Learning by the Dendritic Prediction of Somatic Spiking

Urbanczik, Robert, Senn, Walter·2014·Neuron
DOI 10.1016/j.neuron.2013.11.030

Cited by (228)

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  81. Neural mechanisms of context-dependent segmentation tested on large-scale recording data
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  83. Synapses learn to utilize pre-synaptic noise for the prediction of postsynaptic dynamics
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  84. Spike-Timing Dependent Plasticity, Learning Rules
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  85. Few-shot pattern detection by transient boosting of somato-dendritic coupling
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