Using the common-sense model of illness representations to explore individuals' experiences and perceptions of migraine and its management in the United Kingdom.

OBJECTIVES: Migraine is considered a chronic health condition that impacts both quality of life and psychological wellbeing. People with migraines use a range of management strategies, which include pharmacological and non-pharmacological treatments. The aim of this study was to explore individuals' experiences and perceptions of migraines and its treatment using the Common-Sense Model (CSM) of Illness Representations. METHODS: Semi-structured, one-to-one interviews were conducted with eleven individuals with a history of migraine to explore their experiences and perceptions of migraine and its treatment. Participants were recruited from across the United Kingdom via convenience sampling using social media advertisement. Interviews were recorded, transcribed verbatim, and qualitative data were analysed using theoretical framework analysis using the CSM. RESULTS: The three dimensions of the CSM were mapped on to the qualitative data. These were: (i) Cognitive representations of migraine, within five domains: (a) identity of migraine, (b) perceived causes, (c) perceived timeline, (d) perceived control/cure, and (e) perceived consequences; (ii) Emotional representations of migraine relating to (a) migraine specific emotions and (b) emotional representation of the impact of migraine; and (iii) Coping/self-management behaviours, namely (a) self-medicating behaviours and (b) care-seeking behaviours. No incongruous data were found; therefore, no further thematic analysis was required. CONCLUSION: This is the first study to apply the CSM to migraine for framework analysis of qualitative data in this way. The findings illustrate the emotional impact of migraine and the range of illness perceptions associated with appropriate self-management. The data will be used to design a questionnaire for quantitative studies to investigate the extent to which these perceptions are generalizable to the wider population of people who experience migraines.

Social representation of masculine and feminine sports among Saudi adolescents.

Introduction: This study examined how certain sports are represented as masculine or feminine in Saudi adolescents, namely, which sports adolescents associate with males and which sports they associate with females. Previous research aligned with this concern was conducted within Western culture; however, there is a need to shed light on how the issues of social representation of masculine and feminine sports affect other cultures such as Middle Eastern cultures. Methods: A survey was completed by 280 Saudi adolescents, aged between 12 and 17 (M = 13.5, SD = 1.3). The survey contained open-ended recall questions that asked participants to name three masculine, feminine, and natural sports. Results: Most participants were familiar with using feminine and masculine terminology to describe sports, and nearly half had personally used gendered terms to describe sports. Overall, the participants generated 2,195 names of various sports, with the majority classified as natural (appropriate for both men and women), many masculine, and the fewest feminine. Discussion: The connection between specific sports and masculinity or femininity can restrict the activities of adolescents who do not conform to traditional gender roles. Also, adolescents who are interested in sports that are not typically associated with their gender may experience social stigma or exclusion, which can discourage their participation. Therefore, it is important to establish inclusive environments in sports, regardless of the gender.

b-MAR: bidirectional artifact representations learning framework for metal artifact reduction in dental CBCT.

OBJECTIVE: Metal artifacts in computed tomography (CT) images hinder diagnosis and treatment significantly. Specifically, dental cone-beam computed tomography (Dental CBCT) images are seriously contaminated by metal artifacts due to the widespread use of low tube voltages and the presence of various high-attenuation materials in dental structures. Existing supervised metal artifact reduction (MAR) methods mainly learn the mapping of artifact-affected images to clean images, while ignoring the modeling of the metal artifact generation process. Therefore, we propose the bidirectional artifact representations learning framework to adaptively encode metal artifacts caused by various dental implants and model the generation and elimination of metal artifacts, thereby improving MAR performance. Approach. we introduce an efficient artifact encoder to extract multi-scale representations of metal artifacts from artifact-affected images. These extracted metal artifact representations are then bidirectionally embedded into both the metal artifact generator and the metal artifact eliminator, which can simultaneously improve the performance of artifact removal and artifact generation. The artifact eliminator learns artifact removal in a supervised manner, while the artifact generator learns artifact generation in an adversarial manner. To further improve the performance of the bidirectional task networks, we propose artifact consistency loss to align the consistency of images generated by the eliminator and the generator with or without embedding artifact representations. Main results. To validate the effectiveness of our algorithm, experiments are conducted on simulated and clinical datasets containing various dental metal morphologies. Quantitative metrics are calculated to evaluate the results of the simulation tests,which demonstrate b-MAR improvements of > 1.4131 dB in PSNR, > 0.3473 HU decrements in RMSE, and > 0.0025 promotion in SSIM over the current state-of-the-art MAR methods. All results indicate that the proposed b-MAR method can remove artifacts caused by various metal morphologies and restore the structural integrity of dental tissues effectively. Significance. The proposed b-MAR method strengthens the joint learning of the artifact removal process and the artifact generation process by bidirectionally embedding artifact representations, thereby improving the model's artifact removal performance. Compared with other comparison methods, b-MAR can robustly and effectively correct metal artifacts in dental CBCT images caused by different dental metals.

