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Wulfram Gerstner

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Publications associées (129)

Improved Similarity Measures for Small Sets of Spike Trains

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

Multiple measures have been developed to quantify the similarity between two spike trains. These measures have been used for the quantification of the mismatch between neuron models and experiments as well as for the classification of neuronal responses in ...

Massachusetts Institute of Technology Press2011

A history of spike-timing-dependent plasticity

Wulfram Gerstner, Henry Markram

How learning and memory is achieved in the brain is a central question in neuroscience. Key to today’s research into information storage in the brain is the concept of synaptic plasticity, a notion that has been heavily influenced by Hebb’s (1949) postulat ...

2011

Extraction of network topology from multi-electrode recordings: is there a small-world effect?

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estima ...

Frontiers Research Foundation2011

Neural Pre-coding Increases the Pattern Retrieval Capacity of Hopﬁeld and Bidirectional Associative Memories

Wulfram Gerstner, Mohammad Amin Shokrollahi, Amir Hesam Salavati, Krishna Kumar

We consider the problem of neural association, which deals with the retrieval of a previously memorized pattern from its noisy version. The performance of various neural networks developed for this task may be judged in terms of their pattern retrieval cap ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

STDP in adaptive neurons gives close-to-optimal information transmission

Wulfram Gerstner, Jean-Pascal Théodor Pfister, Guillaume Hennequin

Spike-frequency adaptation is known to enhance the transmission of information in sensory spiking neurons by rescaling the dynamic range for input processing, matching it to the temporal statistics of the sensory stimulus. Achieving maximal information tra ...

Frontiers Research Foundation2010

From Hebb rules to Spike-Timing-Dependent Plasticity: a personal account

Wulfram Gerstner

2010

Functional Requirements for Reward-Modulated Spike-Timing-Dependent Plasticity

Wulfram Gerstner, Nicolas Frémaux

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity ...

Society for Neuroscience2010

Voltage and spike timing interact in STDP – a unified model

Wulfram Gerstner, Claudia Clopath

2010

Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

Generalized Linear Models (GLMs) are an increasingly popular framework for modeling neural spike trains. They have been linked to the theory of stochastic point processes and researchers have used this relation to assess goodness-of-fit using methods from ...

Massachusetts Institute of Technology Press2010

Spike-timing dependent plasticity

Wulfram Gerstner

Spike Timing Dependent Plasticity (STDP) is a temporally asymmetric form of Hebbian learning induced by tight temporal correlations between the spikes of pre- and postsynaptic neurons. As with other forms of synaptic plasticity, it is widely believed that ...

2010

Complexity and performance in simple neuron models

Wulfram Gerstner, Skander Mensi, Richard Naud

The ability of simple mathematical models to predict the activity of single neurons is important for computational neuroscience. In neurons, stimulated by a time-dependent current or conductance, we want to predict precisely the timing of spikes and the su ...

2010

Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning

Wulfram Gerstner, Maria del Carmen Sandi Perez, Gediminas Luksys

Suppose we train an animal in a conditioning experiment. Can one predict how a given animal, under given experimental conditions, would perform the task? Since various factors such as stress, motivation, genetic background, and previous errors in task perf ...

Curran Associates, Inc.2009

Spike-timing prediction in a neuron model with active dendrites

Wulfram Gerstner, Brice Bathellier, Richard Naud

A complete model for single neurons must reproduce correctly the firing of spikes and bursts. Yet it must remain simple enough to be tractable in large-scale simulations. We present a study of a simplified model of Layer V pyramidal cells of the cortex wit ...

2009

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

Is there a geometric module for spatial orientation? Insights from a rodent navigation model

Wulfram Gerstner, Angelo Arleo, Thomas Strösslin, Ricardo Andres Chavarriaga Lozano

Modern psychological theories of spatial cognition postulate the existence of a geometric module for reorientation. This concept is derived from experimental data showing that in rectangular arenas with distinct landmarks in the corners, disoriented rats o ...

American Psychological Association2009

Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learning

Wulfram Gerstner, Maria del Carmen Sandi Perez, Gediminas Luksys

Individual behavioral performance during learning is known to be affected by modulatory factors, such as stress and motivation, and by genetic predispositions that influence sensitivity to these factors. Despite numerous studies, no integrative framework i ...

Nature Publishing Group2009

The quantitative single-neuron modeling competition

Wulfram Gerstner, Renaud Jolivet, Thomas Berger, Felix Schürmann, Richard Naud

As large-scale, detailed network modeling projects are flourishing in the field of computational neuroscience, it is more and more important to design single neuron models that not only capture qualitative features of real neurons but are quantitatively ac ...

Springer Verlag2008

Extracting non-linear integrate-and-fire models from experimental data using dynamic I – V curves

Wulfram Gerstner, Laurent Badel, Carl Petersen, Sandrine Lefort, Thomas Berger

The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctua ...

Springer Verlag2008

Phenomenological models of synaptic plasticity based on spike timing

Wulfram Gerstner

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of ...

Springer Verlag2008

Special issue on quantitative neuron modeling

Wulfram Gerstner, Walter Senn, Renaud Jolivet, Felix Schürmann

Springer Verlag2008

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