The use of a population dynamics approach promises efficient simulation of large assemblages of neurons. Depending on the issues addressed and the degree of realism incorporated in the simulated neurons, a wide range of different population dynamics formulations can be appropriate. Here we present a common mathematical structure that these various formulations share and that implies dynamical behaviors that they have in common. This underlying structure serves as a guide toward efficient means of simulation. As an example, we derive the general population firing-rate frequency-response and show how it may be used effectively to address a broad range of interacting-population response and stability problems. A few specific cases will be work...
This thesis presents numerical methods and modeling related to simulating neurons. Two approaches to...
How does reliable computation emerge from networks of noisy neurons? While individual neurons are in...
A: Gain curve for quadratic-integrate-and-fire neurons. Population density techniques handle deviati...
Population density techniques can be used to simulate the behavior of a population of neurons which ...
International audienceNeurons within a population are strongly correlated, but how to simply capture...
ABSTRACT A simple encoder model, which is a reasonable idealization from known electrophysiological ...
Population density methods provide promising time-saving alternatives to direct Monte Carlo simulati...
Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable underst...
Population density methods provide promising time-saving alternatives to direct Monte Carlo simulati...
We present a new technique, based on a proposed event-based strategy (Mattia & Del Giudice, 2000...
We review a statistical physics approach for reduced descriptions of neuronal network dynamics. From...
A dynamical equation is derived for the spike emission rate nu(t) of a homogeneous network of integr...
The brain is arguably the most complex system known to man. Under the eyes of a physicist, brains sh...
The motivation for this thesis is to devise a simple model of transient dynamics in neural networks....
We propose a macroscopic approach towards realistic simulations of population activity of cortical n...
This thesis presents numerical methods and modeling related to simulating neurons. Two approaches to...
How does reliable computation emerge from networks of noisy neurons? While individual neurons are in...
A: Gain curve for quadratic-integrate-and-fire neurons. Population density techniques handle deviati...
Population density techniques can be used to simulate the behavior of a population of neurons which ...
International audienceNeurons within a population are strongly correlated, but how to simply capture...
ABSTRACT A simple encoder model, which is a reasonable idealization from known electrophysiological ...
Population density methods provide promising time-saving alternatives to direct Monte Carlo simulati...
Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable underst...
Population density methods provide promising time-saving alternatives to direct Monte Carlo simulati...
We present a new technique, based on a proposed event-based strategy (Mattia & Del Giudice, 2000...
We review a statistical physics approach for reduced descriptions of neuronal network dynamics. From...
A dynamical equation is derived for the spike emission rate nu(t) of a homogeneous network of integr...
The brain is arguably the most complex system known to man. Under the eyes of a physicist, brains sh...
The motivation for this thesis is to devise a simple model of transient dynamics in neural networks....
We propose a macroscopic approach towards realistic simulations of population activity of cortical n...
This thesis presents numerical methods and modeling related to simulating neurons. Two approaches to...
How does reliable computation emerge from networks of noisy neurons? While individual neurons are in...
A: Gain curve for quadratic-integrate-and-fire neurons. Population density techniques handle deviati...