Invited Speakers > Lisa Feigenson

 

 

 

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Constraints and flexibility in early quantification

Lisa Feigenson

Johns Hopkins University

 

 

The act of quantification (e.g., knowing how many objects are in a scene) requires selecting a relevant entity and storing it in working memory for further processing.  Critically, multiple kinds of entities can be selected and stored.  In this talk I offer evidence that humans can represent at least three different levels of entities in working memory.  They can represent an individual object (e.g., “that bird”).  They can represent a collection of items (e.g., “that flock of birds”).  And they can represent a set of discrete items (e.g., “the set containing Bird A, Bird B, and Bird C”).  Each of these types of representations permits a different type of quantificational processing.  Storing individual objects in working memory permits exact but implicit representation of the number of objects present, up to a maximum of 3 objects.  Storing collections of items in working memory permits explicit but inexact representation of the number of items present, with no in principle upper limit.  And storing sets of individual items permits exact implicit representation of the number of items present, but is accompanied by a loss of representational precision.  Hence, which quantity-relevant computations may be performed in any given situation depends on which level of representation is stored.  This framework for thinking about interactions between attention, working memory, and quantification applies throughout development, starting in infancy.

 

 

                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     

 

 

          

 

 

 

 

 

 

 

 

       

 

 

 

 

 

 

 

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