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It is becoming increasingly common for face morphs (weighted combinations of two people's photographs) to be submitted for inclusion in an official document, such as a passport. These images may sufficiently resemble both individuals that they can be used by either person in a 'fraudulently obtained genuine' document. Problematically, people are poor at detecting face morphs and there is limited evidence that this can be improved. Here, we tested whether the 'pairs training effect' (working in pairs, which we know improves unfamiliar face matching) can improve face morph detection. We found morph detection was more accurate when working in a pair. Further, the lower performer in the pair maintained this benefit when completing the task again individually. We conclude that the pairs training effect translates to face morph detection, and these findings have important implications for improving the detection of face morphs at the initial application stage. [ABSTRACT FROM AUTHOR]

Summary: Low‐quality images are problematic for face identification, for example, when the police identify faces from CCTV images. Here, we test whether face averages, comprising multiple poor‐quality images, can improve both human and computer recognition. We created averages from multiple pixelated or nonpixelated images and compared accuracy using these images and exemplars. To provide a broad assessment of the potential benefits of this method, we tested human observers (n = 88; Experiment 1), and also computer recognition, using a smartphone application (Experiment 2) and a commercial one‐to‐many face recognition system used in forensic settings (Experiment 3). The third experiment used large image databases of 900 ambient images and 7,980 passport images. In all three experiments, we found a substantial increase in performance by averaging multiple pixelated images of a person's face. These results have implications for forensic settings in which faces are identified from poor‐quality images, such as CCTV. [ABSTRACT FROM AUTHOR]

Photographs of people are commonly said to be 'good likenesses' or 'poor likenesses', and this is a concept that we readily understand. Despite this, there has been no systematic investigation of what makes an image a good likeness, or of which cognitive processes are involved in making such a judgement. In three experiments, we investigate likeness judgements for different types of images: natural images of film stars (Experiment 1), images of film stars from specific films (Experiment 2), and iconic images and face averages (Experiment 3). In all three experiments, participants rated images for likeness and completed speeded name verification tasks. We consistently show that participants are faster to identify images which they have previously rated asa good likeness compared to a poor likeness. We also consistently show that the more familiar we are with someone, the higher likeness rating we give to all images of them. A key finding is that our perception of likeness is idiosyncratic (Experiments 1 and 2), and can be tied to our specific experience of each individual (Experiment 2). We argue that likeness judgements require a comparison between the stimulus and our own representation of the person, and that this representation differs according to our prior experience with that individual. This has theoretical implications for our understanding of how we represent familiar people, and practical implications for how we go about selecting images for identity purposes such as photo-ID. [ABSTRACT FROM AUTHOR]

While sustained-release buprenorphine (BSR) is used as a long-lasting opioid analgesic in common marmosets (Callithrix jacchus), there are no published studies on pharmaceutical-grade extended-release buprenorphine options such as Ethiqa XR (EXR) for this species. However, BSR is a compounded product and has been reported to cause injection site reactions in multiple species, including marmosets. Additionally, now with the availability of EXR, a pharmaceutical-grade veterinary product, the use of BSR in laboratory animals is not compliant with the Guide for the Care and Use of Laboratory Animals (Guide) unless scientifically justified and approved by the IACUC. We compared pharmacokinetic and safety profiles of BSR (0.15 mg/kg) and EXR (0.1–0.2 mg/kg) administered subcutaneously to adult marmosets. Blood was collected by venipuncture of the saphenous vein at multiple time points (0.25–72 h) and analyzed by liquid chromatography-tandem mass spectrometry (LC–MS/MS). EXR between 0.1 and 0.2 mg/kg resulted in a dose-dependent increase in Cmax (1.43–2.51 ng/mL) and were not statistically different from BSR (1.82 ng/mL). Tmax, lambdaz, and t1/2 were not statistically different between formulations. Mean plasma buprenorphine concentrations for BSR and EXR exceeded the therapeutic threshold (0.1 ng/mL) within 0.25 h and lasted for > 72 h. Mild sedation, but neither respiratory depression nor ataxia, was observed for both formulations. BSR injection sites had significantly higher histopathological scores compared to EXR. Video recordings for monitoring drug-induced behavioral changes showed increased animal activity levels after BSR and EXR versus saline controls. Norbuprenorphine, a buprenorphine metabolite associated with respiratory depression, was detected in the plasma after BSR and EXR administration as well as by in vitro liver microsome assays. In conclusion, we recommend using EXR over BSR as a long-lasting buprenorphine analgesic in marmosets because EXR is a pharmaceutical-grade formulation that is compliant with FDA guidelines and the Guide as well as exhibits comparable PK and safety profiles as BSR. [ABSTRACT FROM AUTHOR]

