Abstract
BackgroundSince the pioneering study by Rosch and colleagues in the 70s, it is commonly agreed that basic level perceptual categories (dog, chair…) are accessed faster than superordinate ones (animal, furniture…). Nevertheless, the speed at which objects presented in natural images can be processed in a rapid go/no-go visual superordinate categorization task has challenged this “basic level advantage”.Principal FindingsUsing the same task, we compared human processing speed when categorizing natural scenes as containing either an animal (superordinate level), or a specific animal (bird or dog, basic level). Human subjects require an additional 40–65 ms to decide whether an animal is a bird or a dog and most errors are induced by non-target animals. Indeed, processing time is tightly linked with the type of non-targets objects. Without any exemplar of the same superordinate category to ignore, the basic level category is accessed as fast as the superordinate category, whereas the presence of animal non-targets induces both an increase in reaction time and a decrease in accuracy.Conclusions and SignificanceThese results support the parallel distributed processing theory (PDP) and might reconciliate controversial studies recently published. The visual system can quickly access a coarse/abstract visual representation that allows fast decision for superordinate categorization of objects but additional time-consuming visual analysis would be necessary for a decision at the basic level based on more detailed representations.
Highlights
Since the pioneering study by Rosch and colleagues in the 70s, it is commonly agreed that basic level perceptual categories are accessed faster than superordinate ones
The visual system can quickly access a coarse/abstract visual representation that allows fast decision for superordinate categorization of objects but additional time-consuming visual analysis would be necessary for a decision at the basic level based on more detailed representations
A Parallel Distributed Processing (PDP) theory was proposed by McClelland, Rogers and Patterson [19,20] in which objects representations would be activated from broad to fine so that large categories would be activated before tuning to more specific representation
Summary
These results support the parallel distributed processing theory (PDP) and might reconciliate controversial studies recently published. The visual system can quickly access a coarse/abstract visual representation that allows fast decision for superordinate categorization of objects but additional time-consuming visual analysis would be necessary for a decision at the basic level based on more detailed representations
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