Gauge Symmetry and Neural Networks
arXiv:cond-mat/0112463 · doi:10.1142/9789812811240_0025
Abstract
We propose a new model of neural network. It consists of spin variables to describe the state of neurons as in the Hopfield model and new gauge variables to describe the state of synapses. The model possesses local gauge symmetry and resembles lattice gauge theory of high-energy physics. Time dependence of synapses describes the process of learning. The mean field theory predicts a new phase corresponding to confinement phase, in which brain loses ablility of learning and memory.
9 pages, 7 figures