A cost-efficient face learning mechanism: The impact of stability in appearance on the resolution of facial representations

The way faces become familiar and what information is represented as familiarity develops has puzzled researchers in the field of human face recognition for decades. In this paper, we propose a cost-efficient mechanism of face learning to describe how facial representations form over time and that explains why recognition errors occur. Encoding of diagnostic facial information would follow a coarse-to-fine trajectory, modulated by the intrinsic stability in individual faces’ appearance. In four experiments, we draw on a robust and ecological method using a proxy of exposure to famous faces in the real world to test hypotheses generated by the model and we manipulate test images to probe the nature of facial representations. We consistently show that stable facial appearances help create more reliable representation in early stages of familiarisation but that their resolution remains relatively low and therefore less discriminative over time. In contrast, variations in appearance hinder recognition at first but encourage refinement of representations with further exposure. Consistent with the cost-efficient face learning mechanism we propose, facial representations built on a foundation of large-scale coarse information. When coarse information loses its diagnostic value through the experience of variations across encounters, facial details and their spatial relationships receive additional representational weights.

What can we experience and report on a rapidly presented image? Intersubjective measures of specificity of freely reported contents of consciousness

Previous studies have established a view that human observers can only perceive coarse information from a natural scene image when it is presented rapidly (<100ms, masked). In these studies, participants were often forced to choose an answer from options that experimenters preselected. These options can underestimate what participants experience and can report on it. Here, we used a novel free-report paradigm to examine what people can freely report following a rapidly presented natural scene image (67/133/267ms, masked). N = 670 online participants typed up to five words to report what they saw in the image together with confidence of the respective responses. We developed a novel index, Intersubjective Agreement (IA). IA quantifies how specifically the response words were used to describe the target image, with a high value meaning the word is not often reported for other images. IA eliminates the need for experimenters to preselect response options. With IA, unlike commonly believed, we demonstrated that participants reported highly specific and detailed aspects of the briefly (even at 67ms, masked) shown image. Further, IA is positively correlated with confidence, indicating metacognitive conscious access to the reported aspects of the image. These new findings challenge the dominant view that the content of rapid scene experience is limited to global and coarse gist. Our novel paradigm opens a door to investigate various contents of consciousness with a free-report paradigm.

Both high and low spatial frequencies are critical for visual consciousness in autism: Evidence of an emotional attentional blink paradigm.

High Spatial Frequencies (HSF - conveying local information) may serve a critical role in visual consciousness. Despite an HSF bias during visual perception in autism, autistic individuals demonstrate impairments in face processing. Our aim was to investigate the respective role of HSF and Low Spatial Frequencies (LSF - conveying coarse information) on visual consciousness in autism. Thirty-two autistic adults and 35 typically developing (TD) controls performed an emotional attentional blink paradigm with spatially filtered distractors. TD participants showed reduced T2 accuracy (i.e., accuracy for the second target given the correct report of the first target T1) after unfiltered and HSF distractors compared to LSF distractors. In the autistic group, we observed lower T2 accuracy than controls after HSF and LSF distractors but not after unfiltered distractors. Results suggest the importance of HSF for visual consciousness in TD participants whereas, both LSF and HSF seem important in autism.

Demand for longer quarantine period among common and uncommon COVID-19 infections: a scoping review

