Dataset Information

Face processing in humans is compatible with a simple shape-based model of vision.

ABSTRACT: Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence, a general class of recognition models has emerged, which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity. However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ 'featurally' are much easier to distinguish when inverted than those that differ 'configurally'; a finding that is difficult to reconcile with the physiological models. Here, we show that after controlling for subjects' expectations, there is no difference between 'featurally' and 'configurally' transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in the cortex.

SUBMITTER: Riesenhuber M

PROVIDER: S-EPMC1810084 | biostudies-other | 2004 Dec

REPOSITORIES: biostudies-other

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Face processing in humans is compatible with a simple shape-based model of vision.

Riesenhuber Maximilian M Jarudi Izzat I Gilad Sharon S Sinha Pawan P

Proceedings. Biological sciences 20041201

Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence, a general class of recognition models has emerged, which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity. However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investig ...[more]

PMID: 15801600

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Project description:BACKGROUND: In many animals, exaggerated sex-typical male traits are preferred by females, and may be a signal of both past and current disease resistance. The proposal that the same is true in humans--i.e., that masculine men are immunocompetent and attractive--underpins a large literature on facial masculinity preferences. Recently, theoretical models have suggested that current condition may be a better index of mate value than past immunocompetence. This is particularly likely in populations where pathogenic fluctuation is fast relative to host life history. As life history is slow in humans, there is reason to expect that, among humans, condition-dependent traits might contribute more to attractiveness than relatively stable traits such as masculinity. To date, however, there has been little rigorous assessment of whether, in the presence of variation in other cues, masculinity predicts attractiveness or not. METHODOLOGY/PRINCIPAL FINDINGS: The relationship between masculinity and attractiveness was assessed in two samples of male faces. Most previous research has assessed masculinity either with subjective ratings or with simple anatomical measures. Here, we used geometric morphometric techniques to assess facial masculinity, generating a morphological masculinity measure based on a discriminant function that correctly classified >96% faces as male or female. When assessed using this measure, there was no relationship between morphological masculinity and rated attractiveness. In contrast, skin colour--a fluctuating, condition-dependent cue--was a significant predictor of attractiveness. CONCLUSIONS/SIGNIFICANCE: These findings suggest that facial morphological masculinity may contribute less to men's attractiveness than previously assumed. Our results are consistent with the hypothesis that current condition is more relevant to male mate value than past disease resistance, and hence that temporally fluctuating traits (such as colour) contribute more to male attractiveness than stable cues of sexual dimorphism.

Dataset Information

Face processing in humans is compatible with a simple shape-based model of vision.

Publications

Face processing in humans is compatible with a simple shape-based model of vision.

Similar Datasets

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