| dc.creator |
Meagher, Brian J. |
|
| dc.date |
2022-11-14T17:03:00Z |
|
| dc.date |
2022-11-14T17:03:00Z |
|
| dc.date |
2022-10 |
|
| dc.date.accessioned |
2023-02-24T18:27:24Z |
|
| dc.date.available |
2023-02-24T18:27:24Z |
|
| dc.identifier |
https://hdl.handle.net/2022/28402 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/260345 |
|
| dc.description |
Thesis (Ph.D.) - Indiana University, Department of Psychological & Brain Sciences and the Cognitive Science Program, 2022 |
|
| dc.description |
Categorization and old-new recognition memory are closely linked topics in the psychological literature, and have both benefitted from extensive formal modelling efforts. However, the existing literature examining their relationship has almost exclusively used simplified artificial stimuli. The present work extends this literature by collecting both categorization and old-new recognition judgments on a set of naturalistic stimuli: namely, a set of 540 images of rocks. The abilities of different models to fit the categorization and recognition data are discussed in detail, as are various efforts at improving the feature space representation of the stimuli. Ultimately, the categorization data was fit well by an exemplar and clustering model, but not a prototype model. Only the exemplar model was able to provide an account of the recognition data; however, the model had difficulty capturing variability in participants’ recognition judgments of previously seen stimuli. |
|
| dc.language |
en |
|
| dc.publisher |
[Bloomington, Ind.] : Indiana University |
|
| dc.rights |
CC-BY-SA: This work is under a CC-BY-SA license. You are free to copy and redistribute the material in any format as well as remix, transform, and build upon the material as long as you give appropriate credit to the original creator, provide a link to the license, and indicate any changes made. You must distribute any contributions under an identical license. |
|
| dc.rights |
https://creativecommons.org/licenses/by-sa/4.0/ |
|
| dc.subject |
Categorization, Recognition, Formal models, High-dimensional, Naturalistic stimuli, Concepts |
|
| dc.title |
Categorization and Recognition in a Naturalistic Stimulus Domain |
|
| dc.type |
Doctoral Dissertation |
|