Background As one of the non-pharmacological interventions to control the transmission of COVID-19, determining the quarantine duration is mainly based on the accurate estimates of the incubation period. However, patients with coarse information of the exposure date, as well as infections other than the symptomatic, were not taken into account in previously published studies. Thus, by using the statistical method dealing with the interval-censored data, we assessed the quarantine duration for both common and uncommon infections. The latter type includes the presymptomatic, the asymptomatic and the recurrent test positive patients. Methods As of 10 December 2020, information on cases have been collected from the English and Chinese databases, including Pubmed, Google scholar, CNKI (China National Knowledge Infrastructure) and Wanfang. Official websites and medias were also searched as data sources. All data were transformed into doubly interval-censored and the accelerated failure time model was applied. By estimating the incubation period and the time-to-event distribution of worldwide COVID-19 patients, we obtain the large percentiles for determining and suggesting the quarantine policies. For symptomatic and presymptomatic COVID-19 patients, the incubation time is the duration from exposure to symptom onset. For the asymptomatic, we substitute the date of first positive result of nucleic acid testing for that of symptom onset. Furthermore, the time from hospital discharge or getting negative test result to the positive recurrence has been calculated for recurrent positive patients. Results A total of 1920 laboratory confirmed COVID-19 cases were included. Among all uncommon infections, 34.1% (n = 55) of them developed symptoms or were identified beyond fourteen days. Based on all collected cases, the 95th and 99th percentiles were estimated to be 16.2 days (95% CI 15.5–17.0) and 22.9 days (21.7‒24.3) respectively. Besides, we got similar estimates based on merely symptomatic and presymptomatic infections as 15.1 days (14.4‒15.7) and 21.1 days (20.0‒22.2). Conclusions There are a certain number of infected people who require longer quarantine duration. Our findings well support the current practice of the extended active monitoring. To further prevent possible transmissions induced and facilitated by such infectious outliers after the 14-days quarantine, properly prolonging the quarantine duration could be prudent for high-risk scenarios and in regions with insufficient test resources.

High spatial frequency information in primes hastens happy faces categorization in autistic adults.

Where does the remarkable human ability to quickly identify facial emotion come from? Coarse-to-Fine integration of visual information may play a critical role. Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide inhibition of irrelevant information and facilitate fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging and may contribute to socio-emotional difficulties. It has been suggested that perceptual changes, such as a bias toward HSF or a reduced LSF processing, could partly explain atypical face processing in autism. However, alterations in predictive processes related to LSF have not been investigated so far. Here, we analyzed the data of 27 autistic adults and 34 matched typically developing (TD) controls on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs. LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face stimulus in the context of incongruent information, compared to HSF primes, in the control group but not in the autistic group. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups and irrespective of the congruency. Moreover, whereas the advantage of HSF vs. LSF primes was stronger for angry than happy faces in the control group, it was stronger for happy than angry faces in autistic participants. Additional exploratory analyses using drift diffusion modelling confirmed HSF advantage for achieving the task and showed a longer non-decision time (i.e., encoding and motor response) in autism compared to control. Our main hypothesis of predictive impairments in autism in relation to LSF was not corroborated by our data. However, our analyses suggest specificities in autistic individuals according to the type of emotion processed and in the slower non-decision-related processes.

Spatially Filtered Emotional Faces Dominate during Binocular Rivalry

The present investigation explores the role of bottom-up and top-down factors in the recognition of emotional facial expressions during binocular rivalry. We manipulated spatial frequencies (SF) and emotive features and asked subjects to indicate whether the emotional or the neutral expression was dominant during binocular rivalry. Controlling the bottom-up saliency with a computational model, physically comparable happy and fearful faces were presented dichoptically with neutral faces. The results showed the dominance of emotional faces over neutral ones. In particular, happy faces were reported more frequently as the first dominant percept even in the presence of coarse information (at a low SF level: 2–6 cycle/degree). Following current theories of emotion processing, the results provide further support for the influence of positive compared to negative meaning on binocular rivalry and, for the first time, showed that individuals perceive the affective quality of happiness even in the absence of details in the visual display. Furthermore, our findings represent an advance in knowledge regarding the association between the high- and low-level mechanisms behind binocular rivalry.

