title: Modeling recognition memory using the similarity structure of natural input.
abstract: The natural input memory (NIM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During recognition, the model compares incoming preprocessed natural input to stored representations. By complementing the recognition memory process with a perceptual front end, the NIM model is able to make predictions about memorability based directly on individual natural stimuli. We demonstrate that the NIM model is able to simulate experimentally obtained similarity ratings and recognition memory for individual stimuli (i.e., face images).
authors.affiliation: IKAT/Department of Computer Science, Universiteit Maastricht, The NetherlandsDepartment of Psychology, University of Amsterdam, The Netherlands.
authors.forename: Joyca P W
authors.initials: JP
authors.lastname: Lacroix
authors.forename: Jaap M J
authors.initials: JM
authors.lastname: Murre
authors.forename: Eric O
authors.initials: EO
authors.lastname: Postma
authors.forename: H Jaap
authors.initials: HJ
authors.lastname: Herik