Fisher information for spike-based population decoding.
We evaluate the Fisher information of a population of model neurons that receive dynamical input and interact via spikes. With spatially independent threshold noise, the spike-based Fisher information that summarizes the information carried by individual spike timings has a particularly simple analytical form. We calculate the loss of information caused by abandoning spike timing and study the effect of synaptic connections on the Fisher information. For a simple spatiotemporal input, we derive the optimal recurrent connectivity that has a local excitation and global inhibition structure. The optimal synaptic connections depend on the spatial or temporal feature of the input that the system is designed to code.
Toyoizumi
Taro
T
Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro, Tokyo 113-8656, Japan. taro.toyoizumi@brain.riken.jp
Aihara
Kazuyuki
K
Amari
Shun-ichi
S
D000465:Algorithms; D004594:Electrophysiology; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000502:physiology*; D011153:Population; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology