Aftereffects support opponent coding of expression.

Abstract

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.

Facial expression coding in children and adolescents with autism: Reduced adaptability but intact norm‐based coding

“…If coding is norm-based, then expression aftereffects should get larger as adaptors get more extreme (i.e., further from the norm) ( Figure 1). This increase reflects the greater activation of channels (which are tuned to extreme values) by more extreme adaptors, resulting in greater reductions in responsiveness and therefore larger aftereffects Rhodes et al, 2017). This pattern has been reported for expression aftereffects in typically developing children and adults (Skinner & Benton, 2010 and holds across the full natural range of possible faces .…”

“…This increase reflects the greater activation of channels (which are tuned to extreme values) by more extreme adaptors, resulting in greater reductions in responsiveness and therefore larger aftereffects (McKone, Jeffery, Boeing, Clifford, & Rhodes, , ; Rhodes et al ., ). This pattern has been reported for expression aftereffects in typically developing children (Burton et al ., ) and adults (Skinner & Benton, , ) and holds across the full natural range of possible faces (Rhodes et al ., ). We used a size change between adapt and test faces and allowed free eye movements, both of which should reduce the contribution of low‐level (retinotopic) adaptation to the observed aftereffects.…”

“…We used a size change between adapt and test faces and allowed free eye movements, both of which should reduce the contribution of low‐level (retinotopic) adaptation to the observed aftereffects. This procedure is widely used to ensure that aftereffects tap higher‐level face‐coding mechanisms (e.g., Ewing, Pellicano, & Rhodes, ; Rhodes et al ., , ).…”

“…Here, we seek to better understand affective processing in autism, by examining the underlying visual coding of facial expressions. In typical populations, facial expressions appear to be adaptively coded as deviations from a norm or average expression in a multidimensional face space ( Figure 1) (Burton, Jeffery, Skinner, Benton, & Rhodes, 2013;Rhodes et al, 2017;Skinner & Benton, 2010. Norm-based coding can be neurally implemented by opponent coding, with pairs of neural populations, tuned to opposite extremes, coding each expression-related dimension in face space.…”

A hierarchical model of social perception: Psychophysical evidence suggests late rather than early integration of visual information from facial expression and body posture

“…They indicate that changes in neuronal sensitivity underlying aftereffects occur in response to isolated physical characteristics of a face rather than the integrated, global conscious percept. Results from psychophysics and monkey electrophysiology suggest that the brain represents facial characteristics, including expressions, as points within a face space centred on a neutral norm (e.g., Cook et al, 2011, Leopold et al, 2006, Leopold et al, 2001, Rhodes et al, 2017, Skinner and Benton, 2010, Webster and MacLeod, 2011). The average norm or origin of the coordinate system is continuously updated to optimally represent the faces an observer encounters, a re-calibration that underlies perceptual aftereffects.…”