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Wulfram Gerstner

Cette personne a quitté l’EPFL

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Publications associées (124)

Page 5 sur 7

Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making

Michael Herzog, Wulfram Gerstner, Alireza Modirshanechi, He Xu, Marco Philipp Lehmann

Classic reinforcement learning (RL) theories cannot explain human behavior in the absence of external reward or when the environment changes. Here, we employ a deep sequential decision-making paradigm with sparse reward and abrupt environmental changes. To ...

2021

A Computational Framework for Memory Engrams

Wulfram Gerstner, Chiara Gastaldi

Memory engrams in mice brains are potentially related to groups of concept cells in human brains. A single concept cell in human hippocampus responds, for example, not only to different images of the same object or person but also to its name written down ...

Springer Cham2024

Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements

Wulfram Gerstner, Guillaume Hennequin, Tim Vogels

Populations of neurons in motor cortex engage in complex transient dynamics of large amplitude during the execution of limb movements. Traditional network models with stochastically assigned synapses cannot reproduce this behavior. Here we introduce a clas ...

Cell Press2014

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

Quantitative single-neuron modeling: competition 2008

Wulfram Gerstner, Richard Naud, Laurent Badel

How well are single-cell properties reproduced by the present-day neuronal models? Recently, several labs have approached this question by assessing the quality of the models with respect to spike timing prediction or characteristic features of the voltage ...

2008

A functional model of adult dentate gyrus neurogenesis

Wulfram Gerstner, Olivia Gozel

In adult dentate gyrus neurogenesis, the link between maturation of newborn neurons and their function, such as behavioral pattern separation, has remained puzzling. By analyzing a theoretical model, we show that the switch from excitation to inhibition of ...

2021

A benchmark test for a quantitative assessment of simple neuron models

Wulfram Gerstner, Richard Naud, Renaud Jolivet

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activi ...

Elsevier2008

A computational model of parallel navigation systems in rodents

Wulfram Gerstner, Ricardo Andres Chavarriaga Lozano, Thomas Strösslin

Several studies in rats support the idea of multiple neural systems competing to select the best action for reaching a goal or food location. Locale navigation strategies, necessary for reaching invisible goals, seem to be mediated by the hippocampus and t ...

Humana Press2005

Kernel Memory Networks: A Unifying Framework for Memory Modeling

Wulfram Gerstner, Johanni Michael Brea, Georgios Iatropoulos

We consider the problem of training a neural network to store a set of patterns with maximal noise robustness. A solution, in terms of optimal weights and state update rules, is derived by training each individual neuron to perform either kernel classifica ...

Curran Associates2022

Optimality Model of Unsupervised Spike-Timing Dependent Plasticity: Synaptic Memory and Weight Distribution

Wulfram Gerstner, Jean-Pascal Théodor Pfister

We studied the hypothesis that synaptic dynamics is controlled by three basic principles: (1) synapses adapt their weights so that neurons can effectively transmit information, (2) homeostatic processes stabilize the mean firing rate of the postsynaptic ne ...

Massachusetts Institute of Technology Press2007

Curiosity-driven exploration: foundations in neuroscience and computational modeling

Wulfram Gerstner, Alireza Modirshanechi

Curiosity refers to the intrinsic desire of humans and animals to explore the unknown, even when there is no apparent reason to do so. Thus far, no single, widely accepted definition or framework for curiosity has emerged, but there is growing consensus th ...

Cell Press2023

Consciousness & the Small Network Argument

Michael Herzog, Wulfram Gerstner

The last decade has experienced a vivid enthusiasm to unravel the mystery of consciousness believed to be one of the major puzzles of humankind. We share this enthusiasm. Still,we feel that current models are incomplete suffering from a problem that we cal ...

Elsevier2007

A Model of Synaptic Reconsolidation

Wulfram Gerstner, Tilo Schwalger, Lorric Ziegler

Reconsolidation of memories has mostly been studied at the behavioral and molecular level. Here, we put forward a simple extension of existing computational models of synaptic consolidation to capture hippocampal slice experiments that have been interprete ...

Frontiers Research Foundation2016

A biologically plausible 3-factor learning rule for expectation maximization in reinforcement learning and decision making

Wulfram Gerstner, Mohammadjavad Faraji, Kerstin Preuschoff

2015

Fast adaptation to rule switching using neuronal surprise

Wulfram Gerstner, Martin Louis Lucien Rémy Barry

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

2024

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

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

Wulfram Gerstner, 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

Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model

Wulfram Gerstner, Jean-Pascal Théodor Pfister

We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a spike-timing dependent plasticity (STDP) function which depends on the time co ...

MIT Press2005

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

Approximating Relu Networks By Single-Spike Computation

Wulfram Gerstner, Stanislaw Andrzej Wozniak, Angeliki Pantazi, Ana Stanojevic

Developing energy-saving neural network models is a topic of rapidly increasing interest in the artificial intelligence community. Spiking neural networks (SNNs) are biologically inspired models that strive to leverage the energy efficiency stemming from a ...

IEEE2022