Researchers have suggested that dogs are able to recognise human faces, but conclusive evidence has yet to be found. Experiment 1 of this study investigated whether dogs can recognise humans using visual information from the face/head region, and whether this also occurs in conditions of suboptimal visibility of the face. Dogs were presented with their owner's and a stranger's heads, protruding through openings of an apparatus in opposite parts of the experimental setting. Presentations occurred in conditions of either optimal or suboptimal visibility; the latter featured non-frontal orientation, uneven illumination and invisibility of outer contours of the heads. Instances where dogs approached their owners with a higher frequency than predicted by chance were considered evidence of recognition. This occurred only in the optimal condition. With a similar paradigm, Experiment 2 investigated which of the alterations in visibility that characterised the suboptimal condition accounted for dogs' inability to recognise owners. Dogs approached their owners more frequently than predicted by chance if outer head contours were visible, but not if heads were either frontally oriented or evenly illuminated. Moreover, male dogs were slightly better at recognition than females. These findings represent the first clear demonstration that dogs can recognise human faces and that outer face elements are crucial for such a task, complementing previous research on human face processing in dogs. Parallels with face recognition abilities observed in other animal species, as well as with human infants, point to the relevance of these results from a comparative standpoint. [ABSTRACT FROM AUTHOR]

A wealth of studies have shown that humans are remarkably poor at determining whether two face images show the same person or not (face matching). Given the prevalence of photo-ID, and the fact that people employed to check photo-ID are typically unfamiliar with the person pictured, there is a need to improve unfamiliar face matching accuracy. One method of improvement is to have participants complete the task in a pair, which results in subsequent improvements in the low performer ("the pairs training effect"). Here, we sought to replicate the original finding, to test the longevity of the pairs training effect, and to shed light on the potential underlying mechanisms. In two experiments, we replicated the pairs training effect and showed it is maintained after a delay (Experiment 1). We found no differences between high and low performers in confidence (Experiment 1) or response times (Experiment 2), and the content of the pairs' discussions (Experiment 2) did not explain the results. The pairs training effect in unfamiliar face matching is robust, but the mechanisms underlying the effects remain as yet unexplained. [ABSTRACT FROM AUTHOR]

Common variants in the MicroRNA 137 host gene MIR137HG and its adjacent gene DPYD have been associated with schizophrenia risk and the latest Psychiatric Genomics Consortium (PGC). Genome-Wide Association Study on schizophrenia has confirmed and extended these findings. To elucidate the association of schizophrenia risk-associated SNPs in this genomic region, we examined the expression of both mature and immature transcripts of the miR-137 host gene (MIR137HG) in the dorsolateral prefrontal cortex (DLPFC) and subgenual anterior cingulate cortex (sgACC) of postmortem brain samples of donors with schizophrenia and psychiatrically-unaffected controls using qPCR and RNA-Seq approaches. No differential expression of miR-137, MIR137HG, or its transcripts was observed. Two schizophrenia risk-associated SNPs identified in the PGC study, rs11165917 (DLPFC: P = 2.0e-16; sgACC: P = 6.4e-10) and rs4274102 (DLPFC: P = 0.036; sgACC: P = 0.002), were associated with expression of the MIR137HG long non-coding RNA transcript MIR137HG-203 (ENST00000602672.2) in individuals of European ancestry. Carriers of the minor (risk) allele of rs11165917 had significantly lower expression of MIR137HG-203 compared with those carrying the major allele. However, we were unable to validate this result by short-read sequencing of RNA extracted from DLPFC or sgACC tissue. This finding suggests that immature transcripts of MIR137HG may contribute to genetic risk for schizophrenia., (Published by Oxford University Press 2024.)

