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Pierre Yger

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. To make predictions or models of in vivo data, one need large-scale simulations of spiking neuronal network mimicking the emerging properties at the network level. Neurons are modifying the synapses between them as a function of their joint activities. Understanding the molecular processes and the computational consequences of such plasticity is crucial to unravel how the brain can adapt. Spike sorting in real time.

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Pierre Yger | yger.net Reviews
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Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. To make predictions or models of in vivo data, one need large-scale simulations of spiking neuronal network mimicking the emerging properties at the network level. Neurons are modifying the synapses between them as a function of their joint activities. Understanding the molecular processes and the computational consequences of such plasticity is crucial to unravel how the brain can adapt. Spike sorting in real time.
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1 pierre yger
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4 key principles
5 spontaneous activity
6 the balanced network
7 realistic networks
8 cortical plasticity
9 types of plasticity
10 software
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Pierre Yger | yger.net Reviews

https://yger.net

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. To make predictions or models of in vivo data, one need large-scale simulations of spiking neuronal network mimicking the emerging properties at the network level. Neurons are modifying the synapses between them as a function of their joint activities. Understanding the molecular processes and the computational consequences of such plasticity is crucial to unravel how the brain can adapt. Spike sorting in real time.

INTERNAL PAGES

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Pierre Yger » PyNN

http://www.yger.net/pynn

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. Get a better browser!

2

Pierre Yger » Brian

http://www.yger.net/brian

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. Get a better browser!

3

Pierre Yger » Spontaneous activity

http://www.yger.net/spontaneous-activity

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. Rhythm, with frequencies around 8-12 Hz, can be seen as an awake resting state, when eyes are closed. Rhythm (10-30 Hz) is a kind of normal working state. Oscillations, at more than 30 Hz appear during cross-modal tasks, active and intense concentration and memory tasks (in addition to slow oscillations observed in the EEG signal, such as. Origin of Spontaneous activity. Brain slices [ Timofeev2000. One can see the spi...

4

Pierre Yger » Spike Timing Dependent Plasticity

http://www.yger.net/spike-timing

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. Spike Timing Dependent Plasticity. Spike Timing Dependent Plasticity. The best experimental setup for exploring plasticity in a controlled manner is the. In neocortex that the efficiency of a synaptic connection between two neurons may be regulated by the precise timing of the joint activity of the neurons. This postulate. Originally made by [ Hebb1949. Has been demonstrated in a lot of. For positive values of. The imp...

5

Pierre Yger » Software

http://www.yger.net/software

Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. Here are some of the tools that I used/developped in order to simulate large-scale neuronal networks of spiking neurons, or extract spikes from real recordings.

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computational-neuroscience-of-sensory-systems.org computational-neuroscience-of-sensory-systems.org

Pierre Yger – Computational Neuroscience of Sensory Systems

http://www.computational-neuroscience-of-sensory-systems.org/people/pierre-yger

Computational Neuroscience of Sensory Systems. Institut de la Vision. Webpage: http:/ www.yger.net. Email: pierre.yger[at]inserm.fr. Bellec, G, Galtier, M, Brette, R, Yger, P. 2016 Slow feature analysis with spiking neurons and its application to audio stimuli. Yger, P, Gilson, M. 2016 Erratum: Addendum: Models of Metaplasticity: A Review of Concepts. Yger, P, Gilson, M. 2015 Models of Metaplasticity: A Review of Concepts. Yger, P, Stimberg, M, Brette, R. 2015 Fast Learning with Weak Synaptic Plasticity.

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Dr Michel Tsamados | Links

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How does the brain works?

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Computational neuroscience and cortical plasticity. Spike Timing Dependent Plasticity. To make predictions or models of in vivo data, one need large-scale simulations of spiking neuronal network mimicking the emerging properties at the network level. Neurons are modifying the synapses between them as a function of their joint activities. Understanding the molecular processes and the computational consequences of such plasticity is crucial to unravel how the brain can adapt. Spike sorting in real time.

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