Learning by the Dendritic Prediction of Somatic Spiking
Data(s) |
2014
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Resumo |
Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms. |
Formato |
application/pdf |
Identificador |
http://boris.unibe.ch/42829/1/Urbanczik2014Neuron_1.pdf Urbanczik, Robert; Senn, Walter (2014). Learning by the Dendritic Prediction of Somatic Spiking. Neuron, 81(3), pp. 521-528. Cell Press 10.1016/j.neuron.2013.11.030 <http://dx.doi.org/10.1016/j.neuron.2013.11.030> doi:10.7892/boris.42829 info:doi:10.1016/j.neuron.2013.11.030 urn:issn:0896-6273 |
Idioma(s) |
eng |
Publicador |
Cell Press |
Relação |
http://boris.unibe.ch/42829/ |
Direitos |
info:eu-repo/semantics/restrictedAccess |
Fonte |
Urbanczik, Robert; Senn, Walter (2014). Learning by the Dendritic Prediction of Somatic Spiking. Neuron, 81(3), pp. 521-528. Cell Press 10.1016/j.neuron.2013.11.030 <http://dx.doi.org/10.1016/j.neuron.2013.11.030> |
Palavras-Chave | #610 Medicine & health #570 Life sciences; biology |
Tipo |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion PeerReviewed |