No evidence for an other-race effect in dominance and trustworthy judgements from faces.

A variety of evidence shows that social categorization of people based on their race can lead to stereotypical judgements and prejudicial behaviour. Here, we explore the extent to which trait judgements of faces are influenced by race. To address this issue, we measured the reliability of first impressions for own-race and other-race faces in Asian and White participants. Participants viewed pairs of faces and were asked to indicate which of the two faces was more dominant or which of the two faces was more trustworthy. We measured the consistency (or reliability) of these judgements across participants for own-race and other-races faces. We found that judgements of dominance or trustworthiness showed similar levels of reliability for own-race and other-race faces. Moreover, an item analysis showed that the judgements on individual trials were very similar across participants from different races. Next, participants made overall ratings of dominance and trustworthiness from own-race and other-race faces. Again, we found that there was no evidence for an ORE. Together, these results provide a new approach to measuring trait judgements of faces and show that in these conditions there is no ORE for the perception of dominance and trustworthiness.

Substratifying the risk of covert malignancy in significant rectal polyps: Outcomes from a specialist multidisciplinary team (MDT).

AIM: A treatment strategy for patients with a significant polyp or early colon cancer (SPECC) of the rectum presents a challenge due to the significant rate of covert malignancy and lack of standardized assessment. For this reason, NICE recommends multidisciplinary meetings to improve outcomes. The primary aim of the present study was to report the performance of our specialist early rectal cancer (SERC) multidisciplinary team (MDT) in correctly substratifying the risk of cancer and to discuss the limitations of staging investigations in those patients with "poor outcomes". METHOD: This was a retrospective review of patients referred to our SERC MDT from 2014 to 2019. Lesions were assigned by the MDT to three pre-resection categories (low, intermediate, high) according to the risk of covert malignancy. Resection method and final histology were compared to the pre-resection categories. RESULTS: Of 350 SPECC lesions, 174 were assessed as low-risk, 108 intermediate-risk and 68 high-risk. The cancer incidence was 4.8%, 8.3% and 53%, respectively (15.5% overall). Eight lesions were categorized as low-risk but following piecemeal resection were found to be malignant. Five lesions, three of which were categorized as high-risk, were ultimately benign following conventional surgery. One pT1sm1 cancer, removed by anterior resection, may have been treated by local excision. CONCLUSION: A total of 83% of malignant polyps were triaged to an en bloc resection technique and surgical resection avoided for nearly all benign lesions. However, 12 patients from this cohort were deemed to have a poor outcome because of miscategorization. Further comparative research is needed to establish the optimum strategy for rectal SPECC lesion assessment. ORIGINALITY STATEMENT: There is currently no consensus for staging significant polyps of the rectum. This paper reports the effectiveness of a specialist early rectal cancer MDT to correctly risk-stratify significant rectal polyps. It underscores the importance of accurate categorization for treatment decision-making, while acknowledging the limitations of current staging modalities.

Last Glacial Maximum pattern effects reduce climate sensitivity estimates.

Here, we show that the Last Glacial Maximum (LGM) provides a stronger constraint on equilibrium climate sensitivity (ECS), the global warming from increasing greenhouse gases, after accounting for temperature patterns. Feedbacks governing ECS depend on spatial patterns of surface temperature ("pattern effects"); hence, using the LGM to constrain future warming requires quantifying how temperature patterns produce different feedbacks during LGM cooling versus modern-day warming. Combining data assimilation reconstructions with atmospheric models, we show that the climate is more sensitive to LGM forcing because ice sheets amplify extratropical cooling where feedbacks are destabilizing. Accounting for LGM pattern effects yields a median modern-day ECS of 2.4°C, 66% range 1.7° to 3.5°C (1.4° to 5.0°C, 5 to 95%), from LGM evidence alone. Combining the LGM with other lines of evidence, the best estimate becomes 2.9°C, 66% range 2.4° to 3.5°C (2.1° to 4.1°C, 5 to 95%), substantially narrowing uncertainty compared to recent assessments.

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity.

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

Mapping the functional and structural connectivity of the scene network.

The recognition and perception of places has been linked to a network of scene-selective regions in the human brain. While previous studies have focussed on functional connectivity between scene-selective regions themselves, less is known about their connectivity with other cortical and subcortical regions in the brain. Here, we determine the functional and structural connectivity profile of the scene network. We used fMRI to examine functional connectivity between scene regions and across the whole brain during rest and movie-watching. Connectivity within the scene network revealed a bias between posterior and anterior scene regions implicated in perceptual and mnemonic aspects of scene perception respectively. Differences between posterior and anterior scene regions were also evident in the connectivity with cortical and subcortical regions across the brain. For example, the Occipital Place Area (OPA) and posterior Parahippocampal Place Area (PPA) showed greater connectivity with visual and dorsal attention networks, while anterior PPA and Retrosplenial Complex showed preferential connectivity with default mode and frontoparietal control networks and the hippocampus. We further measured the structural connectivity of the scene network using diffusion tractography. This indicated both similarities and differences with the functional connectivity, highlighting biases between posterior and anterior regions, but also between ventral and dorsal scene regions. Finally, we quantified the structural connectivity between the scene network and major white matter tracts throughout the brain. These findings provide a map of the functional and structural connectivity of scene-selective regions to each other and the rest of the brain.

Distinct patterns of neural response to faces from different races in humans and deep networks.

Social categories such as the race or ethnicity of an individual are typically conveyed by the visual appearance of the face. The aim of this study was to explore how these differences in facial appearance are represented in human and artificial neural networks. First, we compared the similarity of faces from different races using a neural network trained to discriminate identity. We found that the differences between races were most evident in the fully connected layers of the network. Although these layers were also able to predict behavioural judgements of face identity from human participants, performance was biased toward White faces. Next, we measured the neural response in face-selective regions of the human brain to faces from different races in Asian and White participants. We found distinct patterns of response to faces from different races in face-selective regions. We also found that the spatial pattern of response was more consistent across participants for own-race compared to other-race faces. Together, these findings show that faces from different races elicit different patterns of response in human and artificial neural networks. These differences may underlie the ability to make categorical judgements and explain the behavioural advantage for the recognition of own-race faces.

A narrow band of image dimensions is critical for face recognition.

A key challenge in human and computer face recognition is to differentiate information that is diagnostic for identity from other sources of image variation. Here, we used a combined computational and behavioural approach to reveal critical image dimensions for face recognition. Behavioural data were collected using a sorting and matching task with unfamiliar faces and a recognition task with familiar faces. Principal components analysis was used to reveal the dimensions across which the shape and texture of faces in these tasks varied. We then asked which image dimensions were able to predict behavioural performance across these tasks. We found that the ability to predict behavioural responses in the unfamiliar face tasks increased when the early PCA dimensions (i.e. those accounting for most variance) of shape and texture were removed from the analysis. Image similarity also predicted the output of a computer model of face recognition, but again only when the early image dimensions were removed from the analysis. Finally, we found that recognition of familiar faces increased when the early image dimensions were removed, decreased when intermediate dimensions were removed, but then returned to baseline recognition when only later dimensions were removed. Together, these findings suggest that early image dimensions reflect ambient changes, such as changes in viewpoint or lighting, that do not contribute to face recognition. However, there is a narrow band of image dimensions for shape and texture that are critical for the recognition of identity in humans and computer models of face recognition.

Connectopic mapping techniques do not reflect functional gradients in the brain.

