975 resultados para motor timing variability


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OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

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This investigation aimed to pinpoint the elements of motor timing control that are responsible for the increased variability commonly found in children with developmental dyslexia on paced or unpaced motor timing tasks (Chapter 3). Such temporal processing abilities are thought to be important for developing the appropriate phonological representations required for the development of literacy skills. Similar temporal processing difficulties arise in other developmental disorders such as Attention Deficit Hyperactivity Disorder (ADHD). Motor timing behaviour in developmental populations was examined in the context of models of typical human timing behaviour, in particular the Wing-Kristofferson model, allowing estimation of the contribution of different timing control systems, namely timekeeper and implementation systems (Chapter 2 and Methods Chapters 4 and 5). Research examining timing in populations with dyslexia and ADHD has been inconsistent in the application of stimulus parameters and so the first investigation compared motor timing behaviour across different stimulus conditions (Chapter 6). The results question the suitability of visual timing tasks which produced greater performance variability than auditory or bimodal tasks. Following an examination of the validity of the Wing-Kristofferson model (Chapter 7) the model was applied to time series data from an auditory timing task completed by children with reading difficulties and matched control groups (Chapter 8). Expected group differences in timing performance were not found, however, associations between performance and measures of literacy and attention were present. Results also indicated that measures of attention and literacy dissociated in their relationships with components of timing, with literacy ability being correlated with timekeeper variance and attentional control with implementation variance. It is proposed that these timing deficits associated with reading difficulties are attributable to central timekeeping processes and so the contribution of error correction to timing performance was also investigated (Chapter 9). Children with lower scores on measures of literacy and attention were found to have a slower or failed correction response to phase errors in timing behaviour. Results from the series of studies suggest that the motor timing difficulty in poor reading children may stem from failures in the judgement of synchrony due to greater tolerance of uncertainty in the temporal processing system.

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The impacts of psychoactive drugs on timing have usefully informed theories of timing and its substrates.

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 Objective: This study investigated the relationship between motor performance and social-communicative impairment in children with ADHD-combined type (ADHD-CT). Method: An upper limb Fitts’ aiming task was used as a measure of motor performance and the Social Responsiveness Scale as a measure of social-communicative/autistic impairment in the following groups: ADHD-CT (n = 11) and typically developing (TD) controls (n = 10). Results: Children with ADHD-CT displayed greater variability in their movements, reflected in increased error variance over repeated aiming trials compared with TD controls. Motor performance variability was associated with social-communicative deficits in the ADHD-CT but not in the TD group. Conclusion: Social-communicative impairments further complicate the clinical picture of ADHD-CT; therefore, further research in this area is warranted to ascertain whether a particular pattern of motor disturbance in children with ADHD-CT may be clinically useful in identifying and assessing children with a more complex ADHD presentation. © 2012 SAGE Publications.

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The behavior and stability of motor units (MUs) in response to electrical stimulation of different intensities can be assessed with the stimulus-response curve, which is a graphical representation of the size of the compound muscle action potential (CMAP) in relation to stimulus intensity. To examine MU characteristics across the whole stimulus range, the variability of CMAP responses to electrical stimulation, and the differences that occur between normal and disease states, the curve was studied in 11 normal subjects and 16 subjects with amyotrophic lateral sclerosis (ALS). In normal subjects, the curve showed a gradual increase in CMAP size with increasing stimulus intensity, although one or two discrete steps were sometimes observed in the upper half of the curve, indicating the activation of large MUs at higher intensities. In ALS subjects, large discrete steps, due to loss of MUs and collateral sprouting, were frequently present. Variability of the CMAP responses was greater than baseline variability, indicating variability of MU responses, and at certain levels this variability was up to 100 mu Vms. The stimulus-response curve shows differences between normal and ALS subjects and provides information on MU activation and variability throughout the curve.

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The Wing-Kristofferson (WK) model of movement timing emphasises the separation of central timer and motor processes. Several studies of repetitive timing have shown that increase in variability at longer intervals is attributable to timer processes; however, relatively little is known about the way motor aspects of timing are affected by task movement constraints. In the present study, we examined timing variability in finger tapping with differences in interval to assess central timer effects, and with differences in movement amplitude to assess motor implementation effects. Then, we investigated whether effects of motor timing observed at the point of response (flexion offset/tap) are also evident in extension, which would suggest that both phases are subject to timing control. Eleven participants performed bimanual simultaneous tapping, at two target intervals (400, 600 ms) with the index finger of each hand performing movements of equal (3 or 6 cm) or unequal amplitude (left hand 3, right hand 6 cm and vice versa). As expected, timer variability increased with the mean interval but showed only small, non-systematic effects with changes in movement amplitude. Motor implementation variability was greater in unequal amplitude conditions. The same pattern of motor variability was observed both at flexion and extension phases of movement. These results suggest that intervals are generated by a central timer, triggering a series of events at the motor output level including flexion and the following extension, which are explicitly represented in the timing system.

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In fast bowling, cricketers are expected to produce a range of delivery lines and lengths while maximising ball speed. From a coaching perspective, technique consistency has been typically associated with superior performance in these areas. However, although bowlers are required to bowl consistently, at the elite level they must also be able to vary line, length and speed to adapt to opposition batters’ strengths and weaknesses. The relationship between technique and performance variability (and consistency) has not been investigated in previous fast bowling research. Consequently, the aim of this study was to quantify both technique (bowling action and coordination) and performance variability in elite fast bowlers from Australian Junior and National Pace Squads. Technique variability was analysed to investigate whether it could be classified as functional or dysfunctional in relation to speed and accuracy.

