Reaching While Learning to Sit: Capturing the Kinematics of Co-Developing Skills at Home.

This study examined the co-development of infant reaching and postural control across the transition to arms-free sitting at home. We observed infants with typical likelihood (TL; n = 24) and elevated likelihood (EL; n = 20) for autism at four biweekly sessions spanning the transition to arms-free sitting (infant age = 4.5-8 months at first session). At each session, infants sat on a pressure-sensitive mat with external support or independently, wore magneto-inertial sensors on both wrists, and reached for toys presented at midline. Analyses focused on characterizing and comparing control of sitting during reaching actions and standard kinematic metrics of reaching during Supported versus Independent Sitting. Although EL infants achieved arms-free sitting later than TL peers, there were no group differences on any measures. Across sessions, infants' control of the sitting posture during concurrent reaching movements improved in both contexts, though they were less stable as they reached when sitting independently compared to when sitting with support. A similar effect was apparent in the kinematics of reaches, with overall improvement over time, but evidence of poorer control in Independent relative to Supported Sitting. Taken together, these findings underscore the mutually influential and dynamic relations between emerging skills and well-established behaviors.

MCF-SMSIS: Multi-tasking with complementary functions for stereo matching and surgical instrument segmentation.

Stereo matching and instrument segmentation of laparoscopic surgical scenarios are key tasks in robotic surgical automation. Many researchers have been studying the two tasks separately for stereo matching and instrument segmentation. However, the relationship between these two tasks is often neglected. In this paper, we propose a model framework for multi-tasking with complementary functions for stereo matching and surgical instrument segmentation (MCF-SMSIS). We aim to complement the features of instrument prediction segmentation to the parallax matching block of stereo matching. We also propose two new evaluation metrics (MINPD and MAXPD) for assessing how well the parallax range matches the migrated domain when the model used for the stereo matching task undergoes domain migration. We performed stereo matching experiments on the SCARED , SERV-CT dataset as well as instrumentation segmentation experiments on the AutoLaparo dataset. The results demonstrate the effectiveness of the proposed method. In particular, stereo matching supplemented with instrument features reduced EPE, >3px and RMSE Depth in the surgical instrument section by 9.5%, 12.7% and 6.51%, respectively. The instrumentation segmentation performance also achieves a DSC value of 0.9233. Moreover, MCF-SMSIS takes only 0.14 s to infer a set of images. The model code and model weights for each stage are available from https://github.com/wurenkai/MCF-SMSIS.

Validity of a motor-cognitive dual-task agility test in elite youth football players.

Agility, as the ability to react rapidly to unforeseen events, is an essential component of football performance. However, existing agility diagnostics often do not reflect the complex motor-cognitive interaction required on the field. Therefore, this study evaluates the criterion and ecological validity of a newly developed motor-cognitive dual-task agility approach in elite youth football players and compare it to a traditional reactive agility test. Twenty-one male youth elite football players (age:17.4 ±0 .6; BMI:23.2 ± 1.8) performed two agility tests (reactive agility, reactive agility with integrated multiple-object-tracking (Dual-Task Agility)) on the SKILLCOURT system. Performance was correlated to motor (sprint, jump), cognitive (executive functions, attention, reaction speed) and football specific tests (Loughborough soccer passing test (LSPT)) as well as indirect game metrics (coaches' rating, playing time). Reactive agility performance showed moderate correlations to attention and choice reaction times (r = 0.48-0.63), as well as to the LSPT (r = 0.51). The dual-task agility test revealed moderate relationships with attention and reaction speed (r = 0.47-0.58), executive functions (r = 0.45-0.63), as well as the game metrics (r = 0.51-0.61). Finally, the dual-task agility test significantly differentiated players based on their coaches' rating and playing time using a median split (p < 0.05; d = 0.8-1.28). Motor-cognitive agility performance in elite youth football players seems to be primarily determined by cognitive functions. The integration of multiple object tracking into reactive agility testing seems to be an ecologically valid approach for performance diagnostics in youth football.

