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Modulating Attentional Load Affects Numerosity Estimation: Evidence against a Pre-Attentive Subitizing Mechanism

Overview of attention for article published in PLOS ONE, September 2008
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Title
Modulating Attentional Load Affects Numerosity Estimation: Evidence against a Pre-Attentive Subitizing Mechanism
Published in
PLOS ONE, September 2008
DOI 10.1371/journal.pone.0003269
Pubmed ID
Authors

Petra Vetter, Brian Butterworth, Bahador Bahrami

Abstract

Traditionally, the visual enumeration of a small number of items (1 to about 4), referred to as subitizing, has been thought of as a parallel and pre-attentive process and functionally different from the serial attentive enumeration of larger numerosities. We tested this hypothesis by employing a dual task paradigm that systematically manipulated the attentional resources available to an enumeration task. Enumeration accuracy for small numerosities was severely decreased as more attentional resources were taken away from the numerical task, challenging the traditionally held notion of subitizing as a pre-attentive, capacity-independent process. Judgement of larger numerosities was also affected by dual task conditions and attentional load. These results challenge the proposal that small numerosities are enumerated by a mechanism separate from large numerosities and support the idea of a single, attention-demanding enumeration mechanism.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 3 2%
United States 3 2%
Australia 2 1%
United Kingdom 2 1%
Korea, Republic of 1 <1%
Chile 1 <1%
Unknown 128 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 26%
Student > Ph. D. Student 30 21%
Student > Master 18 13%
Professor 9 6%
Student > Bachelor 8 6%
Other 23 16%
Unknown 16 11%
Readers by discipline Count As %
Psychology 81 58%
Neuroscience 13 9%
Agricultural and Biological Sciences 5 4%
Computer Science 5 4%
Medicine and Dentistry 5 4%
Other 12 9%
Unknown 19 14%