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Estimating a time interval and temporally coordinating movements in space are fundamental skills, but the relationships between these different forms of timing, and the neural processes that they incur, are not well understood. While different theories have been proposed to account for time perception, time estimation, and the temporal patterns of coordination, there are no general mechanisms which unify these various timing skills. This study considers whether a model of perceptuo-motor timing, the tau(GUIDE), can also describe how certain judgements of elapsed time are made. To evaluate this, an equation for determining interval estimates was derived from the tau(GUIDE) model and tested in a task where participants had to throw a ball and estimate when it would hit the floor. The results showed that in accordance with the model, very accurate judgements could be made without vision (mean timing error -19.24 msec), and the model was a good predictor of skilled participants' estimate timing. It was concluded that since the tau(GUIDE) principle provides temporal information in a generic form, it could be a unitary process that links different forms of timing.

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Traditionally, audio-motor timing processes have been understood as motor output from an internal clock, the speed of which is set by heard sound pulses. In contrast, this paper proposes a more ecologically-grounded approach, arguing that audio-motor processes are better characterized as performed actions on the perceived structure of auditory events. This position is explored in the context of auditory sensorimotor synchronization and continuation timing. Empirical research shows that the structure of sounds as auditory events can lead to marked differences in movement timing performance. The nature of these effects is discussed in the context of perceived action-relevance of auditory event structure. It is proposed that different forms of sound invite or support different patterns of sensorimotor timing. Hence, the temporal information in looped auditory signals is more than just the interval durations between onsets: all metronomes are not created equal. The potential implications for auditory guides in motor performance enhancement are also described.

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We argue that impulsiveness is characterized by compromised timing functions such as premature motor timing, decreased tolerance to delays, poor temporal foresight and steeper temporal discounting. A model illustration for the association between impulsiveness and timing deficits is the impulsiveness disorder of attention-deficit hyperactivity disorder (ADHD). Children with ADHD have deficits in timing processes of several temporal domains and the neural substrates of these compromised timing functions are strikingly similar to the neuropathology of ADHD. We review our published and present novel functional magnetic resonance imaging data to demonstrate that ADHD children show dysfunctions in key timing regions of prefrontal, cingulate, striatal and cerebellar location during temporal processes of several time domains including time discrimination of milliseconds, motor timing to seconds and temporal discounting of longer time intervals. Given that impulsiveness, timing abnormalities and more specifically ADHD have been related to dopamine dysregulation, we tested for and demonstrated a normalization effect of all brain dysfunctions in ADHD children during time discrimination with the dopamine agonist and treatment of choice, methylphenidate. This review together with the new empirical findings demonstrates that neurocognitive dysfunctions in temporal processes are crucial to the impulsiveness disorder of ADHD and provides first evidence for normalization with a dopamine reuptake inhibitor.

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To maintain synchrony in group activities, each individual within the group must continuously correct their movements to remain in time with the temporal cues available. Cues might originate from one or more members of the group. Current research suggests that when synchronising movements, individuals optimise their performance in terms of minimising variability of timing errors (asynchronies) between external cues and their own movements. However, the cost of this is an increase in the timing variability of their own movements. Here we investigate whether an individual’s timing strategy changes according to the task, in a group scenario. To investigate this, we employed a novel paradigm that positioned six individuals to form two chains with common origin and termination on the circumference of a circle. We found that participants with access to timing cues from only one other member used a strategy to minimise their asynchrony variance. In contrast, the participant at the common termination of the two chains, who was required to integrate timing cues from two members, used a strategy that minimised movement variability. We conclude that humans are able to flexibly switch timekeeping strategies to maintain task demands and thus optimise the temporal performance of their movements.

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Motor timing tasks have been employed in studies of neurodevelopmental disorders such as developmental dyslexia and ADHD, where they provide an index of temporal processing ability. Investigations of these disorders have used different stimulus parameters within the motor timing tasks which are likely to affect performance measures. Here we assessed the effect of auditory and visual pacing stimuli on synchronised motor timing performance and its relationship with cognitive and behavioural predictors that are commonly used in the diagnosis of these highly prevalent developmental disorders. Twenty- one children (mean age 9.6 years) completed a finger tapping task in two stimulus conditions, together with additional psychometric measures. As anticipated, synchronisation to the beat (ISI 329 ms) was less accurate in the visually paced condition. Decomposition of timing variance indicated that this effect resulted from differences in the way that visual and auditory paced tasks are processed by central timekeeping and associated peripheral implementation systems. The ability to utilise an efficient processing strategy on the visual task correlated with both reading and sustained attention skills. Dissociations between these patterns of relationship across task modality suggest that not all timing tasks are equivalent.

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Changes in stride characteristics and gait rhythmicity characterize gait in Parkinson's disease and are widely believed to contribute to falls in this population. However, few studies have examined gait in PD patients who fall. This study reports on the complexities of walking in PD patients who reported falling during a 12-month follow-up. Forty-nine patients clinically diagnosed with idiopathic PD and 34 controls had their gait assessed using three-dimensional motion analysis. Of the PD patients, 32 (65%) reported at least one fall during the follow-up compared with 17 (50%) controls. The results showed that PD patients had increased stride timing variability, reduced arm swing and walked with a more stooped posture than controls. Additionally, PD fallers took shorter strides, walked slower, spent more time in double-support, had poorer gait stability ratios and did not project their center of mass as far forward of their base of support when compared with controls. These stride changes were accompanied by a reduced range of angular motion for the hip and knee joints. Relative to walking velocity, PD fallers had increased mediolateral head motion compared with PD nonfallers and controls. Therefore, head motion could exceed “normal” limits, if patients increased their walking speed to match healthy individuals. This could be a limiting factor for improving gait in PD and emphasizes the importance of clinically assessing gait to facilitate the early identification of PD patients with a higher risk of falling.