
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
High Energy Physics - Lattice, FOS: Biological sciences, High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Quantitative Biology (q-bio), Quantitative Biology
High Energy Physics - Lattice, FOS: Biological sciences, High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Quantitative Biology (q-bio), Quantitative Biology
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