ReviewVisual prediction and perceptual expertise
Introduction
When walking on the street, we are not surprised to see cars, parking meters, or traffic lights. If we catch a glimpse of something that appears on the sidewalk and quickly disappears into the bushes, we may think that it could be a bird, a squirrel, or a cat, depending on its size and shape. However, we would be baffled if we instead saw something unpredicted, such as a goat or an anchor, on the street, because it would be completely out of context. While external information from the world is continuously extracted and processed by various sensory modalities, the human brain readily generates top–down predictions1 based on associations in memory formed from previous experience to make sense of and interact with the environment (Bar, 2007). Various predictions may be formed continuously. For instance, when we see a parking meter, we predict that it is likely a car next to it. Or we predict that a blurry impression is a harmless squirrel. Recent work on visual prediction has suggested that predictions are formed rapidly and draw on associative connections stored in long-term memory (e.g., Bar, 2004, Bar, 2009, Gilbert and Wilson, 2007, Schacter et al., 2007, Schacter et al., 2008).
Strong associative activations and fast processing speed are also characteristics of expert processing (e.g., Chase and Ericsson, 1981, Freyhof et al., 1992, Richler et al., 2009). For instance, while most people may recognize a fast approaching car merely as a ‘silver car’, a car expert may recognize it instantaneously as the newest model of Jaguar XF, know what engine it may have, and can distinguish between this and other comparable models. In this review, we highlight the possible relations between the processes responsible for prediction and the processes involved in expert processing. We focus our discussion on recent behavioral and imaging findings on visual prediction and on visual expertise, as theories in these two areas have been elaborated and studied especially in the last decade (e.g., Bar, 2003, Bar, 2004, Gauthier et al., 2000a, Wong et al., 2009a). Merging the findings from these two literatures offers new insights on the role of associative processing in a variety of cognitive processes that are central to our mental lives, such as recognition, learning, memory and prediction.
Section snippets
Generating visual predictions based on analogies and associations
Making rapid and accurate predictions is beneficial in many situations and can facilitate perception and action. To do so, one needs to acquire knowledge about various attributes and relations of objects, people, and events in the world. Such knowledge, stored in memory, constitutes the basis of recognition and prediction for both familiar and unfamiliar instances (e.g., recognizing your own cat vs. a stray cat). While interacting with the environment, the human brain not only makes use of
Associative processes in perceptual expertise
Observers appear to be able to generate associations and predictions reliably and possibly automatically, and this ability is likely acquired through extensive experience while interacting with the world. Just how much our ability to produce helpful predictions is enhanced by experience and further training is an important open question. Every person possesses some level of expertise in many domains, but enthusiasts of various domains (e.g., birdwatchers, chess players, musicians, stamp
Neural mechanisms for visual prediction and perceptual expertise
Although associative processing appears critical in both visual prediction and perceptual expertise, past studies from these two lines of research have asked distinct sets of questions. For instance, most studies in visual prediction are concerned with recognition of everyday objects and scenes, while most perceptual expertise research has emphasized rapid subordinate-level processing of objects in only one or a few categories. Investigation of the underlying neural mechanisms for these
Proposed associative prediction framework in experts
In the current framework of associative prediction (e.g., Bar, 2003, Bar, 2004), the PHC, RSC and OFC influence processing in the perceptual system to guide object recognition (Bar et al., 2006a, Kveraga et al., 2011). Additionally, perceptual and semantic associations are strengthened with expertise (Gauthier et al., 2003, Tanaka and Taylor, 1991, Herzmann and Curran, 2011). Critically, how does the associative prediction network interact with the perceptual system in experts? Let's take face
Acknowledgments
This work was supported by NEI-NIH grant 1R01EY019477-01, NSF grant BCS-0842947, and DARPA grant N10AP20036. We thank Daryl Fougnie, Eiran Vadim Harel and Tomer Livne for helpful comments on the manuscript.
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