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NEURON and Python

Related publications (32)

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NineML: the network interchange for neuroscience modeling language

Sean Lewis Hill, Eilif Benjamin Muller, Michael Lee Hines

The growing number of large-scale neuronal network models has created a need for standards and guidelines to ease model sharing and facilitate the replication of results across different simulators. To foster community efforts towards such standards, the I ...

2011

Engineering Neuron Models

Rajnish Ranjan

The neocortex is one of the most evolved and complex region of the brain. For more than a century scientists have been curious about the neocortex, to identify the anatomical blueprint of its cellular organization and to understand its role in higher brain ...

EPFL2011

Predictive Engineering the Membrane Composition of Neocortical Neurons

Georges Khazen

The brain is the most mysterious and intricate biological structure known to man. It dominates the way we live, think, reason and behave. It is built of billions of neurons that communicate with each other through trillions of connections using electrical ...

EPFL2011

Emergent Properties of in silico Synaptic Transmission in a Model of the Rat Neocortical Column

Srikanth Ramaswamy

The cerebral cortex occupies nearly 80% of the entire volume of the mammalian brain and is thought to subserve higher cognitive functions like memory, attention and sensory perception. The neocortex is the newest part in the evolution of the cerebral corte ...

EPFL2011

The Dynamics of Adapting Neurons

Richard Naud

How do neurons dynamically encode and treat information? Each neuron communicates with its distinctive language made of long silences intermitted by occasional spikes. The spikes are prompted by the pooled effect of a population of pre-synaptic neurons. To ...

EPFL2011

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

Simple Neuron Models and Adaptation

Skander Mensi

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

Fully implicit parallel simulation of single neurons

Henry Markram, Felix Schürmann

When a multi-compartment neuron is divided into subtrees such that no subtree has more than two connection points to other subtrees, the subtrees can be on different processors and the entire system remains amenable to direct Gaussian elimination with only ...

2008

Neuron models of the generic bifurcation type

Minimal nonlinear dynamic neuron models of the generic bifurcation type may provide the middle way between the detailed models favored by experimentalists and the simplified threshold and rate model of computational neuroscientists. This thesis investigate ...

EPFL2006