Place-Coding and One-Spike behavior with Nengo

In some articles there are SNN models using 1D N size Place-Code populations (rather than Rate-Coding).

These 1D populations can represent numerical input and output values by linear mapping of intervals. Every neuron in a population represents a numerical value ranging within the input limits i.e., values within the range [-lim, lim] are mapped to a single spiking neuron with index [0, N-1] in the 1D population.

Also, in these models there is a One-Spike behavior in order to synchronize the computation in time steps. Meaning, only one neuron in each population fires at any time-step.

My experience with Nengo is pretty basic. Any explanation on how Place-Coding and One-Spike behavior can be implemented with Nengo would be much appreciated. A working example or tutorial would be excellent.

Thanks in advance!

Hi there i have something to tell

To implement Place-Coding in Nengo, create a 1D population of neurons where each neuron represents a numerical value within a specified range. Assign firing rates to neurons based on the values they represent. Map input values to the population by setting the firing rates accordingly, and read the firing rates to decode represented values.

For achieving One-Spike behavior, control input currents to neurons so that only one specific neuron fires at a time step. Inject a constant input current to the chosen neuron, ensuring it’s the only one that fires. Adapt this concept for more complex networks as needed.