The role of body-object interaction in children's concept processing: insights from two Chinese communities.

A rating of body-object interactions (BOIs) reflects the ease with which a human body can interact physically with a word's referent. Studies with adults have demonstrated a facilitating BOI effect in language tasks, with faster and more accurate responses for high BOI words (e.g., cup) than low BOI words (e.g., coal). A few studies have explored the BOI effect in children. However, these studies have all adopted adult-rated BOIs, which may differ from children's. Using child-rated BOIs, the present study investigated the BOI effect in Chinese children and its relationship with age, as well as whether there was a community difference in the BOI effect. Children (aged 7-8) from Mainland China (N = 100) and Hong Kong SAR (HK; N = 90) completed a lexical decision task used to measure the BOI effect. The children were asked to judge whether each item was a real Chinese word; each real word was assigned a child-rated BOI score. After controlling nonverbal intelligence, gender, working memory, and Chinese character reading, a significant BOI effect was observed at the response accuracy and speed levels. The accuracy and latency analyses illustrated a community difference; the BOI effect was smaller in the HK children. This study suggests that BOI measures may be sensitive to the ecological differences between tested communities. The findings support the need for further investigations into the BOI effect across Chinese communities, particularly those in Mainland China.

Insufficient responses to rape in Ouagadougou: Reflections on the experiences of young female survivors / Insuffisances des réponses aux viols à Ouagadougou : réflexions à partir du vécu de jeunes survivantes.

The rape of girls and women raises questions about both prevention and the response in Burkina Faso. This article looks at the inadequacy of the response to rape in Ouagadougou. It is based on an analysis of cases of rape experienced by young women in the city and documented between 2005 and 2009. The study highlights the gap between the attitude of the victims, whether or not they are inclined to report the act and seek support, and the existing response in this area, whether in their entourage, at the community level, or at the institutional level. The study concludes that there is a need for more in-depth research into the representations and experiences of rape survivors in Ouagadougou and, more broadly, in Burkina Faso. Such research will enable us to identify gaps and appropriate strategies so that survivors are offered a holistic response that is more conducive to respect for their sexual and reproductive rights. Appropriate responses should involve improving the response system, so as to minimize obstacles and make institutional support more accessible to survivors.

Les viols sur des filles et femmes interpellent autant au sujet de leur prévention que par rapport aux réponses qui y sont apportées au Burkina Faso. L'article fournit une réflexion sur les insuffisances de réponses à ces viols à Ouagadougou. La réflexion s'appuie sur l'analyse de cas de viols vécus par des jeunes femmes dans cette ville et documentés entre 2005 et 2009. La réflexion met en exergue le fossé entre la posture des victimes, leur propension ou non à dénoncer l'acte et à rechercher un soutien et la réponse existante en la matière, que cela soit dans leur entourage, au niveau communautaire ou au niveau institutionnel. L'article démontre la nécessité de mener des investigations plus approfondies sur les représentations et le vécu des survivantes de viols à Ouagadougou et, plus largement, au Burkina Faso. Cela permettra d'identifier les gaps à combler ainsi que les stratégies adéquates pour offrir aux survivantes une réponse holistique et plus propice au respect de leurs droits sexuels et reproductifs. Les réponses appropriées devraient passer par l'amélioration du dispositif de réponse, de façon à minimiser ces entraves et à rendre le soutien institutionnel plus accessible aux survivantes.

The neural representations of valence transformation in indole processing.

