Gender and hometown population density interact to predict face recognition ability

Face recognition's practical relevance: Social bonds, not social butterflies

Research on individual differences in face recognition has provided important foundational insights: their broad range, cognitive specificity, strong heritability, and resilience to change. Elusive, however, has been the key issue of practical relevance: do these individual differences correlate with aspects of life that go beyond the recognition of faces, per se? Though often assumed, especially in social realms, such correlates remain largely theoretical, without empirical support. Here, we investigate an array of potential social correlates of face recognition. We establish social relationship quality as a reproducible correlate. This link generalises across face recognition tasks and across independent samples. In contrast, we detect no robust association with the sheer quantity of social connections, whether measured directly via number of social contacts or indirectly via extraversion-related personality indices. These findings document the existence of a key social correlate of face recognition and provide some of the first evidence to support its practical relevance. At the same time, they challenge the naive assumption that face recognition relates equally to all social outcomes. In contrast, they suggest a focused link of face recognition to the quality, not quantity, of one's social connections.

Effects of expectation on face perception and its association with expertise

Perceptual decisions are derived from the combination of priors and sensorial input. While priors are broadly understood to reflect experience/expertise developed over one's lifetime, the role of perceptual expertise at the individual level has seldom been directly explored. Here, we manipulate probabilistic information associated with a high and low expertise category (faces and cars respectively), while assessing individual level of expertise with each category. 67 participants learned the probabilistic association between a color cue and each target category (face/car) in a behavioural categorization task. Neural activity (EEG) was then recorded in a similar paradigm in the same participants featuring the previously learned contingencies without the explicit task. Behaviourally, perception of the higher expertise category (faces) was modulated by expectation. Specifically, we observed facilitatory and interference effects when targets were correctly or incorrectly expected, which were also associated with independently measured individual levels of face expertise. Multivariate pattern analysis of the EEG signal revealed clear effects of expectation from 100 ms post stimulus, with significant decoding of the neural response to expected vs. not stimuli, when viewing identical images. Latency of peak decoding when participants saw faces was directly associated with individual level facilitation effects in the behavioural task. The current results not only provide time sensitive evidence of expectation effects on early perception but highlight the role of higher-level expertise on forming priors.

Community diversity and the other-race effect in infancy

The other-race effect (ORE) is characterized by processing advantages for faces of one's own race over faces of another race and is observed at ~9 months of age. Environmental exposure to other races has an impact on the development of the ORE. In the current study, we examined the effects of community racial diversity on the ORE in 9- to 12-month-olds from across the United States. We hypothesized that community racial diversity would influence the amount of experience that infants have with individuals of other races and be an important factor in predicting the ORE across broad regions of the United States. We predicted that infants from more diverse communities would demonstrate successful processing of own- and other-race faces, while infants from less diverse communities would demonstrate successful processing of own-race but not other-race faces. This would indicate that the ORE is exhibited more strongly in infants from less diverse communities than in infants from more diverse communities. Participants completed familiarization and visual paired comparison (VPC) trials with own- and other-race faces in an online study. Our results showed that although the ORE was present, the effect was driven by community members who were the racial majority. Recognition biases were not observed in community racial or ethnic minority participants, potentially due to increased exposure to racial out-group members, which mitigated the development of the ORE in this subset of participants. This study has far-reaching implications in the study of infant face perception, child development, and social justice, as the ORE develops at a young age, and may lead to a complex pattern of racial biases contributing to systemic barriers in society.

Differences between high and low performers in face recognition in electrophysiological correlates of face familiarity and distance-to-norm

Valentine's influential norm-based multidimensional face-space model (nMDFS) predicts that perceived distinctiveness of a face increases with its distance to the norm. Occipito-temporal event-related potentials (ERPs) have been recently shown to respond selectively to variations in distance-to-norm (P200) or familiarity (N250, late negativity), respectively (Wuttke & Schweinberger, 2019). Despite growing evidence on interindividual differences in face perception skills at the behavioral level, little research has focused on their electrophysiological correlates. To reveal potential interindividual differences in face spaces, we contrasted high and low performers in face recognition in regards to distance-to-norm (P200) and familiarity (N250). We replicated both the P200 distance-to-norm and the N250 familiarity effect. Importantly, we observed: i) reduced responses in low compared to high performers of face recognition, especially in terms of smaller distance-to-norm effects in the P200, possibly indicating less 'expanded' face spaces in low compared to high performers; ii) increased N250 responses to familiar original faces in high performers, suggesting more robust face identity representations. In summary, these findings suggest the contribution of both early norm-based face coding and robust face representations to individual face recognition skills, and indicate that ERPs can offer a promising route to understand individual differences in face perception and their neurocognitive correlates.

