Publications by Claudia Clopath

Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks

Wulfram Gerstner, Claudia Clopath, Friedemann Zenke, Tim Vogels

Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance could be established and maintained in an experience-dependent manner by synaptic plasticity at inhibitory synapses. We show that this mechanism provides an expla ...

American Association for the Advancement of Science2011

A triplet spike-timing-dependent plasticity model generalizes the Bienenstock-Cooper-Munro rule to higher-order spatiotemporal correlations

Jean-Pascal Théodor Pfister, Claudia Clopath, Juliette Audet

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock-Cooper-Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsyn ...

National Academy of Sciences2011

Voltage and spike timing interact in STDP – a unified model

Wulfram Gerstner, Claudia Clopath

2010

Synaptic plasticity across different time scales and its functional implications

Claudia Clopath

Humans and animals learn by modifying the synaptic strength between neurons, a phenomenon known as synaptic plasticity. These changes can be induced by rather short stimuli (lasting, for instance, only a few seconds), yet, in order to be useful for long-te ...

EPFL2009

An online Hebbian learning rule that performs Independent Component Analysis

Wulfram Gerstner, Claudia Clopath, André Longtin

Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but only higher moments of its amplitude distribution. Moreover, they require some ...

MIT Press2008

Firing patterns in the adaptive exponential integrate-and-fire model

Wulfram Gerstner, Claudia Clopath, Nicolas Marcille, Richard Naud

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show th ...

Springer Verlag2008

Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments

Wulfram Gerstner, Claudia Clopath, Renaud Jolivet

An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protocol has been developed to extract the parameters of the aEIF model using an op ...

Elsevier2007