Motor cortex excitability is not differentially modulated following skill and strength training

AIM: A single session of skill or strength training can modulate the primary motor cortex (M1), which manifests as increased corticospinal excitability (CSE) and decreased short-latency intra-cortical inhibition (SICI). We tested the hypothesis that both skill and strength training can propagate the neural mechanisms mediating cross-transfer and modulate the ipsilateral M1 (iM1). METHODS: Transcranial magnetic stimulation (TMS) measured baseline CSE and SICI in the contralateral motor cortex (cM1) and iM1. Participants completed 4 sets of unilateral training with their dominant arm, either visuomotor tracking, metronome-paced strength training (MPST), self-paced strength training (SPST) or control. Immediately post training, TMS was repeated in both M1s. RESULTS: Motor-evoked potentials (MEPs) increased and inhibition was reduced for skill and MPST training from baseline in both M1s. Self-paced strength training and control did not produce changes in CSE and SICI when compared to baseline in both M1s. After training, skill and MPST increased CSE and decreased SICI in cM1 compared to SPST and control. Skill and MPST training decreased SICI in iM1 compared to SPST and control post intervention; however, CSE in iM1 was not different across groups post training. CONCLUSION: Both skill training and MPST facilitated an increase in CSE and released SICI in iM1 and cM1 compared to baseline. Our results suggest that synchronizing to an auditory or a visual cue promotes neural adaptations within the iM1, which is thought to mediate cross transfer.

Reduced mu suppression and altered motor resonance in euthymic bipolar disorder: evidence for a dysfunctional mirror system?

Social cognitive difficulties are common in the acute phase of bipolar disorder and, to a lesser extent, during the euthymic stage, and imaging studies of social cognition in euthymic bipolar disorder have implicated mirror system brain regions. This study aimed to use a novel multimodal approach (i.e., including both transcranial magnetic stimulation (TMS) and electroencephalogram (EEG)) to investigate mirror systems in bipolar disorder. Fifteen individuals with euthymic bipolar disorder and 16 healthy controls participated in this study. Single-pulse TMS was applied to the optimal site in the primary motor cortex (M1), which stimulates the muscle of interest during the observation of hand movements (goal-directed or interacting) designed to elicit mirror system activity. Single EEG electrodes (C3, CZ, C4) recorded mu rhythm modulation concurrently. Results revealed that the patient group showed significantly less mu suppression compared to healthy controls. Surprisingly, motor resonance was not significantly different overall between groups; however, bipolar disorder participants showed a pattern of reduced reactivity on some conditions. Although preliminary, this study indicates a potential mirror system deficit in euthymic bipolar disorder, which may contribute to the pathophysiology of the disorder.

Influence of prolonged bed-rest on spectral and temporal electromyographic motor control characteristics of the superficial lumbo-pelvic musculature

Little is known about the motor control of the lumbo-pelvic musculature in microgravity and its simulation (bed-rest). Analysis of spectral and temporal electromyographic variables can provide information on motor control relevant for normal function. This study examined the effect of 56-days of bed-rest with 1-year follow-up in 10 male subjects on the median frequency and the activation timing in surface electromyographic recordings from five superficial lumbo-pelvic muscles during a repetitive knee movement task. Trunk fat mass (from whole body-composition measurements) and movement accuracy as possible explanatory factors were included. Increased median frequency was observed in the lumbar erector spinae starting late in bed-rest, but this was not seen in its synergist, the thoracic erector spinae (p<.0001). These changes persisted up to 1-year after bed-rest and were independent of changes in body-composition or movement accuracy. Analysis suggested decreases of median frequency (p<.0001) in the abdominal and gluteal muscles to result from increased (p<.01) trunk fat levels during and after bed-rest. No changes in lumbo-pelvic muscle activation timing were seen. The results suggest that bed-rest particularly affects the shorter lumbar erector spinae and that the temporal sequencing of superficial lumbo-pelvic muscle activation is relatively robust.

Resistive vibration exercise during bed-rest reduces motor control changes in the lumbo-pelvic musculature

To understand the effects of a resistive vibration exercise (RVE) countermeasure on changes in lumbo-pelvic muscle motor control during prolonged bed-rest, 20 male subjects took part in the Berlin Bed-Rest Study (in 2003-2005) and were randomised to a RVE group or an inactive control group. Surface electromyographic signals recorded from five superficial lumbo-pelvic muscles during a repetitive knee movement task. The task, which required stabilisation of the lumbo-pelvic region, was performed at multiple movement speeds and at multiple time points during and after bed-rest. After excluding effects that could be attributed to increases in subcutaneous fat changes and improvements in movement skill, we found that the RVE intervention ameliorated the generalised increases in activity ratios between movement speeds (p⩽0.012), reductions in lumbo-pelvic extensor and flexor co-contraction (p=0.058) and increases in root-mean-square electromyographic amplitude (p=0.001) of the lumbar erector spinae muscles. Effects of RVE on preventing increases in amplitude-modulation (p=0.23) of the lumbar erector spinae muscles were not significant. Few significant changes in activation-timing were seen. The RVE intervention during bed-rest, with indirect loading of the spine during exercise, was capable of reducing some, but not all, motor control changes in the lumbo-pelvic musculature during and after bed-rest.

Motor functioning in autism spectrum disorders

Motor impairment is consistently reported in autism spectrum disorders (ASD) and may be an early risk factor for core ASD symptomatology. This chapter provides an overview of empirical motor studies in ASD and considers clinical, behavioral, neurophysiological, and neuroimaging studies of motor impairment in ASD. The association between motor impairment and core social communication disturbance is also explored, as well as the high comorbidity between ASD, motor impairment, and other neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). Future research which aims to understand the specific motor pattern that may characterize ASD is suggested.

Alongside the core diagnostic features of autism, research has highlighted the significant and pervasive impact of motor dysfunction in autism spectrum disorders (ASD) (Fournier et al., J Autism Dev Disord 40(10):1227–40, 2010). Motor difficulties are commonly associated with ASD and potentially may be considered a “cardinal feature” (Fournier et al., J Autism Dev Disord 40(10):1227–40, 2010) of the disorder. Indeed, there has been an increase in the trajectory of motor research over the past decade, with greater understanding of the underlying neurobiological disruption that characterizes the disorder (Mostofsky et al., Brain 132:2413–25, 2009). This chapter will illustrate the importance of neuromotor assessment as a routine part of the diagnostic process and provide an overview of empirical research in the field.

Motor competence and its effect on positive developmental trajectories of health

In 2008, Stodden and colleagues took a unique developmental approach toward addressing the potential role of motor competence in promoting positive or negative trajectories of physical activity, health-related fitness, and weight status. The conceptual model proposed synergistic relationships among physical activity, motor competence, perceived motor competence, health-related physical fitness, and obesity with associations hypothesized to strengthen over time. At the time the model was proposed, limited evidence was available to support or refute the model hypotheses. Over the past 6 years, the number of investigations exploring these relationships has increased significantly. Thus, it is an appropriate time to examine published data that directly or indirectly relate to specific pathways noted in the conceptual model. Evidence indicates that motor competence is positively associated with perceived competence and multiple aspects of health (i.e., physical activity, cardiorespiratory fitness, muscular strength, muscular endurance, and a healthy weight status). However, questions related to the increased strength of associations across time and antecedent/consequent mechanisms remain. An individual’s physical and psychological development is a complex and multifaceted process that synergistically evolves across time. Understanding the most salient factors that influence health and well-being and how relationships among these factors change across time is a critical need for future research in this area. This knowledge could aid in addressing the declining levels of physical activity and fitness along with the increasing rates of obesity across childhood and adolescence.

Fuzzy logic controller optimized by particle swarm optimization for DC motor speed control

In this paper, we presented an optimized fuzzy logic controller using particle swarm optimization for DC motor speed control. The controller model is simulated using MATLAB software and also experimentally tested on a laboratory DC motor. A comparison of the performance of different controllers such as PID controller, fuzzy logic controller and optimized fuzzy logic controller is presented as well. With reference to the results of digital simulations and experiment, the designed FLC-PSO speed controller obtains much better dynamic behavior compared to PID and the normal FLC designed. Moreover, it can acquire superior performance of the DC motor, and also perfect speed tracking with no overshoot. The optimized membership functions (MFs) are obviously proved to be able to provide a better performance and higher robustness in comparison with a regular fuzzy model, when the MFs were heuristically defined. Besides, experimental results verify the ability of proposed FLC under sudden change of the load torque which leads to speed variances.

The role of internal action representations in motor development

This research suggests that internal ‘neural’ action representations may subserve the development of important motor functions and, where impaired or delayed, may be associated with atypical function. This knowledge provides critical validation of current motor control theories and is central to our understanding of the neuro-cognitive basis of motor development.

Prosthetic motor imaginary task classification using single channel of electroencephalography

Brain Computer Interface (BCI) is playing a very important role in human machine communications. Recent communication systems depend on the brain signals for communication. In these systems, users clearly manipulate their brain activity rather than using motor movements in order to generate signals that could be used to give commands and control any communication devices, robots or computers. In this paper, the aim was to estimate the performance of a brain computer interface (BCI) system by detecting the prosthetic motor imaginary tasks by using only a single channel of electroencephalography (EEG). The participant is asked to imagine moving his arm up or down and our system detects the movement based on the participant brain signal. Some features are extracted from the brain signal using Mel-Frequency Cepstrum Coefficient and based on these feature a Hidden Markov model is used to help in knowing if the participant imagined moving up or down. The major advantage in our method is that only one channel is needed to take the decision. Moreover, the method is online which means that it can give the decision as soon as the signal is given to the system. Hundred signals were used for testing, on average 89 % of the up down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial prosthetic limbs and wheelchairs due to it's high speed and accuracy.

