Intact predictive motor sequence learning in autism spectrum disorder

Atypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to (a) build stable expectations of upcoming events and (b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional “surprising” trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.

Intact Predictive Motor Sequence Learning in Autism Spectrum Disorder

Background. Atypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to a) build stable expectations of upcoming events and b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning.Methods. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional “surprising” trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials.Results. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. Conclusions. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.

Endogenous Spatial Attention Modulates the Magnitude of the Colavita Visual Dominance Effect

The Colavita effect refers to the phenomenon wherein people tend to not respond to an auditory stimulus when a visual stimulus is simultaneously presented. Although previous studies have shown that endogenous modality attention influences the Colavita effect, whether the Colavita effect is influenced by endogenous spatial attention remains unknown. In the present study, we established endogenous spatial cues to investigate whether the size of the Colavita effect changes under visual or auditory cues. We measured three indexes to investigate the effect of endogenous spatial attention on the size of the Colavita effect. These three indexes were developed based on the following observations in bimodal trials: (a) The proportion of the “only vision” response was significantly higher than that of the “only audition” response; (b) the proportion of the “vision precedes audition” response was significantly higher than that of the “audition precedes vision” response; and (c) the reaction time difference of the “vision precedes audition” response was significantly higher than that of the “audition precedes vision” response. Our results showed that the Colavita effect was always influenced by endogenous spatial attention and that its size was larger at the cued location than at the uncued location; the cue modality (visual vs. auditory) had no effect on the size of the Colavita effect. Taken together, the present results shed light on how endogenous spatial attention affects the Colavita effect.

Physics and Psychology: Practical Works

The book provides a description of the interdisciplinary practical works in physics and psychology: “Observation”; “Scientific Facts”; “Time Perception”; “Reaction Time”; “Difference Thresholds”; “Scarborough’s Experiment”; “Monte Carlo Method”; “Brownian Motion”; “Speed Comparison”. It is addressed to high school and undergraduate students, as well as school and university teachers.

Individual differences in inhibitory control: A latent variable analysis

Inhibitory control represents a central component of executive functions and focuses on the ability to actively inhibit or delay a dominant response to achieve a goal. Although various tasks exist to measure inhibitory control, correlations between these tasks are rather small, partly because of the task impurity problem. To alleviate this problem, a latent variable approach has been previously applied and two closely related to each other yet separable functions have been identified: prepotent response inhibition and resistance to distractor interference. The goal of our study was a) to replicate the proposed structure of inhibitory control and b) to extend previous literature by additionally accounting for speed-accuracy trade-offs, thereby potentially increasing explained variance in the investigated latent factors. To this end, 190 participants completed six inhibitory control tasks (stroop task, antisaccade task, stop-signal task, Eriksen flanker task, shape-matching task, word-naming task). Analyses were conducted using standard scores (response times) as well as inverse efficiency scores (combining response times and error rates). In line with previous studies, we found generally low zero-order correlations between the six tasks. By applying confirmatory factor analysis using standard reaction time difference scores, we were not able to replicate a satisfactory model with good fit to the data. By using inverse efficiency scores, a single latent variable response–distractor inhibition emerged that resembled previous literature, but only four out of six tasks demonstrated significant factor loadings. Our results highlight the difficulty in finding robust inter-correlations between commonly used inhibitory control tasks, even when applying a latent variable analysis and accounting for speed-accuracy trade-offs.

The association between number magnitude and space is dependent on notation: Evidence from an adaptive perceptual orientation task

Research on adults' numerical abilities suggests that number representations are spatially oriented. This association of numbers with spatial response is referred to as the SNARC (i.e., spatial–numerical association of response codes) effect. The notation-independence hypothesis of numeric processing predicts that the SNARC effect will not vary with notation (e.g., Arabic vs. number word). To test such assumption, the current study introduced an adaptive experimental procedure based on a simple perceptual orientation task that can automatically smooth out the mean reaction time difference between Arabic digits and traditional Chinese number. We found that the SNARC effect interacted with notation, showing a SNARC effect for Arabic digits, but not for verbal number words. The results of this study challenged the commonly held view that notation does not affect numerical processes associated with spatial representations. We introduced a parallel model to explain the notation-dependent SNARC effect in the perceptual orientation judgment task.

Reaction Time Difference Electric Actuator and Pneumatic Actuator Using Simulation X program

Electric actuator and pneumatic actuator have some difference in the system, but need to find which one that have better efficiency and applicable on the designed system. Comparing two different system is not an easy task, need to find the right variable to be compared to define which one is more applicable. Reaction time is one of the variable determined by the velocity and the distance reached by the actuator to find which one is applicable. Using simulation X 3.3 to take the simulation on the pneumatics and the electronics using another parameter to find the reaction time of each system.

Developmental Differences in Sleep's Role for Implicit Off-line Learning: Comparing Children with Adults

Sleep crucially contributes to the off-line consolidation of memories. Although this view was confirmed in numerous studies in adults, it is not known whether it can be generalized to sleep during development. Here, we examined effects of sleep on implicit memory formation considered of particular relevance in children, because brain structures underlying implicit learning develop earlier in ontogeny than structures supporting explicit learning. Subjects were 7- to 11-year-old children (n = 14) and 20- to 30-year-old adults (n = 12) tested on a serial reaction time task before (learning) and after (retest) equal length retention periods of overnight sleep and daytime wakefulness. At learning, after eight training blocks, all subjects had acquired implicit knowledge of the probabilistic rules underlying the sequential stimulus materials, as indicated by a substantial difference in response time to grammatical versus nongrammatical trials in two test blocks that followed the training blocks. At learning, this response time difference was greater in children (48.49 ± 6.08 msec) than adults (28.02 ± 3.65 msec, p < .01), but did not differ between sleep and wake retention conditions in either age group. Consistent with previous studies, retesting in the adults revealed that the reaction time differences between grammatical and nongrammatical trials increased by 9.78 ± 4.82 msec after sleep, but decreased by −12.76 ± 5.49 msec after the wake retention period (p < .01). Contrary to this finding in adults, sleep in children did not lead to an increase, but to a decrease in the reaction time difference averaging −26.68 ± 12.25 msec (p < .05), whereas across the wake retention interval the reaction time difference remained nearly unchanged. The sleep-dependent deterioration in measures of implicit sequence knowledge in children was in striking contrast to the gain of such knowledge in the adults during sleep (p < .01). Our findings indicate that the functional role of sleep in implicit memory consolidation depends on age. We speculate that the overnight decrease of implicit knowledge in children reflects a preferential effect of sleep toward the enhancement of explicit aspects of task performance that interferes with implicit performance gains.