Functional gradients, in which response properties change gradually across a brain region, have been proposed as a key organising principle of the brain. Recent studies using both resting-state and natural viewing paradigms have indicated that these gradients may be reconstructed from functional connectivity patterns via "connectopic mapping" analyses. However, local connectivity patterns may be confounded by spatial autocorrelations artificially introduced during data analysis, for instance by spatial smoothing or interpolation between coordinate spaces. Here, we investigate whether such confounds can produce illusory connectopic gradients. We generated datasets comprising random white noise in subjects' functional volume spaces, then optionally applied spatial smoothing and/or interpolated the data to a different volume or surface space. Both smoothing and interpolation induced spatial autocorrelations sufficient for connectopic mapping to produce both volume- and surface-based local gradients in numerous brain regions. Furthermore, these gradients appeared highly similar to those obtained from real natural viewing data, although gradients generated from real and random data were statistically different in certain scenarios. We also reconstructed global gradients across the whole-brain - while these appeared less susceptible to artificial spatial autocorrelations, the ability to reproduce previously reported gradients was closely linked to specific features of the analysis pipeline. These results indicate that previously reported gradients identified by connectopic mapping techniques may be confounded by artificial spatial autocorrelations introduced during the analysis, and in some cases may reproduce poorly across different analysis pipelines. These findings imply that connectopic gradients need to be interpreted with caution.

Recognition of animal faces is impaired in developmental prosopagnosia.

An on-going debate in psychology and neuroscience concerns the way faces and objects are represented. Domain-specific theories suggest that faces are processed via a specialised mechanism, separate from objects. Developmental prosopagnosia (DP) is a neurodevelopmental disorder in which there is a deficit in the ability to recognize conspecific (human) faces. It is unclear, however, whether prosopagnosia also affects recognition of heterospecific (animal) faces. To address this question, we compared recognition performance with human and animal faces in neurotypical controls and participants with DP. We found that DPs showed deficits in the recognition of both human and animal faces compared to neurotypical controls. In contrast to, we found no group-level deficit in the recognition of animate or inanimate non-face objects in DPs. Using an individual-level approach, we demonstrate that in 60% of cases in which face recognition is impaired, there is a concurrent deficit with animal faces. Together, these results show that DPs have a general deficit in the recognition of faces that encompass a range of configural and morphological structures.

Genomic profiling of idiopathic peri-hilar cholangiocarcinoma reveals new targets and mutational pathways.

Peri-hilar cholangiocarcinoma (pCCA) is chemorefractory and limited genomic analyses have been undertaken in Western idiopathic disease. We undertook comprehensive genomic analyses of a U.K. idiopathic pCCA cohort to characterize its mutational profile and identify new targets. Whole exome and targeted DNA sequencing was performed on forty-two resected pCCA tumors and normal bile ducts, with Gene Set Enrichment Analysis (GSEA) using one-tailed testing to generate false discovery rates (FDR). 60% of patients harbored one cancer-associated mutation, with two mutations in 20%. High frequency somatic mutations in genes not typically associated with cholangiocarcinoma included mTOR, ABL1 and NOTCH1. We identified non-synonymous mutation (p.Glu38del) in MAP3K9 in ten tumors, associated with increased peri-vascular invasion (Fisher's exact, p < 0.018). Mutation-enriched pathways were primarily immunological, including innate Dectin-2 (FDR 0.001) and adaptive T-cell receptor pathways including PD-1 (FDR 0.007), CD4 phosphorylation (FDR 0.009) and ZAP70 translocation (FDR 0.009), with overlapping HLA genes. We observed cancer-associated mutations in over half of our patients. Many of these mutations are not typically associated with cholangiocarcinoma yet may increase eligibility for contemporary targeted trials. We also identified a targetable MAP3K9 mutation, in addition to oncogenic and immunological pathways hitherto not described in any cholangiocarcinoma subtype.

An evaluation of how connectopic mapping reveals visual field maps in V1.

