Personalizing driver safety interfaces via driver cognitive factors inference.

Recent advances in AI and intelligent vehicle technology hold the promise of revolutionizing mobility and transportation through advanced driver assistance systems (ADAS). Certain cognitive factors, such as impulsivity and inhibitory control have been shown to relate to risky driving behavior and on-road risk-taking. However, existing systems fail to leverage such factors in assistive driving technologies adequately. Varying the levels of these cognitive factors could influence the effectiveness and acceptance of ADAS interfaces. We demonstrate an approach for personalizing driver interaction via driver safety interfaces that are are triggered based on the inference of the driver's latent cognitive states from their driving behavior. To accomplish this, we adopt a data-driven approach and train a recurrent neural network to infer impulsivity and inhibitory control from recent driving behavior. The network is trained on a population of human drivers to infer impulsivity and inhibitory control from recent driving behavior. Using data collected from a high-fidelity vehicle motion simulator experiment, we demonstrate the ability to deduce these factors from driver behavior. We then use these inferred factors to determine instantly whether or not to engage a driver safety interface. This approach was evaluated using leave-one-out cross validation using actual human data. Our evaluations reveal that our personalized driver safety interface that captures the cognitive profile of the driver is more effective in influencing driver behavior in yellow light zones by reducing their inclination to run through them.

Intuitive Sociology: Children Recognize Decision-Making Structures and Prefer Groups With Less-Concentrated Power.

From an early age, children recognize that people belong to social groups. However, not all groups are structured in the same way. The current study asked whether children recognize and distinguish among different decision-making structures. If so, do they prefer some decision-making structures over others? In these studies, children were told stories about two groups that went camping. In the hierarchical group, one character made all the decisions; in the egalitarian group, each group member made one decision. Without being given explicit information about the group's structures, 6- to 8-year-old children, but not 4- and 5-year-old children, recognized that the two groups had different decision-making structures and preferred to interact with the group where decision-making was shared. Children also inferred that a new member of the egalitarian group would be more generous than a new member of the hierarchical group. Thus, from an early age, children's social reasoning includes the ability to compare social structures, which may be foundational for later complex political and moral reasoning.

The efficacy of a task model approach to ADL rehabilitation in stroke apraxia and action disorganisation syndrome: A randomised controlled trial.

BACKGROUND: Apraxia and action disorganization syndrome (AADS) after stroke can disrupt activities of daily living (ADL). Occupational therapy has been effective in improving ADL performance, however, inclusion of multiple tasks means it is unclear which therapy elements contribute to improvement. We evaluated the efficacy of a task model approach to ADL rehabilitation, comparing training in making a cup of tea with a stepping training control condition. METHODS: Of the 29 stroke survivors with AADS who participated in this cross-over randomized controlled feasibility trial, 25 were included in analysis [44% females; mean(SD) age = 71.1(7.8) years; years post-stroke = 4.6(3.3)]. Participants attended five 1-hour weekly tea making training sessions in which progress was monitored and feedback given using a computer-based system which implemented a Markov Decision Process (MDP) task model. In a control condition, participants received five 1-hour weekly stepping sessions. RESULTS: Compared to stepping training, tea making training reduced errors across 4 different tea types. The time taken to make a cup of tea was reduced so the improvement in accuracy was not due to a speed-accuracy trade-off. No improvement linked to tea making training was evident in a complex tea preparation task (making two different cups of tea simultaneously), indicating a lack of generalisation in the training. CONCLUSIONS: The clearly specified but flexible training protocol, together with information on the distribution of errors, provide pointers for further refinement of task model approaches to ADL rehabilitation. It is recommended that the approach be tested under errorless learning conditions with more impaired patients in future research. TRIAL REGISTRATION: Retrospectively registered at ClinicalTrials.gov on 5th August 2019 [NCT04044911] https://clinicaltrials.gov/ct2/show/NCT04044911?term=Cogwatch&rank=1.

Cake or broccoli? Recency biases children's verbal responses.

One of the greatest challenges of developmental psychology is figuring out what children are thinking. This is particularly difficult in early childhood, for children who are prelinguistic or are just beginning to speak their first words. In this stage, children's responses are commonly measured by presenting young children with a limited choice between one of a small number of options (e.g., "Do you want X or Y?"). A tendency to choose one response in these tasks may be taken as an indication of a child's preference or understanding. Adults' responses are known to exhibit order biases when they are asked questions. The current set of experiments looks into the following question: do children demonstrate response biases? Together, we show that 1) toddlers demonstrate a robust verbal recency bias when asked "or" questions in a lab-based task and a naturalistic corpus of caretaker-child speech interactions, 2) the recency bias weakens with age, and 3) the recency bias strengthens as the syllable-length of the choices gets longer. Taken together, these results indicate that children show a different type of response bias than adults, recency instead of primacy. Further, the results may suggest that this bias stems from increased constraints on children's working memory.

Adverse vascular risk is related to cognitive decline in older adults.

BACKGROUND: Cardiovascular disease (CVD) and related risk factors are associated with Alzheimer's disease (AD). This association is less well-defined in normal cognition (NC) or prodromal AD (mild cognitive impairment, MCI). OBJECTIVE: Cross-sectionally and longitudinally relate a vascular risk index to cognitive outcomes among elders free of clinical dementia. METHODS: 3,117 MCI (74 ± 8 years, 56% female) and 6,603 NC participants (72 ± 8 years, 68% female) were drawn from the National Alzheimer's Coordinating Center. A composite measure of vascular risk was defined using the Framingham Stroke Risk Profile (FSRP) score (i.e., age, systolic blood pressure, anti-hypertensive medication, diabetes, cigarette smoking, CVD history, atrial fibrillation). Ordinary linear regressions and generalized linear mixed models related baseline FSRP to cross-sectional and longitudinal cognitive outcomes, separately for NC and MCI, adjusting for age, gender, race, education, and follow-up time (in longitudinal models). RESULTS: In NC participants, increasing FSRP was related to worse baseline global cognition, information processing speed, and sequencing abilities (p-values <0.0001) and a worse longitudinal trajectory on all cognitive measures (p-values <0.0001). In MCI, increasing FSRP correlated with worse longitudinal delayed memory (p = 0.004). In secondary models using an age-excluded FSRP score, associations persisted in NC participants for global cognition, naming, information processing speed, and sequencing abilities. CONCLUSIONS: An adverse vascular risk profile is associated with worse cognitive trajectory, especially global cognition, naming, and information processing speed, among NC elders. Future studies are needed to understand how effective management of CVD and related risk factors can modify cognitive decline to identify the ideal timeframe for primary prevention implementation.