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How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

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Publications associées à How single neuron properties shape chaotic dynamics and signal transmission in random neural networks | EPFL Graph Search

Modeling and classification of approximately periodic signals using chaotic systems

Martin Hasler, Oscar De Feo

A new chaos-based technique for modeling the diversity of approximately periodic signals is introduced and exploited, combined with generalized chaotic synchronization phenomena, for the solution of temporal pattern recognition problems ...

2002

Effect of lateral connections on the accuracy of the population code for a network of spiking neurons

Wulfram Gerstner

We study how neuronal connections in a population of spiking neurons affect the accuracy of stimulus estimation. Neurons in our model code for a one-dimensional orientation variable

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2001

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

Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

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The spike timing in rhythmically active interneurons in the mammalian spinal locomotor network varies from cycle to cycle. We tested the contribution from passive membrane properties to this variable firing pattern, by measuring the reliability of spike ti ...

American Physiological Society2001

Synchrony generation in recurrent networks with frequency-dependent synapses

Henry Markram

Throughout the neocortex, groups of neurons have been found to fire synchronously on the time scale of several milliseconds. This near coincident firing of neurons could coordinate the multifaceted information of different features of a stimulus. The mecha ...

2000

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

Effect of noise on neuron transient response

Wulfram Gerstner

A good approximation to the integrate-and-fire model with diffusive noise can be obtained using a noisy threshold model. This allows the response of a population of noisy neurons to a current transient to be described using a linear filter. Here we apply t ...

Elsevier2000

Different synchronization regimes in a system of three coupled 1-d maps

Martin Hasler

The notions of strong and weak synchronization of chaotic systems are reviewed in the context of three coupled identical one-dimensional maps. Two possibilities exist. Either all three systems synchronize (total synchronization), or only two out of three 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

Channel networks

Andrea Rinaldo

This review proceeds from Luna Leopold's and Ronald Shreve's lasting accomplishments dealing with the study of random-walk and topologically random channel networks. According to the random perspective, which has had a profound influence on the interpretat ...

1998

Effect of lateral connections on the accuracy of the population code for a network of spiking neurons

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We study how neuronal connections in a population of spiking neurons affect the accuracy of stimulus estimation. Neurons in our model code for a one-dimensional orientation variable

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. Connectivity between two neurons depends on the absolute differenc ...

2001