Functional gradients, in which response properties change gradually across the cortical surface, have been proposed as a key organising principle of the brain. However, the presence of these gradients remains undetermined in many brain regions. Resting-state neuroimaging studies have suggested these gradients can be reconstructed from patterns of functional connectivity. Here we investigate the accuracy of these reconstructions and establish whether it is connectivity or the functional properties within a region that determine these "connectopic maps". Different manifold learning techniques were used to recover visual field maps while participants were at rest or engaged in natural viewing. We benchmarked these reconstructions against maps measured by traditional visual field mapping. We report an initial exploratory experiment of a publicly available naturalistic imaging dataset, followed by a preregistered replication using larger resting-state and naturalistic imaging datasets from the Human Connectome Project. Connectopic mapping accurately predicted visual field maps in primary visual cortex, with better predictions for eccentricity than polar angle maps. Non-linear manifold learning methods outperformed simpler linear embeddings. We also found more accurate predictions during natural viewing compared to resting-state. Varying the source of the connectivity estimates had minimal impact on the connectopic maps, suggesting the key factor is the functional topography within a brain region. The application of these standardised methods for connectopic mapping will allow the discovery of functional gradients across the brain. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 19 April 2022. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.19771717 .

Pharmacogenomics: an opportunity for personalised psychotropic prescribing in adults with intellectual disabilities.

There is growing evidence for the use of pharmacogenomics in psychotropic prescribing. People with intellectual disabilities are disproportionately prescribed psychotropics and are at risk of polypharmacy. There is an urgent need for safeguards to prevent psychotropic overprescribing but it is equally crucial that this population is not left behind in such exciting initiatives. Understanding how genetic variations affect medications is a step towards personalised medicine. This may improve personalised prescribing for people with intellectual disabilities, especially given the high rate of psychiatric and behavioural problems in this population. Our editorial explores opportunities and challenges that pharmacogenomics offers for the challenges of polypharmacy and overprescribing of psychotropics in people with intellectual disabilities.

Covariation in the recognition of own-race and other-race faces argues against the role of group bias in the other race effect.

A dominant theory of the other race effect (ORE) is that group-bias causes us to process own-race and other-race faces using different cognitive processes. To test this theory, we measured individual differences across two face recognition tasks. Our predictions were that the magnitude and pattern of performance on own-race faces would not predict performance on other-race faces and that participants would take more time with own-race faces. In a face matching task, we found that participants were more accurate with own-race faces compared to other-race faces. However, performance on own-race faces was highly correlated with performance on other-race faces. In a face sorting task, participants made fewer piles and fewer errors (i.e. higher accuracy) with own-race faces compared to other-race faces. However, we again found that performance on own-race faces was highly correlated with performance on other-race faces. The covariation in performance between own-race and other-race faces suggests that they engage similar perceptual processes. Finally, we found that participants did not spend more time on tasks involving own-race faces suggesting that different levels of motivation do not explain the ORE. Together, these findings argue against the idea that group bias leads to different perceptual processing of own-race and other-race faces.

The emergence of view-symmetric neural responses to familiar and unfamiliar faces.

Successful recognition of familiar faces is thought to depend on the ability to integrate view-dependent representations of a face into a view-invariant representation. It has been proposed that a key intermediate step in achieving view invariance is the representation of symmetrical views. However, key unresolved questions remain, such as whether these representations are specific for naturally occurring changes in viewpoint and whether view-symmetric representations exist for familiar faces. To address these issues, we compared behavioural and neural responses to natural (canonical) and unnatural (noncanonical) rotations of the face. Similarity judgements revealed that symmetrical viewpoints were perceived to be more similar than non-symmetrical viewpoints for both canonical and non-canonical rotations. Next, we measured patterns of neural response from early to higher level regions of visual cortex. Early visual areas showed a view-dependent representation for natural or canonical rotations of the face, such that the similarity between patterns of response were related to the difference in rotation. View symmetric patterns of neural response to canonically rotated faces emerged in higher visual areas, particularly in face-selective regions. The emergence of a view-symmetric representation from a view-dependent representation for canonical rotations of the face was also evident for familiar faces, suggesting that view-symmetry is an important intermediate step in generating view-invariant representations. Finally, we measured neural responses to unnatural or non-canonical rotations of the face. View-symmetric patterns of response were also found in face-selective regions. However, in contrast to natural or canonical rotations of the face, these view-symmetric responses did not arise from an initial view-dependent representation in early visual areas. This suggests differences in the way that view-symmetrical representations emerge with canonical or non-canonical rotations. The similarity in the neural response to canonical views of familiar and unfamiliar faces in the core face network suggests that the neural correlates of familiarity emerge at later stages of processing.

