Visual Domain Research Articles

Image Analysis in Visual Anthropology Photography: The Biddy’s Photo

Visual anthropology is the study of humans such as through photographs. Although when appreciating how culture is represented visually and when understanding visual concepts, it is not uncommon but rarely used to recognize culture. The primary purpose of this research is to empirically analyse the concept of visual anthropology in culture employing photography as a medium. This study utilises photography as a cultural signal to explore the significance of visual preservation in culture. In addition, this study’s theoretical framework is based on Terry Barrett’s theory of interpreting photographs. Furthermore, this study analyses the photographs from The Biddy’s Photo using a descriptive analysis of photographs as the predominant method of data gathering and utilising the 12 characteristics of a merit image by the Professional Photographers of America, PPA. The outcomes of this research will have a significant influence on the way the public in general perceives the value of cultural photography preservation, visual anthropology, as well as other visual domains relevant to this research, including photography, visual culture, and therefore more. Is it fundamental to comprehend the significance of cultural preservation, particularly when marginalised cultures lack visual representation, as is the situation with certain communities? If predicated on the concept of visual anthropology, photography should be more objective and meaningful in any field of visual and cultural studies.

Methylphenidate improves cognitive function and health-related quality of life in survivors of childhood brain tumours

ABSTRACT Objectives: The growing population of survivors of childhood brain tumors present the challenge of long-term quality of survival. The domains most affected by tumor and treatment are those implicated in development of typical intellectual functions: attention, working memory, and processing speed, with consequent effects upon function and quality of life. In this paper we present service evaluation data on the 12-month effect upon processing speed, visual and auditory attentional domains in 29 patients receiving methylphenidate aged 5-16 years (Mean=10.6). Methods: Patients received immediate-release methylphenidate and were converted to modified-release as appropriate. Mean optimal dose of immediate-release methylphenidate was 0.34 mg/kg per dose (range 0.2-0.67). Results: Patients showed a significant positive impact of methylphenidate on attention in all tests of selective visual attention from the Test of Everyday Attention for Children 2. A significant improvement was also shown on response time. Significant change was not found on psychometric measures of sustained auditory or visual attention, or selective auditory attention. Ratings of Health-Related Quality of Life showed a positive benefit of methylphenidate at 12 months. Side effects were minimal and not statistically significant. Conclusions: Survivors of childhood brain tumor with attentional and processing speed deficit show clinical benefit from methylphenidate.

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification

Machine learning is key for automated detection of malicious network activity to ensure that computer networks and organizations are protected against cyber security attacks. Recently, there has been growing interest in the domain of adversarial machine learning, which explores how a machine learning model can be compromised by an adversary, resulting in misclassified output. Whilst to date, most focus has been given to visual domains, the challenge is present in all applications of machine learning where a malicious attacker would want to cause unintended functionality, including cyber security and network traffic analysis. We first present a study on conducting adversarial attacks against a well-trained network traffic classification model. We show how well-crafted adversarial examples can be constructed so that known attack types are misclassified by the model as benign activity. To combat this, we present a novel defensive strategy based on hierarchical learning to help reduce the attack surface that an adversarial example can exploit within the constraints of the parameter space of the intended attack. Our results show that our defensive learning model can withstand crafted adversarial attacks and can achieve classification accuracy in line with our original model when not under attack.

Validation of Music Therapy Assessment Tool for Awareness in Disorders of Consciousness (MATADOC) with CRS-R

<h3>Research Objectives</h3> To examine the concurrent validity of the MATADOC with the criterion standard Coma Recovery Scale (CRS-R) for diagnostic outcomes of awareness To explore the function of comparable MATADOC items and CRS-R function scales across similar domains (e.g. auditory, visual). <h3>Design</h3> Prospective multisite cohort study collected concurrent MATADOC and CRS-R data using repeated measures with patients with disorders of consciousness (DOC). Raters were blinded. <h3>Setting</h3> Three specialist inpatient rehabilitation units for DOC (US, UK, Ireland). <h3>Participants</h3> 74 adults with prolonged DOC stemming from acquired brain injury recruited using convenience sampling. <h3>Interventions</h3> The MATADOC protocol elicits behavioral responsiveness using live music in five tasks during four clinical contacts of 15-30 minutes duration (60-120 mins total). Observed behavioral responses are rated across motor, communication, arousal, visual and auditory domains using a 14-item measure. Pre and post observation period records spontaneous behaviors. The CRS-R protocol delivers tasks in the motor, visual, auditory and communication domains in clinical contacts of 15-30 minutes duration (60 – 120 minutes in total for 4 contacts). Observed responses are rated in six function scales. <h3>Main Outcome Measures</h3> Two measures of awareness: MATADOC and CRS-R. <h3>Results</h3> Fair (Cohen's kappa or "k"=0.238, p=.006) ranging to moderate (k=0.419, p<.001) significant agreement found between CRS-R and MATADOC diagnostic outcomes for each contact, with significant correlations between scores (mean Pearson = 0.721, p<.001). Agreement increased over repeated contacts. Moderate agreement found for overall diagnostic outcomes ranging across VS, MCS and EMCS (k=0.397, p<.001). Moderate significant agreement found between measures for motor scores (k=.556, p<.001) and visual outcomes (mean k=0.326). No agreement was found for item outcomes assessing auditory responsiveness. <h3>Conclusions</h3> The MATADOC complements the CRS-R in treatment planning for DOC. MATADOC measures of auditory responsiveness suggest musical stimuli may elicit more complex behaviors than non-music protocols. The MATADOC rates complexity of auditory localization as MCS in line with recent recommendations which may explain diagnostic outcome differences with CRS-R outcomes. <h3>Author(s) Disclosures</h3> None.

Aligning Source Visual and Target Language Domains for Unpaired Video Captioning.

Training supervised video captioning model requires coupled video-caption pairs. However, for many targeted languages, sufficient paired data are not available. To this end, we introduce the unpaired video captioning task aiming to train models without coupled video-caption pairs in target language. To solve the task, a natural choice is to employ a two-step pipeline system: first utilizing video-to-pivot captioning model to generate captions in pivot language and then utilizing pivot-to-target translation model to translate the pivot captions to the target language. However, in such a pipeline system, 1) visual information cannot reach the translation model, generating visual irrelevant target captions; 2) the errors in the generated pivot captions will be propagated to the translation model, resulting in disfluent target captions. To address these problems, we propose the Unpaired Video Captioning with Visual Injection system (UVC-VI). UVC-VI first introduces the Visual Injection Module (VIM), which aligns source visual and target language domains to inject the source visual information into the target language domain. Meanwhile, VIM directly connects the encoder of the video-to-pivot model and the decoder of the pivot-to-target model, allowing end-to-end inference by completely skipping the generation of pivot captions. To enhance the cross-modality injection of the VIM, UVC-VI further introduces a pluggable video encoder, i.e., Multimodal Collaborative Encoder (MCE). The experiments show that UVC-VI outperforms pipeline systems and exceeds several supervised systems. Furthermore, equipping existing supervised systems with our MCE can achieve 4% and 7% relative margins on the CIDEr scores to current state-of-the-art models on the benchmark MSVD and MSR-VTT datasets, respectively.

The distorted hand: systematic but 'independent' distortions in both explicit and implicit hand representations in young female adults.

It has long been assumed that an accurate representation of the size and shape of one's body is necessary to successfully interact with the environment. Previous research has shown accurate representations when healthy participants make overt judgments (i.e. explicit) about the size of their bodies. However, when body size is judged implicitly, studies have shown systematic distortions. One suggestion for these differences, is that explicit and implicit representations are informed by different sensory modalities. Explicit representations rely on vision whereas implicit representations are informed by haptics. We designed an experiment to investigate if explicit representations that are informed by haptics are more like implicit representation featuring systematic distortions. We asked female participants to estimate the size of their fingers and hands in three different tasks: an explicit-haptic, an implicit, and an explicit-vision task. The results showed that all three representations were distorted and furthermore, the distortions for each representation were different from one another. These results suggest that inaccurate finger and hand length are a stereotypical feature of body representation that is present in both visual and haptic domains. We discuss the results in relation to theories of body representation.

Exploring Brain Connectivity of Single-Digit and Double-Digit in Familiar and Unfamiliar Numerals: A Functional MRI Study

Learning and memory are closely related in a way that the ability to learn new information is done through working memory and the retrieval of the learned information is done through long-term memory [1]. Over the years, a keen interest in investigating the functional network and interaction in the brain regions during processing number magnitudes has increased among cognitive neuroscientists [2]. The majority of studies related to brain connectivity, especially on numeral cognition focus on children as these investigations could provide insight into neurodevelopmental performance [3].&#x0D; &#x0D; In the current study, we aim to explore brain connectivity associated with familiar and unfamiliar numerals of single-digit and double-digit among young adults. Figure 1 demonstrates the conceptual framework of the current study. This is a quantitative experimental design study that uses a combination of cognitive performance assessment and task-based fMRI block design to measure brain connectivity during learning and retrieval of the acquired information. Fifteen healthy young Malaysian adults in the age range of 18-30 years old who meet the inclusion criteria will be recruited via convenience sampling. Participants will be in one group performing two categories of tasks namely familiar (Chinese) and unfamiliar (Arabic) with two conditions each (single-digit and double-digit). A 3-Tesla MRI Philips Achieva (Philips Medical Systems, Best, Netherlands) scanner with a 32-channel SENSE head coil will be used for data acquisition.&#x0D; Descriptive statistics will be used to summarise the socio-demographic characteristics of subjects. The mean difference in reaction time and accuracy of answers for single and double-digit in familiar and unfamiliar numerals will be analysed using two-way repeated-measures ANOVA and reported. The pre-processing of the fMRI images will be carried out using MATLAB software, Statistical Parametric Mapping 12, and CONN toolbox. The identification and comparison of the brain's functional connectivity will be done using the GIFT toolbox and Statistical Parametric Mapping 12. Results will be reported in the form of figures and tables.&#x0D; &#x0D; Both familiar and unfamiliar numerals are expected to activate the fronto-parietal-occipital networks by extracting the network from the cognitive-control domain, sub-cortical domain, and visual domain but with different connectivity values. Unfamiliar numerals are anticipated to have higher connectivity values than familiar numerals. Similar findings are expected to double and single digits, whereby higher connectivity values in double digits than in the single digits. The limited studies on functional connectivity show the main regions involved in mathematic processing are the inferior frontal gyrus (IPG), intraparietal sulcus (IPS), and inferior temporal gyrus (ITG) [4]. The outcome of this study would be beneficial as it could provide baseline data to investigate abnormalities of brain connectivity in learning and memory-related to numerical cognition among the young adult population.&#x0D;

Disability Phenotypes and Job Accommodations Utilization Among People with Physical Disability.

Purpose People with disabilities (PWD) are less likely to be employed than those without disabilities. Reasonable job accommodations are an essential factor for ensuring equal access to jobs for PWD. However, use of job accommodation is less than optimal among PWD with various types of disabilities. Sometimes, PWD have co-occurring impairments, which might affect accommodation use. This research aimed to explore disability phenotypes, frequently used accommodations, and employee- and job-related factors associated with the extent of job accommodation use. Methods A cross-sectional online survey of PWD was conducted in the Midwest region of the United States. Latent class analyses were used to identify disability phenotypes. Descriptive analysis and stepwise Poisson regression were used to identify factors associated with job accommodation use. Results A total of 326 PWD with work experience after acquiring a disability were included in this analysis. We identified three disability phenotypes: (1) Severe disability in cognitive, physical, emotional, communication and visual domains (32%), (2) Moderate cognitive and low physical disability (48%), and (3) High physical disability phenotypes (20%). 80% of PWD received at least one accommodation. Flexible working schedules, telework, and access to a support person in the workplace were the most common accommodations. Employee- (age, disability phenotypes, motor function) and job-related factors (job preparation, self-employment) are associated dependently with accommodation use. Conclusion This analysis identifies three disability phenotypes and highlights both employee- and job-related factors associated with accommodations used. It may be beneficial to consider multiple contextual factors, including co-occurring disability, employee- and job-related factors, when assisting people with job accommodations.

Between-item similarity frees up working memory resources through compression: A domain-general property.

Compression, the ability to recode information in a denser format, is a core property of working memory (WM). Previous studies have shown that the ability to compress information largely benefits WM performance. Importantly, recent evidence also suggests compression as freeing up WM resources, thus enhancing recall performance for other, less compressible information. Contrary to the traditional view positing that between-item similarity decreases WM performance, this study shows that between-item similarity can be used to free up WM resources through compression. Across a series of four experiments, we show that between-item similarity not only enhances recall performance for similar items themselves, but also for other, less compressible items within the same list, and this in the semantic (Experiment 1), phonological (Experiment 2), visuospatial (Experiment 3), and visual (Experiment 4) domains. Across these different domains, a consistent pattern of results emerged: between-item similarity proactively-but not retroactively-enhanced WM performance for other items, and this as compared with a condition in which between-item similarity at the whole-list level was minimized. We propose that between-item similarity in any domain may impact WM using the same underlying machinery: via a compression mechanism, which allows an efficient reallocation of WM resources. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Complexity in sign languages

Abstract Sign languages are human communication systems that are equivalent to spoken language in their capacity for information transfer, but which use a dynamic visual signal for communication. Thus, linguistic metrics of complexity, which are typically developed for linear, symbolic linguistic representation (such as written forms of spoken languages) do not translate easily into sign language analysis. A comparison of physical signal metrics, on the other hand, is complicated by the higher dimensionality (spatial and temporal) of the sign language signal as compared to a speech signal (solely temporal). Here, we review a variety of approaches to operationalizing sign language complexity based on linguistic and physical data, and identify the approaches that allow for high fidelity modeling of the data in the visual domain, while capturing linguistically-relevant features of the sign language signal.

Initial Provider and Patient-Reported Outcomes of a Phase II Study of Short Course Hypofractionated Proton Beam Therapy Incorporating 18F-DOPA-PET/MRI for Elderly Patients with Newly Diagnosed Glioblastoma

<h3>Purpose/Objective(s)</h3> Due to poorer prognosis, hypofractionated radiation therapy is considered for elderly patients with newly diagnosed glioblastoma. Targeted radiation delivery with proton beam therapy (PBT) utilizing 18F-DOPA PET to identify biologically aggressive disease may be desirable. We report both provider and patient reported outcomes of a phase II trial evaluating hypofractionated PBT incorporating 18F-DOPA in treatment planning. <h3>Materials/Methods</h3> Patients ≥ 65 with histologically confirmed glioblastoma without contraindications to 18-FDOPA were enrolled. Target volumes were defined by PET (tumor/normal brain SUV ≥2.0) and MRI areas of contrast enhancement (MRI-CE) including surgical cavity. A combined volume of 65 cc or less was treated with 25 (1 cm margin), 30 (MRI-CE), and 35 (PET) GyE over 5 fractions with a simultaneous integrated boost. A combined volume of more than 65 cc was treated with 30 (1 cm margin), 35 (MRI-CE), and 40 (PET) GyE over 10 fractions. Patients received concurrent/adjuvant temozolomide. Provider-reported toxicity was assessed according to CTCAE V4. Patients completed EORTC BN20, QLQ-C30, and MMSE. QOL outcomes were compared with prior published phase III trials (NCT00482677 and NCT00430911). Time to deterioration, defined as a 10-point decrease in the score of the function domain or 10-point increase in score of symptom domain, was evaluated. <h3>Results</h3> Between 5/19 and 10/21, 39 patients were enrolled. 36 (92.3%) patients were IDH1 wt and 3 were IDH1 (7.7%) mt. MGMT promotor methylation was present in 13 (33%). The median clinical follow-up was 5.2 months. Tumors were multifocal in 10 (25.6%) and unifocal in 29 (74.4%). The median tumor diameter was 5.2 cm. Twenty-one patients (53.8%) received 40 GyE in 10 fractions and 18 (46.2%) received 35 GyE in 5 fractions. Baseline adjusted treatment related grade 2+ adverse events were: 8 (20.5%) CNS necrosis, 3 (7.7%) confusion, 1 (2.5%) dysphasia, 9 (23.1%) fatigue, 2 (5.1%) headache, 5 (12.8%) seizure, and 4 (10.2%) alopecia. Grade 3 baseline adjusted treatment related adverse events included 1 (2.6%) confusion, 2 (5.1%) fatigue, and 1 (2.6%) seizure. There were no grade 4/5 events. The median time to deterioration per QLQ-C30 was 6.3 months which was greater compared to the treatment arms (1.2 months, p<0.05) of NCT00482677 trial. At 90 days, there was improved (p<0.05) functioning in global, physical, role, emotional, social domains of QLQ-C30 and visual domain of BN20 for patients receiving PBT versus the supportive care arm of the NCT00430911. <h3>Conclusion</h3> Hypofractionated PBT incorporating 18F-DOPA in elderly patients was feasible with reasonable provider reported toxicity. Patient-reported outcomes compared favorably to prior phase III studies with similar patient populations.

A plea for visual inquiry

This contribution is intended as a plea for the reappraisal of drawing as a means of active visual inquiry in Visual Literacy. Active visual inquiry is a most adequate concept to describe the first two phases of the sub-domain of ‘producing’ in the revised Common European Framework of Reference for Visual Competency (CEFR-VC): ‘the competency to generate visual ideas’ and ‘the competency to do visual research’. It also relates to activities covered by the first two phases of the sub-domain of ‘responding’ in the CEFR-VC: the ‘competency to perceive images with an open mind’ and ‘the competency to explore images’. All four competencies rely on ways of visual thinking, visual analysis and understanding of images in visual terms. They suggest that learning in the visual domain should be compulsory for all students in education. These competencies and their underlying skills were paramount in art education before World War II. Since then we have witnessed a gradual marginalization of these competencies – in particular technique and repertoire – in favour of interests in content, communication and creativity. We think it is time to address the neglect of these competencies and make a plea for active visual inquiry through drawing to be given a more prominent place in visual literacy education than it is given now.

Excluding People With Disabilities From Clinical Research: Eligibility Criteria Lack Clarity And Justification.

The exclusion of people with disabilities from clinical research without appropriate justification is discriminatory, is counter to federal regulations and research guidelines, and limits study generalizability. This matter is understudied, and data on the disability status of trial participants are rarely collected or reported. We analyzed ninety-seven recent interventional protocols in four therapeutic areas registered on ClinicalTrials.gov. Eighty-five percent of protocols allowed broad investigator discretion to determine eligibility, whereas only 18percent explicitly permitted people with disabilities to use forms of support (such as supported decision making or assistive devices) to facilitate study participation. Eligibility criteria affecting people with disabilities included exclusions for psychiatric (68percent), substance use (62percent), HIV or hepatitis (53percent), cognitive or intellectual (42percent), visual (34percent), hearing (10percent), mobility (9percent), long-term care (6percent), and speech and communication (3percent) disability-related domains. Documented justification was provided for only 24percent of these exclusions. We recommend greater scrutiny of study eligibility criteria, scientific or ethical justification of exclusions, and accessible study design.

Deep Active Cross-Modal Visuo-Tactile Transfer Learning for Robotic Object Recognition

We propose for the first time, a novel deep active visuo-tactile cross-modal full-fledged framework for object recognition by autonomous robotic systems. Our proposed network <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">xAVTNet</i> is actively trained with labelled point clouds from a vision sensor with one robot and tested with an active tactile perception strategy to recognise objects never touched before using another robot. We propose a novel visuo-tactile loss ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VTLoss</i> ) to minimise the discrepancy between the visual and tactile domains for unsupervised domain adaptation. Our framework leverages the strengths of deep neural networks for cross-modal recognition along with active perception and active learning strategies for increased efficiency by minimising redundant data collection. Our method is extensively evaluated on a real robotic system and compared against baselines and other state-of-art approaches. We demonstrate clear outperformance in recognition accuracy compared to the state-of-art visuo-tactile cross-modal recognition method.

Light field quality assessment based on aggregation learning of multiple visual features.

Light field imaging is a way to represent human vision from a computational perspective. It contains more visual information than traditional imaging systems. As a basic problem of light field imaging, light field quality assessment has received extensive attention in recent years. In this study, we explore the characteristics of light field data for different visual domains (spatial, angular, coupled, projection, and depth), study the multiple visual features of a light field, and propose a non-reference light field quality assessment method based on aggregation learning of multiple visual features. The proposed method has four key modules: multi-visual representation of a light field, feature extraction, feature aggregation, and quality assessment. It first extracts the natural scene statistics (NSS) features from the central view image in the spatial domain. It extracts gray-level co-occurrence matrix (GLCM) features both in the angular domain and in the spatial-angular coupled domain. Then, it extracts the rotation-invariant uniform local binary pattern (LBP) features of depth map in the depth domain, and the statistical characteristics of the local entropy (SDLE) features of refocused images in the projection domain. Finally, the multiple visual features are aggregated to form a visual feature vector for the light field. A prediction model is trained by support vector machines (SVM) to establish a light field quality assessment method based on aggregation learning of multiple visual features.

Multiple Case Studies in German Children with Dyslexia: Characterization of Phonological, Auditory, Visual, and Cerebellar Processing on the Group and Individual Levels.

Background: The underlying mechanisms of dyslexia are still debated. The question remains as to whether there is evidence of a predominant type of deficit or whether it is a multideficit disorder with individual profiles. The assumptions of which mechanism causes the disorder influences the selection of the training approach. Methods: A sample of German neurotypical reading children (NT) and children with dyslexia (DYSL) was investigated with a comprehensive behavioral test battery assessing phonological, auditory, visual, and cerebellar performance, thus addressing performance described in three major theories in dyslexia. Results: In the present sample using the test battery of the present study, DYSL had the strongest impairment in phonological and auditory processing, accompanied by individual processing deficits in cerebellar performance, but only a few in the investigated visual domains. Phonological awareness and auditory performance were the only significant predictors for reading ability. Conclusion: These findings point out that those reading difficulties were associated with phonological as well as auditory processing deficits in the present sample. Future research should investigate individual deficit profiles longitudinally, with studies starting before literacy acquisition at as many processing domains as possible. These individual deficit profiles should then be used to select appropriate interventions to promote reading and spelling.

Manifold embedded joint geometrical and statistical alignment for visual domain adaptation

Supervised learning algorithms like KNN assume that the training and the testing data come from the same source, and hence, have the same distribution. However, in real life, such instances are rare. Domain adaptation (DA) aims to model a classifier that is invariant to the different features of the training data. Domain invariant features are utilized to reduce distribution differences, ensuring an iterative improvement on the predicted target labels. Existing DA approaches either perform manifold subspace learning or align cross-domain distributions. At the same time, there exists a couple of imperative limitations: (1) degenerated feature transformation, wherein the seemingly domain invariant features are distorted during transformation (2) formulation of a robust objective function that must consider critical objectives in a unified framework to minimize deviations geometrically and statistically. To the best of our knowledge, none of the existing DA approaches address these two limitations simultaneously. Therefore, we propose a novel domain adaptation framework, called Manifold Embedded Joint Geometrical and Statistical Alignment (MEJGSA) for visual domain adaptation to address these limitations. MEJGSA first learns manifold features, and then formulates a robust objective function to reduce divergence between domains geometrically and statistically. We also consider more reliable classifiers to generate pseudo-labels to preserve objective functions such as conditional distributions and target domain discriminant information. Extensive experiments on two widely used cross-domain adaptation datasets demonstrate that MEJGSA exhibits significant improvements in classification accuracy as compared to cutting-edge shallow and deep DA approaches. The MATLAB code for our proposed method will be publicly available at 11https://github.com/rakesh1000/MEJGSA.

Irrelevant sights and sounds require spatial suppression: ERP evidence.

Both real-world experience and behavioral laboratory research suggest that entirely irrelevant stimuli (distractors) can interfere with a primary task. However, it is as yet unknown whether such interference reflects competition for spatial attention - indeed, prominent theories of attention predict that this should not be the case. Whilst electrophysiological indices of spatial capture and spatial suppression have been well-investigated, experiments have primarily utilized distractors which share a degree of task-relevance with targets, and are limited to the visual domain. The present research measured behavioral and ERP responses to test the ability of salient yet entirely task-irrelevant visual and auditory distractors to compete for spatial attention during a visual task, while also testing for potentially enhanced competition from multisensory distractors. Participants completed a central letter search task, while ignoring lateralized visual (e.g., image of a dog), auditory (e.g., barking), or multisensory (e.g., image + barking) distractors. Results showed that visual and multisensory distractors elicited a PD component indicative of active lateralized suppression. We also establish for the first time an auditory analog of the PD component, the PAD , elicited by auditory and multisensory distractors. Interestingly, there was no evidence to suggest enhanced ability of multisensory distractors to compete for attentional selection, despite previous proposals of a "special" saliency status for such items. Our findings hence suggest that irrelevant multisensory and unisensory distractors are similarly capable of eliciting a spatial "attend-to-me" signal - a precursor of spatial attentional capture - but at least in the present data set did not elicit full spatial attentional capture.

Sensory and motor correlates of frailty: dissociation between frailty phenotype and frailty index

BackgroundFrailty has been associated with a decline in sensory and motor function. However, given that different frailty measures were shown to overlap but also differ in their diagnostic properties, sensory and motor correlates of frailty might be different depending on the operationalization of frailty. Our objective was to identify sensory and motor determinants of frailty and compare the results between frailty phenotype (FP) and frailty index (FI).MethodsData from 44 pre-frail and frail subjects aged 65 and above were used. Frailty was measured using the FP and the FI. Sensory function in the visual, auditory, and tactile domain was assessed using visual acuity, absolute hearing threshold and mechanical detection threshold. Upper extremity motor performance was evaluated by the Purdue Pegboard Test and the Short Physical Performance Battery was used to assess lower extremity motor function. Multiple logistic regression models were employed to determine associations of sensory and motor function with frailty vs. pre-frailty for both frailty measures.ResultsThe frailty measures were moderately correlated (0.497, p ≤ 0.01) and had a Kappa agreement of 0.467 (p = 0.002). Using the FP, frailty was significantly associated with reduced upper extremity motor function only (OR = 0.50, 95% CI 0.29–0.87, p = 0.014). Frailty as assessed by the FI was significantly related to higher hearing thresholds (OR = 1.21, 95% CI 1.02–1.43, p = 0.027) and reduced lower extremity performance (OR = 0.32, 95% CI 0.13–0.77, p = 0.012).ConclusionFrailty is related to reduced performance in measures of sensory and motor function. However, traditional measures of frailty might be differentially sensitive to capture sensory and motor decline, possibly contributing to the much-observed discordance between the diagnostic instruments. This should be taken into account by researchers and clinicians when planning and evaluating therapeutic interventions for frailty.Trial registrationClinicalTrials.gov NCT03666039. Registered 11 September 2018 – Retrospectively registered.

Oculomotor system can differentially process red and green colors during saccade programming in the presence of a competing distractor.

Selective attention filters irrelevant information entering our brain to allow for fine-tuning of the relevant information processing. In the visual domain, shifts of attention are most often followed by a saccadic eye movement to objects and places of high relevance. Recent studies have shown that the stimulus color can affect saccade target selection and saccade trajectories. While those saccade modulations are based on perceptual color space, the level in the visual processing hierarchy at which color selection biases saccade programming remains unclear. As color has also been shown to influence manual response inhibition which is a key function of the prefrontal cortex, we hypothesized that the effects of color on executive functions would also inherently affect saccade programming. To test this hypothesis, we measured behavioral performance and saccade metrics during a modified saccadic Stroop task which reflects competition between color words ("RED" and "GREEN") and their color at the level of the prefrontal cortex. Our results revealed that the oculomotor system can differentially process red and green colors when planning a saccade in the presence of a competing distractor.