Indole is often associated with a sweet and floral odor typical of jasmine flowers at low concentrations and an unpleasant, animal-like odor at high concentrations. However, the mechanism whereby the brain processes this opposite valence of indole is not fully understood yet. In this study, we aimed to investigate the neural mechanisms underlying indole valence encoding in conversion and nonconversion groups using the smelling task to arouse pleasantness. For this purpose, 12 conversion individuals and 15 nonconversion individuals participated in an event-related functional magnetic resonance imaging paradigm with low (low-indole) and high (high-indole) indole concentrations in which valence was manipulated independent of intensity. The results of this experiment showed that neural activity in the right amygdala, orbitofrontal cortex and insula was associated with valence independent of intensity. Furthermore, activation in the right orbitofrontal cortex in response to low-indole was positively associated with subjective pleasantness ratings. Conversely, activation in the right insula and amygdala in response to low-indole was positively correlated with anticipatory hedonic traits. Interestingly, while amygdala activation in response to high-indole also showed a positive correlation with these hedonic traits, such correlation was observed solely with right insula activation in response to high-indole. Additionally, activation in the right amygdala in response to low-indole was positively correlated with consummatory pleasure and hedonic traits. Regarding olfactory function, only activation in the right orbitofrontal cortex in response to high-indole was positively correlated with olfactory identification, whereas activation in the insula in response to low-indole was negatively correlated with the level of self-reported olfactory dysfunction. Based on these findings, valence transformation of indole processing in the right orbitofrontal cortex, insula, and amygdala may be associated with individual hedonic traits and perceptual differences.

A Semi-Supervised Learning Framework for Classifying Colorectal Neoplasia Based on the NICE Classification.

Labelling medical images is an arduous and costly task that necessitates clinical expertise and large numbers of qualified images. Insufficient samples can lead to underfitting during training and poor performance of supervised learning models. In this study, we aim to develop a SimCLR-based semi-supervised learning framework to classify colorectal neoplasia based on the NICE classification. First, the proposed framework was trained under self-supervised learning using a large unlabelled dataset; subsequently, it was fine-tuned on a limited labelled dataset based on the NICE classification. The model was evaluated on an independent dataset and compared with models based on supervised transfer learning and endoscopists using accuracy, Matthew's correlation coefficient (MCC), and Cohen's kappa. Finally, Grad-CAM and t-SNE were applied to visualize the models' interpretations. A ResNet-backboned SimCLR model (accuracy of 0.908, MCC of 0.862, and Cohen's kappa of 0.896) outperformed supervised transfer learning-based models (means: 0.803, 0.698, and 0.742) and junior endoscopists (0.816, 0.724, and 0.863), while performing only slightly worse than senior endoscopists (0.916, 0.875, and 0.944). Moreover, t-SNE showed a better clustering of ternary samples through self-supervised learning in SimCLR than through supervised transfer learning. Compared with traditional supervised learning, semi-supervised learning enables deep learning models to achieve improved performance with limited labelled endoscopic images.

The central role of social exclusion when representing ethnic minorities and its association with intergroup attitudes.

A mixed-methods approach was used to analyze the social representations of four ethnic minorities in southern Spain. Following a between-subjects design, Spanish participants (n = 532) were assigned to evaluate either Romanian Roma, Spanish Roma, Moroccan, or Romanian non-Roma people, with a free-association task and scales of stereotypes, emotions, and behavioral tendencies. Results showed that Romanian Roma was the most devalued target, eliciting the worst representation and attitudes. The content analysis revealed that participants described minorities mainly in terms of social exclusion, culture, appearance, personality, opportunity seeking, stigmatization, and personalization/equality, with social exclusion being a key category associated with worst attitudes.

Numerical values modulate size perception.

The link between various codes of magnitude and their interactions has been studied extensively for many years. In the current study, we examined how the physical and numerical magnitudes of digits are mapped into a combined mental representation. In two psychophysical experiments, participants reported the physically larger digit among two digits. In the identical condition, participants compared digits of an identical value (e.g., "2" and "2"); in the different condition, participants compared digits of distinct numerical values (i.e., "2" and "5"). As anticipated, participants overestimated the physical size of a numerically larger digit and underestimated the physical size of a numerically smaller digit. Our results extend the shared-representation account of physical and numerical magnitudes.

Me or we? Action-outcome learning in synchronous joint action.

