Differences between motor execution and motor imagery of grasping movements in the motor cortical excitatory circuit

Background Both motor imagery (MI) and motor execution (ME) can facilitate motor cortical excitability. Although cortical excitability is modulated by intracortical inhibitory and excitatory circuits in the human primary motor cortex, it is not clear which intracortical circuits determine the differences in corticospinal excitability between ME and MI. Methods We recruited 10 young healthy subjects aged 18−28 years (mean age: 22.1 ± 3.14 years; five women and five men) for this study. The experiment consisted of two sets of tasks involving grasp actions of the right hand: imagining and executing them. Corticospinal excitability and short-interval intracortical inhibition (SICI) were measured before the interventional protocol using transcranial magnetic stimulation (baseline), as well as at 0, 20, and 40 min (T0, T20, and T40) thereafter. Results Facilitation of corticospinal excitability was significantly greater after ME than after MI in the right abductor pollicis brevis (APB) at T0 and T20 (p < 0.01 for T0, and p < 0.05 for T20), but not in the first dorsal interosseous (FDI) muscle. On the other hand, no significant differences in SICI between ME and MI were found in the APB and FDI muscles. The facilitation of corticospinal excitability at T20 after MI correlated with the Movement Imagery Questionnaire (MIQ) scores for kinesthetic items (Rho = −0.646, p = 0.044) but did not correlate with the MIQ scores for visual items (Rho = −0.265, p = 0.458). Discussion The present results revealed significant differences between ME and MI on intracortical excitatory circuits of the human motor cortex, suggesting that cortical excitability differences between ME and MI may be attributed to the activation differences of the excitatory circuits in the primary motor cortex

The accuracy of the motor imagery and the ball reception in children

Estudios recientes observaron que las imágenes motrices se desarrollan de forma entrelazada con el desarrollo de las habilidades motrices en niños. La finalidad de este estudio es analizar en qué medida la imagen motriz de los elementos necesarios para resolver un problema motor (la recepción de un balón), se relaciona con los niveles de habilidad en niños (3 - 9 años). La muestra estuvo formada por 215 participantes (87 chicos y 118 chicas), (M = 5,94, DT = 1,47). Se ha utilizado una metodología mixta: dibujos, indicaciones gestuales, verbalización del pensamiento y una prueba práctica de recepción de balón. El MANOVA reveló diferencias significativas en las capacidades meta-cognitivas y motrices en función de las etapas de desarrollo. Un análisis de ecuaciones estructurales reveló que las capacidades meta-cognitivas median la relación entre las etapas de desarrollo y la habilidad de recepción de móviles. Se discuten sus repercusiones en el aprendizaje motorRecent studies have found that motor imaginery is developed linked to the development of motor skills in children. The purpose of this study is to analyze how the motor imaginery of the principal elements to solve a motor problem (ball reception) relates to the motor skill levels in children (3-9 years). The sample consisted of 215 participants (87 boys and 118 girls), (M = 5.94, SD = 1.47).We used a mixed methodology: drawings, gestural prompts, verbalization of thought and a practical test of ball reception. The MANOVA revealed significant differences in the meta-cognitive abilities and motor function of the developmental stages. A structural equation analysis revealed that meta-cognitive abilities mediate the relationship between the stages of development and the ability in the reception of moving objects. Their implications in motor learning are discusse

Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning

BACKGROUND: Neural substrates underlying motor learning have been widely investigated with neuroimaging technologies. Investigations have illustrated the critical regions of motor learning and further revealed parallel alterations of functional activation during imagination and execution after learning. However, little is known about the functional connectivity associated with motor learning, especially motor imagery learning, although benefits from functional connectivity analysis attract more attention to the related explorations. We explored whether motor imagery (MI) and motor execution (ME) shared parallel alterations of functional connectivity after MI learning. METHODOLOGY/PRINCIPAL FINDINGS: Graph theory analysis, which is widely used in functional connectivity exploration, was performed on the functional magnetic resonance imaging (fMRI) data of MI and ME tasks before and after 14 days of consecutive MI learning. The control group had no learning. Two measures, connectivity degree and interregional connectivity, were calculated and further assessed at a statistical level. Two interesting results were obtained: (1) The connectivity degree of the right posterior parietal lobe decreased in both MI and ME tasks after MI learning in the experimental group; (2) The parallel alterations of interregional connectivity related to the right posterior parietal lobe occurred in the supplementary motor area for both tasks. CONCLUSIONS/SIGNIFICANCE: These computational results may provide the following insights: (1) The establishment of motor schema through MI learning may induce the significant decrease of connectivity degree in the posterior parietal lobe; (2) The decreased interregional connectivity between the supplementary motor area and the right posterior parietal lobe in post-test implicates the dissociation between motor learning and task performing. These findings and explanations further revealed the neural substrates underpinning MI learning and supported that the potential value of MI learning in motor function rehabilitation and motor skill learning deserves more attention and further investigation

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance

Role of medial premotor areas in action language processing in relation to motor skills

The literature reports that the supplementary motor area (SMA) and pre-supplementary motor area (pre-SMA) are involved in motor planning and execution, and in motor-related cognitive functions such as motor imagery. However, their specific role in action language processing remains unclear. In the present study, we investigated the impact of repetitive transcranial magnetic stimulation (rTMS) over SMA and pre-SMA during an action semantic analogy task (SAT) in relation with fine motor skills (i.e., manual dexterity) and motor imagery abilities in healthy non-expert adults. The impact of rTMS over SMA (but not pre-SMA) on reaction times (RT) during SAT was correlated with manual dexterity. Specifically, results show that rTMS over SMA modulated RT for those with lower dexterity skills. Our results therefore demonstrate a causal involvement of SMA in action language processing, as well as the existence of inter-individual differences in this involvement. We discuss these findings in light of neurolinguistic theories of language processing

