WWW.JNEUROSCI.ORG
-
The Journal of Neuroscience
 QUICK SEARCH:   [advanced]


     
-


HOME
  |  
SEARCH  |   ARCHIVE  |   SUBSCRIBE  |   CONTACT  |   HELP

The Journal of Neuroscience, October 28, 2009, 29(43):13621-13629; doi:10.1523/JNEUROSCI.2612-09.2009

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Submit an eLetter
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Google Scholar
Right arrow Articles by Gölcü, D.
Right arrow Articles by Gilbert, C. D.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gölcü, D.
Right arrow Articles by Gilbert, C. D.

 Previous Article  |  Next Article 

Behavioral/Systems/Cognitive
Perceptual Learning of Object Shape

Doruk Gölcü and Charles D. Gilbert

The Rockefeller University, New York, New York 10065

Correspondence should be addressed to Dr. Charles D. Gilbert, The Rockefeller University, 1230 York Avenue, New York, NY 10065. Email: gilbert{at}rockefeller.edu

Recognition of objects is accomplished through the use of cues that depend on internal representations of familiar shapes. We used a paradigm of perceptual learning during visual search to explore what features human observers use to identify objects. Human subjects were trained to search for a target object embedded in an array of distractors, until their performance improved from near-chance levels to over 80% of trials in an object-specific manner. We determined the role of specific object components in the recognition of the object as a whole by measuring the transfer of learning from the trained object to other objects sharing components with it. Depending on the geometric relationship of the trained object with untrained objects, transfer to untrained objects was observed. Novel objects that shared a component with the trained object were identified at much higher levels than those that did not, and this could be used as an indicator of which features of the object were important for recognition. Training on an object also transferred to the components of the object when these components were embedded in an array of distractors of similar complexity. These results suggest that objects are not represented in a holistic manner during learning but that their individual components are encoded. Transfer between objects was not complete and occurred for more than one component, regardless of how well they distinguish the object from distractors. This suggests that a joint involvement of multiple components was necessary for full performance.


Received June 4, 2009; revised Sept. 8, 2009; accepted Sept. 27, 2009.

Correspondence should be addressed to Dr. Charles D. Gilbert, The Rockefeller University, 1230 York Avenue, New York, NY 10065. Email: gilbert{at}rockefeller.edu






-
-

Home  |   Search  |   Archive  |   Subscribe  |   Contact  |   Help

-
Copyright 2009 by Society for Neuroscience ONLINE ISSN: 1529-2401
-