ChatGPT's large language model, GPT-4V, has been trained on vast numbers of image-text pairs and is therefore capable of processing visual input. This model operates very differently from current state-of-the-art neural networks designed specifically for face perception and so I chose to investigate whether ChatGPT could also be applied to this domain. With this aim, I focussed on the task of face matching, that is, deciding whether two photographs showed the same person or not. Across six different tests, ChatGPT demonstrated performance that was comparable with human accuracies despite being a domain-general 'virtual assistant' rather than a specialised tool for face processing. This perhaps surprising result identifies a new avenue for exploration in this field, while further research should explore the boundaries of ChatGPT's ability, along with how its errors may relate to those made by humans., Competing Interests: Declaration of Conflicting InterestsThe author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

First impressions based on facial appearance affect our behaviour towards others. Since the same face will appear different across images, over time, and so on, our impressions may not be equally weighted across exposures but are instead disproportionately influenced by earlier or later instances. Here, we followed up on previous work which identified an anchoring effect, whereby higher attractiveness ratings were given to a person after viewing naturally varying images of their face presented in descending (high-to-low), rather than ascending (low-to-high), order of attractiveness of these images. In Experiment 1 ( n  = 301), we compared these 'descending' and 'ascending' conditions for unfamiliar identities by presenting six-image sequences. Although we found higher attractiveness ratings for the 'descending' condition, this small effect equated to only 0.22 points on a 1-7 response scale. In Experiment 2 ( n  = 307), we presented these six-image sequences in a random order and found no difference in attractiveness ratings given to these randomly ordered sequences when compared with those resulting from both our 'descending' and 'ascending' conditions. Further, we failed to detect an influence of the earlier images in these random sequences on attractiveness ratings. Taken together, we found no compelling evidence that anchoring could have an effect on real-world impression formation., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background/objectives: It is vital to identify children whose weight status means that they may benefit from medical or behavioural support, but adult visual judgements of child weight status are inaccurate, and children are seldom routinely weighed and measured. Consequently, there is a need for validated visual tools for use in training, communication, and interventions relating to child weight., Methods: This paper presents validation data for a set of innovative photo-realistic colour body size scales depicting boys and girls aged 4-5 and 10-11. Each age- and gender-specific scale consists of 7 figures based on three-dimensional (3D) scans of 388 children to accurately represent the change in body size caused by changing adiposity. To assess scale validity, 238 adult participants (105 men, 132 women, 1 non-binary individual) undertook two tasks: rating figure adiposity using a visual analogue scale and ranking figures in ascending order of adiposity (OSF Reference: gdp9j)., Results: Participants accurately estimated the relative adiposity of each figure, i.e., they were able to tell the difference between figures and correctly rank them by size. This demonstrates scale validity for use in body size tasks. One hundred and fifty-one participants also provided 3-day test-retest data, which demonstrates excellent short-term reliability., Conclusions: Overall, the MapMe child body size scales provide an anthropometrically accurate, valid, reliable, and usable tool for size-related tasks and communication with adults regarding child weight.

