The extent to which object identification is influenced by the background of the scene is still controversial. On the one hand, the global context of a scene might be considered as an ultimate representation, suggesting that object processing is performed almost systematically before scene context analysis. Alternatively, the gist of a scene could be extracted sufficiently early to be able to influence object categorization. It is thus essential to assess the processing time of scene context. In the present study, we used a go/no-go rapid visual categorization task in which subjects had to respond as fast as possible when they saw a "man-made environment", or a "natural environment", that was flashed for only 26 ms. "Man-made" and "natural" scenes were categorized with very high accuracy (both around 96%) and very short reaction times (median RT both around 390 ms). Compared with previous results from our group, these data demonstrate that global context categorization is remarkably fast: (1) it is as fast as object categorization [Fabre-Thorpe, M., Delorme, A., Marlot, C., & Thorpe, S. (2001). A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes. Journal of Cognitive Neuroscience, 13(2), 171-180]; (2) it is faster than contextual categorization at more detailed levels such as sea, mountain, indoor or urban contexts [Rousselet, G. A., Joubert, O. R., & Fabre-Thorpe, M. (2005). How long to get to the "gist" of real-world natural scenes? Visual Cognition, 12(6), 852-877]. Further analysis showed that the efficiency of contextual categorization was impaired by the presence of a salient object in the scene especially when the object was incongruent with the context. Processing of natural scenes might thus involve in parallel the extraction of the global gist of the scene and the concurrent object processing leading to categorization. These data also suggest early interactions between scene and object representations compatible with contextual influences on object categorization in a parallel network.

Models of visual processing often include an initial parallel stage that is restricted to relatively low-level features, whereas activation of higher-level object descriptions is generally assumed to require attention. Here we report that even high-level object representations can be accessed in parallel: in a rapid animal versus non-animal categorization task, both behavioral and electrophysiological data show that human subjects were as fast at responding to two simultaneously presented natural images as they were to a single one. The implication is that even complex natural images can be processed in parallel without the need for sequential focal attention.