Reduced trunk movement control during motor dual-tasking in older adults.

Older adults have a decreased trunk movement control which is linked to their higher fall risk. While motor/cognitive dual-tasking deteriorates balance and walking in older adults, there is limited understanding on how trunk kinematics and kinetics are affected by dual-tasking in scenarios where falls can occur. Therefore, the purpose of the study was to determine the impacts of a challenging motor dual-task, specifically obstacle avoidance during walking, on trunk and lower-body kinematics and kinetics of older adults compared to young adults. The study captured three-dimensional kinematic and kinetic data from 12 young adults and 10 older adults as they walked on a treadmill and stepped over an obstacle with both legs. The study analyzed trunk, hip, knee, and ankle angles and torques. Trunk torque was further broken down to trunk muscle torque, gravitational torque, and inertia torque. A linear mixed effects model was used to investigate the difference in each variable between the two groups. Older adults exhibited significantly increased trunk flexion angle and trunk extension muscle torque compared to young adults, with the trunk being the only segment/joint showing differences in both kinematics and kinetics. Trunk torque breakdown analysis revealed that larger trunk flexion led to a larger gravitational torque, which contributed to an increased compensatory trunk muscle torque. Moreover, older adults' less controlled trunk flexion during weight shifting from trail leg to the lead leg, necessitated a compensatory trunk deceleration during trail leg obstacle avoidance which was achieved by generating additional increase in trunk muscle torque. The study demonstrated that motor dual-tasking has the most negative effects on trunk control in older adults compared to young adults. This exposes older adults to a higher fall risk. Therefore, future work should focus on supporting trunk control during daily multi-tasking conditions where falls can occur.

A Comparison of Two Multi-Tasking Approaches to Cognitive Training in Cardiac Surgery Patients.

BACKGROUND: The multi-tasking approach may be promising for cognitive rehabilitation in cardiac surgery patients due to a significant effect on attentional and executive functions. This study aimed to compare the neuropsychological changes in patients who have undergone two variants of multi-tasking training and a control group in the early postoperative period of coronary artery bypass grafting (CABG). METHODS: One hundred and ten CABG patients were divided into three groups: cognitive training (CT) I (a postural balance task with mental arithmetic, verbal fluency, and divergent tasks) (n = 30), CT II (a simple visual-motor reaction with mental arithmetic, verbal fluency, and divergent tasks) (n = 40), and control (n = 40). RESULTS: Two or more cognitive indicators improved in 93.3% of CT I patients, in 72.5% of CT II patients, and in 62.5% of control patients; CT I patients differed from CT II and control (p = 0.04 and p = 0.008, respectively). The improving short-term memory and attention was found more frequently in the CT I group as compared to control (56.7% vs. 15%; p = 0.0005). The cognitive improvement of all domains (psychomotor and executive functions, attention, and short-term memory) was also revealed in CT I patients more frequently than CT II (46.7% vs. 20%; p = 0.02) and control (46.7% vs. 5%; p = 0.0005). CONCLUSIONS: The CT I multi-tasking training was more effective at improving the cognitive performance in cardiac surgery patients as compared to CT II training and standard post-surgery management. The findings of this study will be helpful for future studies involving multi-tasking training.

G4-QuadScreen: A Computational Tool for Identifying Multi-Target-Directed Anticancer Leads against G-Quadruplex DNA.

