“Are you looking at me?” How children’s gaze judgments improve with age

Adults’ judgments of another person’s gaze reflect both sensory (e.g., perceptual) and nonsensory (e.g., decisional) processes. We examined how children’s performance on a gaze categorization task develops over time by varying uncertainty in the stimulus presented to 6- to 11- year-olds (n = 57). We found that younger children responded “direct” over a wider range of gaze deviations. We also found that increasing uncertainty led to an increase in direct responses, across all age groups. A simple model to account for these data revealed that although younger children had a noisier sensory representation of the stimulus, most developmental changes in gaze were because of a change in children’s response criteria (category boundaries). These results suggest that although the core mechanisms for gaze processing are already in place by the age of 6, their development continues across the whole of childhood. (PsycINFO Database Record (c) 2016 APA, all rights reserved

Gaze constancy in upright and inverted faces

This work is supported by Australian Research Council Discovery Project [DP120102589]; CC is supported by an Australian Research Council Future Fellowship

Post-migration living difficulties and poor mental health associated with increased interpretation bias for threat.

Previous research has found associations between mental health difficulties and interpretation biases, including heightened interpretation of threat from neutral or ambiguous stimuli. Building on this research, we explored associations between interpretation biases (positive and negative) and three constructs that have been linked to migrant experience: mental health symptoms (Global Severity Index [GSI]), Post-Migration Living Difficulties (PMLD), and Perceived Ethnic Discrimination Questionnaire (PEDQ). Two hundred thirty students who identified as first- (n = 94) or second-generation ethnic minority migrants (n = 68), and first-generation White migrants (n = 68) completed measures of GSI, PEDQ, and PMLD. They also performed an interpretation bias task using Point Light Walkers (PLW), dynamic stimuli with reduced visual input that are easily perceived as humans performing an action. Five categories of PLW were used: four that clearly depicted human forms undertaking positive, neutral, negative, or ambiguous actions, and a fifth that involved scrambled animations with no clear action or form. Participants were asked to imagine their interaction with the stimuli and rate their friendliness (positive interpretation bias) and aggressiveness (interpretation bias for threat). We found that the three groups differed on PEDQ and PMLD, with no significant differences in GSI, and the three measured were positively correlated. Poorer mental health and increased PMLD were associated with a heightened interpretation for threat of scrambled animations only. These findings have implications for understanding of the role of threat biases in mental health and the migrant experience

Testing the dual-route model of perceived gaze direction: Linear combination of eye and head cues

This work is supported by Australian Research Council Discovery Project [DP120102589 & DP160102239] to CC. IM is supported by a Leverhulme Project Grant RPG-2013-218. YO is supported by a Grant-in-Aid for Research Activity Start-up [15H06456] from the Japan Society for the Promotion of Science. We thank Matthew Patten for his help in data collection

Emotion recognition bias depends on stimulus morphing strategy

Emotion recognition is vital for social interactions, and atypical (or biased) emotion recognition has been linked to mental health disorders including depression and anxiety. However, biases in emotion recognition vary across studies, and it is unclear whether this reflects genuine group differences in psychological processes underlying emotion recognition or differences in methodologies. One common method to measure biases in emotion recognition involves morphing a face between two emotional expressions in different ratios and asking participants to categorise the faces as belonging to one of the two emotion categories (‘direct-morphing’ method). However, this method creates morphed faces that are not ecologically valid. Alternatively, faces may be morphed through a neutral expression (‘morphing-through-neutral’ method), which is more ecologically valid since emotional expressions usually start from a neutral face. To compare these two approaches, we measured emotion recognition biases using two morphing techniques in 136 participants who also completed measures of anxiety (GAD-7) and depression (PHQ-9). Biases obtained using the two methods differed significantly: In the direct-morphing method, participants perceived the central 50% happy/50% angry face as slightly happy, whereas in the morphing-through-neutral method the neutral face was seen as angry. There were no associations between biases and depression or anxiety scores for either morphing method. This study is the first to directly compare emotion recognition biases obtained using two different morphing methods and is a first step towards reconciling discrepancies in the literature. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13414-022-02532-0

Perceiving threat in others: The role of body morphology.

