title: Scaling laws of associative memory retrieval.
abstract: Most people have great difficulty in recalling unrelated items. For example, in free recall experiments, lists of more than a few randomly selected words cannot be accurately repeated. Here we introduce a phenomenological model of memory retrieval inspired by theories of neuronal population coding of information. The model predicts nontrivial scaling behaviors for the mean and standard deviation of the number of recalled words for lists of increasing length. Our results suggest that associative information retrieval is a dominating factor that limits the number of recalled items.
authors.affiliation: Weizmann Institute, Department of Neurobiology, Rehovot, Israel 76100. sandro.romani@gmail.com
authors.forename: Sandro
authors.initials: S
authors.lastname: Romani
authors.forename: Itai
authors.initials: I
authors.lastname: Pinkoviezky
authors.forename: Alon
authors.initials: A
authors.lastname: Rubin
authors.forename: Misha
authors.initials: M
authors.lastname: Tsodyks
mesh_terms: D000465:Algorithms; D001245:Association Learning / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008568:Memory / Q000502:physiology*; D011939:Mental Recall / Q000502:physiology*; D008959:Models, Neurological; D016571:Neural Networks, Computer