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Wulfram Gerstner

Cette personne a quitté l’EPFL

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Publications associées (124)

Page 2 sur 7

Surprise and novelty in the brain

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Sophia Becker

Notions of surprise and novelty have been used in various experimental and theoretical studies across multiple brain areas and species. However, 'surprise' and 'novelty' refer to different quantities in different studies, which raises concerns about whethe ...

CURRENT BIOLOGY LTD2023

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

Wulfram Gerstner, Skander Mensi, Christian Antonio Pozzorini, Olivier Richard Hagens

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong i ...

Public Library of Science2016

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

Wulfram Gerstner, Ricardo Andres Chavarriaga Lozano, Thomas Strösslin

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

Maria del Carmen Sandi Perez, Wulfram Gerstner, 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

Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive

Wulfram Gerstner, Laurent Badel

A path-integral approach is developed for the analysis of spike-triggered-average quantities in neurons with voltage-gated subthreshold currents. Using a linearization procedure to reduce the models to the generalized integrate-and-fire form, analytical ex ...

2008

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

Wulfram Gerstner, Tilo Schwalger, Richard Naud, Moritz Deger

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

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

Wulfram Gerstner, Richard Naud, Nicolas Marcille

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

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

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

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

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

When shared concept cells support associations: Theory of overlapping memory engrams

Wulfram Gerstner, Tilo Schwalger, Emanuela De Falco, Chiara Gastaldi

Assemblies of neurons, called concepts cells, encode acquired concepts in human Medial Temporal Lobe. Those concept cells that are shared between two assemblies have been hypothesized to encode associations between concepts. Here we test this hypothesis in ...

2021

Perceptual learning, roving and the unsupervised bias

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

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

Complexity and performance in simple neuron models

Wulfram Gerstner, Richard Naud, Skander Mensi

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

From spiking neurons to rate models: a cascade model as an approximation to spiking neuron models with refractoriness

Wulfram Gerstner

A neuron that is stimulated repeatedly by the same time-dependent stimulus exhibits slightly different spike timing at each trial. We compared the exact solution of the time-dependent firing rate for a stochastically spiking neuron model with refractorines ...

2006

Subthreshold cross-correlations between cortical neurons: A reference model with static synapses

Wulfram Gerstner, Henry Markram, Gilad Silberberg

The structure of cross-correlations between subthreshold potentials of neocortical neurons was recently examined. Characteristic features included broad widths and significant peak advances. It was suggested that dynamic synapses shape these cross-correlat ...

Elsevier2005

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

Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response

Wulfram Gerstner, Carl Petersen, Sylvain Crochet, Alireza Modirshanechi, Vahid Esmaeili, Samuel Pavio Muscinelli, Georgios Foustoukos, Keita Tamura, Yanqi Liu, Anastasiia Oryshchuk

The neuronal mechanisms generating a delayed motor response initiated by a sensory cue remain elusive. Here, we tracked the precise sequence of cortical activity in mice transforming a brief whisker stimulus into delayed licking using wide-field calcium im ...

2021

The quantitative single-neuron modeling competition

Wulfram Gerstner, Felix Schürmann, Richard Naud, Renaud Jolivet

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

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

Effects of stress and genotype on meta-parameter dynamics in reinforcement learning

Wulfram Gerstner, Maria del Carmen Sandi Perez, Gediminas Luksys, Jérémie Knüsel

Stress and genetic background regulate different aspects of behavioral learning through the action of stress hormones and neuromodulators. In reinforcement learning (RL) models, meta-parameters such as learning rate, future reward discount factor, and expl ...

2007

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021