Abnormal visual representations associated with confusion of perceived facial expression in schizophrenia with social anxiety disorder

Deficits in social functioning are especially severe amongst schizophrenia individuals with the prevalent comorbidity of social anxiety disorder (SZ&SAD). Yet, the mechanisms underlying the recognition of facial expression of emotions—a hallmark of social cognition—are practically unexplored in SZ&SAD. Here, we aim to reveal the visual representations SZ&SAD (n = 16) and controls (n = 14) rely on for facial expression recognition. We ran a total of 30,000 trials of a facial expression categorization task with Bubbles, a data-driven technique. Results showed that SZ&SAD’s ability to categorize facial expression was impared compared to controls. More severe negative symptoms (flat affect, apathy, reduced social drive) was associated with more impaired emotion recognition ability, and with more biases in attributing neutral affect to faces. Higher social anxiety symptoms, on the other hand, was found to enhance the reaction speed to neutral and angry faces. Most importantly, Bubbles showed that these abnormalities could be explained by inefficient visual representations of emotions: compared to controls, SZ&SAD subjects relied less on fine facial cues (high spatial frequencies) and more on coarse facial cues (low spatial frequencies). SZ&SAD participants also never relied on the eye regions (only on the mouth) to categorize facial expressions. We discuss how possible interactions between early (low sensitivity to coarse information) and late stages of the visual system (overreliance on these coarse features) might disrupt SZ&SAD’s recognition of facial expressions. Our findings offer perceptual mechanisms through which comorbid SZ&SAD impairs crucial aspects of social cognition, as well as functional psychopathology.

Cortical Thickness and Natural Scene Recognition in the Child’s Brain

Visual scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information, whereas high spatial frequencies (HSF) subsequently carry information about fine details. The present magnetic resonance imaging study investigated how cortical thickness covaried with LSF/HSF processing abilities in ten-year-old children and adults. Participants indicated whether natural scenes that were filtered in either LSF or HSF represented outdoor or indoor scenes, while reaction times (RTs) and accuracy measures were recorded. In adults, faster RTs for LSF and HSF images were consistently associated with a thicker cortex (parahippocampal cortex, middle frontal gyrus, and precentral and insula regions for LSF; parahippocampal cortex and fronto-marginal and supramarginal gyri for HSF). On the other hand, in children, faster RTs for HSF were associated with a thicker cortex (posterior cingulate, supramarginal and calcarine cortical regions), whereas faster RTs for LSF were associated with a thinner cortex (subcallosal and insula regions). Increased cortical thickness in adults and children could correspond to an expansion mechanism linked to visual scene processing efficiency. In contrast, lower cortical thickness associated with LSF efficiency in children could correspond to a pruning mechanism reflecting an ongoing maturational process, in agreement with the view that LSF efficiency continues to be refined during childhood. This differing pattern between children and adults appeared to be particularly significant in anterior regions of the brain, in line with the proposed existence of a postero-anterior gradient of brain development. Taken together, our results highlight the dynamic brain processes that allow children and adults to perceive a visual natural scene in a coherent way.

Geostatistical analysis for Uncertainty Quantification in the SMART-SED model: a downscaling approach based on Digital Soil Mapping data

<p>SMART-SED is a project aimed at developing an innovative framework for the numerical simulation of sediment motion in river catchments, intended to be used by local territorial management institutions and professionals to design proper strategies for the mitigation of hydrogeological instability. Uncertainty analysis is an intrinsic feature of models simulating natural processes. In order to perform an effective uncertainty quantification, it is necessary to properly identify the variability of the input parameters and to design stochastic simulation methods able to provide realistic realisations, based on the available data. This thesis focuses on the use of digital soil maps for the prediction and stochastic simulation of terrain-related quantities used for the estimation of the input parameters of the SMART-SED model. The digital maps are obtained from SoilGrids, a system for automated soil mapping based on state-of-the-art spatial predictions methods. Innovative approaches are introduced to account for the limitations of SoilGrids data (low resolution, inaccuracy) and for the specificities of the variables in exam. Although the focus is on the SMART- SED project, the methods proposed can be generally used for geostatistical modelling at a local scale using auxiliary coarse information obtained through remote sensing or from previously fitted digital maps.</p>

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.