The study presents 'G4-QuadScreen', a user-friendly computational tool for identifying MTDLs against G4s. Also, it offers a few hit MTDLs based on in silico and in vitro approaches. Multi-tasking QSAR models were developed using linear discriminant analysis and random forest machine learning techniques for predicting the responses of interest (G4 interaction, G4 stabilization, G4 selectivity, and cytotoxicity) considering the variations in the experimental conditions (e.g., G4 sequences, endpoints, cell lines, buffers, and assays). A virtual screening with G4-QuadScreen and molecular docking using YASARA (AutoDock-Vina) was performed. G4 activities were confirmed via FRET melting, FID, and cell viability assays. Validation metrics demonstrated the high discriminatory power and robustness of the models (the accuracy of all models is ~>90% for the training sets and ~>80% for the external sets). The experimental evaluations showed that ten screened MTDLs have the capacity to selectively stabilize multiple G4s. Three screened MTDLs induced a strong inhibitory effect on various human cancer cell lines. This pioneering computational study serves a tool to accelerate the search for new leads against G4s, reducing false positive outcomes in the early stages of drug discovery. The G4-QuadScreen tool is accessible on the ChemoPredictionSuite website.

Cognitive-motor dual-task interference in Alzheimer's disease, Parkinson's disease, and prodromal neurodegeneration: A scoping review.

BACKGROUND: Cognitive-motor interference (CMI) is a common deficit in Alzheimer's (AD) disease and Parkinson's disease (PD) and may have utility in identification of prodromal neurodegeneration. There is lack of consensus regarding measurement of CMI resulting from dual task paradigms. RESEARCH QUESTION: How are individuals with AD, PD, and prodromal neurodegeneration impacted by CMI as measured by dual-task (DT) performance? METHODS: A systematic literature search was performed in six datasets using the PRISMA guidelines. Studies were included if they had samples of participants with AD, PD, or prodromal neurodegeneration and reported at least one measure of cognitive-motor DT performance. RESULTS: 4741 articles were screened and 95 included as part of this scoping review. Articles were divided into three non-mutually exclusive groups based on diagnoses, with 26 articles in AD, 56 articles in PD, and 29 articles in prodromal neurodegeneration, and results presented accordingly. SIGNIFICANCE: Individuals with AD and PD are both impacted by CMI, though the impact is likely different for each disease. We found a robust body of evidence regarding the utility of measures of DT performance in the detection of subtle deficits in prodromal AD and some signals of utility in prodromal PD. There are several key methodological challenges related to DT paradigms for the measurement of CMI in neurodegeneration. Overall, DT paradigms show good potential as a clinical method to probe specific brain regions, networks, and function; however, task selection and effect measurement should be carefully considered.

A multi-objective multi-tasking evolutionary algorithm based inverse mapping and adaptive transformation strategy: IM-MFEA.

Multi-tasking optimization algorithm attracts much attention because the knowledge transfer between tasks enables the algorithm to process multiple related tasks simultaneously. However, negative knowledge transfer occasionally occurs, which may weaken the performance of the algorithm. To reduce the impact of negative knowledge transfer, a multi-objective multi-tasking optimization algorithm (IM-MFEA) based on inverse model mapping and an objective transformation strategy is proposed. First, correlation analysis is applied in an inverse mapping strategy to improve the accuracy of the inverse mapping model. Then, following the pattern of using the source domain solutions to assist the optimization of the target domain, the adaptive transformation strategy is used to improve the quality of the source domain solution in the objective space. These transformed solutions are reconstructed through the inverse mapping strategy. Finally, these reconstructed source domain solutions are mated with the target domain solutions to generate competitive offspring individuals for the target domain. To verify the effectiveness of the IM-MFEA, comprehensive experiments were conducted on nine multi-objective multi-factorial optimization (MFO) benchmark problems. Empirical results demonstrate that IM-MFEA is superior to other algorithms in 90% of test instances by inverted generational distance (IGD) and hypervolume (HV) value indicators.

Evaluating the dual-task decrement within a simulated environment: Word recall and visual search.

Simulated environments have become better able to replicate the real world and can be used for a variety of purposes, such as testing new technology without any of the costs or risks associated with working in the real world. Because of this, it is now possible to gain a better understanding of cognitive demands when working in operational environments, where individuals are often required to multitask. Multitasking often results in performance decrements, where adding more tasks can cause a decrease in performance in each of the individual tasks. However, little research investigated multitasking performance in simulated environments. In the current study we examined how multitasking affects performance in simulated environments. Forty-eight participants performed a dual visual search and word memory task where participants were navigated through a simulated environment while being presented with words. Performance was then compared to single-task performance (visual search and word memory alone). Results showed that participants experienced significant dual-task interference when comparing the dual-tasks to the single-tasks and subjective measures confirmed these findings. These results could provide useful insight for the design of technology in operational environments, but also serve as an evaluation of MRT in simulated environments.