Within the domain of face processing, researchers have been interested in quantifying the relationship between objective (i.e., performance on laboratory tests of recognition and matching) and subjective measures of ability (typically, self-report questionnaires). Put simply, do people show high levels of metacognitive insight into their own abilities with faces? Although several studies have suggested that the association between these two types of measures may only be moderate, there remain several important issues that require consideration before this question can be sensibly investigated. First, specificity is needed regarding both objective and subjective measurements because both tend to span a wide range of potentially separable abilities. Second, experimental tasks appear to focus on different contexts to those tapped in self-report questionnaire items. Third, recent issues with statistical approaches and visualisation can result in numerical artefacts and misinterpretations. Finally, the sizes of population-level insights suggested by recent work provide only limited information regarding individuals within these populations, and so researchers aiming to identify people at the extremes of ability must be careful when drawing conclusions. Taken together, we argue that more attention to these issues is needed when attempting to investigate metacognitive insight within this domain., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Facial first impressions influence jurors in both laboratory experiments and real courtrooms. Often, more attractive defendants are perceived as less guilty and receive more lenient sentences. However, the type of crime under consideration, as well as the ecological validity of the stimuli presented, may determine the nature of this bias. Here, extending previous work, we considered three crime types (robbery, sexual assault, and murder) and utilised short video clips of male defendants, accompanied by real-world crime descriptions. Crucially, we varied attractiveness by presenting a large set of identities, in comparison with the typical use of one "high" and one "low" attractive face. Using null hypothesis significance testing, we found no evidence that either attractiveness or crime type influenced guilt perceptions. Taking a Bayesian perspective, our results provided some evidence that more attractive defendants were rated as less guilty of murder but more guilty of sexual assault, with no bias observed for robbery. Importantly, however, none of these effects had high certainty and all were small in size. By comparing the extremes of attractiveness, we again found inconclusive evidence of any attractiveness effects, with small differences in all cases. The implications for this departure from previous findings are discussed in terms of ecological validity and the need to consider attractiveness as a continuous rather than binary measure., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Perceiving facial attractiveness is an important behaviour across psychological science due to these judgments having real-world consequences. However, there is little consensus on the measurement of this behaviour, and practices differ widely. Research typically asks participants to provide ratings of attractiveness across a multitude of different response scales, with little consideration of the psychometric properties of these scales. Here, we make psychometric comparisons across nine different response scales. Specifically, we analysed the psychometric properties of a binary response, a 0-100 scale, a visual analogue scale, and a set of Likert scales (1-3, 1-5, 1-7, 1-8, 1-9, 1-10) as tools to measure attractiveness, calculating a range of commonly used statistics for each. While certain properties suggested researchers might choose to favour the 1-5, 1-7 and 1-8 scales, we generally found little evidence of an advantage for one scale over any other. Taken together, our investigation provides consideration of currently used techniques for measuring facial attractiveness and makes recommendations for researchers in this field., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

