Models that contain the Modeling Application : Brian (web link to method) (Home Page)

( Brian is a new simulator for spiking neural networks available on almost all platforms. The motivation for this project is that a simulator should not only save the time of processors, but also the time of scientists. Brian is easy to learn and use, highly flexible and easily extensible. The Brian package itself and simulations using it are all written in the Python programming language, which is an easy, concise and highly developed language with many advanced features and development tools, excellent documentation and a large community of users providing support and extension packages.)
Re-display model names with descriptions
1.  A threshold equation for action potential initiation (Platkiewicz & Brette 2010)
2.  Adaptive exponential integrate-and-fire model (Brette & Gerstner 2005)
3.  Fast global oscillations in networks of I&F neurons with low firing rates (Brunel and Hakim 1999)
4.  High entrainment constrains synaptic depression in a globular bushy cell (Rudnicki & Hemmert 2017)
5.  Impact of fast Na channel inact. on AP threshold & synaptic integration (Platkiewicz & Brette 2011)
6.  Late emergence of the whisker direction selectivity map in rat barrel cortex (Kremer et al. 2011)
7.  Phase locking in leaky integrate-and-fire model (Brette 2004)
8.  Reliability of spike timing is a general property of spiking model neurons (Brette & Guigon 2003)
9.  Sensitivity of noisy neurons to coincident inputs (Rossant et al. 2011)
10.  Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999)
11.  Theory of arachnid prey localization (Sturzl et al. 2000)
12.  Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009)
13.  Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011)

Re-display model names with descriptions