The representation of shape and texture in category-selective regions of ventral-temporal cortex.

Neuroimaging studies using univariate and multivariate approaches have shown that the fusiform face area (FFA) and parahippocampal place area (PPA) respond selectively to images of faces and places. The aim of this study was to determine the extent to which this selectivity to faces or places is based on the shape or texture properties of the images. Faces and houses were filtered to manipulate their texture properties, while preserving the shape properties (spatial envelope) of the images. In Experiment 1, multivariate pattern analysis (MVPA) showed that patterns of fMRI response to faces and houses in FFA and PPA were predicted by the shape properties, but not by the texture properties of the image. In Experiment 2, a univariate analysis (fMR-adaptation) showed that responses in the FFA and PPA were sensitive to changes in both the shape and texture properties of the image. These findings can be explained by the spatial scale of the representation of images in the FFA and PPA. At a coarser scale (revealed by MVPA), the neural selectivity to faces and houses is sensitive to variation in the shape properties of the image. However, at a finer scale (revealed by fMR-adaptation), the neural selectivity is sensitive to the texture properties of the image. By combining these neuroimaging paradigms, our results provide insights into the spatial scale of the neural representation of faces and places in the ventral-temporal cortex.

Recognition of pareidolic objects in developmental prosopagnosic and neurotypical individuals.

Developmental prosopagnosia (DP) is a neurodevelopmental disorder associated with difficulties in the perception and recognition of faces. However, the extent to which DP affects non-face object is an ongoing debate. In this study, we asked whether pareidolic objects (which give rise to the perception of a face) are also affected in DP. First, we compared performance in DPs (n = 30) and controls (n = 27) on a recognition task with faces, pareidolic objects and non-pareidolic objects (bottles). The pareidolic objects had either similar or dissimilar image statistics to faces. Consistent with our understanding of DP, we found that the pattern of recognition across items between DPs and controls was lowest for faces. Interestingly, there was also a low correlation between DPs and controls for pareidolic-similar objects that was similar to faces. In contrast, there were higher correlations between DPs and controls for pareidolic-dissimilar objects and bottles, which were both significantly different to faces. These findings suggest that the deficit in DP involves processing image properties that are common to faces. Next, using an individual differences approach across a large group of neurotypical adults (n = 94), we found that face recognition covaried with the recognition of pareidolic-similar objects, but not with pareidolic-dissimilar objects or non-pareidolic objects. Together, these findings support the idea that a representation based on image properties plays an important role in the perception and recognition of objects and faces and that the deficit in the perception of some object categories in DP could be explained by their similarity to the image properties found in faces.

Scientific data from precipitation driver response model intercomparison project.

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

The roles of shape and texture in the recognition of familiar faces.

The surface texture of the face is proposed to be the dominant cue in face recognition. In this study, we investigated the role of shape information in face recognition. We compared the roles of shape and surface texture in the recognition of face identity using familiar and unfamiliar hybrid faces in which the average shape from one facial identity was combined with the average texture of a different identity. In the first experiment (n = 53), participants had to match the name of a familiar person to one of eight hybrid face images. In texture trials, all images had the correct shape, but only one image had the correct texture. In shape trials, all images had the correct texture, but only one image had the correct shape. Importantly, neither task could be performed by perceptual matching. Although performance was lower for the shape trials (81%) compared to texture trials (99%), both were significantly above chance (12.5%). In the second experiment (n = 110), participants had to name hybrid faces. There were two potentially correct answers for each face image: one based on the texture and one based on the shape. Participants reported the correct name based on the texture on 61% of trials and the correct name based on the shape on 12% of trials. In the third experiment (n = 19), fMR-adaptation was used to measure the neural sensitivity to changes in the shape or texture. The core face-selective regions showed a similar sensitivity to shape and texture. These findings confirm that texture is the dominant cue for face recognition, but also show that shape plays an important role in the recognition and neural response to familiar faces.