Alcohol Use Predicts Face Perception Impairments and Difficulties in Face Recognition

Background: Risky alcohol use is related to a variety of cognitive impairments, including memory and visuo-perceptual difficulties. Remarkably, no prior work has assessed whether usage of alcohol can predict difficulties perceiving facial identity. Objectives: Therefore, this study aimed to investigate whether riskier alcohol consumption predicted impairments in face perception and self-reported difficulties in face recognition. Results: Participants (N = 239, male = 77) were over 18 years old and had normal or corrected-to-normal vision. Alcohol use was assessed using the Alcohol Use Disorder Identification Test (AUDIT), while face recognition difficulties were determined by the 20-item Prosopagnosia Index questionnaire (PI20). A subsample of participants (N = 126, male = 51) completed the Cambridge Face Perception task (CFPT) to assess their face perception ability. Multiple linear regressions showed significant models of prediction on both face perception and face recognition when considering AUDIT score and age as predictors. Conclusion: This study suggested, for the first time, that risky alcohol use predicts both poorer visuo-perceptual processing for faces and self-reported difficulties in face recognition.

Face processing in the infant brain after pandemic lockdown

The role of visual experience in the development of face processing has long been debated. We present a new angle on this question through a serendipitous study that cannot easily be repeated. Infants viewed short blocks of faces during fMRI in a repetition suppression task. The same identity was presented multiple times in half of the blocks (repeat condition) and different identities were presented once each in the other half (novel condition). In adults, the fusiform face area (FFA) tends to show greater neural activity for novel versus repeat blocks in such designs, suggesting that it can distinguish same versus different face identities. As part of an ongoing study, we collected data before the COVID-19 pandemic and after an initial local lockdown was lifted. The resulting sample of 12 infants (9-24 months) divided equally into pre- and post-lockdown groups with matching ages and data quantity/quality. The groups had strikingly different FFA responses: pre-lockdown infants showed repetition suppression (novel > repeat), whereas post-lockdown infants showed the opposite (repeat > novel), often referred to as repetition enhancement. These findings provide speculative evidence that altered visual experience during the lockdown, or other correlated environmental changes, may have affected face processing in the infant brain.

The relation between holistic processing as measured by three composite tasks and face processing: A latent variable modeling approach

We investigated the relationship between holistic processing and face processing using a latent variables approach. Three versions of the composite paradigm were used to measure holistic processing: Vanderbilt Holistic Face Processing Test, a sequential composite matching task, and a simultaneous composite matching task. Three tasks were used to measure face perception and face memory abilities respectively. We had three pairs of tasks such that within each pair (of memory and perception task), the stimuli involved, the requirement for matching across viewpoints, etc., are the same, such that the only difference is whether perception or memory is taxed. There were no significant correlations between the different versions of the composite task. We discovered no evidence to support a distinction between face perception and face memory, suggesting the existence of a general face processing factor. Finally, there was no evidence that holistic processing (as captured by either of the three composite tasks) is predictive of better face processing per se, casting doubts on the role of holistic processing in differentiating different levels of efficiency in face processing.

Word and Face Recognition Processing Based on Response Times and Ex-Gaussian Components

The face is a fundamental feature of our identity. In humans, the existence of specialized processing modules for faces is now widely accepted. However, identifying the processes involved for proper names is more problematic. The aim of the present study is to examine which of the two treatments is produced earlier and whether the social abilities are influent. We selected 100 university students divided into two groups: Spanish and USA students. They had to recognize famous faces or names by using a masked priming task. An analysis of variance about the reaction times (RT) was used to determine whether significant differences could be observed in word or face recognition and between the Spanish or USA group. Additionally, and to examine the role of outliers, the Gaussian distribution has been modified exponentially. Famous faces were recognized faster than names, and differences were observed between Spanish and North American participants, but not for unknown distracting faces. The current results suggest that response times to face processing might be faster than name recognition, which supports the idea of differences in processing nature.

Optimum Feature Selection with Particle Swarm Optimization to Face Recognition System Using Gabor Wavelet Transform and Deep Learning

In this study, Gabor wavelet transform on the strength of deep learning which is a new approach for the symmetry face database is presented. A proposed face recognition system was developed to be used for different purposes. We used Gabor wavelet transform for feature extraction of symmetry face training data, and then, we used the deep learning method for recognition. We implemented and evaluated the proposed method on ORL and YALE databases with MATLAB 2020a. Moreover, the same experiments were conducted applying particle swarm optimization (PSO) for the feature selection approach. The implementation of Gabor wavelet feature extraction with a high number of training image samples has proved to be more effective than other methods in our study. The recognition rate when implementing the PSO methods on the ORL database is 85.42% while it is 92% with the three methods on the YALE database. However, the use of the PSO algorithm has increased the accuracy rate to 96.22% for the ORL database and 94.66% for the YALE database.

To Google or Not: Differences on How Online Searches Predict Names and Faces

Word and face recognition are processes of interest for a large number of fields, including both clinical psychology and computer calculations. The research examined here aims to evaluate the role of an online frequency’s ability to predict both face and word recognition by examining the stability of these processes in a given amount of time. The study will further examine the differences between traditional theories and current contextual frequency approaches. Reaction times were recorded through both a logarithmic transformation and through a Bayesian approach. The Bayes factor notation was employed as an additional test to support the evidence provided by the data. Although differences between face and name recognition were found, the results suggest that latencies for both face and name recognition are stable for a period of six months and online news frequencies better predict reaction time for both classical frequentist analyses. These findings support the use of the contextual diversity approach.

