One important thing to model is the output (set of parallel spiking trains)that population of neurons produces upon receiving a certain input (set of parallel spiking trains).
For a single neuron, we can define the asynchronous synaptic transmission curve (aka synaptic response curve), which is the instantaneous firing rate as a function of time, when the neuron receives a single isolated spike. If integrated it gives the asynchronous gain (ASG), the total number of output spikes per input spike.
Stimulus or task-related activity is said to be ‘rate coded’ when it can be decoded using only the firing rates of neurons in an ensemble. On the other hand, when stimulus or task-related activity can be decoded using synchrony (BOX 2), it is referred to as a time (or ‘synchrony’) code
Cross-correlation, post-synaptic potentials..
Neural chains
Synchronous transmission. Synchronous gain
Firing rates of neurons from noise.
Effect of postsynaptic potentials in the firing rate, thus giving a way to compute the synaptic transmission curve (which we can experimentally find with cross-correlations).
The study of neuronal networks in the Cortex is known as Corticonics.
Neural Networks - intro – LC circuits – Linear systems
See Neural system for well studied neuronal networks