MEMORY CAPACITY IN LARGE IDIOTYPIC NETWORKS

摘要

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.