Not just the norm: Exemplar-based models also predict face aftereffects

Ross, David A.; Deroche, Mickael L. D.; Palmeri, Thomas J.

doi:10.3758/s13423-013-0449-5

Cited by 51 publications

(66 citation statements)

References 74 publications

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“…For example, Ross et al (2014) have shown that both two-pool opponent coding (norm-based) and exemplar (cf. non-norm-based, multichannel) models can account for a range of aftereffect results, although they did not consider the precise pattern of increase across the full natural range seen here.…”

Section: Discussionmentioning

confidence: 99%

Aftereffects support opponent coding of expression.

Rhodes¹,

Pond²,

Jeffery³

et al. 2017

Journal of Experimental Psychology: Human Perception and Perfor

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms AbstractWe used aftereffects to investigate the coding mechanisms underlying our perception of facial expression. Recent evidence for dimensions that are common to the coding of both expression and identity suggest that the same coding system could be used for both attributes. Identity is adaptively opponent coded by pairs of neural populations tuned to opposite extremes of relevant dimensions. Therefore, we hypothesized that expression would also be opponent coded. An important line of support for opponent coding is that aftereffects increase with adaptor extremity (distance from an average test face) over the full natural range of possible faces. Previous studies have reported that expression aftereffects increase with adaptor extremity. Critically, however, they did not establish the extent of the natural range and so have not ruled out a decrease within that range that could indicate narrowband, multichannel coding. Here we show that expression aftereffects, like identity aftereffects, increase linearly over the full natural range of possible faces and remain high even for impossibly distorted adaptors. These results suggest that facial expression, like face identity, is opponent coded.

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Section: Discussionmentioning

confidence: 99%

Aftereffects support opponent coding of expression.

Rhodes¹,

Pond²,

Jeffery³

et al. 2017

Journal of Experimental Psychology: Human Perception and Perfor

View full text Add to dashboard Cite

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“…Typically, two-pool models have been employed to account for what appears to be opponent processing (e.g. Over, 1971) and have been successfully Consistently, many face after-effects are found to be larger for strong (e.g., extremely large or unusual) than weak adaptors indicating norm-based coding for many facial attributes (Burton, Jeffery, Skinner, Benton, & Rhodes, 2013 results have recently been modeled (Ross et al, 2014) indicating that an exemplar-based model of face-space can account for after-effects.…”

Section: Facial Adaptationmentioning

confidence: 99%

Face-Space: A Unifying Concept in Face Recognition Research

Valentine

Lewis

Hills

2016

Quarterly Journal of Experimental Psychology

183

214

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Phone: +44 (0)207 919 7871.Face-space: A unifying concept. 2 AbstractThe concept of a multi-dimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to Valentine's (1991a) face-space is explained and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms is reviewed. Facespace as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

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“…This raises the possibility that decision-level processes may interact with adaptation-induced perceptual changes, perhaps in non-obvious ways. In a model of face identification decisions, simulations based on both multichannel and opponent-channel encodings of high dimensional face spaces predicted greater shifts in identity boundaries along stimulus trajectories that span an average face than along trajectories that do not (Ross et al, 2013). These simulations suggest that this paradigm is not diagnostic.…”

Section: Larger Shifts In Category Boundaries Along Stimulus Trajementioning

confidence: 87%

“…Alternatively, locations in face space might be encoded by multiple channels, each relatively narrowly-tuned to a sub-region of face space, analogous to the channels thought to underlie the perception of orientation (Giese & Leopold, 2005;Robbins et al, 2007;Ross, Deroche, & Palmeri, 2013;Wallis, 2013;Webster & MacLeod, 2011;Zhao, Seriès, Hancock, & Bednar, 2011). According to this proposal, any dimension of facial variance is encoded by many channels, each responding maximally to some particular value along the dimension and less to values 'higher' or 'lower' than it, with the average face having no unique status.…”

Section: Adaptation To Faces and Other Complex Objects 30mentioning

confidence: 99%

“…While facial appearance is popularly thought to be subject to recalibrative perceptual aftereffects, there is some contention on this point, with some suggesting that these perceptual distortions are better explained as contrastive aftereffects (Ross et al, 2013;Storrs, 2015b;Storrs & Arnold, 2012, 2015bZhao et al, 2011). From a conceptual perspective, this would mean that adaptation-induced distortions of complex form, such as facial appearance, are qualitatively similar to distortions of attributes often described as low-level, such as spatial frequency and orientation (Blakemore & Sutton, 1969;Mitchell & Muir, 1976).…”

Section: Introductionmentioning

confidence: 99%

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Norms are Not the Norm: Testing Theories of Sensory Encoding Using Visual Aftereffects

Storrs¹

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A thesis submitted for the degree of Doctor of Philosophy at the University of Queensland in 2015School of Psychology A B S T R A C TThe goal of visual neuroscience is to explain how patterns of neural activity give rise to visual experiences. Here I use visual aftereffects to explore the computational principles underlying the perception of simple, intermediate, and complex forms (orientations, shapes, and faces). Aftereffects occur when exposure to one stimulus changes the appearance of a subsequent stimulus. In the tilt aftereffect, for example, staring at a left-tilted line can make a vertical line seem briefly to lean to the right. Aftereffects are thought to be caused by neural adaptation -changes in the responsiveness of neurons after prolonged stimulation.Visual aftereffects allow us to probe sensory encoding, because adaptation within different encoding schemes can predict different patterns of perceptual aftereffect. I focus on two theories of encoding prominent in the face recognition literature. According to norm-based accounts, faces are represented in terms of how they deviate from a unique norm, such as the average of all experienced faces. Similar proposals have been raised in other contexts, for example to encode the aspect ratio of shapes. Norm-based encoding can be implemented by a population in which neurons respond increasingly as a stimulus moves further in the neuron's preferred direction, away from a normative value in stimulus space. Alternatively, exemplar-based accounts propose that faces are encoded in terms of their similarity to a number of previously-experienced exemplars. Exemplar-based encoding can be implemented by a population of non-monotonically tuned neurons that prefer particular points in stimulus space, rather than directions.Norm-based and exemplar-based accounts make distinct predictions for the pattern of aftereffects one should experience following adaptation. Norm-based encoding is associated with renormalisation, in which the adapting stimulus appears more 'neutral' or 'average' after prolonged viewing, and the appearances of other stimuli are altered in the same fashion (e.g. after adapting to a male face, all faces should look more feminine).Exemplar-based encoding is associated with 'local repulsion,' in which the adapting stimulus appears unchanged, but differences between it and subsequent stimuli are exaggerated (e.g. after adapting to a male face, a very masculine face should look even more masculine, while an androgynous or female face should look more feminine).Over the past fifteen years, norm-based theories of shape and face encoding have gained traction, ostensibly supported by evidence from aftereffects. In Chapter 1, I review this evidence, and relate it to an older debate concerning the role of norms in orientation perception. I conclude that the evidence for renormalisation in form perception is under-2 3 whelming. In Chapter 2 I empirically address the most recent evidence for orientation renormalisation. I show that these data likely arise from an ...

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Not just the norm: Exemplar-based models also predict face aftereffects

Cited by 51 publications

References 74 publications

Aftereffects support opponent coding of expression.

Aftereffects support opponent coding of expression.

Face-Space: A Unifying Concept in Face Recognition Research

Norms are Not the Norm: Testing Theories of Sensory Encoding Using Visual Aftereffects

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