Dendritic computation for neural networks

Abstract

A dendrite computing network is provided. The network comprises a dendrite comprising a number of dendrite compartments in a sequential chain, wherein each dendrite compartment has a respective state with an electrical current value for a given time step, and wherein each dendrite compartment saves electrical current values computed in previous time steps. Each dendrite compartment receives a respective external electrical input current with a respective input weight. Each dendrite compartment has a respective leak weight. A temporal modifier determines how quickly each dendrite compartment responds to input signals, and a spatial signal transmission constant that controls communication between dendrite compartments. The temporal modifier and spatial signal transmission constant are used to create a kernel that iterates through a specified number of time steps to compute a new electrical current value in the state of each dendrite compartment.

Dependencies are inferred from the claim text.