Systematic balance exercises influence cortical activation and serum BDNF levels in older adults

We sought to investigate whether systematic balance training modulates brain area activity responsible for postural control and influence brain-derived neurotrophic factor (BDNF) mRNA protein expression. Seventy-four older adults were randomly divided into three groups (mean age 65.34 ± 3.79 years, 30 females): Classic balance exercises (CBT), virtual reality balance exercises (VBT), and control (CON). Neuroimaging studies were performed at inclusion and after completion of the training or 12 weeks later (CON). Blood samples were obtained to measure BDNF expression. The study revealed significant interaction of sessions and groups: In the motor imagery (MI) condition for supplementary motor area (SMA) activity (Fat peak = 5.25, p < 0.05); in the action observation (AO) condition for left and right supramarginal gyrus/posterior insula (left: Fat peak = 6.48, p < 0.05; right: Fat peak = 6.92, p < 0.05); in the action observation together with motor imagery (AOMI) condition for the middle occipital gyrus (laterally)/area V5 (left: Fat peak = 6.26, p < 0.05; right: Fat peak = 8.37, p < 0.05), and in the cerebellum–inferior semilunar lobule/tonsil (Fat peak = 5.47, p < 0.05). After the training serum BDNF level has increased in CBT (p < 0.001) and in CBT compared to CON (p < 0.05). Systematic balance training may reverse the age-related cortical over-activations and appear to be a factor mediating neuroplasticity in older adults

Identifying Abnormal Connectivity in Patients Using Dynamic Causal Modeling of fMRI Responses

Functional imaging studies of brain damaged patients offer a unique opportunity to understand how sensorimotor and cognitive tasks can be carried out when parts of the neural system that support normal performance are no longer available. In addition to knowing which regions a patient activates, we also need to know how these regions interact with one another, and how these inter-regional interactions deviate from normal. Dynamic causal modeling (DCM) offers the opportunity to assess task-dependent interactions within a set of regions. Here we review its use in patients when the question of interest concerns the characterization of abnormal connectivity for a given pathology. We describe the currently available implementations of DCM for fMRI responses, varying from the deterministic bilinear models with one-state equation to the stochastic non-linear models with two-state equations. We also highlight the importance of the new Bayesian model selection and averaging tools that allow different plausible models to be compared at the single subject and group level. These procedures allow inferences to be made at different levels of model selection, from features (model families) to connectivity parameters. Following a critical review of previous DCM studies that investigated abnormal connectivity we propose a systematic procedure that will ensure more flexibility and efficiency when using DCM in patients. Finally, some practical and methodological issues crucial for interpreting or generalizing DCM findings in patients are discussed

Investigating changes in motor activation after tDCS

Transcranial direct current stimulation (tDCS) is a stimulation modality commonly used in motor rehabilitation research, however there is still debate surrounding the neural effects, even in healthy participants. This study thus looked to assess whether tDCS over the primary motor cortex (M1) had any significant effects on the brain motor areas in healthy right-handed participants. Within a functional magnetic resonance imaging (fMRI) scanner, a motor task, comprised move and rest blocks, was performed baseline and post stimulation. Anodal, cathodal or sham tDCS (1mA - 20 minutes) were performed on the left M1 in a within subject design (3 separate sessions per participant). Region of Interest (ROI) group baseline analysis for the contrast move>rest found the task activated all motor ROIs [p value <0.05, Family wise error (FWE) corrected]. The contrast baseline<post revealed a significant increase in brain activity in the stimulated M1 [p value <0.001, uncorrected] for cathodal stimulation, and a significant increase in brain activity in the stimulated M1 [p value <0.001, uncorrected] and ipsilateral SMA [p value <0.05, FWE corrected]. No significant changes in activity were found for sham stimulation or the contrast baseline<post. Interactional analysis of all tDCS polarities across the baseline<post contrast found significant brain activity changes in the Cerebellum Areas 4, 5 and 6 [p value <0.05, FWE corrected]. This study therefore indicates that tDCS has widespread effects on the motor network, with anodal tDCS increasing brain activity in certain motor areas as predicted

Interface cérebro-computador não invasiva baseada em OpenVibe

O Objectivo desta dissertação é desenvolver uma Interface Cérebro – Computador (ICC) não invasiva baseada em sinais de Electroencefalograma, no ambiente computacional OpenVibe. Os sistemas ICC congregam várias áreas distintas de conhecimento. Dessa forma, foi necessário efectuar um estudo do estado de arte, de forma a conhecer o ponto presente relativo ás várias variáveis que contribuem para o desempenho global dos sistemas deste tipo. Procedeu-se a uma descrição do ambiente computacional OpenVibe e do driver para o hardware de aquisição de EEG utilizado na aquisição de dados. Foram efectuados dois paradigmas de ICC, a Imaginação Motora e a P300 implementados primeiro offline com dados fornecidos para o OpenVibe e segundo em online com aquisição e processamento em tempo - real. Os resultados dos testes são apresentados para os dados fornecidos e adquiridos e são relativos ao funcionamento do sistema em geral.The objective of this dissertation is to develop a Brain - Computer Interface (BCI) based on non-invasive signs of Electroencephalogram in the computing environment OpenVibe. Systems BCI congregate various distinct knowledge areas. Of this form, necessary was going to effectuate a state-owned study of art, of form various variable what contribute for the global performance of the systems gave type to the point know present relative ace. One proceeded to a description of the ambient computational OpenVibe and the driver for the EEG hardware used in the acquisition of data. We made two paradigms of BCI Motor Imagination and P300 implemented first with offline data to OpenVibe and second in online acquisition and processing in real - time. The upshots of the tests are presented for the supplied and acquired data and are relative to the functioning of the system generally