POI recommendation with queuing time and user interest awareness.

Point-of-interest (POI) recommendation is a challenging problem due to different contextual information and a wide variety of human mobility patterns. Prior studies focus on recommendation that considers user travel spatiotemporal and sequential patterns behaviours. These studies do not pay attention to user personal interests, which is a significant factor for POI recommendation. Besides user interests, queuing time also plays a significant role in affecting user mobility behaviour, e.g., having to queue a long time to enter a POI might reduce visitor's enjoyment. Recently, attention-based recurrent neural networks-based approaches show promising performance in the next POI recommendation task. However, they are limited to single head attention, which can have difficulty in finding the appropriate user mobility behaviours considering complex relationships among POI spatial distances, POI check-in time, user interests and POI queuing times. In this research work, we are the first to consider queuing time and user interest awareness factors for next POI recommendation. We demonstrate how it is non-trivial to recommend a next POI and simultaneously predict its queuing time. To solve this problem, we propose a multi-task, multi-head attention transformer model called TLR-M_UI. The model recommends the next POIs to the target users and predicts queuing time to access the POIs simultaneously by considering user mobility behaviours. The proposed model utilises POIs description-based user personal interest that can also solve the new categorical POI cold start problem. Extensive experiments on six real-world datasets show that the proposed models outperform the state-of-the-art baseline approaches in terms of precision, recall, and F1-score evaluation metrics. The model also predicts and minimizes the queuing time. For the reproducibility of the proposed model, we have publicly shared our implementation code at GitHub (https://github.com/sajalhalder/TLR-M_UI).

Conflict monitoring or multi-tasking? Tracking within-task performance in single-item and multi-item Stroop tasks.

Cognitive control is applied in situations that require overriding a habitual and automatic response. The conflict monitoring hypothesis and the Expected Value of Control (EVC) theory as its extension posit a control system responsible for detecting conflicting occasions and adapting to them dynamically within a task. Here we evaluate this prediction in two versions of one of the most popular tasks in cognitive control, namely the Stroop task. We hypothesized that nearby-items interference combines with task interference in the multi-item version effectively turning it into a multi-task that may challenge cognitive control. Adopting an alternative methodology tracking within-task performance, we compared the classical multi-item version of the Stroop task and its single-item counterpart in adults and children. The results revealed a within-task performance decline only in the multi-item version of the task, in both incongruent and neutral conditions, modulated by the presumed maturity of the control system. These findings suggest capacity constraints in control implementation and allocation under conditions requiring parallel execution of multiple cognitive tasks. Task complexity and demands seem to modulate effects on performance. We discuss implications for cognitive control as well as substantial concerns regarding the calculation and use of indices of interference based on the commonly used multi-item version of the Stroop task.

Understanding sexual activity while driving as a form of distracted driving.

