Beyond perceptual expertise: revisiting the neural substrates of expert object recognition

Abstract

Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex.

Keywords: expertise; fMRI; object recognition; review; visual cortex; visual perception.

Figure 1

Expert visual object recognition. (A) Expertise in visual object recognition has been demonstrated in several domains, including cars (e.g., Kanwisher, ; Rossion and Curran, ; Harel and Bentin, 2013), dogs (Diamond and Carey, ; Robbins and Mckone, 2007), birds (e.g., Johnson and Mervis, ; Kanwisher, 2000), x-rays (Harley et al., 2009), fingerprints (Busey and Vanderkolk, 2005), and chess (e.g., Krawczyk et al., ; Bilalić et al., 2012). (B) Discrimination performance of car experts and car novices with cars and airplanes. Relative to naïve observers (novices), car experts are very good at telling whether two car images varying in color, view and orientation are of the same model or not. However, when these car experts have to perform a similar task with airplane images, their performance drops dramatically and is as equally poor as of novices. This exemplifies the definition of expertise as consistently superior performance within a domain relative to other people and other domains. Figure adapted from Harel et al. (2010). (C) A schematic representation of the different levels of visual representation that may be modified by expertise (simple features, intermediate complexity features, holistic and conceptual representations). Here we highlight the interaction between these different representational levels in the visual system. There will be further interactions between visual representations and the higher-level conceptual system representing domain-specific knowledge.

Figure 2

Widespread distributed effects of expertise across the cortex. Comparison of car expertise-related effects reported by (A) McGugin et al. (2012b) and (B) Harel et al. (2010). Common regions outside FFA visible in both maps include lingual gyrus/collateral sulcus (CoS), precuneus, and STS. Importantly, the field of view used by McGugin et al. (outlined in black) did not include early visual cortex, but expertise effects were observed by Harel et al. (2010) in these areas. (C) Re-analyzed data from Harel et al. (2010); Experiment 1 showing correlations between behavioral car expertise (car discrimination relative to airplane discrimination) and car-selective activity (expressed as the difference between percent signal change for cars and the mean of percent signal change of the other two categories tested) in the four independently defined regions used in that study (for details see Harel et al., 2010): FFA, early visual cortex, object-selective cortex and scene-selective cortex. Together, the distributed expertise effects (a, b) and the widespread correlations between expertise and car selectivity (c) strongly suggest that the expertise effect reported by McGugin et al. reflects attentional engagement.

Figure 3

The effect of attentional engagement on the neural correlates of expertise. Data from Harel et al. (2010), Experiment 2 demonstrating that when experts are attending to their category of expertise (high engagement, top row), there are widespread effects of expertise compared with novices. However, these effects diminish drastically when car experts (compared with novices) engagement is drawn toward another object category (low engagement, bottom row). For further details see Harel et al. (2010).