Goal-directed behaviour requires mental representations that encode instrumental relationships between actions and their outcomes. The present study investigated how people acquire representations of joint actions where co-actors perform synchronized action contributions to produce joint outcomes in the environment. Adapting an experimental procedure to assess individual action-outcome learning, we tested whether co-acting individuals link jointly produced action outcomes to individual-level features of their own action contributions or to group-level features of their joint action instead. In a learning phase, pairs of participants produced musical chords by synchronizing individual key press responses. In a subsequent test phase, the previously produced chords were presented as imperative stimuli requiring forced-choice responses by both pair members. Stimulus-response mappings were systematically manipulated to be either compatible or incompatible with the individual and joint action-outcome mappings of the preceding learning phase. Only joint but not individual compatibility was found to modulate participants' performance in the test phase. Yet, opposite to predictions of associative accounts of action-outcome learning, jointly incompatible mappings between learning and test phase resulted in better performance. We discuss a possible explanation of this finding, proposing that pairs' group-level learning experience modulated how participants encoded ambiguous task instructions in the test phase. Our findings inform current debates about mechanistic explanations of action-outcome learning effects and provide novel evidence that joint action is supported by dedicated mental representations encoding own and others' actions on a group level.

Stressful life events and prenatal representations of the child.

Caregivers' mental representations of their children can be assessed prenatally and are prospectively associated with later caregiving quality and caregiver-child attachment. Compared to balanced, distorted or disengaged representations are linked to insecure caregiver-child attachments. The present study explored factors (i.e. stressful life experiences and positive experiences) that may be linked to risk for distorted and disengaged representations. We used a brief version of the Prenatal Working Model of the Child Interview in a sample of 298 pregnant people (ages 19 to 45 years; M = 30.83, SD = 5.00) between gestational age 11-38 weeks (M = 23.49, SD = 5.70). A greater number of stressful events across three developmental periods (i.e., lifespan, childhood, and pregnancy) were related to increased odds of distorted, compared to balanced classification. Pregnancy stress had the largest association. Positive experiences from childhood did not buffer the association between stress and representations. Findings highlight the importance of stress on prenatal representations of one's child.

Distinct neural mechanisms for action access and execution in the human brain: insights from an fMRI study.

Goal-directed actions are fundamental to human behavior, whereby inner goals are achieved through mapping action representations to motor outputs. The left premotor cortex (BA6) and the posterior portion of Broca's area (BA44) are two modulatory poles of the action system. However, how these regions support the representation-output mapping within the system is not yet understood. To address this, we conducted a finger-tapping functional magnetic resonance imaging experiment using action categories ranging from specific to general. Our study found distinct neural behaviors in BA44 and BA6 during action category processing and motor execution. During access of action categories, activity in a posterior portion of BA44 (pBA44) decreased linearly as action categories became less specific. Conversely, during motor execution, activity in BA6 increased linearly with less specific categories. These findings highlight the differential roles of pBA44 and BA6 in action processing. We suggest that pBA44 facilitates access to action categories by utilizing motor information from the behavioral context while the premotor cortex integrates motor information to execute the selected action. This finding enhances our understanding of the interplay between prefrontal cortical regions and premotor cortex in mapping action representation to motor execution and, more in general, of the cortical mechanisms underlying human behavior.

Computational role of structure in neural activity and connectivity.

One major challenge of neuroscience is identifying structure in seemingly disorganized neural activity. Different types of structure have different computational implications that can help neuroscientists understand the functional role of a particular brain area. Here, we outline a unified approach to characterize structure by inspecting the representational geometry and the modularity properties of the recorded activity and show that a similar approach can also reveal structure in connectivity. We start by setting up a general framework for determining geometry and modularity in activity and connectivity and relating these properties with computations performed by the network. We then use this framework to review the types of structure found in recent studies of model networks performing three classes of computations.

Vacillating between "strange" and "familiar" - representations of children in migrant families and their health in Swedish school health services.

Representations of migrants influence how they are perceived by others. Hence, how children who have migrated or whose parents have migrated (Children in Migrant Families: CMFs) are represented in clinical practice guidelines (CPGs) for Swedish school health services (SHS) may influence how they are perceived by school nurses. Thus, this study aimed to explore representations of CMFs in school nurses' CPGs. Data consisted of 130 CPGs from municipalities in Sweden. Documents were analyzed using the "What is the Problem Represented to be" (WPR) approach - an analytic strategy for investigating embedded assumptions of "problems". In the analysis, Sarah Ahmed's work on "strangers" and "strangeness" was applied. In the CPGs, the CMFs and their health were repeatedly mentioned in conjunction with the need for particular or additional actions, efforts, or routines when assessing or discussing their health, to a degree beyond what is "usually" provided. This need was motivated by representing the CMFs and their health as being the same, yet different in relation to "Swedish" children in general. Thus, the children were not only represented as different, but they were "foreignized". These representations of difference and foreignness placed the children on a continuum in relation to what is recognized as "familiar" in their health, and constructed elastic boundaries between the strange and the familiar. By illustrating how these boundaries were used for difference-making between "familiar" and "strange", this study showed how CMFs are alternately represented as similar and different, and foreignized while provided with SHS aiming to make them "familiar".

