, as well as the source code for the cortical model examples is publicly available.

【 授权许可】

Unknown