Abstract
The human visual system is very fast and efficient at extracting information about objects present in complex natural scenes. For example, Thorpe, Fize, and Marlot (1996) showed that participants were able to decide whether a natural scene contained an animal even when the image was presented briefly. Moreover, Rousselet, Fabre-Thorpe, and Thorpe (2002) used the animal versus non-animal categorization task and showed that participants could reliably indicate the side containing an animal when two images were simultaneously flashed in the left and right hemi-fields. Together, these results suggest that a great deal of visual information is processed in a fast and feedforward way so that object categorization in natural scenes can be achieved rapidly. The current study aimed to examine whether recurrent visual processing plays a role in rapid object categorization in natural scenes by using an object substitution masking paradigm. We had participants perform an object categorization task. On each trial, two images were simultaneously presented for 20 ms in the left and right visual fields; participants then had to indicate whether an animal or a vehicle appeared in the target picture, which was surrounded by eight dots. These dots either disappeared simultaneously with the target and distractor pictures or remained on the screen for 200 ms. According to Di Lollo, Enns, and Rensink (2000), object substitution masking occurs when a lateral mask (e.g., small dots) persists beyond the duration of a target, reflecting reentrant processes in vision. Therefore, the trailing dots should not affect categorization performance if rapid object categorization requires no reentrant processing from higher-level visual areas. However, our results showed that the trailing dots impaired participants' categorization performance, suggesting that reentrant visual processing affects rapid object categorization in natural scenes.
This project was supported by Grant Number 1P20 RR020151 from the National Center for Research Resources (NCRR) as well as the National Science Foundation under Grant Number BCS-0443998.