Effect of lateral connections on the accuracy of the population code for a network of spiking neurons.
We study how neuronal connections in a population of spiking neurons affect the accuracy of stimulus estimation. Neurons in our model code for a one-dimensional orientation variable phi. Connectivity between two neurons depends on the absolute difference absolute value(phi - phi') between the preferred orientation of the two neurons. We derive an analytical expression of the activity profile for a population of neurons described by the spike response model with noisy threshold. We estimate the stimulus orientation and the trial-to-trial fluctuations using the population vector method. For stationary stimuli, uniform inhibitory connections produce a more reliable estimation of the stimulus than short-range excitatory connections with long-range inhibitions, although the latter interaction type produces a sharper tuning curve. These results are consistent with previous analytical studies of the Fisher information.
Spiridon
M
M
Center for Neuromimetic Systems, Swiss Federal Institute of Technology, Lausanne.
Gerstner
W
W
D000200:Action Potentials / Q000502:physiology; D003198:Computer Simulation; D007257:Information Theory; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology*