Lower Childhood Socioeconomic Status Is Associated with Greater Neural Responses to Ambient Auditory Changes in Adulthood.

Humans' early life experience varies by socioeconomic status (SES), raising the question of how this difference is reflected in the adult brain. An important aspect of brain function is the ability to detect salient ambient changes while focusing on a task. Here, we ask whether subjective social status during childhood is reflected by the way young adults' brain detecting changes in irrelevant information. In two studies (total n = 58), we examine electrical brain responses in the frontocentral region to a series of auditory tones, consisting of standard stimuli (80%) and deviant stimuli (20%) interspersed randomly, while participants were engaged in various visual tasks. Both studies showed stronger automatic change detection indexed by MMN in lower SES individuals, regardless of the unattended sound's feature, attended emotional content, or study type. Moreover, we observed a larger MMN in lower-SES participants, although they did not show differences in brain and behavior responses to the attended task. Lower-SES people also did not involuntarily orient more attention to sound changes (i.e., deviant stimuli), as indexed by the P3a. The study indicates that individuals with lower subjective social status may have an increased ability to automatically detect changes in their environment, which may suggest their adaptation to their childhood environments.

Action control costs in task selection: Agents avoid actions with incompatible movement and effect features.

When a movement triggers effects with incompatible features, conflict between action and effect features creates costs for action planning and initiation. We investigated whether such action control costs also factor into action choices in terms of the principle of least effort. Participants completed a reaction-time experiment, where they were instructed to perform left and right mouse swipes in response to directional cues presented on the screen. Participants could select between two action options on each trial: Depending on which part of the screen (upper or lower) the action was performed in, the swipe resulted in a visual stimulus moving in the same (compatible) or in the opposite (incompatible) direction as the mouse. Incompatible action-effect mappings did indeed incur action control costs. In accordance with effort avoidance, the proportion of compatible choices was significantly above chance level, suggesting that action selection and initiation costs factor into participants preferences. Interestingly, however, participants' choice tendencies were not predicted by the actual increase in action-initiation costs in the incompatible condition. This indicates that effort-related decisions are not simply based on monitoring performance in the actual task, but they are also influenced by preestablished notions of action-planning costs.

Interrelatedness of steering and lateral position parameters: Recommendations for the assessment of driving performance.

INTRODUCTION: Loss of attention leads to less steady driving within the lane and is one of the main causes of road accidents. To improve road safety, vehicle-based parameters such as steering wheel angle and lateral position are used to objectively assess driving performance, especially in monotonous driving tasks. METHOD: The present driving simulator study investigated the extent to which eight commonly used parameters are independent indicators of driving performance. Fifteen participants undertook a monotonous highway driving task for 1 h. Four steering angle parameters were examined: average steering angle (ASA), standard deviation of steering angle (SDSA), steering angle range (SAR), and steering reversal rate (SRR); as well as four lateral position parameters: mean lateral position (MLP), standard deviation of lateral position (SDLP), lateral position range (LPR), and the out-of-lane duration. Measurements were averaged across 2-minute epochs. Repeated measures correlation analysis evaluated the similarity between each parameter, and the variance inflation factor test evaluated the multicollinearity of all the parameters. RESULTS: The results demonstrated that some parameters are highly correlated and should not be used together to assess driving performance. It is recommended that the optimal combination is ASA and SAR to assess steering angle, and SDLP and out-of-lane to assess lateral position. Out-of-lane, as a factor directly contributing to road safety, is recommended because it has the least correlation with other parameters. PRACTICAL APPLICATIONS: If implemented, these recommendations may improve the assessment of driving performance in future studies.

Assessment of Drivers' Mental Workload by Multimodal Measures during Auditory-Based Dual-Task Driving Scenarios.

Assessing drivers' mental workload is crucial for reducing road accidents. This study examined drivers' mental workload in a simulated auditory-based dual-task driving scenario, with driving tasks as the main task, and auditory-based N-back tasks as the secondary task. A total of three levels of mental workload (i.e., low, medium, high) were manipulated by varying the difficulty levels of the secondary task (i.e., no presence of secondary task, 1-back, 2-back). Multimodal measures, including a set of subjective measures, physiological measures, and behavioral performance measures, were collected during the experiment. The results showed that an increase in task difficulty led to increased subjective ratings of mental workload and a decrease in task performance for the secondary N-back tasks. Significant differences were observed across the different levels of mental workload in multimodal physiological measures, such as delta waves in EEG signals, fixation distance in eye movement signals, time- and frequency-domain measures in ECG signals, and skin conductance in EDA signals. In addition, four driving performance measures related to vehicle velocity and the deviation of pedal input and vehicle position also showed sensitivity to the changes in drivers' mental workload. The findings from this study can contribute to a comprehensive understanding of effective measures for mental workload assessment in driving scenarios and to the development of smart driving systems for the accurate recognition of drivers' mental states.

Integrating visual large language model and reasoning chain for driver behavior analysis and risk assessment.

Driver behavior is a critical factor in driving safety, making the development of sophisticated distraction classification methods essential. Our study presents a Distracted Driving Classification (DDC) approach utilizing a visual Large Language Model (LLM), named the Distracted Driving Language Model (DDLM). The DDLM introduces whole-body human pose estimation to isolate and analyze key postural features-head, right hand, and left hand-for precise behavior classification and better interpretability. Recognizing the inherent limitations of LLMs, particularly their lack of logical reasoning abilities, we have integrated a reasoning chain framework within the DDLM, allowing it to generate clear, reasoned explanations for its assessments. Tailored specifically with relevant data, the DDLM demonstrates enhanced performance, providing detailed, context-aware evaluations of driver behaviors and corresponding risk levels. Notably outperforming standard models in both zero-shot and few-shot learning scenarios, as evidenced by tests on the 100-Driver dataset, the DDLM stands out as an advanced tool that promises significant contributions to driving safety by accurately detecting and analyzing driving distractions.

Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease.

OBJECTIVE: Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD. METHOD: Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials. RESULTS: Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites. CONCLUSIONS: Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

An Objective Assessment of Effect of Stimulants on Attention in Individuals With ADHD.

INTRODUCTION: Currently, assessing ADHD treatment response to stimulants relies on rating scales and subjective questionnaires and sometimes a CPT. Such tools fall short of objective, quantifiable measurement of effect, especially in natural settings and can result in inconsistent treatment. METHOD: We report results from two studies using a novel proof-of-concept approach. A preliminary trial of 10 individuals used a high-fidelity eye tracker; a second study of 100 individuals used webcams at the participants' homes. RESULTS: Both studies evaluated stimulant effect using reading behavior analysis, being an ADHD symptom that stimulants affect and a major symptom patients want to improve. Both showed a significant change in reading behavior related to medication state, suggesting a clear, objective measure of stimulant effect. CONCLUSION: Using ubiquitous hardware, investigators created a user-friendly treatment assessment platform where individuals can collect their own objective data within minutes in any setting where they have access to a web camera and computer.

Attention network training promotes selective attention of children with low socioeconomic status.

The objectives of this study were to evaluate the difference of selective attention efficiency between children with low and high socioeconomic status (SES) and the promotional effect of attention network training (an attention network test was used as the training task) on selective attention in children with the low SES. A total of 139 10- to 12-year-old children participated in two experiments (71 in Experiment 1 and 68 in Experiment 2). The results suggest that selective attention and switch ability of children with high SES are better than those of children with low SES. After attention network training, selective attention, switch ability, and working memory of low-SES children improved significantly. The findings provide evidence that attention network training could enhance selective attention in low-SES children and that the beneficial training effect could also transfer to switch ability and working memory. The research may provide a promising method to compensate cognitive delay of low-SES children.

Global practitioner assessment and management of mental fatigue and mental recovery in high-performance sport: A need for evidence-based best-practice guidelines.

BACKGROUND: Mental fatigue and mental recovery have gained scientific attention in relation to sporting performance, yet best practice assessment and management methods are lacking. A greater understanding of current knowledge and practices in high-performance sport are necessary. OBJECTIVE: To understand the contemporary knowledge, beliefs, monitoring processes, management strategies, perceived responsibility, sources of evidence, and challenges, when assessing the mental fatigue and mental recovery of athletes in high-performance sport. METHODS: A mixed-methods survey approach obtained information from 156 multi-disciplinary high-performance sport practitioners. Descriptive outputs were reported and potential differences between key concepts were detected using Wilcoxon-signed rank analysis. Thematic analysis interpreted open-text responses. RESULTS: Only 11.5% and 5.1% of respondents indicated they were "very" knowledgeable about mental fatigue and mental recovery, respectively. Knowledge (p < 0.001) and confidence in application (p = 0.001) were significantly greater for mental fatigue than mental recovery. Nearly all respondents perceived mental fatigue and mental recovery impacted training and competition performance, with a greater negative impact during competition (p < 0.001). A limited number of respondents reported deliberate assessment (31.1%) or management (51.2%) of mental fatigue and mental recovery. A combination of sources of evidence were used to inform practice, with common challenges to implementation including staff knowledge, athlete-buy in, time-availability, and a lack of evidence. Practitioners reported that assessing and managing mental fatigue and mental recovery was multi-disciplinary in nature. CONCLUSION: Practitioners reported that mental fatigue and mental recovery did impact performance, yet this was not reflected in the implementation of evidence-based assessment and management practices in high-performance sport.