Classification of Motor Imagery EEG signals using high resolution time-frequency representations and convolutional neural network.

A Motor Imagery (MI) based Brain Computer Interface (BCI) system aims to provide neuro-rehabilitation for the motor disabled people and patients with brain injuries (e.g., stroke patients) etc. The aim of this work is to classify the left and right hand MI tasks by utilizing the occurrence of event related desynchronization and synchronization (ERD\ERS) in the Electroencephalogram (EEG) during these tasks. This study proposes to use a set of Complex Morlet Wavelets (CMW) having frequency dependent widths to generate high-resolution time-frequency representations (TFR) of the MI EEG signals present in the channels C3 and C4. A novel method for the selection of the value of number of cycles relative to the center frequency of the CMW is studied here for extracting the MI task features. The generated TFRs are given as input to a Convolutional neural network (CNN) for classifying them into left or right hand MI tasks. The proposed framework attains a classification accuracy of 82.2% on the BCI Competition IV dataset 2a, showing that the TFRs generated in this work give a higher classification accuracy than the baseline methods and other existing algorithms.

Constructing hierarchical attentive functional brain networks for early AD diagnosis.

Analyzing functional brain networks (FBN) with deep learning has demonstrated great potential for brain disorder diagnosis. The conventional construction of FBN is typically conducted at a single scale with a predefined brain region atlas. However, numerous studies have identified that the structure and function of the brain are hierarchically organized in nature. This urges the need of representing FBN in a hierarchical manner for more effective analysis of the complementary diagnostic insights at different scales. To this end, this paper proposes to build hierarchical FBNs adaptively within the Transformer framework. Specifically, a sparse attention-based node-merging module is designed to work alongside the conventional network feature extraction modules in each layer. The proposed module generates coarser nodes for further FBN construction and analysis by combining fine-grained nodes. By stacking multiple such layers, a hierarchical representation of FBN can be adaptively learned in an end-to-end manner. The hierarchical structure can not only integrate the complementary information from multiscale FBN for joint analysis, but also reduce the model complexity due to decreasing node sizes. Moreover, this paper argues that the nodes defined by the existing atlases are not necessarily the optimal starting level to build FBN hierarchy and exploring finer nodes may further enrich the FBN representation. In this regard, each predefined node in an atlas is split into multiple sub-nodes, overcoming the scale limitation of the existing atlases. Extensive experiments conducted on various data sets consistently demonstrate the superior performance of the proposed method over the competing methods.

Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study.

BACKGROUND: In this paper, we present an automated method for article classification, leveraging the power of large language models (LLMs). OBJECTIVE: The aim of this study is to evaluate the applicability of various LLMs based on textual content of scientific ophthalmology papers. METHODS: We developed a model based on natural language processing techniques, including advanced LLMs, to process and analyze the textual content of scientific papers. Specifically, we used zero-shot learning LLMs and compared Bidirectional and Auto-Regressive Transformers (BART) and its variants with Bidirectional Encoder Representations from Transformers (BERT) and its variants, such as distilBERT, SciBERT, PubmedBERT, and BioBERT. To evaluate the LLMs, we compiled a data set (retinal diseases [RenD] ) of 1000 ocular disease-related articles, which were expertly annotated by a panel of 6 specialists into 19 distinct categories. In addition to the classification of articles, we also performed analysis on different classified groups to find the patterns and trends in the field. RESULTS: The classification results demonstrate the effectiveness of LLMs in categorizing a large number of ophthalmology papers without human intervention. The model achieved a mean accuracy of 0.86 and a mean F1-score of 0.85 based on the RenD data set. CONCLUSIONS: The proposed framework achieves notable improvements in both accuracy and efficiency. Its application in the domain of ophthalmology showcases its potential for knowledge organization and retrieval. We performed a trend analysis that enables researchers and clinicians to easily categorize and retrieve relevant papers, saving time and effort in literature review and information gathering as well as identification of emerging scientific trends within different disciplines. Moreover, the extendibility of the model to other scientific fields broadens its impact in facilitating research and trend analysis across diverse disciplines.

