.png){kind=icon}
Return
Subitizing, unlike estimation, does not process sets in parallel
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-020-72860-4.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Enumeration of very small quantities is a common task that we perform everyday. Much research has highlighted that in these conditions humans display fast, near errorless performance, a phenomenon dubbed subitizing. It has been suggested that this regime has a pivotal role in numerosity perception. Here we asked if this system can process multiple sets of items in parallel. At odds with what happens for moderate numerosities, we found a strong impairment caused already by the introduction of a second group of items marked by a different color. Adding shape as a cue provided no benefit. The only case in which subitizing was possible was when the target and distractor group were held constant through the experimental block. These results show the surprising fact that whilst being rapid and errorless, subitizing does not have the capability to disentangle multiple groups of items and deals only with coarse stimulus statistics.
Keywords:
ATTENTION
PERCEPTION
NUMEROSITY
OBJECTS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.9
Papers:
27.9W
Citations:
83.5W
Organization
View more organizations
Cited Papers
Investigating whole‐brain metabolite abnormalities in the chronic stages of moderate or severe traumatic brain injury.png)
PM&ROAAI
PM&RIF0
OAAIShareSaveShareSaveShareSaveShareSaveShareSaveShareSave View more