Memory capacity in large idiotypic networks.
Many models of immune networks have been proposed since the original work of Jerne [1974, Ann. Immun. (Inst. Pasteur)125C, 373-389]. Recently, a limited class of models (Weisbuch et al., 1990, J. theor. Biol 146, 483-499) have been shown to maintain immunological memory by idiotypic network interactions. We examine generalizations of these models when the networks are both large and highly connected to study their memory capacity, i.e., their ability to account for immunization to a large number of random antigens. Our calculations show that in these minimal models, random connectivities with continuously distributed affinities reduce the memory capacity to essentially nil.
Division de Physique Théorique, Unité de Recherche des Universités Paris, Cedex, France.
J H
JH
Boutet de Monvel
O C
OC
Martin
D000818:Animals; D001402:B-Lymphocytes / Q000276:immunology*; D007130:Immunoglobulin Idiotypes / Q000276:immunology; D007156:Immunologic Memory; D018448:Models, Immunological; D008962:Models, Theoretical; D016571:Neural Networks, Computer
D007130:Immunoglobulin Idiotypes