Concept

Règle de Hebb

Publications associées (104)

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Mathematical Formulations of Hebbian Learning

Wulfram Gerstner

Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival. The state of the postsynaptic neuron can be described by its membrane potential ...

Springer Verlag2002

Coding of temporal information by activity-dependent synapses

Henry Markram, Idan Segev

Synaptic transmission in the neocortex is dynamic, such that the magnitude of the postsynaptic response changes with the history of the presynaptic activity. Therefore each response carries information about the temporal structure of the preceding presynap ...

2002

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

Wulfram Gerstner

We study analytically a model of long-term synaptic plasticity where synaptic changes are triggered by presynaptic spikes, postsynaptic spikes, and the time differences between pre- and postsynaptic spikes. We show that plasticity can lead to an intrinsic ...

Massachusetts Institute of Technology Press2001

An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing

Henry Markram

The precise times of occurrence of individual pre- and postsynaptic action potentials are known to play a key role in the modification of synaptic efficacy. Based on stimulation protocols of two synaptically connected neurons, we infer an algorithm that re ...

2001

Coding properties of spiking neurons: reverse- and cross-correlations

Wulfram Gerstner

What is the meaning' of a single spike? Spike-triggered averaging (reverse correlations') yields the typical input just before a spike. Similarly, cross-correlations describe the probability of firing an output spike given (one additional) presynaptic in ...

Elsevier2001

Hebbian learning and spiking neurons

Wulfram Gerstner

A correlation-based (

Hebbian'') learning rule at the spike level is formulated, mathematically analyzed, and compared with learning in a firing-rate description. As for spike coding, we take advantage of a

learning window'' that describes the effect of ...

1999

Anatomical and functional differentiation of glutamatergic synaptic innervation in the neocortex

Henry Markram

Pyramidal neurons are the principal neurons of the neocortex and their excitatory impact on other pyramidal neurons and interneurons is central to neocortical dynamics. A fundamental principal that has emerged which governs pyramidal neuron excitation of o ...

1999

Information processing with frequency-dependent synaptic connections

Henry Markram, Yi Wang

The efficacy of synaptic transmission between two neurons changes as a function of the history of previous activations of the synaptic connection. This history dependence can be characterized by examining the dependence of transmission on the frequency of ...

1998

All-or-none potentiation at CA3-CA1 synapses

Carl Petersen

The molecular mechanisms underlying long-term potentiation in the hippocampus have received much attention because of the likely functional importance of synaptic plasticity for information storage and the development of neuronal connectivity. Surprisingly ...

1998

Signal recognition by synchronization of chaotic systems

Martin Hasler

It is shown that the synchronization of two coupled tent maps can be used for a practical signal classification task. Hebbian learning is used to set the coupling coefficients for correct classification. For the problem with real data considered, it is sur ...

1997