There has been an assumption in the literature that the three concepts of ideal body shape (personal ideal, cultural ideal, and the most attractive body shape) are effectively the same percept. To test this presumption, 554 participants completed either a between- or within-subjects condition using a matrix of 32 bodies varying in two dimensions: muscle and adiposity. Three separate groups of participants were recruited to the between-subjects design and made only one of these judgements, whilst participants in the within-subjects version completed all three of these judgments. These bodies are based on 3D scans of 221 women's bodies and so accurately represent the change in size and shape caused by changing body composition. The participants also completed a set of psychometric questionnaires to index the degree to which external concepts of body image have been internalised. The results show that in both conditions, all three judgements collapse onto the same average preferred body shape, with low adiposity and relatively high muscularity. However, this masked systematic differences in responses between personal ideals and the other body judgements, which may be explained by a difference in how information directly related to oneself is processed relative to more abstract third person judgements., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Deciding whether two face photographs depict the same person or not can be a challenging task, and there are substantial individual differences in face matching ability. Far less is known about differences in metacognitive ability; that is, how well people can estimate the quality of their own face matching judgements. The purpose of this Registered Report was to determine the relationship between first-order performance in a face matching task, and three metacognitive measures: metacognitive sensitivity (the information exploited by metacognition), metacognitive efficiency (the quality of metacognitive processing itself), and metacognitive bias (the overall tendency towards high or low confidence). Participants completed a 200-trial unfamiliar face matching task, providing a second-order (metacognitive) confidence rating after each first-order (cognitive) response. Cognitive performance and metacognitive sensitivity showed a substantial positive association ( r s  = .60), suggesting that they were based on overlapping information, with poorer performers having lower quality information available. Once these differences in the information available to metacognition were accounted for, the quality of metacognitive processing itself (metacognitive efficiency) did not vary systematically with cognitive performance ( r s  = .00). Moreover, poor performers were not less or more confident overall than good performers, as cognitive performance and metacognitive bias did not correlate significantly ( r s  = .11). These findings allow us to move beyond consideration of group-level insight and inform regarding individual differences in cognitive and metacognitive abilities., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Introduction: To determine men's body ideals and the factors that influence these choices, this study used a matrix of computer generated (CG) male bodies (based on an analysis of 3D scanned real bodies) which independently varied in fat and muscle content., Methods: Two hundred and fifty-eight male participants completed a range of psychometric measures to index body concerns and body ideal internalization and then chose the CG body that best reflected their own current body, as well as the body that reflected their personal ideal. A subset of participants was then retested to check that these judgements were stable over time., Results: While judgements of the ideal body seem to be influenced by a shared appearance ideal, the degree to which this ideal was internalized showed significant variability between participants. The effect of this internalization was reflected in the difference between the estimated current body and the ideal., Discussion: Higher internalization led to a preference for higher muscle and lower fat content. This preference was most marked for fat content, although reducing adiposity also made the underlying musculature more salient. Additionally, the ideal body composition was modulated by the composition the participant believed his current body had (i.e., it seemed that a participant's ideal body was anchored by what they believed to be their current body and what change was possible from this starting point)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Groves, Ridley, Cornelissen, Maalin, Mohamed, Kramer, McCarty, Tovée and Cornelissen.)

Background: Although researchers have begun to consider metacognitive insight during face matching, little is known about the underlying mechanism. Here, I investigated whether objective ability, as well as self-assessed ability, were able to predict metacognitive performance, that is, the ability to differentiate correct and incorrect responses in terms of confidence. In addition, I considered whether a training intervention resulted in improvements to both face matching performance and metacognitive insight., Methods: In this experiment ( N = 220), participants completed a face matching task, with either a diagnostic feature training course or a control course presented at the halfway point. In addition, a second face matching task, as well as a self-report questionnaire regarding ability, were completed to provide measures of objective and self-assessed ability respectively., Results: Higher self-assessed ability with faces, as well as higher objective ability with face matching, predicted better metacognitive performance, i.e ., greater confidence in correct, in comparison with incorrect, responses. This pattern of results was evident both when objective ability was measured through performance on the same task used to measure metacognitive insight and when a different task was used. Finally, the training intervention failed to produce improvements in face matching performance and showed no evidence of altering metacognitive ability., Discussion: The current work begins to address the mechanism underlying individual differences in metacognitive insight during face matching. Although support was provided for a competence-based account, where better face matchers showed greater performance on the task and were more successful in monitoring their performance, further work might focus on decoupling task performance and competence in order to more conclusively explain why some people are more insightful than others., Competing Interests: Robin S. S. Kramer is an Academic Editor for PeerJ., (© 2023 Kramer.)

We used attractiveness judgements as a proxy to visualize the ideal female and male body for male and female participants and investigated how individual differences in the internalization of cultural ideals influence these representations. In the first of two studies, male and female participants judged the attractiveness of 242 male and female computer-generated bodies which varied independently in muscle and adipose. This allowed us to map changes in attractiveness across the complete body composition space, revealing single peaks for the attractiveness of both men and women. In the second study, we asked our participants to choose the most attractive male and female bodies in a method of adjustment task in which they could independently vary muscle and adipose to create the most attractive body. We asked whether individual differences in internalization of cultural ideals, drive for muscularity, eating disorder symptomatology and depressive symptoms could systematically shift the location of peak attractiveness in body composition space. We found a clear preference by both genders for a male body with high muscle and low adipose, and a toned, low adipose female body. The degree of internalization of cultural ideals predicted large individual differences in the composition of the most attractive bodies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ridley, Cornelissen, Maalin, Mohamed, Kramer, McCarty and Tovée.)

