• Publications
  • Influence
Brian: A Simulator for Spiking Neural Networks in Python
TLDR
A new simulator for spiking neural networks, written in Python, which will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations.
The Brian Simulator
TLDR
“Brian” is a simulator for spiking neural networks that uses vector-based computation to allow for efficient simulations, and is particularly useful for neuroscientific modelling at the systems level, and for teaching computational neuroscience.
Spike sorting for large, dense electrode arrays
TLDR
A set of tools to solve the problem of decoding the spike times of the recorded neurons from the raw data captured from the probes, implemented in a suite of practical, user-friendly, open-source software is presented.
Brian 2: an intuitive and efficient neural simulator
TLDR
“Brian” 2 is a complete rewrite of Brian that addresses this issue by using runtime code generation with a procedural equation-oriented approach, and enables scientists to write code that is particularly simple and concise, closely matching the way they conceptualise their models.
Equation-oriented specification of neural models for simulations
TLDR
This work proposes an alternative approach that allows flexible definition of models by writing textual descriptions based on mathematical notation that allows the definition of a wide range of models with minimal syntax and is implemented in the Brian2 simulator.
High-Dimensional Cluster Analysis with the Masked EM Algorithm
TLDR
This work introduces a “masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions, and demonstrates its applicability to synthetic data and to real-world high-channel-count spike sorting data.
Brian: a simulator for spiking neural networks in Python
TLDR
A new simulator for spiking neural networks, written in Python, which will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations.
Brian 2, an intuitive and efficient neural simulator
TLDR
Brian 2 allows scientists to simply and efficiently simulate spiking neural network models by transforming code with simple and concise high-level descriptions into efficient low-level code that can run interleaved with their code.
Simulating spiking neural networks on GPU
TLDR
This work reviews the ongoing efforts to make parallel simulation of spiking neural networks available to a large audience, without the requirements of a cluster, and outlines the main difficulties.
Graph Drawing by Stochastic Gradient Descent
TLDR
This work presents an algorithm to minimize its energy function, known as stress, by using stochastic gradient descent (SGD) to move a single pair of vertices at a time, and shows how the unique properties of SGD make it easier to produce constrained layouts than previous approaches.
...
...