title: Symmetry breaking in neural nets.
abstract: In this paper two well-known homogeneous models of neural nets undergoing symmetry-breaking transitions are studied in order to see if, after the transition, there is the appearance of Goldstone modes. These have been found only in an approximate way; there are indications, however, that they can play a prominent role when the tissue is subjected to external inputs, constraining it to be slaved to the characteristics of those. This circumstance should be essential in explaining how a structured net can store complex inputs and give subsequently ordered outputs.
authors.affiliation: Dipartimento di Matematica, Università degli Studi di Roma La Sapienza, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Pessa
mesh_terms: D008433:Mathematics; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009424:Nervous System Physiological Phenomena