Sexual activity while driving has been reported in emerging research. Sexual activity while driving is a form of distracted driving because it includes an individual (the driver) who deviates resources from the primary task (driving) towards a secondary task (sexual activity). However, most of our current knowledge about the range of sexual activities while driving is based on self-reported data or media reports. Thus, an in-depth understanding of sexual activities while driving and their interactions with non-sexual driving behaviours and vehicle control is missing. Additionally, there is limited information on the context of where sexual activities while driving occurs and the influence of factors such as the environment, the vehicle, interactions with other road users, and other in-vehicle distractions. To cover this gap, a content analysis of sexually explicit media (SEM) was conducted on a sample of 270 videos depicting real driving. We conducted descriptive analyses and used decision tree analysis to explore the association between sexual activities while driving and their interactions with non-sexual driving behaviours and vehicle control. The videos portrayed a naturalistic driving situation of a driver of a moving vehicle engaging in sexual activity. The results show that when engaging in sexual activity, drivers do not present safe vehicle control. Sexual activity imposes additional cognitive, physical, and visual demands on the driver, thereby decreasing safety. Similar to other distractions, drivers engaging in sexual activity while driving appear to mitigate risks. Concerning the potential for legal sanctions, it appears that drivers may attempt to conceal sexual activity by reducing their visible nudity and minimising interactions with other road users. Finally, mobile phones and cameras appear to interact with sexual activities while driving, by imposing potential restrictions on the range of sexual activities. Implications for policymakers and practitioners are discussed.

Effect of variable priority training on police officer driving performance and workload.

Motor vehicle crashes are a leading cause of police injuries and deaths in line of duty. These crashes have been mainly attributed to the use of in-vehicle technologies while driving. Police officers receive extensive training on driving skills; however, limited training is provided on the use of in-vehicle technologies. Variable priority training (VPT) is a computer-based training that has shown promising results in improving multi-tasking performance. Eighteen police officers participated in a driving simulation study to assess the effect of VPT on officers' performance and workload. Findings suggested that although VPT was effective in improving officers' performance in dual and multi-task simulations across the training sessions, this effect was not generally transferred to driving. However, the VPT might be effective for training of high-demand situations involving pursuit driving and multiple secondary tasks. The findings can be beneficial for police agencies to improve training protocols. Practitioner summary: A driving simulation study was conducted to assess the effect of a computer-based training approach on police officers' driving performance and cognitive workload. The findings suggested that the proposed training approach might be effective for training of high-demand situations involving pursuit driving and multi-tasking.

A Simulated Scenario to Improve Resident Efficiency in an Emergency Department.

Introduction Multitasking is a core competency in emergency medicine. Simulation has been shown to be an effective method of education, which allows learners to prepare for real-world challenges in a controlled environment. Methods In this study, trainees were given a scenario that simulated the experience of managing two patient encounters within a time metric while addressing interruptions that take place in a typical ED. Residents were evaluated using an internally developed scoresheet, which assessed task-switching abilities, documentation skills, and adherence to door to disposition time metric. Residents were asked to evaluate their experience with a survey. Results All the participants reported that they would translate some of the skills learned to their daily clinical practice. Five out of six residents reported improvements in their skills as a result of the task-switching training. The following three common themes were pervasive in the debrief discussion: (1) the residents felt the added pressure of the door-to-disposition metric, (2) the objectives of the simulation did not fit within their pre-constructed concept of a successful simulation equating to establishing the correct diagnosis, and (3) the interruptions were very realistic. Discussion Emergency physicians are interrupted approximately every 9-14 minutes, and this number increases with the number of patients being managed simultaneously. By developing a safe, simulated training environment, we sought to transfer key strategies for improving focus and learning to prioritize while also helping them to identify how certain pressures and interruptions affected their stress levels and concentration.

Rural healthcare providers coping with clinical care delivery challenges: lessons from three health centres in Ghana.

