spiking neural network

SpikeFun 1.05 - First release of DigiCortex SDK

SpikeFun 1.05 release comes with the first version of DigiCortex SDK. With DigiCortex SDK it is now possible to connect to the running simulation and obtain information about neuron states, inject current into any compartment and get spiking information. Click on the title to read more...

SpikeFun 1.01 – Spontaneous emergence of orientation sensitivity in population of V1 cells with voltage-based Spike Timing Dependent Plasticity (STDP)

DigiCortex Engine can be used to model some of the emergent phenomena of the developing cortex. In this article we show how spontaneous orientation sensitivity of the primary visual cortex (V1) cells develops in presence of natural video signal and voltage-dependent spike-timing dependent plasticity (vSTDP). Click on the title to read more...

DigiCortex 1.0 Released - Visualization with Oculus Rift

Today, DigiCortex engine has reached version 1.0 after almost two and a half years of development. Version 1.0 brings experimental visualization support for Oculus Rift next-generation virtual reality headset. When running in "Oculus" mode, it is now possible to enter the world of the brain simulation! We will add more and more interesting VR visualization concepts in the near future! Click on the title to read more...

DigiCortex 0.97 - Updated Model of Early Visual System

DigiCortex v0.97 adds further improvements to the model of early vision: thalamic (dLGN) processing. Signal coming from the virtual retina is now passed through a pool of neurons in dorsal Lateral Geniculate Nucleus (dLGN) and projected to primary visual cortex (V1). Cortico-thalamic feedback and inhibition through Reticular Thalamic Nucleus (RTN) is also modeled. Click on the article to read more!

DigiCortex 0.96 - Preview of the Retinal Module

DigiCortex v0.96 brings early support for visual input from the outside world. Input from a web camera or a Sony(R) PS3 Eye Cam can be fed to artificial retina processing stage (using Virtual Retina package from INRIA Neuromathcomp research-team) and then to two arrays of simulated retinal ganglion cells ('ON' and 'OFF' layers). Final destination for the retinal signal is primary visual cortex (V1). Click on the article to read more!

insideHPC interview with Ana and Ivan on GTC2013

Ana Balevic and Ivan Dimkovic from DigiCortex.net talk with Rich Brueckner from insideHPC about the DigiCortex project - video of the interview is posted here: http://insidehpc.com/2013/03/26/amazing-digicortex-engine-maps-the-brain... check it out!

NVIDIA GK110 vs. Dual Intel Xeon E5 2687W - Fight!

We tested early version of the SpikeFun v0.95 CUDA compute plug-in against the reference optimized x86 code-path. For the test, two state of the art GPU and CPU solutions were used: NVIDIA GK110 ("Big Kepler") and dual eight-core Intel Xeon E5 2687W. Click on the title to find out who gets the performance crown...

DigiCortex 0.95 - running on CUDA/GPU!

DigiCortex v0.95 brings the early preview of CUDA acceleration. Despite the early stage of the CUDA compute plug-in, simulation performance is more than 7 times faster than optimized multi-threaded CPU code running on a high-end dual 8-core Xeon E5 for large simulations. Click on the title to find out more...

SpikeFun v0.94 - Adaptive Exponential Integrate and Fire (AdEx) Neuron Model

SpikeFun v0.94 brings support for Adaptive Exponential Integrate and Fire (AdEx or Brette-Gerstner) neuron model. AdEx neuron model is qualitatively similar to Izhikevich' neuron model, undergoes the same bifurcations and can reproduce various spiking patterns of cortical neurons. However, AdEx model parameters could be directly related to biophysical quantities and its spike initiation is exponential, not quadratic. DigiCortex Engine can simulate neurons with both models in the same simulation. Click on the title to find out more...

SpikeFun v0.91 - Voltage Based STDP

SpikeFun v0.91 is out and brings support for more advanced long-term plasticity - Voltage-based STDP (based on the model of Clopath et. al). Voltage-based STDP is in agreement with more experimental data than conventional STDP models that consider spike timing only.


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