Architecture of the model network and stimulus preprocessing.

<p>Architecture of the model network and network activity. <b>a:</b> Architecture of the model network and stimulus preprocessing. The final preprocessing step of separating the stimulus into two non-negative “ON” and “OFF” populations allows the visible layer activities to remain positive. <b>b:</b> Example activity of two neurons in the spiking network. In response to external stimulus onset (gray bar), the visible neuron <i>i</i> fires several spikes in the “initial bout” of activity. After a delay, feedforward excitation causes the hidden neuron <i>j</i> to fires spikes in the “intermediate bout”. After another delay, feedback causes the visible neuron to spike in the “final bout”, the network’s attempted reconstruction. The average time between spikes in the initial and intermediate bouts and intermediate and final bouts are given by Δ<i>t</i>₁ and Δ<i>t</i>₂, respectively. Every pair of visible and hidden spikes contributes to plasticity, dependent on their relative times. Learning from two example dotted spikes is described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004566#pcbi.1004566.g002" target="_blank">Fig 2</a>. <b>c:</b> Biological feedforward and feedback connections are physically distinct. For the feedforward connection, the visible neuron is pre-synaptic, the hidden neuron is post-synaptic, and the synapse lies close to the hidden neuron’s cell body. For the feedback connection, the hidden neuron is pre-synaptic, the visible neuron post-synaptic, and the synapse is far out on the visible neuron’s dendritic tree.