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ERIC Number: EJ747072
Record Type: Journal
Publication Date: 2006
Pages: 25
Abstractor: Author
ISBN: N/A
ISSN: ISSN-0364-0213
Modeling Recognition Memory Using the Similarity Structure of Natural Input
Lacroix, Joyca P. W.; Murre, Jaap M. J.; Postma, Eric O.; van den Herik, H. Jaap
Cognitive Science, v30 n1 p121-145 2006
The natural input memory (NAM) 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).
Lawrence Erlbaum Associates, Inc. 10 Industrial Avenue, Mahwah, NJ 07430. Tel: 800-926-6579; Tel: 201-258-2200; Fax: 201-236-0072; e-mail: journals@erlbaum.com; Web site: https://www.erlbaum.com
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A