Document Detail


The effects of sampling and internal noise on the representation of ensemble average size.
MedLine Citation:
PMID:  23188732     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Increasing numbers of studies have explored human observers' ability to rapidly extract statistical descriptions from collections of similar items (e.g., the average size and orientation of a group of tilted Gabor patches). Determining whether these descriptions are generated by mechanisms that are independent from object-based sampling procedures requires that we investigate how internal noise, external noise, and sampling affect subjects' performance. Here we systematically manipulated the external variability of ensembles and used variance summation modeling to estimate both the internal noise and the number of samples that affected the representation of ensemble average size. The results suggest that humans sample many more than one or two items from an array when forming an estimate of the average size, and that the internal noise that affects ensemble processing is lower than the noise that affects the processing of single objects. These results are discussed in light of other recent modeling efforts and suggest that ensemble processing of average size relies on a mechanism that is distinct from segmenting individual items. This ensemble process may be more similar to texture processing.
Authors:
Hee Yeon Im; Justin Halberda
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-28
Journal Detail:
Title:  Attention, perception & psychophysics     Volume:  -     ISSN:  1943-393X     ISO Abbreviation:  Atten Percept Psychophys     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-28     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101495384     Medline TA:  Atten Percept Psychophys     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Psychological and Brain Sciences, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA, heeyeon.im@jhu.edu.
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