The roles of visual expertise and visual input in the face inversion effect: Behavioral and neurocomputational evidence

McCleery, Joseph P.; Zhang, Li Min; Ge, Liezhong; Wang, Zhongyan; Christiansen, Eric; Lee, Ki-Young; Cottrell, Garrison W.

doi:10.1016/j.visres.2007.11.025

Cited by 22 publications

(22 citation statements)

References 24 publications

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“…Thus, it is possible that an unspecific mechanism that responds to first-order face configurations and resembling stimuli [37,52] quickly determines whether a visual stimulus is a face and thus will be preferentially attended to in primates. Computational models that have been applied successfully to investigate face processing [26,[140][141][142] may help solve the question whether such a mechanism is necessary to (re-)produce the characteristics of face processing.…”

Section: Discussionmentioning

confidence: 99%

The early development of face processing — What makes faces special?

Hoehl

Peykarjou

2012

Neurosci. Bull.

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Abstract:In the present article we review behavioral and neurophysiological studies on face processing in adults and in early development. From the existing empirical and theoretical literature we derive three aspects that distinguish face processing from the processing of other visual object categories. Each of these aspects is discussed from a developmental perspective. First, faces are recognized and represented at the individual level rather than at the basic level. Second, humans typically acquire extensive expertise in individuating faces from early on in development. And third, more than other objects, faces are processed holistically. There is a quantitative difference in the amount of visual experience for faces and other object categories in that the amount of expertise typically acquired for faces is greater than that for other object categories. In addition, we discuss possible qualitative differences in experience for faces and objects. For instance, there is evidence for a sensitive period in infancy for building up a holistic face representation and for perceptual narrowing for faces of one's own species and race. We conclude our literature review with questions for future research, for instance, regarding the exact relationship between behavioral and neuronal markers of face processing across development.

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Section: Discussionmentioning

confidence: 99%

The early development of face processing — What makes faces special?

Hoehl

Peykarjou

2012

Neurosci. Bull.

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“…! used, the nonsense characters are farther apart in representational space, and hence better discriminated, as in the behavioral data (McCleery, et al, 2008).…”

Section: Additional Behavioral Data Accounted Formentioning

confidence: 99%

“…The basic idea of the model was that other race faces contain more information in the Shannon sense, and hence are more salient (see also (Zhang, et al, 2007) for a similar account). Finally, the model has been used to account for priming effects in the discrimination of nonsense characters (McCleery, et al, 2008). It had been shown that Chinese subjects primed to think of nonsense characters as a face discriminated them better than when they were primed to think of them as a Chinese character, when they differed configurally.…”

Section: Additional Behavioral Data Accounted Formentioning

confidence: 99%

Neurocomputational Models of Face Processing

Cottrell

Hsiao

2011

Oxford Handbooks Online

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Until the day we can record from multiple neurons in undergraduates, understanding how humans process faces requires an interdisciplinary approach, including building computational models that mimic how the brain processes faces.Using machine learning techniques, we can often build models that perform the same tasks people do, in neurophysiologically plausible ways. These models can then be manipulated and analyzed in ways that people cannot, providing insights that are unavailable from behavioral experiments. For example, as we will see below, our model of perceptual expertise can be "raised" in an environment where its "parents" are cups or cans instead of faces, and the same kind of processing ensues. This demonstrates, at least from our point of view, that there is nothing special about faces as an object class per se; rather, it is what we have to do with them -fine level discrimination of a homogeneous class -that is special.In this chapter, we will delineate two dimensions along which computational models of face (and object) processing may vary, and briefly review three such models (Dailey and Cottrell, 1999;O'Reilly and Munakata, 2000;Riesenhuber and Poggio, 1999). Subsequently, we will focus primarily on the model we are most familiar with (our own!) and how this model has been used to reveal potential mechanisms underlying the neural processing of faces and objects -the development of a specialized face processor, how it could be recruited for other domains, hemispheric lateralization of face processing, facial expression processing, and the development of face discrimination. At the end, we return to the Riesenhuber and Poggio model to describe the elegant way it has been used to predict fMRI data on face processing. The overall strategy of these modeling efforts is

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“…It has been suggested that Chinese character recognition shares some similarities with face recognition (McCleery et al, 2008). They consist of strokes packed into a relatively constant square-shaped configuration, in contrast to words in most alphabetic languages, which are linear combinations of letters.…”

Section: Introductionmentioning

confidence: 99%

Transfer of Perceptual Expertise: The Case of Simplified and Traditional Chinese Character Recognition

et al. 2016

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Expertise in Chinese character recognition is marked by reduced holistic processing (HP), which depends mainly on writing rather than reading experience. Here we show that, while simplified and traditional Chinese readers demonstrated a similar level of HP when processing characters shared between the simplified and traditional scripts, simplified Chinese readers were less holistic than traditional Chinese readers in perceiving simplified characters; this effect depended mainly on their writing rather than reading performance. However, the two groups did not differ in HP of traditional characters, regardless of their difference in reading and writing performances. Our image analysis showed high visual similarity between the two character types, with a larger variance among simplified characters; this may allow simplified Chinese readers to interpolate and generalize their skills to traditional characters. Thus, transfer of perceptual expertise may be constrained by both the similarity in feature and the difference in exemplar variance between the categories.

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The roles of visual expertise and visual input in the face inversion effect: Behavioral and neurocomputational evidence

Cited by 22 publications

References 24 publications

The early development of face processing — What makes faces special?

The early development of face processing — What makes faces special?

Neurocomputational Models of Face Processing

Transfer of Perceptual Expertise: The Case of Simplified and Traditional Chinese Character Recognition

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