Prosthetic motor imaginary task classification based on EEG quality assessment features

Brain Computer Interface (BCI) plays an important role in the communication between human and machines. This communication is based on the human brain signals. In these systems, users use their brain instead of the limbs or body movements to do tasks. The brain signals are analyzed and translated into commands to control any communication devices, robots or computers. In this paper, the aim was to enhance the performance of a brain computer interface (BCI) systems through better prosthetic motor imaginary tasks classification. The challenging part is to use only a single channel of electroencephalography (EEG). Arm movement imagination is the task of the user, where (s)he was asked to imagine moving his arm up or down. Our system detected the imagination based on the input brain signal. Some EEG quality features were extracted from the brain signal, and the Decision Tree was used to classify the participant's imagination based on the extracted features. Our system is online which means that it can give the decision as soon as the signal is given to the system (takes only 20 ms). Also, only one EEG channel is used for classification which reduces the complexity of the system which leads to fast performance. Hundred signals were used for testing, on average 97.4% of the up-down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial limbs and wheelchairs due to it's high speed and accuracy.

Multivariate adaptive autoregressive modeling and kalman filtering for motor imagery BCI

Adaptive autoregressive (AAR) modeling of the EEG time series and the AAR parameters has been widely used in Brain computer interface (BCI) systems as input features for the classification stage. Multivariate adaptive autoregressive modeling (MVAAR) also has been used in literature. This paper revisits the use of MVAAR models and propose the use of adaptive Kalman filter (AKF) for estimating the MVAAR parameters as features in a motor imagery BCI application. The AKF approach is compared to the alternative short time moving window (STMW) MVAAR parameter estimation approach. Though the two MVAAR methods show a nearly equal classification accuracy, the AKF possess the advantage of higher estimation update rates making it easily adoptable for on-line BCI systems.

A monster that lives in our lives: experiences of caregivers of people with motor neuron disease and identifying avenues for support

BACKGROUND: A developing body of evidence has provided valuable insight into the experiences of caregivers of people with motor neuron disease; however, understandings of how best to support caregivers remain limited. AIM: This study sought to understand concepts related to the motor neuron disease caregiver experience which could inform the development of supportive interventions.

DESIGN: A qualitative thematic analysis of a one-off semistructured interview with caregivers was undertaken.

SETTING/PARTICIPANTS: Caregivers of people with motor neuron disease were recruited from a progressive neurological diseases clinic in Melbourne, Australia.

RESULTS: 15 caregivers participated. Three key themes were identified: (1) The Thief: the experience of loss and grief across varied facets of life; (2) The Labyrinth: finding ways to address ever changing challenges as the disease progressed; (3) Defying fate: being resilient and hopeful as caregivers tried to make the most of the time remaining.

CONCLUSIONS: Caregivers are in need of more guidance and support to cope with experiences of loss and to adapt to changeable care giving duties associated with disease progression. Therapeutic interventions which target these experiences of loss and change are worth investigation.

Cathodal transcranial Direct Current Stimulation (tDCS) to the right cerebellar hemisphere affects motor adaptation during gait

The cerebellum appears to play a key role in the development of internal rules that allow fast, predictive adjustments to novel stimuli. This is crucial for adaptive motor processes, such as those involved in walking, where cerebellar dysfunction has been found to increase variability in gait parameters. Motor adaptation is a process that results in a progressive reduction in errors as movements are adjusted to meet demands, and within the cerebellum, this seems to be localised primarily within the right hemisphere. To examine the role of the right cerebellar hemisphere in adaptive gait, cathodal transcranial direct current stimulation (tDCS) was administered to the right cerebellar hemisphere of 14 healthy adults in a randomised, double-blind, crossover study. Adaptation to a series of distinct spatial and temporal templates was assessed across tDCS condition via a pressure-sensitive gait mat (ProtoKinetics Zeno walkway), on which participants walked with an induced 'limp' at a non-preferred pace. Variability was assessed across key spatial-temporal gait parameters. It was hypothesised that cathodal tDCS to the right cerebellar hemisphere would disrupt adaptation to the templates, reflected in a failure to reduce variability following stimulation. In partial support, adaptation was disrupted following tDCS on one of the four spatial-temporal templates used. However, there was no evidence for general effects on either the spatial or temporal domain. This suggests, under specific conditions, a coupling of spatial and temporal processing in the right cerebellar hemisphere and highlights the potential importance of task complexity in cerebellar function.