Independent neurons representing a finite set of stimuli: dependence of the mutual information on the number of units sampled.
We study the capacity with which a system of independent neuron-like units represents a given set of stimuli. We assume that each neuron provides a fixed amount of information and that the information provided by different neurons has a random overlap. We derive analytically the dependence of the mutual information between the set of stimuli and the neural responses on the number of units sampled. For a large set of stimuli, the mutual information rises linearly with the number of neurons and later saturates exponentially at its maximum value.
Samengo
I
I
International School of Advanced Studies, Trieste, Italy.
D000818:Animals; D003198:Computer Simulation; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D010812:Physical Stimulation; D011336:Probability