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NineML: the network interchange for neuroscience modeling language

Publications associées (50)

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Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem

Joao Emanuel Felipe Gerhard

Statistical models of neural activity are at the core of the field of modern computational neuroscience. The activity of single neurons has been modeled to successfully explain dependencies of neural dynamics to its own spiking history, to external stimuli ...

2010

Statistical tests for neural population models - The multivariate time rescaling theorem

Joao Emanuel Felipe Gerhard

The coordinated, collective spiking activity of neuronal populations encodes and processes information. One approach towards understanding such population based computation is to fit statistical models to simultaneously recorded spike trains and use these ...

2010

Interpretation of neuronal response properties with simplified neuron models

Laurent Badel

Computational neuroscience is a branch of the neurosciences that attempts to elucidate the principles underlying the operation of neurons with the help of mathematical modeling. In contrast with a number of fields pursuing a tightly related goal, such as m ...

EPFL2009

In computational neuroscience, it is of crucial importance to dispose of a model that is able to accurately describe the single-neuron activity. This model should be at the same time biologically relevant and computationally fast. Many different phenomenol ...

2009

The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engine ...

Frontiers Research Foundation2009

Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System

Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the ...

Frontiers Research Foundation2009

PyNN: a common interface for neuronal network simulators

Eilif Benjamin Muller

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to con ...

Frontiers Research Foundation2008

Predicting activity of single neuron is an important part of the computational neuroscience and a great challenge. Several mathematical models exist, from the simple (one compartment and few parameters, like the SRM or the IF-type models), to the more comp ...

2008

Synchronization in dynamical networks

Mahdi Jalili

Complex dynamical networks are ubiquitous in many fields of science from engineering to biology, physics, and sociology. Collective behavior, and in particular synchronization,) is one of the most interesting consequences of interaction of dynamical system ...

EPFL2008

The response of cortical neurons to in vivo-like input current: theory and experiment

Michele Giugliano, Walter Senn

The study of several aspects of the collective dynamics of interacting neurons can be highly simplified if one assumes that the statistics of the synaptic input is the same for a large population of similarly behaving neurons (mean field approach). In part ...

2008