Facial first impressions are known to influence how we behave towards others. As a result of the COVID-19 pandemic, we often view incomplete faces due to the commonplace wearing of face masks. Previous research has shown that perceptions of attractiveness are often increased due to these coverings, with initial evidence suggesting that this may be caused by viewers using a mental representation of the average face to complete any missing information. Here, we directly address this hypothesis by presenting participants with incomplete faces (either the lower or upper half removed) and asking them to decide how they thought the actual, full face looked. Participants were able to manipulate the missing half of the face onscreen by increasing or decreasing the averageness of its shape. Our results demonstrated that participants did not select the original versions of the faces but instead chose more average versions when manipulating both the lower and upper face. Further, the typicality of the original image influenced responses, with less typical faces (in comparison with more typical ones) being completed using an even more average version of the missing half of the faces. Taken together, these findings provide the first direct evidence that people utilise an average/typical internal representation when inferring information about incomplete faces. This result has theoretical importance in terms of visual perception, as well as real-world relevance in a time where face masks are commonplace due to the COVID-19 pandemic., (© 2022. The Author(s).)

Kruger and Dunning (1999) described a metacognitive bias in which insight into performance is linked to competence: poorer performers are less aware of their mistakes than better performers. Competence-based insight has been argued to apply generally across task domains, including a recent report investigating social cognition using a variety of face-matching tasks. Problematically, serious statistical and methodological criticisms have been directed against the traditional method of analysis used by researchers in this field. Here, we further illustrate these issues and investigate new sources of insight within unfamiliar face matching. Over two experiments (total N = 1077), where Experiment 2 was a preregistered replication of the key findings from Experiment 1, we found that insight into performance was multi-faceted. Participants demonstrated insight which was not based on competence, in the form of accurate updating of estimated performance. We also found evidence of insight which was based on competence: the difference in confidence on correct versus incorrect trials increased with competence. By providing ways that we can move beyond problematic, traditional approaches, we have begun to reveal a more realistic story regarding the nature of insight into face perception., (© 2022 The British Psychological Society.)

Physiologic changes during development, aging, and pregnancy may affect clinical parameters. Previously available reference values have been based on samples that may include wild and captive marmosets, with little representation of geriatric or pregnant animals. Establishing reference values under various conditions would support better recognition of pathologic conditions in marmosets. One hundred and forty-seven (70 males and 77 females) healthy marmosets from a research colony were included in this study. Exclusion criteria were abnormal physical exam findings at the time of blood sampling, chronic medications, or clinical or pathologic evidence of disease. Reference intervals were calculated for serum chemistry and hematology. Using metadata, samples were classified based on age, sex, colony source and pregnancy status. Multiple tests indicated significant differences with varying effect sizes, indicating that developing reference intervals based on metadata can be useful. Across all the comparisons, medium or large effect sizes were observed most frequently in blood urea nitrogen (BUN), calcium, total protein, alkaline phosphatase (ALP), weight and serum albumin. We report normative clinical pathologic data for captive common marmosets through all life stages and reproductive status. Significant differences were observed in most parameters when stratifying data based on age, sex, colony source, or pregnancy, suggesting that developing reference intervals considering this information is important for clinicians.