Socially constructed beliefs and the uptake of the Child Dental Benefits Schedule.

BACKGROUND: The Child Dental Benefits Schedule (CDBS) provides automatic access to subsidized dental care for eligible Australian children, but uptake is low. As cost is not a factor, socially constructed perceptions, which may be subscribed to without personal experience, were explored as potential barriers. METHODS: Two studies with parents (child <18 years) were conducted. In Study one (N=317) participants completed a free-response task eliciting socially constructed perceptions about the dentist. These were factor-analysed in Study two (N=231), and the salience of these perceptions in relation to uptake was measured for the 113 eligible to access the CDBS participants. RESULTS: In Study one, similar positive, negative, procedural and time words were elicited across conditions. Study two revealed Negative, Positive and Hassle perception factors associated with the dentist and that 61% of eligible participants had accessed the CDBS. Generalized Structural Equation Modelling with eligible participants revealed Positive and Negative perceptions were negatively correlated, Negative perceptions were positively correlated with Hassle, and, as Hassle increased, the probability of parents accessing the CDBS significantly decreased. CONCLUSIONS: Confusion around eligibility to access CDBS is still an issue. Low CDBS uptake may be associated with perceived hassle associated with the dentist, which may reflect parental negative perceptions. © 2024 Australian Dental Association.

Beliefs and practices of the nursing team related to pressure injury preventive measures: A analysis of social representations.

AIMS AND OBJECTIVES: To analyse the process of elaborating social representations about pressure injury preventive measures by the nursing team (nurses and nurse technicians) and how this process relates to preventive practices for hospitalized patients. DESIGN: Qualitative study, with the application of the theory of social representations in its procedural methodological approach. METHODS: The study was carried out in an inpatient clinic of a public hospital in the state of Rondônia, Brazil. Totally, 28 nursing professionals in the medical clinic sectors who had worked directly with patient care for more than 6 months participated. The data were collected between July and September 2021 via in-depth interviews with the application of a semi-structured instrument. Analysis was carried out with the help of ALCESTE software, which performed a lexicographic analysis, and also via thematic analysis. The COREQ guided the presentation of the research report. RESULTS: The social representations were developed based on the professionals' symbolic beliefs about the visibility/invisibility of the results of applying preventive care. These symbolic constructions mobilized positive and negative feelings among the nursing team, which guided the classification of prevention practices as being of greater or lesser priority among other care activities. There were favourable attitudes among professionals, which included applying prevention measures in their daily routines, and unfavourable attitudes of non-adherence to the institution's protocol for preventing pressure injuries. CONCLUSIONS: The nursing team's perception of pressure injury prevention is influenced by symbolic, affective, values, and social dimensions. Non-adherence behaviours are attributed to the belief in the invisibility of prevention outcomes, resulting in a reluctance to implement preventive measures. RELEVANCE TO CLINICAL PRACTICE: Understanding the subjective logic that explains the thinking and actions of the nursing team suggests the need to incorporate discussions on beliefs, values, sentiments, and attitudes of nursing professionals into educational programs on pressure injury prevention. PATIENT OR PUBLIC CONTRIBUTION: No public contribution.

Orthogonal neural representations support perceptual judgements of natural stimuli.

In natural behavior, observers must separate relevant information from a barrage of irrelevant information. Many studies have investigated the neural underpinnings of this ability using artificial stimuli presented on simple backgrounds. Natural viewing, however, carries a set of challenges that are inaccessible using artificial stimuli, including neural responses to background objects that are task-irrelevant. An emerging body of evidence suggests that the visual abilities of humans and animals can be modeled through the linear decoding of task-relevant information from visual cortex. This idea suggests the hypothesis that irrelevant features of a natural scene should impair performance on a visual task only if their neural representations intrude on the linear readout of the task relevant feature, as would occur if the representations of task-relevant and irrelevant features are not orthogonal in the underlying neural population. We tested this hypothesis using human psychophysics and monkey neurophysiology, in response to parametrically variable naturalistic stimuli. We demonstrate that 1) the neural representation of one feature (the position of a central object) in visual area V4 is orthogonal to those of several background features, 2) the ability of human observers to precisely judge object position was largely unaffected by task-irrelevant variation in those background features, and 3) many features of the object and the background are orthogonally represented by V4 neural responses. Our observations are consistent with the hypothesis that orthogonal neural representations support stable perception of objects and features despite the tremendous richness of natural visual scenes.