Factor structure of the Harmonized Cognitive Assessment Protocol neuropsychological battery in the Health and Retirement Study.

OBJECTIVE: The Harmonized Cognitive Assessment Protocol (HCAP) describes an assessment battery and a family of population-representative studies measuring neuropsychological performance. We describe the factorial structure of the HCAP battery in the US Health and Retirement Study (HRS). METHOD: The HCAP battery was compiled from existing measures by a cross-disciplinary and international panel of researchers. The HCAP battery was used in the 2016 wave of the HRS. We used factor analysis methods to assess and refine a theoretically driven single and multiple domain factor structure for tests included in the HCAP battery among 3,347 participants with evaluable performance data. RESULTS: For the eight domains of cognitive functioning identified (orientation, memory [immediate, delayed, and recognition], set shifting, attention/speed, language/fluency, and visuospatial), all single factor models fit reasonably well, although four of these domains had either 2 or 3 indicators where fit must be perfect and is not informative. Multidimensional models suggested the eight-domain model was overly complex. A five-domain model (orientation, memory delayed and recognition, executive functioning, language/fluency, visuospatial) was identified as a reasonable model for summarizing performance in this sample (standardized root mean square residual = 0.05, root mean square error of approximation = 0.05, confirmatory fit index = 0.94). CONCLUSIONS: The HCAP battery conforms adequately to a multidimensional structure of neuropsychological performance. The derived measurement models can be used to operationalize notions of neurocognitive impairment, and as a starting point for prioritizing pre-statistical harmonization and evaluating configural invariance in cross-national research.

If Opportunity Knocks: Understanding Contextual Factors' Influence on Cognitive Systems.

Central to the Research Domain Criteria (RDoC) framework is the idea that RDoC constructs, which vary dimensionally by individual, are heavily influenced by contextual factors. Perhaps chief among these contextual factors is structural opportunity - the quality of resources available to a child as they grow. The aim of this study is to understand the impact of access to opportunity during childhood on three central RDoC cognitive systems constructs: language, visual perception, and attention. These constructs were measured using clinical data from psychological evaluations of youth ages 4-18 years (N = 16,523; Mage = 10.57, 62.3% male, 55.3% White). Structural opportunity was measured using the geocoded Child Opportunity Index 2.0 (COI), a composite score reflecting 29 weighted indicators of access to the types of neighborhood conditions that help children thrive. Findings indicate that, controlling for demographic and socioeconomic factors, greater access to opportunity is associated with significantly stronger cognitive skills across all three constructs. However, opportunity uniquely explains the largest proportion of the variance in language skills (8.4%), compared to 5.8% of the variance in visual processing skills and less than 2% of the variance in attention. Further, a moderating effect of age was found on the relation between COI and language skills, suggesting that the longer children remain exposed to lower levels of opportunity, the lower their language skills tend to be. Understanding how opportunity impacts cognitive development allows clinicians to offer better tailored recommendations to support children with cognitive systems deficits, and will support policy recommendations around access to opportunity.

Attentional heterogeneity in social anxiety disorder: Evidence from Hidden Markov Models.

There is some evidence for heterogeneity in attentional processes among individuals with social anxiety. However, there is limited work considering how attentional processes may differ as a mechanism in a naturalistic task-based context (e.g., public speaking). In this secondary analysis we tested attentional heterogeneity among individuals diagnosed with social anxiety disorder (N = 21) in the context of a virtual reality exposure treatment study. Participants completed a public speaking challenge in an immersive 360°-video virtual reality environment with eye tracking at pre-treatment, post-treatment, and at 1-week follow-up. Using a Hidden Markov Model (HMM) approach with clustering we tested whether there were distinct profiles of attention pre-treatment and whether there were changes following the intervention. As a secondary aim we tested whether the distinct attentional profiles at pre-treatment predicted differential treatment outcomes. We found two distinct attentional profiles pre-treatment that we characterized as audience-focused and audience-avoidant. However, by the 1-week follow-up the two profiles were no longer meaningfully different. We found a meaningful difference between HMM groups for fear of public speaking at post-treatment b = -8.54, 95% Highest Density Interval (HDI) [-16.00, -0.90], Bayes Factor (BF) = 8.31 but not at one-week follow-up b = -5.83, 95% HDI [-13.25, 1.81], BF = 2.28. These findings provide support for heterogeneity in attentional processes among socially anxious individuals, but our findings indicate that this may change following treatment. Moreover, our results offer preliminary mechanistic evidence that patterns of avoidance may be specifically related to poorer treatment outcomes for virtual reality exposure therapy.

The Mex-Cog cognitive assessment battery: discriminant analysis of the cognitive performance profile in older adults.

OBJECTIVE: To analyze the cognitive profile of a clinical sample using the Mex-Cog cognitive battery and establish which cognitive measures and domains contribute most to group separation. MATERIALS AND METHODS: A group of 145 older adults previously diagnosed with dementia (n= 47), mild cognitive impairment MCI (n= 47), or as cognitively normal (n= 51) were assessed with the Mex-Cog cognitive battery. Six linear discriminant analyses (LDA) were estimated to compare dementia vs. cognitively normal, MCI vs. cognitively normal, and MCI vs. dementia, using ten individual measures and six cognitive domains. We used a leave-one-out cross-validation procedure to evaluate the predictive capacity of LDA models. RESULTS: Discriminant functions using individual measures and domains distinguished correctly 100% of dementia and cognitively normal groups showing a memory and executive function profile. The predictive group membership for MCI versus cognitively normal varied between 82 and 85%, with a cognitive profile associated with attention-executive function followed by memory. Group separation between MCI and dementia was between 80 and 87%, characterized by orientation, memory, and visuospatial abilities. CONCLUSIONS: The Mex-Cog cognitive battery is useful for identifying cognitive impairment in older adults.

A novel multisensory device for the assessment and rehabilitation of perceptual and attentional competencies.

The present study aims to assess a novel technological device suitable for investigating perceptual and attentional competencies in people with or without sensory impairment. The TechPAD is a cabled system including embedded sensors and actuators to enable visual, auditory, and tactile interactions and a capacitive surface receiving inputs from the user. The system is conceived to create multisensory environments, using multiple units controlled separately and simultaneously. We assessed the device by adapting a spatial attention task comparing performances in different cognitive load conditions (high or low) and stimulation (unimodal, bimodal, or trimodal). 28 sighted adults were asked to monitor both the central and peripheral parts of the device and to tap a target stimulus (either visual, auditory, haptic, or multimodal) as fast as they could. Our results suggest that this new device can provide congruent and incongruent multimodal stimuli and quantitatively measure parameters such as reaction time and accuracy, allowing to investigate perceptual mechanisms in multisensory environments.Clinical Relevance-The TechPad is a reliable tool for the assessment of spatial attention during interactive tasks. its application in clinical trials will pave the way to its role in multisensory rehabilitation.

Serial attentional resource allocation during parallel feature value tracking.

The visual system has evolved the ability to track features like color and orientation in parallel. This property aligns with the specialization of processing these feature dimensions in the visual cortex. But what if we ask to track changing feature-values within the same feature dimension? Parallel tracking would then have to share the same cortical representation, which would set strong limitations on tracking performance. We address this question by measuring the precision of color representations when human observers track the color of two superimposed dot clouds that simultaneously change color along independent trajectories in color-space. We find that tracking precision is highly imbalanced between streams and that tracking precision changes over time by alternating between streams at a rate of ~1 Hz. These observations suggest that, while parallel color tracking is possible, it is highly limited, essentially allowing for only one color-stream to be tracked with precision at a given time.

Validation of cost-efficient EEG experimental setup for neural tracking in an auditory attention task.

When individuals listen to speech, their neural activity phase-locks to the slow temporal rhythm, which is commonly referred to as "neural tracking". The neural tracking mechanism allows for the detection of an attended sound source in a multi-talker situation by decoding neural signals obtained by electroencephalography (EEG), known as auditory attention decoding (AAD). Neural tracking with AAD can be utilized as an objective measurement tool for diverse clinical contexts, and it has potential to be applied to neuro-steered hearing devices. To effectively utilize this technology, it is essential to enhance the accessibility of EEG experimental setup and analysis. The aim of the study was to develop a cost-efficient neural tracking system and validate the feasibility of neural tracking measurement by conducting an AAD task using an offline and real-time decoder model outside the soundproof environment. We devised a neural tracking system capable of conducting AAD experiments using an OpenBCI and Arduino board. Nine participants were recruited to assess the performance of the AAD using the developed system, which involved presenting competing speech signals in an experiment setting without soundproofing. As a result, the offline decoder model demonstrated an average performance of 90%, and real-time decoder model exhibited a performance of 78%. The present study demonstrates the feasibility of implementing neural tracking and AAD using cost-effective devices in a practical environment.

"Investor attention fluctuation and stock market volatility: Evidence from China".

This paper examines the linkage between Chinese stock market volatility and investor attention fluctuation. In Heterogeneous autoregressive (HAR) model, first, we analyzed the linkage between both decomposed and undecomposed stock market realized volatility and investor attention fluctuations across full-sample and two-year moving window sub-samples. Second, we compare the predictive power of four models in short-, medium-, and long-term volatility forecasting. Empirical results show large positive attention fluctuation amplified Chinese stock market volatility after the outbreak of COVID-19, and negative small attention fluctuation significantly stabilized stock market volatility before COVID-19, and the impact dwindled in after COVID-19. The model incorporating decomposed realized volatility and decomposed attention fluctuation performs better in volatility Forecasting. This research underscores a shift in the dynamics between stock market volatility and investor attention fluctuations, and investor attention fluctuation improves the volatility forecasting accuracy of the Chinese stock market.

Attention Test Assessment from a Cluster Randomized Controlled Trial of Caregiver Training for Ugandan Preschool Children Living with Perinatal HIV.

Fifty-six Ugandan mothers/caregivers received Mediational Intervention for Sensitizing Caregivers (MISC) biweekly for one year; 46 mothers received treatment-as-usual. Preschool PHIV child attention was measured by proportion of time viewing a 7-min animation (early childhood vigilance test or ECVT) at enrollment, 6 and 12 months. Analysis of covariance compared ECVT outcomes for the two intervention groups, controlling for baseline ECVT performance, age and weight-for-age z scores. Differences by trial arm were not significant at any of the three time points. MISC trial-arm children on combination ART during the study period displayed more stable ECVT scores across time points compared to controls.

A psychometric study of an executive function assessment instrument (TDI-FE).

BACKGROUND: This study aims to present and discuss the psychometric properties of executive functions, which were measured using the TDI-FE instrument. The analysis encompasses its internal structure, potential sensitivity to fatigue factors, relationships with external criteria, and diagnostic accuracy. METHODS: The study sample comprised 382 students from Brazil, aged 6-8 years. Child development variables were screened using the TDI-FE and gold standard tests (Cancellation Attention and Trail Making Tests). The proposed scale comprised four activities: a test with fruit images with three tasks, and one memory game. RESULTS: The one-factor model of EF of the TDI-FE failed to fit to the data. However, fit substantially improved once a latent fatigue factor was controlled in the model. The latent factor of EF assessed by the TDI-FE tasks was coherently associated with a series of external variables, including two popular collateral measures of EF. The diagnostic accuracy was reasonable, and a cut-off of 37 points produced 70% of sensitivity and 60% of specificity. CONCLUSION: Results indicated that the TDI-FE demonstrated sound psychometric properties and diagnostic accuracy, then consisting of an efficient alternative for the assessment of EFs in early childhood education. The study also proved the need to control for response biases such as fatigue in the latent variable models of EF. The TDI-FE is notable because of its low cost and easy application, and it might fulfill a need for instruments for individuals from different contexts at this stage of development in Brazil.

Detection cost: A nonnegligible factor contributing to inhibition of return in the discrimination task under the cue-target paradigm.

The three-factor model argues that the spatial orienting benefit triggered by the cue, the spatial selection benefit of cue-target matching, and the detection cost of distinguishing the cue from the target contribute to the measured inhibition of return (IOR) effect. According to the three-factor model, the spatial selection benefit dominates the occurrence of the IOR effect in the discrimination task, while the detection cost is negligible. The present study verified the three-factor model in the discrimination task under the cue-target paradigm by manipulating the spatial location and nonspatial feature consistency of the cue and the target as well as the promotion or hindrance of attentional disengagement from the cued location with a central reorienting cue. The results indicated that the three factors of the three-factor model contributed to the measured IOR effect in the discrimination task. Interestingly, the IOR effect was stable when the cue and target were perfectly repeated and attention was maintained at the cued location, implying that detection cost was not a negligible factor. The current study supported the contribution of all three factors in the three-factor model to the measured IOR effect; however, we argue that the role of detection cost in the discrimination task under different paradigms should be further refined.