Bidirectional Gender Face Aftereffects: Evidence Against Normative Facial Coding.

Facial appearance can be altered, not just by restyling but also by sensory processes. Exposure to a female face can, for instance, make subsequent faces look more masculine than they would otherwise. Two explanations exist. According to one, exposure to a female face renormalizes face perception, making that female and all other faces look more masculine as a consequence-a unidirectional effect. According to that explanation, exposure to a male face would have the opposite unidirectional effect. Another suggestion is that face gender is subject to contrastive aftereffects. These should make some faces look more masculine than the adaptor and other faces more feminine-a bidirectional effect. Here, we show that face gender aftereffects are bidirectional, as predicted by the latter hypothesis. Images of real faces rated as more and less masculine than adaptors at baseline tended to look even more and less masculine than adaptors post adaptation. This suggests that, rather than mental representations of all faces being recalibrated to better reflect the prevailing statistics of the environment, mental operations exaggerate differences between successive faces, and this can impact facial gender perception.

Why the long face? The importance of vertical image structure for biological "barcodes" underlying face recognition.

Humans are experts at face recognition. The mechanisms underlying this complex capacity are not fully understood. Recently, it has been proposed that face recognition is supported by a coarse-scale analysis of visual information contained in horizontal bands of contrast distributed along the vertical image axis-a biological facial "barcode" (Dakin & Watt, 2009). A critical prediction of the facial barcode hypothesis is that the distribution of image contrast along the vertical axis will be more important for face recognition than image distributions along the horizontal axis. Using a novel paradigm involving dynamic image distortions, a series of experiments are presented examining famous face recognition impairments from selectively disrupting image distributions along the vertical or horizontal image axes. Results show that disrupting the image distribution along the vertical image axis is more disruptive for recognition than matched distortions along the horizontal axis. Consistent with the facial barcode hypothesis, these results suggest that human face recognition relies disproportionately on appropriately scaled distributions of image contrast along the vertical image axis.

Uncertainty information that is irrelevant for report impacts confidence judgments.

Humans intuitively evaluate their decisions with different levels of confidence. Although confidence and sensitivity are highly correlated, recent evidence has shown that confidence is disproportionately impacted by signal variability (e.g., de Gardelle & Mamassian, 2015; Spence, Dux, & Arnold, 2016; Zylberberg, Roelfsema, & Sigman, 2014). Previous studies investigating this issue have involved manipulations of variability in the components of the decision stimulus itself. Here, in 3 experiments, we investigated whether discrete variability, from a visual stimulus that does not require a response, can affect confidence in a secondary visual task. Participants made brightness or direction judgments about the dots in motion kinematograms with different ranges of motion around the global direction. Specifically, after viewing pairs of dot-motion displays, participants received a postcue at the end of each trial asking them to report either the relative brightness or the direction of the second display relative to the first. Importantly, the range of motion directions was irrelevant to the task when individuals were required to judge the brightness of the dots. We found that a larger range of motion directions reduced participants' confidence in their brightness judgments but with no corresponding change in performance. These findings suggest that confidence is impacted not only by variability directly relevant to the decision stimulus itself but also by variability in the context in which the decision evidence was encoded. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Computations underlying confidence in visual perception.

Humans intuitively evaluate their decisions by forming different levels of confidence. Despite being highly correlated, decisional confidence and sensitivity can be differentiated. The computational processes underlying this remain unknown. Here we find that, for visual judgments concerning global direction, signal range has a greater impact on confidence than it does sensitivity. We equated sensitivity for stimuli containing different degrees of directional variability. This failed, however, to equate confidence-participants were less confident when judging more variable signals despite constant sensitivity. When stimuli were instead calibrated to equate confidence, participants were more sensitive when judging more variable signals. Directional range had no impact on an unrelated judgment of brightness, helping to establish that these results cannot be attributed to a simple decisional confound. Our complementary results show that directional sensitivity and decisional confidence rely on independent transformations of sensory input. We propose that confidence will generally be shaped by the range of differently tuned neural mechanisms responsive to input during evidence accumulation, with this having a lesser impact on sensitivity. (PsycINFO Database Record