Figure 3. Two-neuron network.

(a) Schematic of recurrently connected two-neuron network derived from efficient coding framework. Neuron 1 is strongly excitable ($w_i=1$), while neuron 2 is weakly excitable ($w_i=2$). (b) Spikes from neuron 1 (light blue) and neuron 2 (dark blue) show the transient response of the strongly excitable neuron and the delayed, but sustained response of the weakly excitable neuron (top) in response to a constant stimulus. Postsynaptic activity, $r(t)$ (bottom) [$\mu =0.02,\tau =25ms,{\tau }_a=1000ms,\varphi (t)=10$]. (c) The balanced network with adaptation follows a linear manifold (left), whereas the network without recurrent connections but with adaptation cannot be linearly decoded (right). (d) The cost ($\mu {\sum }_n{f}_n^2$, yellow) accumulates steeply until neuron one adapts and neuron two is recruited and the cost increases at a slower rate. The network representation (orange) is maintained despite the redistribution of activity among the neurons.