Psychological concerns are frequently indexed by psychometric questionnaires but the mental representations that they seek to quantify are difficult to visualise. We used a set of questionnaires designed to measure men's concept of their bodies including: the Drive for Muscularity Scale (DMS; McCreary & Sasse, 2000), the Perceived Sociocultural Pressures Scale (PSPS; Stice, Nemeroff, & Shaw, 1996a), the Body Appreciation Scale (BAS-2; Tylka & Wood-Barcalow, 2015), and the Sociocultural Attitudes Towards Appearance Questionnaire-3 (SATAQ-3; Thompson, van den Berg, Roehrig, Guarda, & Heinberg, 2004). We combined their use with an interactive 3D modelling programme to allow men to create computer-generated representations of their ideal bodies. We used a principal component analysis to extract those shape components of our participants' CGI ideal bodies that were predicted by the questionnaires and reconstructed the body shapes that these questionnaires were capturing. Moving from the lowest to the highest score on both the DMS and SATAQ corresponded with changes in muscularity, particularly muscle mass and definition. This approach allows us to demonstrate the actual body features that are being captured by a particular questionnaire., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case-control comparisons detected modest expression differences that were correlated across disorders. Case-case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

Models of social evaluation aim to capture the information people use to form first impressions of unfamiliar others. However, little is currently known about the relationship between perceived traits across gender. In Study 1, we asked viewers to provide ratings of key social dimensions (dominance, trustworthiness, etc.) for multiple images of 40 unfamiliar identities. We observed clear sex differences in the perception of dominance-with negative evaluations of high dominance in unfamiliar females but not males. In Study 2, we used the social evaluation context to investigate the key predictions about the importance of pictorial information in familiar and unfamiliar face processing. We compared the consistency of ratings attributed to different images of the same identities and demonstrated that ratings of images depicting the same familiar identity are more tightly clustered than those of unfamiliar identities. Such results imply a shift from image rating to person rating with increased familiarity, a finding which generalises results previously observed in studies of identification.

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Researchers have long been interested in how social evaluations are made based upon first impressions of faces. It is also important to consider the level of agreement we see in such evaluations across raters and what this may tell us. Typically, high levels of inter-rater agreement for facial judgements are reported, but the measures used may be misleading. At present, studies commonly report Cronbach's α as a way to quantify agreement, although problematically, there are various issues with the use of this measure. Most importantly, because researchers treat raters as items, Cronbach's α is inflated by larger sample sizes even when agreement between raters is fixed. Here, we considered several alternative measures and investigated whether these better discriminate between traits that were predicted to show low (parental resemblance), intermediate (attractiveness, dominance, trustworthiness), and high (age, gender) levels of agreement. Importantly, the level of inter-rater agreement has not previously been studied for many of these traits. In addition, we investigated whether familiar faces resulted in differing levels of agreement in comparison with unfamiliar faces. Our results suggest that alternative measures may prove more informative than Cronbach's α when determining how well raters agree in their judgements. Further, we found no apparent influence of familiarity on levels of agreement. Finally, we show that, like attractiveness, both trustworthiness and dominance show significant levels of private taste (personal or idiosyncratic rater perceptions), although shared taste (perceptions shared with other raters) explains similar levels of variance in people's perceptions. In conclusion, we recommend that researchers investigating social judgements of faces consider alternatives to Cronbach's α but should also be prepared to examine both the potential value and origin of private taste as these might prove informative., Competing Interests: The authors have declared that no competing interests exist.