Recognizing Emotions through Facial Expressions: A Largescale Experimental Study

Experimental research examining emotional processes is typically based on the observation of images with affective content, including facial expressions. Future studies will benefit from databases with emotion-inducing stimuli in which characteristics of the stimuli potentially influencing results can be controlled. This study presents Portuguese normative data for the identification of seven facial expressions of emotions (plus a neutral face), on the Radboud Faces Database (RaFD). The effect of participants’ gender and models’ sex on emotion recognition was also examined. Participants (N = 1249) were exposed to 312 pictures of white adults displaying emotional and neutral faces with a frontal gaze. Recognition agreement between the displayed and participants’ chosen expressions ranged from 69% (for anger) to 97% (for happiness). Recognition levels were significantly higher among women than among men only for anger and contempt. The emotion recognition was higher either in female models or in male models depending on the emotion. Overall, the results show high recognition levels of the facial expressions presented, indicating that the RaFD provides adequate stimuli for studies examining the recognition of facial expressions of emotion among college students. Participants’ gender had a limited influence on emotion recognition, but the sex of the model requires additional consideration.

Predicting Performances on Processing and Memorizing East Asian Faces from Brain Activities in Face-Selective Regions: A Neurocomputational Approach

For more than two decades, a network of face-selective brain regions has been identified as the core system for face processing, including occipital face area (OFA), fusiform face area (FFA), and posterior region of superior temporal sulcus (pSTS). Moreover, recent studies have suggested that the ventral route of face processing and memory should end at the anterior temporal lobes (i.e., vATLs), which may play an important role bridging face perception and face memory. It is not entirely clear, however, the extent to which neural activities in these face-selective regions can effectively predict behavioral performance on tasks that are frequently used to investigate face processing and face memory test that requires recognition beyond variation in pose and lighting, especially when non-Caucasian East Asian faces are involved. To address these questions, we first identified during a functional scan the core face network by asking participants to perform a one-back task, while viewing either static images or dynamic videos. Dynamic localizers were effective in identifying regions of interest (ROIs) in the core face-processing system. We then correlated the brain activities of core ROIs with performances on face-processing tasks (component, configural, and composite) and face memory test (Taiwanese Face Memory Test, TFMT) and found evidence for limited predictability. We next adopted an multi-voxel pattern analysis (MVPA) approach to further explore the predictability of face-selective brain regions on TFMT performance and found evidence suggesting that a basic visual processing area such as calcarine and an area for structural face processing such as OFA may play an even greater role in memorizing faces. Implications regarding how differences in processing demands between behavioral and neuroimaging tasks and cultural specificity in face-processing and memory strategies among participants may have contributed to the findings reported here are discussed.

Profiles on the Orientation Discrimination Processing of Human Faces

Face recognition is a crucial subject for public health, as socialization is one of the main characteristics for full citizenship. However, good recognizers would be distinguished, not only by the number of faces they discriminate but also by the number of rejected stimuli as unfamiliar. When it comes to face recognition, it is important to remember that position, to some extent, would not entail a high cognitive cost, unlike other processes in similar areas of the brain. The aim of this paper was to examine participant’s recognition profiles according to face position. For this reason, a recognition task was carried out by employing the Karolinska Directed Emotional Faces. Reaction times and accuracy were employed as dependent variables and a cluster analysis was carried out. A total of two profiles were identified in participants’ performance, which differ in position in terms of reaction times but not accuracy. The results can be described as follows: first, it is possible to identify performance profiles in visual recognition of faces that differ in position in terms of reaction times, not accuracy; secondly, results suggest a bias towards the left. At the applied level, this could be of interest with a view to conducting training programs in face recognition.

Can You Identify These Celebrities? A Network Analysis on Differences between Word and Face Recognition

Face recognition is located in the fusiform gyrus, which is also related to other tasks such word recognition. Although these two processes have several similarities, there are remarkable differences that include a vast range of approaches, which results from different groups of participants. This research aims to examine how the word-processing system processes faces at different moments and vice versa. Two experiments were carried out. Experiment 1 allowed us to examine the classical discrimination task, while Experiment 2 allowed us to examine very early moments of discrimination. In the first experiment, 20 Spanish University students volunteered to participate. Secondly, a sample of 60 participants from different nationalities volunteered to take part in Experiment 2. Furthermore, the role of sex and place of origin were considered in Experiment 1. No differences between men and women were found in Experiment 1, nor between conditions. However, Experiment 2 depicted shorter latencies for faces than word names, as well as a higher masked repetition priming effect for word identities and word names preceded by faces. Emerging methodologies in the field might help us to better understand the relationship among these two processes. For this reason, a network analysis approach was carried out, depicting sub-communities of nodes related to face or word name recognition, which were replicated across different groups of participants. Bootstrap inferences are proposed to account for variability in estimating the probabilities in the current samples. This supports that both processes are related to early moments of recognition, and rather than being independent, they might be bilaterally distributed with some expert specializations or preferences.