Age differences in the use of implicit visual cues in a response time task

Background: Many activities require a complex interrelationship between a performer and stimuli available in the environment without explicit perception, but many aspects regarding developmental changes in the use of implicit cues remain unknown. Aim: To investigate the use of implicit visual precueing presented at different time intervals in children, adolescents, and adults. Method: Seventy-two people, male and female, constituted four age groups: 8-, 10- and 12-year-olds and adults. Participants performed 32 trials, four-choice-time task across four conditions: no precue and a 43 ms centralized dot appearing in the stimulus circle at 43, 86 or 129 ms prior the stimulus. Response times were obtained for each trial and pooled into each condition. Results: Response times for 8-year-olds were longer than for 12-year-olds and adults and for 10-year-olds were longer than for adults. Response times were longer in the no precue condition compared to when precues were presented at 86 and 129 ms before the stimulus. Response times were longer when precue was presented at 43 ms compared presented at 129 ms before the stimulus. Interpretation: Implicit precues reduce response time in children, adolescents and adults, but young children benefit less from implicit precues than adolescents and adults.</jats:p

Postural control is not systematically related to reading skills:implications for the assessment of balance as a risk factor for developmental dyslexia

Impaired postural control has been associated with poor reading skills, as well as with lower performance on measures of attention and motor control variables that frequently co-occur with reading difficulties. Measures of balance and motor control have been incorporated into several screening batteries for developmental dyslexia, but it is unclear whether the relationship between such skills and reading manifests as a behavioural continuum across the range of abilities or is restricted to groups of individuals with specific disorder phenotypes. Here were obtained measures of postural control alongside measures of reading, attention and general cognitive skills in a large sample of young adults (n = 100). Postural control was assessed using centre of pressure (CoP) measurements, obtained over 5 different task conditions. Our results indicate an absence of strong statistical relationships between balance measures with either reading, cognitive or attention measures across the sample as a whole. © 2014 Loras et al

Effect of a Dual Task on Postural Control in Dyslexic Children

Several studies have examined postural control in dyslexic children; however, their results were inconclusive. This study investigated the effect of a dual task on postural stability in dyslexic children. Eighteen dyslexic children (mean age 10.3±1.2 years) were compared with eighteen non-dyslexic children of similar age. Postural stability was recorded with a platform (TechnoConcept®) while the child, in separate sessions, made reflex horizontal and vertical saccades of 10° of amplitude, and read a text silently. We measured the surface and the mean speed of the center of pressure (CoP). Reading performance was assessed by counting the number of words read during postural measures. Both groups of children were more stable while performing saccades than while reading a text. Furthermore, dyslexic children were significantly more unstable than non-dyslexic children, especially during the reading task. Finally, the number of words read by dyslexic children was significantly lower than that of non-dyslexic children and, in contrast to the non-dyslexic children. In line with the U-shaped non-linear interaction model, we suggest that the attention consumed by the reading task could be responsible for the loss of postural control in both groups of children. The postural instability observed in dyslexic children supports the hypothesis that such children have a lack of integration of multiple sensorimotor inputs

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems

Modelling implicit pre-cues and collision avoidance in a driving simulator

It is well-established that pre-cues, including those observed in an implicit manner, can affect motor skills and reaction times. However, little research currently exists on how pre-cues influence complex motor skills such as driving a car at high speed. This pilot study investigates the effect of implicit pre-cues on collision avoidance under a repeat trial experiment design using a car driving simulator. Seventeen par- ticipants (aged 23.8 ± 4.2 years) were included in this investigation, which consisted of four different one-kilometre driving scenarios. This investigation considers two of the four scenarios. Two scenarios had the stimulus of a child crossing the road, however only one of these scenarios had an implicit pre-cue appear before the stimulus. The remaining two scenarios had no stimulus or pre-cue and were included to reduce any learning effect by participants. The proportion of participants who had a collision differed significantly between scenarios with and without a pre-cue. The primary effect size of the pre-cue is modelled using a logis- tic regression and distributions for point estimators are obtained from bootstrapping results. A power analysis exploring different primary effect sizes is performed to inform sample size considerations for repeat studies. Implications for motor control, such as experiment design and statistical modelling methods, are discussed to inform future large scale trials. References J. A. Barela, A. A. Rocha, A. R. Novak, J. Fransen, and G. A. Figueiredo. Age differences in the use of implicit visual cues in a response time task. Braz. J. Motor Behav. 13.2 (2019), pp. 86–93. doi: 10.20338/bjmb.v13i2.139 J. Cohen. Statistical power analysis for the behavioral sciences. Routledge, 1988. doi: 10.4324/9780203771587 U. Eversheim and O. Bock. The role of precues in the preparation of motor responses in humans. J. Mot. Behav. 34.3 (2002), pp. 271–276. doi: 10.1080/00222890209601945 D. G. Jenkins and P. F. Quintana-Ascencio. A solution to minimum sample size for regressions. PLOS One 15.2 (2020), e0229345. doi: 10.1371/journal.pone.0229345 J. Jiang. Linear and generalized linear mixed models and their applications. Springer Series in Statistics. Springer, 2007. doi: 10.1007/978-0-387-47946-0 C. Kistin and M. Silverstein. Pilot studies: A critical but potentially misused component of interventional research. JAMA 314.15 (2015), pp. 1561–1562. doi: 10.1001/jama.2015.10962 H. C. Kraemer, J. Mintz, A. Noda, J. Tinklenberg, and J. A. Yesavage. Caution regarding the use of pilot studies to guide power calculations for study proposals. Arch. Gen. Psych. 63.5 (2006), pp. 484–489. doi: 10.1001/archpsyc.63.5.484 J. A. Nelder and R. W. M. Wedderburn. Generalized linear models. J. Roy. Stat. Soc. 135.3 (1972), pp. 370–384. doi: 10.2307/2344614 R. Stine. An introduction to bootstrap methods: Examples and ideas. Soc. Meth. Res. 18.2–3 (1989), pp. 243–291. doi: 10.1177/0049124189018002003 </jats:p