TY - JOUR
T1 - Temporal and spatial ensemble statistics are formed by distinct mechanisms
AU - Ying, Haojiang
AU - BURNS, EDWIN
AU - Choo, Amanda
AU - Xu, Hong
N1 - Funding Information:
Supported by Nanyang Technological University Research Scholarship (HY), Undergraduate Research Experience on Campus (AC), College of Arts, Humanities and Social Sciences Incentive Scheme (HX), and Ministry of Education - Singapore Academic Research Fund (AcRF) Tier 1 (HX). H. Ying is also supported by the Ministry of Education - China Project of Humanities and Social Sciences ( 19YJC190030 ), the City & University strategy- Soochow University Leading Research Team in Humanities and Social Sciences. Parts of this research (data from Exp 1) were presented at the Annual Meeting of Visual Science Society (VSS), May 2017, St. Pete Beach, Florida. The research reported here forms part of H. Ying's Ph.D. thesis at Nanyang Technological University. All data have been made publicly available via the Open Science Framework (OSF) and can be accessed at https://osf.io/rgdja/ .
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2020/2
Y1 - 2020/2
N2 - Our brains can extract a summary representation of the facial characteristics provided by a group of faces. To date, there has been a lack of clarity as to what calculations the brain is actually performing during this ensemble perception. For example, does ensemble processing average the fiducial points (e.g., distance between the eyes, width of the mouth) and surface characteristics (e.g., skin tone) of a set of faces in a fashion that produces what we call a ‘morph average’ face from the group? Or does ensemble perception extract a general ‘gist average’ of the face set (e.g., these faces are unattractive)? Here, we take advantage of the fact that the ‘morph average’ face derived from a group of faces is more attractive than the ‘gist average’. If ensemble perception is performing morph averaging, then the adaptation aftereffects elicited by a morphed average face from a group should be equivalent to those elicited by the group. By contrast, if ensemble perception reflects gist averaging, then the aftereffects produced by the group should be distinct from those elicited by the more attractive morphed average face. In support of the morph averaging hypothesis, we show that the adaptation aftereffects derived via temporal ensemble perception of a group of faces are equal to those produced by the group’s morphed average face. Moreover, these effects increase as a linear function of increasing attractiveness in the underlying group. We also reveal that spatial ensemble processing is not equal to temporal ensemble processing, but instead reflects the ‘gist’ attractiveness of the group of faces; e.g., these faces are unattractive. Finally, we show that gist averaging of a spatially presented group of faces is abolished when a temporal manipulation is additionally employed; under these circumstances, morph averaging becomes apparent again. In summary, we have shown for the first time that temporal and spatial ensemble statistics reflect qualitatively different perceptual calculations.
AB - Our brains can extract a summary representation of the facial characteristics provided by a group of faces. To date, there has been a lack of clarity as to what calculations the brain is actually performing during this ensemble perception. For example, does ensemble processing average the fiducial points (e.g., distance between the eyes, width of the mouth) and surface characteristics (e.g., skin tone) of a set of faces in a fashion that produces what we call a ‘morph average’ face from the group? Or does ensemble perception extract a general ‘gist average’ of the face set (e.g., these faces are unattractive)? Here, we take advantage of the fact that the ‘morph average’ face derived from a group of faces is more attractive than the ‘gist average’. If ensemble perception is performing morph averaging, then the adaptation aftereffects elicited by a morphed average face from a group should be equivalent to those elicited by the group. By contrast, if ensemble perception reflects gist averaging, then the aftereffects produced by the group should be distinct from those elicited by the more attractive morphed average face. In support of the morph averaging hypothesis, we show that the adaptation aftereffects derived via temporal ensemble perception of a group of faces are equal to those produced by the group’s morphed average face. Moreover, these effects increase as a linear function of increasing attractiveness in the underlying group. We also reveal that spatial ensemble processing is not equal to temporal ensemble processing, but instead reflects the ‘gist’ attractiveness of the group of faces; e.g., these faces are unattractive. Finally, we show that gist averaging of a spatially presented group of faces is abolished when a temporal manipulation is additionally employed; under these circumstances, morph averaging becomes apparent again. In summary, we have shown for the first time that temporal and spatial ensemble statistics reflect qualitatively different perceptual calculations.
KW - Rapid serial visual presentation
KW - Adaptation
KW - Ensemble statistics
KW - Face
KW - Attractiveness
U2 - 10.1016/j.cognition.2019.104128
DO - 10.1016/j.cognition.2019.104128
M3 - Article (journal)
SN - 0010-0277
VL - 195
JO - Cognition
JF - Cognition
M1 - 104128
ER -