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Wulfram Gerstner

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Publications associées (129)

Limits to high-speed simulations of spiking neural networks using general-purpose computers

Wulfram Gerstner, Friedemann Zenke

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing att ...

Frontiers Research Foundation2014

Fluctuations and information filtering in coupled populations of spiking neurons with adaptation

Wulfram Gerstner, Richard Naud, Moritz Deger, Tilo Schwalger

Finite-sized populations of spiking elements are fundamental to brain function but also are used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasirenewal description of neurons ...

2014

Connection-type-specific biases make uniform random network models consistent with cortical recordings

Wulfram Gerstner, Carl Petersen, Michael Avermann, Christian Tomm, Tim Vogels

Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the implicit hypothesis that they are a good representation of real neuronal networks has been met with skepticism. Here we used two experimental data sets, a stu ...

American Physiological Society2014

Spike-timing prediction in cortical neurons with active dendrites

Wulfram Gerstner, Brice Bathellier, Richard Naud

A complete single-neuron model must correctly reproduce the firing of spikes and bursts. We present a study of a simplified model of deep pyramidal cells of the cortex with active dendrites. We hypothesized that we can model the soma and its apical dendrit ...

Frontiers Research Foundation2014

Temporal whitening by power-law adaptation in neocortical neurons

Wulfram Gerstner, Skander Mensi, Christian Antonio Pozzorini, Richard Naud

Spike-frequency adaptation (SFA) is widespread in the CNS, but its function remains unclear. In neocortical pyramidal neurons, adaptation manifests itself by an increase in the firing threshold and by adaptation currents triggered after each spike. Combini ...

Nature Publishing Group2013

Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector

Wulfram Gerstner, Guillaume Hennequin, Friedemann Zenke

Hebbian changes of excitatory synapses are driven by and further enhance correlations between pre- and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback loop that can lead to instability in simulated neural networks. To keep acti ...

Public Library of Science2013

Inference of neuronal network spike dynamics and topology from calcium imaging data

Wulfram Gerstner, Friedemann Zenke, Joao Emanuel Felipe Gerhard

Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP) occurrence ("spike trains") from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR ...

Frontiers Research Foundation2013

Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo

Wulfram Gerstner

Action Potential (APs) patterns of sensory cortex neurons encode a variety of stimulus features, but how can a neuron change the feature to which it responds? Here, we show that in vivo a spike-timing-dependent plasticity (STDP) protocol-consisting of pair ...

Elife Sciences Publications Ltd2013

Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons

Wulfram Gerstner, Nicolas Frémaux

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic pla ...

Public Library of Science2013

The Silent Period of Evidence Integration in Fast Decision Making

Wulfram Gerstner, Michael Herzog, Johannes Rüter

In a typical experiment on decision making, one out of two possible stimuli is displayed and observers decide which one was presented. Recently, Stanford and colleagues (2010) introduced a new variant of this classical one-stimulus presentation paradigm to ...

Public Library of Science2013

Paradoxical Evidence Integration in Rapid Decision Processes

Wulfram Gerstner, Nicolas Marcille, Michael Herzog, Johannes Rüter

Decisions about noisy stimuli require evidence integration over time. Traditionally, evidence integration and decision making are described as a one-stage process: a decision is made when evidence for the presence of a stimulus crosses a threshold. Here, w ...

Public Library of Science2012

Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms

Wulfram Gerstner, Skander Mensi, Carl Petersen, Christian Antonio Pozzorini, Michael Avermann, Richard Naud

Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CCH, Gerstner W. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. J Neurophysiol 107: 1756-1775, 2012. First published December 7, 2011; do ...

American Physiological Society2012

Non-normal amplification in random balanced neuronal networks

Wulfram Gerstner, Guillaume Hennequin, Tim Vogels

In dynamical models of cortical networks, the recurrent connectivity can amplify the input given to the network in two distinct ways. One is induced by the presence of near-critical eigenvalues in the connectivity matrix W, producing large but slow activit ...

2012

Perceptual learning, roving and the unsupervised bias

Wulfram Gerstner, Nicolas Frémaux, Michael Herzog, Carl Kristoffer Aberg

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervise ...

Elsevier2012

Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram

Wulfram Gerstner, Richard Naud

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for ...

Public Library of Science2012

Theory and Simulation in Neuroscience

Wulfram Gerstner

Modeling work in neuroscience can be classified using two different criteria. The first one is the complexity of the model, ranging from simplified conceptual models that are amenable to mathematical analysis to detailed models that require simulations in ...

American Association for the Advancement of Science2012

Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex

Wulfram Gerstner, Carl Petersen, Céline Matéo, Michael Avermann, Christian Tomm

Avermann M, Tomm C, Mateo C, Gerstner W, Petersen CC. Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex. J Neurophysiol 107: 3116-3134, 2012. First published March 7, 2012; doi:10.1152/jn.00917.2011.-Synaptic interactio ...

American Physiological Society2012

Spike-timing-dependent plasticity: a comprehensive overview

Wulfram Gerstner, Henry Markram

2012

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

Variational Learning for Recurrent Spiking Networks

Wulfram Gerstner, Danilo Jimenez Rezende, Daniël Pieter Wierstra

We derive a plausible learning rule updating the synaptic efficacies for feedforward, feedback and lateral connections between observed and latent neurons. Operating in the context of a generative model for distributions of spike sequences, the learning me ...

2011

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