BACKGROUND: Rural settings in low- and middle-income countries are bedeviled with poverty and high disease burden, and lack adequate resources to deliver quality healthcare to the population. Drug shortage and inadequate number and skill-mix of healthcare providers is very common in rural health facilities. Hence, rural healthcare providers have no choice but to be innovative and introduce some strategies to cope with health delivery challenges at the health centre levels. This study explored how and why rural healthcare providers cope with clinical care delivery challenges at the health centre levels in Ghana. METHODS: This study was a multiple case studies involving three districts: Bongo, Kintampo North, and Juaboso districts. In each case study district, a cross-sectional design was used to explore the research question. Purposive sampling technique was used to select study sites and the study participants. The authors conducted 11 interviews, 9 focus group discussions (involving 61 participants), and 9-week participant observation (in 3 health centres). Transcription of the voice-recordings was done verbatim, cleaned and imported into the Nvivo version 11 platform for analysis. Data was analysed using the inductive content analysis approach. Ethical clearance was granted by the Ethics Review Committee of the Ghana Health Service. RESULTS: The study found three main coping strategies (borrowing, knowledge sharing and multi-tasking). First, borrowing arrangements among primary health care institutions help to address the periodic shortage of medical supplies at the health centres. Secondly, knowledge sharing among healthcare providers mitigates skills gap during service delivery; and finally, rural healthcare providers use multi-tasking to avert staff inadequacy challenges during service delivery at the health centre levels. CONCLUSION: Borrowing, knowledge sharing, and multi-tasking are coping strategies that are sustaining and potentially improving health outcomes at the district levels in Ghana. We recommend that health facilities across all levels of care in Ghana and other settings with similar challenges could adopt and modify these strategies in order to ensure quality healthcare delivery amidst delivery challenges.

Branching Condition of the Color-Word Interference Test Enhances Prediction of Meta-Tasking in Community-Dwelling Older Adults.

OBJECTIVES: Meta-tasking (MT) is an aspect of executive functioning (EF) that involves the ability to branch (i.e., to apply "if-then" rules) and to effectively interleave sub-goals of one task with sub-goals of another task. As such, MT is crucial for successful planning, coordination, and execution of multiple complex tasks in daily life. Traditional tests of EF fail to adequately measure MT. This study examined whether Condition 4 of the Color-Word Interference Test (CWIT-4; the inhibition/switching condition that requires branching) predicted MT beyond Condition 3 (CWIT-3; inhibition-only condition) and beyond other subtests from the Delis-Kaplan Executive Function System (D-KEFS) that have a switching condition. METHOD: Ninety-eight non-Hispanic white community-dwelling older adults completed the first four subtests of the D-KEFS and an ecologically valid measure of MT. RESULTS: Time to completion and total errors on CWIT-4 accounted for variance in MT above and beyond CWIT-3 and beyond the switching conditions of other D-KEFS subtests. Results remained virtually unchanged when controlling for demographics and general cognitive status. CONCLUSIONS: Among older adults, CWIT-4 is more strongly associated with MT than other D-KFES tasks. Future research should examine whether CWIT-4 relates to lapses in instrumental activities of daily living among older adults above and beyond other EF tests.

Do All Switches Cost the Same? Reliability of Language Switching and Mixing Costs.

The current study examined the reliability and consistency of switching and mixing costs in the language and the color-shape tasks in three pre-existing data sets, to assess whether they are equally well suited for the study of individual differences. Specifically, we considered if the language task is as reliable as the color-shape task - an important question given the wide use of language switching tasks but little information available to address this question. Switching costs had low to moderate reliability and internal consistency, and these were similar for the language and the color-shape tasks. Mixing costs were more reliable in the language task than in the color-shape task when tested twice on the same day and trended in the same direction when tested a week apart. In addition, mixing costs were larger and more consistent than switching costs in all data sets and they were also were more reliable than switching costs in the language task when tested on the same day. These results reveal the language task to be as good as the color-shape task for measuring switching and mixing ability. Low variability of switching costs may decrease their reliability and consistency, in turn interfering with the chance of detecting cross task correlations. We advocate for exploring procedures to increase the variability of switching costs, which might increase reliability and consistency of these measures, and improve the ability to determine if bilingual language use relies on cognitive mechanisms that overlap with those underlying nonlinguistic multi-tasking.

Joint Fiber Nonlinear Noise Estimation, OSNR Estimation and Modulation Format Identification Based on Asynchronous Complex Histograms and Deep Learning for Digital Coherent Receivers.