It has been known for many years that identifying familiar faces is much easier than identifying unfamiliar faces, and that this familiar face advantage persists across a range of tasks. However, attempts to understand face familiarity have mostly used a binary contrast between 'familiar' and 'unfamiliar' faces, with no attempt to incorporate the vast range of familiarity we all experience. From family members to casual acquaintances and from personal to media exposure, familiarity is a more complex categorisation than is usually acknowledged. Here we model levels of familiarity using a generic statistical analysis (PCA combined with LDA) computed over some four thousand naturally occurring images that include a large variation in the numbers of images for each known person. Using a strong test of performance with entirely novel, untrained everyday images, we show that such a model can simulate widely documented effects of familiarity in face recognition and face matching, and offers a natural account of the internal feature advantage for familiar faces. Furthermore, as with human viewers, the benefits of familiarity seem to accrue from being able to extract consistent information across different photos of the same face. We argue that face familiarity is best understood as reflecting increasingly robust statistical descriptions of idiosyncratic within-person variability. Understanding how faces become familiar appears to rely on both bottom-up statistical image descriptions (modelled here with PCA), and top-down processes that cohere superficially different images of the same person (modelled here with LDA)., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Photographs of people are commonly said to be 'good likenesses' or 'poor likenesses', and this is a concept that we readily understand. Despite this, there has been no systematic investigation of what makes an image a good likeness, or of which cognitive processes are involved in making such a judgement. In three experiments, we investigate likeness judgements for different types of images: natural images of film stars (Experiment 1), images of film stars from specific films (Experiment 2), and iconic images and face averages (Experiment 3). In all three experiments, participants rated images for likeness and completed speeded name verification tasks. We consistently show that participants are faster to identify images which they have previously rated asa good likeness compared to a poor likeness. We also consistently show that the more familiar we are with someone, the higher likeness rating we give to all images of them. A key finding is that our perception of likeness is idiosyncratic (Experiments 1 and 2), and can be tied to our specific experience of each individual (Experiment 2). We argue that likeness judgements require a comparison between the stimulus and our own representation of the person, and that this representation differs according to our prior experience with that individual. This has theoretical implications for our understanding of how we represent familiar people, and practical implications for how we go about selecting images for identity purposes such as photo-ID., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Viewers are highly accurate at recognizing sex and race from faces-though it remains unclear how this is achieved. Recognition of familiar faces is also highly accurate across a very large range of viewing conditions, despite the difficulty of the problem. Here we show that computation of sex and race can emerge incidentally from a system designed to compute identity. We emphasize the role of multiple encounters with a small number of people, which we take to underlie human face learning. We use highly variable everyday 'ambient' images of a few people to train a Linear Discriminant Analysis (LDA) model on identity. The resulting model has human-like properties, including a facility to cohere previously unseen ambient images of familiar (trained) people-an ability which breaks down for the faces of unknown (untrained) people. The first dimension created by the identity-trained LDA classifies both familiar and unfamiliar faces by sex, and the second dimension classifies faces by race-even though neither of these categories was explicitly coded at learning. By varying the numbers and types of face identities on which a further series of LDA models were trained, we show that this incidental learning of sex and race reflects covariation between these social categories and face identity, and that a remarkably small number of identities need be learnt before such incidental dimensions emerge. The task of learning to recognize familiar faces is sufficient to create certain salient social categories. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Premise of the Study: The common reed (Phragmites australis), one of the most widely distributed of all angiosperms, uses its rhizomes (underground stems) to invade new territory, making it one of the most successful weedy species worldwide. Characterization of the rhizome transcriptome and proteome is needed to identify candidate genes and proteins involved in rhizome growth, development, metabolism, and invasiveness., Methods: We employed next-generation sequencing technologies including 454 and Illumina platforms to characterize the reed rhizome transcriptome and used quantitative proteomics techniques to identify the rhizome proteome., Key Results: Combining 336514 Roche 454 Titanium reads and 103350802 Illumina paired-end reads in a de novo hybrid assembly yielded 124450 unique transcripts with an average length of 549 bp, of which 54317 were annotated. Rhizome-specific and differentially expressed transcripts were identified between rhizome apical tips (apical meristematic region) and rhizome elongation zones. A total of 1280 nonredundant proteins were identified and quantified using GeLC-MS/MS based label-free proteomics, where 174 and 77 proteins were preferentially expressed in the rhizome elongation zone and apical tip tissues, respectively. Genes involved in allelopathy and in controlling development and potentially invasiveness were identified., Conclusions: In addition to being a valuable sequence and protein data resource for studying plant rhizome species, our results provide useful insights into identifying specific genes and proteins with potential roles in rhizome differentiation, development, and function.