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Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation

Related publications (33)

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Improved Similarity Measures for Small Sets of Spike Trains

Wulfram Gerstner, Richard Naud, Joao Emanuel Felipe Gerhard, Skander Mensi

Multiple types of measures have been developed to measure the similarity between two spike trains. These were extensively used to classify neuron responses according to stimuli and to validate mathematical models that predict the spike times. Here we analy ...

2010

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

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

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

Predicting spike timing of neocortical pyramidal neurons by simple threshold models

Wulfram Gerstner, Renaud Jolivet

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current—is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 l ...

2006

Multiscale interactions between surface shear stress and velocity in turbulent boundary layers

Fernando Porté Agel

Understanding and quantifying the multiscale interactions between surface shear stress and velocity in the boundary layer is essential to improving boundary condition parameterizations used in numerical models of turbulent boundary layers. In this study, h ...

2003

Spike frequency adaptation and neocortical rhythms

Henry Markram

Spike-frequency adaptation in neocortical pyramidal neurons was examined using the whole cell patch-clamp technique and a phenomenological model of neuronal activity. Noisy current was injected to reproduce the irregular firing typically observed under in ...

2002

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

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

Wulfram Gerstner

We study analytically a model of long-term synaptic plasticity where synaptic changes are triggered by presynaptic spikes, postsynaptic spikes, and the time differences between pre- and postsynaptic spikes. We show that plasticity can lead to an intrinsic ...

Massachusetts Institute of Technology Press2001

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