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Transient information flow in a network of excitatory and inhibitory model neurons: role of noise and signal autocorrelation

Related publications (32)

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Dynamic noise modeling at roundabouts

Modeling spatial and temporal noise variations at roundabouts is a tedious task. Indeed, noise levels are strongly influenced by the complex vehicle interactions taking place at the entries. An accurate modeling of the merging process and its impact on veh ...

Elsevier2009

Code-specific policy gradient rules for spiking neurons

Wulfram Gerstner, Guillaume Hennequin

Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning r ...

Massachusetts Institute of Technology Press2009

The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro

Michele Giugliano

Cortical neurons are often classified by current-frequency relationship. Such a static description is inadequate to interpret neuronal responses to time-varying stimuli. Theoretical studies suggested that single-cell dynamical response properties are neces ...

Oxford University Press2008

Noise Modeling in Lateral Nonuniform MOSFET

Christian Enz, Jean-Michel Sallese, Ananda Sankar Roy

In this paper, we present an analytical noise modeling methodology for lateral nonuniform MOSFET. We demonstrate that the noise properties of lateral nonuniform MOSFETs are considerably different from the prediction obtained with the conventional Klaassen- ...

2007

Evolution of Spiking Neural Circuits in Autonomous Mobile Robots

Dario Floreano, Jean-Christophe Zufferey, Claudio Mattiussi

We describe evolution of spiking neural architectures to control navigation of autonomous mobile robots. Experimental results with simple fitness functions indicate that evolution can rapidly generate spiking circuits capable of navigating in textured envi ...

2006

A method for determining neural connectivity and inferring the underlying network dynamics using extracellular spike recordings

Oscar De Feo

In the present paper we propose a novel method for the identification and modeling of neural networks using extracellular spike recordings. We create a deterministic model of the effective network, whose dynamic behavior fits experimental data. The network ...

2005

Coding properties of spiking neurons: reverse- and cross-correlations

Wulfram Gerstner

What is the meaning' of a single spike? Spike-triggered averaging (reverse correlations') yields the typical input just before a spike. Similarly, cross-correlations describe the probability of firing an output spike given (one additional) presynaptic in ...

Elsevier2001

Population dynamics of spiking neurons: fast transients, asynchronous states and locking

Wulfram Gerstner

An integral equation describing the time evolution of the population activity in a homogeneous pool of spiking neurons of the integrate-and-fire type is discussed. It is analytically shown that transients from a state of incoherent firing can be immediate. ...

Massachusetts Institute of Technology Press2000

Noise-shaping in populations of coupled model neurons

Wulfram Gerstner

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the s ...

1999

Analogue VLSI building blocks for an electronic auditory pathway

This thesis gives an overview of my work over the last four years on the development of analogue electronic building blocks for the auditory pathway, and their application to some models of processing in the auditory brainstem. The anatomy and physiology o ...

EPFL1998