Brabeeba Wang: Integrating Temporal Information to Spatial Information in a Neural Circuit

Algorithms in the brain are inherently distributed. Although each neuron has relatively simple dynamics, as a distributed system, a network of neurons shows strong computation power. One of the important questions in neuroscience is how humans integrate information over time; for example, how do people recognize a song? In this paper, we consider a network of spiking neurons with deterministic synchronous firing rule at discrete time, and design three networks that solve three problems that translate temporal information into spatial information, "first consecutive spikes counting" , "total spikes counting" and "k-spikes temporal to spatial encoding" (kSTS), with matching lower bounds in both time and number of neurons in all three questions.