In this study, we investigated anticipatory motor planning and the development of cognitive representation of grasp postures in children aged 7, 8, and 9 years. Overall, 9-year-old children were more likely to plan their movements to end in comfortable postures, and have distinct representational structures of certain grasp postures, compared to the 7- and 8-year old children. Additionally, the sensitivity toward comfortable end-states (end-state comfort) was related to the mental representation of certain grasp postures. Children with grasp comfort related and functionally well-structured representations were more likely to have satisfied end-state comfort in both the simple and the advanced planning condition. In contrast, end-state comfort satisfaction for the advanced planning condition was much lower for children whose cognitive representations were not structured by grasp comfort. The results of the present study support the notion that cognitive action representation plays an important role in the planning and control of grasp postures.
Specific relations between executive functions (working memory capacity, planning and problem-solving, inhibitory control) and motor skill performance (anticipatory motor planning, manual dexterity) were examined in 5- to 6-year-old children (N = 40). Results showed that the two motor skill components were not correlated. Additionally, it was found that response planning performance was a significant predictor of anticipatory motor planning performance, whereas inhibitory control and working memory capacity measures were significant predictors of manual dexterity scores. Taken together, these results suggest that cognitive and motor skills are linked, but that manual dexterity and anticipatory motor planning involve different specialized skills. The current study provides support for specific relations between cognitive and motor performance, which has implications for early childhood cognitive-motor training and intervention programs.
BackgroundOver the last two decades, various measures of entropy have been used to examine the complexity of human postural control. In general, entropy measures provide information regarding the health, stability and adaptability of the postural system that is not captured when using more traditional analytical techniques. The purpose of this study was to examine how noise, sampling frequency and time series length influence various measures of entropy when applied to human center of pressure (CoP) data, as well as in synthetic signals with known properties. Such a comparison is necessary to interpret data between and within studies that use different entropy measures, equipment, sampling frequencies or data collection durations.Methods and FindingsThe complexity of synthetic signals with known properties and standing CoP data was calculated using Approximate Entropy (ApEn), Sample Entropy (SampEn) and Recurrence Quantification Analysis Entropy (RQAEn). All signals were examined at varying sampling frequencies and with varying amounts of added noise. Additionally, an increment time series of the original CoP data was examined to remove long-range correlations. Of the three measures examined, ApEn was the least robust to sampling frequency and noise manipulations. Additionally, increased noise led to an increase in SampEn, but a decrease in RQAEn. Thus, noise can yield inconsistent results between the various entropy measures. Finally, the differences between the entropy measures were minimized in the increment CoP data, suggesting that long-range correlations should be removed from CoP data prior to calculating entropy.ConclusionsThe various algorithms typically used to quantify the complexity (entropy) of CoP may yield very different results, particularly when sampling frequency and noise are different. The results of this study are discussed within the context of the neural noise and loss of complexity hypotheses.
Anticipatory motor planning abilities mature as children grow older, develop throughout childhood and are likely to be stable till the late sixties. In the seventh decade of life, motor planning performance dramatically declines, with anticipatory motor planning abilities falling to levels of those exhibited by children. At present, the processes enabling successful anticipatory motor planning in general, as do the cognitive processes mediating these age-related changes, remain elusive. Thus, the aim of the present study was (a) to identify cognitive and motor functions that are most affected by normal aging and (b) to elucidate key (cognitive and motor) factors that are critical for successful motor planning performance in young (n = 40, mean age = 23.1 ± 2.6 years) and older adults (n = 37, mean age = 73.5 ± 7.1 years). Results indicate that normal aging is associated with a marked decline in all aspects of cognitive and motor functioning tested. However, age-related declines were more apparent for fine motor dexterity, processing speed and cognitive flexibility. Furthermore, up to 64% of the variance in motor planning performance across age groups could be explained by the cognitive functions processing speed, response planning and cognitive flexibility. It can be postulated that anticipatory motor planning abilities are strongly influenced by cognitive control processes, which seem to be key mechanisms to compensate for age-related decline. These findings support the general therapeutic and preventive value of cognitive-motor training programs to reduce adverse effects associated with high age.
It has long been postulated that cognitive and motor functions are functionally intertwined. While the idea received convincing support from neuroimaging studies providing evidence that motor and cognitive processes draw on common neural mechanisms and resources, findings from behavioral studies are rather inconsistent. The purpose of the present study was to identify and verify key factors that act on the link between cognitive and motor functions. Specifically we investigated whether it is possible to predict motor skills from cognitive functions. While our results support the idea that motor and cognitive functions are functionally intertwined and different motor skills entail distinct cognitive functions, our data also strongly suggest that the impact of cognitive control processes on motor skill proficiency depends on performance variability, i.e. on how challenging a motor task is. Based on these findings, we presume that motor skills activate specific cognitive control processes on two levels: basic processes that are solely related to the type of the motor task, and variability-driven processes that come into play when performance variability is high. For practitioners, these findings call for specific and challenging motor training interventions to directly tap into the to-be-improved cognitive skills and to involve a maximum of cognitive processes.
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