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. 2015 Jun 8;9:206. doi: 10.3389/fnins.2015.00206

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Copyright © 2015 Lagorce, Stromatias, Galluppi, Plana, Liu, Furber and Benosman.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Learning sub-millisecond time patterns. (A) Network structure: input spikes are produced by neurons A, which represent frequency channels of a simulated silicon cochlea; they drive neurons B1 and B2 with excitatory synapses; B1 is connected to the B2 neuron of its own channel with an inhibitory synapse, while it is connected to the other channels through the delay populations C with plastic connections. Delays are proportional to the tonotopic distance between channels. (B) Input raster plot (left) and final weight distribution (right) when stimulating the network with a forward frequency sweep, activating all channels in rapid succession. (C) Input raster plot (left) and final weight distribution (right) when stimulating the network with a backward frequency sweep, activating all channels in rapid succession; (D) input raster plot (left) and final weight distribution (right) when stimulating the network with a forked frequency sweep starting from the central channels.