People make judgments of others based on appearance, and these inferences can affect social interactions. Although the importance of facial appearance in these judgments is well established, the impact of the body morphology remains unclear. Specifically, it is unknown whether experimentally varied body morphology has an impact on perception of threat in others. In two preregistered experiments (N = 250), participants made judgments of perceived threat of body stimuli of varying morphology, both in the absence (Experiment 1) and presence (Experiment 2) of facial information. Bodies were perceived as more threatening as they increased in mass with added musculature and portliness, and less threatening as they increased in emaciation. The impact of musculature endured even in the presence of faces, although faces contributed more to the overall threat judgment. The relative contributions of the faces and bodies seemed to be driven by discordance, such that threatening faces exerted the most influence when paired with non-threatening bodies, and vice versa. This suggests that the faces and bodies were not perceived as entirely independent and separate components. Overall, these findings suggest that body morphology plays an important role in perceived threat and may bias real-world judgments

Asymmetric contextual effects in age perception

How old we think someone is determines how we interact with them [1–3], and most people regularly make age judgements based on facial appearance. For example, when assessing the age of a suspect in crime scenes, or in daily tasks such as determining eligibility to buy alcohol or tobacco (for meta-analysis on age perception, see [3]). Given the importance of making accurate facial age estimations, and how frequently we make them, one might assume our perceptual system is precise in judging age. Indeed, early research claimed that people make reliable age estimates, with errors of ±3–4 years [4,5]. However, those studies were limited in the number and quality of their stimuli. Faces change as we grow older, and ageing of facial skin is driven by factors such as gender, genetics, lifestyle, diet, smoking, and consuming drugs and alcohol [6,7]. Therefore, given the large amount of variability in faces, using a small set of test faces potentially biases age estimates to the specific test identities used. More recent work has addressed this issue by using both a larger number of stimuli and a broader sample of participants. In this case, the authors find that estimating age is less reliable than originally proposed with a reported mean error magnitude between ±6 years [8,9] and ±8 years [10]. Taken together, this reveals that people make errors in age judgements even for single faces viewed individually

Cortical distance determines whether flankers cause crowding or the tilt illusion

Differences between target and flanker orientations become exaggerated in the tilt illusion. However, small differences sometimes go unnoticed. This small-angle assimilation shares many similarities with other types of visual crowding but is typically found only with small and/or hard-to-see stimuli. In Experiment 1, we investigated the effect of stimulus visibility on orientation bias using relatively large stimuli. The introduction of visual noise increased the perceived similarity of target and flanker orientations at retinal eccentricities of 4- and 10-; however, small-angle assimilation was found only at 10-. The effects of eccentricity were reduced in Experiment 2, when our stimuli were “M-scaled” for equal cortical coverage. Further support for a cortical substrate was obtained in Experiment 3, in which the effects of target–flanker separation were measured. When biases from all three experiments are expressed as a fraction of the inducing flankers’ angle, and plotted as a function of the approximate cortical separation between the target and its closest flanker, they form a curve like the cross-section of half a Mexican hat. We conclude that the tilt illusion and small-angle assimilation reflect opponent influences on orientation perception. The strength of each influence increases with cortical proximity and stimulus visibility, but the one responsible for assimilation has a lesser extent

Perceived pattern regularity computed as a summary statistic: implications for camouflage

Why do the equally spaced dots in figure 1 appear regularly spaced? The answer ‘because they are’ is naive and ignores the existence of sensory noise, which is known to limit the accuracy of positional localization. Actually, all the dots in figure 1 have been physically perturbed, but in the case of the apparently regular patterns to an extent that is below threshold for reliable detection. Only when retinal pathology causes severe distortions do regular grids appear perturbed. Here, we present evidence that low-level sensory noise does indeed corrupt the encoding of relative spatial position, and limits the accuracy with which observers can detect real distortions. The noise is equivalent to a Gaussian random variable with a standard deviation of approximately 5 per cent of the inter-element spacing. The just-noticeable difference in positional distortion between two patterns is smallest when neither of them is perfectly regular. The computation of variance is statistically inefficient, typically using only five or six of the available dots

Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models.

Human visual experience usually provides ample opportunity to accumulate knowledge about events unfolding in the environment. In typical scene perception experiments, however, participants view images that are unrelated to each other and, therefore, they cannot accumulate knowledge relevant to the upcoming visual input. Consequently, the influence of such knowledge on how this input is processed remains underexplored. Here, we investigated this influence in the context of gaze control. We used sequences of static film frames arranged in a way that allowed us to compare eye movements to identical frames between two groups: a group that accumulated prior knowledge relevant to the situations depicted in these frames and a group that did not. We used a machine learning approach based on hidden Markov models fitted to individual scanpaths to demonstrate that the gaze patterns from the two groups differed systematically and, thereby, showed that recently accumulated prior knowledge contributes to gaze control. Next, we leveraged the interpretability of hidden Markov models to characterize these differences. Additionally, we report two unexpected and interesting caveats of our approach. Overall, our results highlight the importance of recently acquired prior knowledge for oculomotor control and the potential of hidden Markov models as a tool for investigating it