In this paper, asynchronous complex histogram (ACH)-based multi-task artificial neural networks (MT-ANNs), are proposed to realize modulation format identification (MFI), optical signal-to-noise ratio (OSNR) estimation and fiber nonlinear (NL) noise power estimation simultaneously for coherent optical communication. Optical performance monitoring (OPM) is demonstrated with polarization mode multiplexing (PDM), 16 quadrature amplitude modulation (QAM), PDM-32QAM, as well as PDM-star 16QAM (S-16QAM) for the first time. The range of launched power is -3 to -2 dBm with a fiber link of 160-1600 km. Then, the accuracy of MFI reaches 100%. The average root mean square error (RMSE) of OSNR estimation can reach 0.37 dB. The average RMSE of NL noise power estimation can reach 0.25 dB. The results show that the monitoring scheme is robust to the increase of fiber length, and the solution can monitor more optical network parameters with better performance and fewer training data, simultaneously. The proposed ACH MT-ANN has certain reference significance for the future long-haul coherent OPM system.

Effects of dichotic listening on gait domains of healthy older adults during dual-tasking: An exploratory observational study.

BACKGROUND: Identification of the cognitive mechanisms behind gait changes in aging is a prime endeavor in gerontology and geriatrics. For this reason, we have implemented a new dual-task paradigm where an auditory attentional task is performed during over-ground walking. Dichotic listening assesses spontaneous attention and voluntary attention directed to right and left-ear. The uniqueness of dichotic listening relies on its requirements that vary in difficulty and recruitment of resources from whole brain to one brain hemisphere. When used in dual-tasking, asymmetric effects on certain gait parameters have been reported. OBJECTIVES: The present study aims to acquire a more global understanding on how dichotic listening affects gait domains. Specifically, we aimed to understand how spontaneous vs lateralized auditory attention altered the Principal Component Analysis (PCA) structure of gait in healthy older adults. METHODS: Seventy-eight healthy older adults (mean age: 71.1 years; 44 women and 34 men) underwent the Bergen dichotic listening test while walking. As this study only focuses on the effects of the cognitive task on gait, only dual-task costs for gait were calculated and entered into the PCA analyses. We explored the PCA structure for the effects on bilateral gait parameters (i.e., both limbs together) as well as on lateralized gait parameters (i.e, separate parameters by limb). We first established gait domains during single-task walking. Then, dual-task cost scores for gait were entered in a series of PCAs. RESULTS: Results from the PCAs for bilateral gait parameters showed limited alterations on gait structure. In contrast, PCAs for lateralized data demonstrated modifications of the gait structure during dichotic listening. The PCAs corresponding for all dichotic listening conditions showed different factor solutions ranging between 4 and 6 factors that explained between 73.8% to 80% of the total variance. As a whole, all conditions had an impact on "pace", "pace variability" and "base of support variability" domains. In the spontaneous attention condition, a six-factor solution explaining 78.3% of the variance showed asymmetrical disruptions on the PCA structure. When attention was focused to right-ear, a five-factor solution explaining 89% of the variance and similar to baseline was found. When attention was directed to left-ear, a four-factor solution explaining 73.8% of the variance was found with symmetrical impact on all factors. CONCLUSIONS: These findings demonstrate for the first time that specific facets of attentional control affects gait domains both symmetrically and asymmetrically in healthy older adults.

Effects of automation reliability on error detection and attention to auditory stimuli in a multi-tasking environment.

Automated aids are engineered to support operators' decision-making in complex and task-saturated environments, alerting them of system status and critical incidents. However, even the most advanced technologies are susceptible to failure. Monitoring imperfect automated systems poses unique challenges related to operator attention and workload. This study empirically examined the effect of unreliable automation on monitoring performance and responses to auditory stimuli in a multi-tasking environment. Participants completed an experimental trial consisting of four flight-related tasks while monitoring for automation failures at one of three levels of automation reliability. Participants in a high reliability condition responded more quickly and frequently to auditory messages. No performance differences were found in system monitoring performance between reliability conditions. These results are relevant to the design of automated system and delivery of automated alerts, and they have implications for operator attention allocation strategies in multi-tasking environments.