Publications de Taro Toyoizumi

Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions

Wulfram Gerstner, Lu Chen, Taro Toyoizumi

We summarize here the results presented and subsequent discussion from the meeting on Integrating Hebbian and Homeostatic Plasticity at the Royal Society in April 2016. We first outline the major themes and results presented at the meeting. We next provide ...

Royal Soc2017

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

Wulfram Gerstner, Jean-Pascal Théodor Pfister, Taro Toyoizumi

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

Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing in Supervised Learning

Wulfram Gerstner, Jean-Pascal Théodor Pfister, Taro Toyoizumi

In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimizes by gradient ascent the likelihood of postsynaptic firing at one or severa ...

Massachusetts Institute of Technology Press2006

Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing in Supervised Learing

Wulfram Gerstner, Taro Toyoizumi

In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimizes via gradient ascent the likelihood of postsynaptic firing at one or sever ...

2005

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

Wulfram Gerstner, Jean-Pascal Théodor Pfister, Taro Toyoizumi

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