The Brian simulator is a simulator for spiking neural networks, written in Python, that focuses on ease-of-use and flexibility (​ It allows to write new neuronal and synaptic models by writing down their high-level mathematical description (using physical units), without having to fiddle around with any low-level code. Behind the scenes, Brian will use a code generation framework to generate and compile executable code. We built the current development version of Brian (Brian 2) with the goal that the code generation framework is fully extensible, so users should be able to adapt it to their specific target device with reasonable effort. Let's have a first meeting where I'll give an overview over Brian 2 -- depending on the interests of the participants we could then either discuss how to simulate your favourite model with Brian or have a more detailed look at the code generation and how to extend it for specific use cases (in which case this would rather transform into a workgroup, I guess).

Here's a paper where we describe some of the reasoning behind Brian2's string-based syntax:

Not directly Brian-related, but since most of you are probably interested in neuronal modeling in general, here are two papers that basically argue that simple integrate-and-fire models may be better models of the spiking activity of real neurons than more complex models (e.g. adaptive exponential, single compartment Hodgkin-Huxley, etc.):

Last modified 4 years ago Last modified on 05/06/15 18:14:04

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