Showing papers on "Motor imagery published in 2010"

Cortical activity during motor execution, motor imagery, and imagery-based online feedback

Abstract: Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in “high frequency” (76–100 Hz) and “low frequency” (8–32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was ∼25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study

Abstract: There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice in conjunction with physical practice (PP) of goal-directed rehabilitation tasks leads to enhanced functional recovery of paralyzed limbs among stroke sufferers. It is however difficult to confirm patient engagement during an MI in the absence of any on-line measure. Fortunately an EEG-based brain-computer interface (BCI) can provide an on-line measure of MI activity as a neurofeedback for the BCI user to help him/her focus better on the MI task. However initial performance of novice BCI users may be quite moderate and may cause frustration. This paper reports a pilot study in which a BCI system is used to provide a computer game-based neurofeedback to stroke participants during the MI part of a protocol. The participants included five chronic hemiplegic stroke sufferers. Participants received up to twelve 30-minute MI practice sessions (in conjunction with PP sessions of the same duration) on 2 days a week for 6 weeks. The BCI neurofeedback performance was evaluated based on the MI task classification accuracy (CA) rate. A set of outcome measures including action research arm test (ARAT) and grip strength (GS), was made use of in assessing the upper limb functional recovery. In addition, since stroke sufferers often experience physical tiredness, which may influence the protocol effectiveness, their fatigue and mood levels were assessed regularly. Positive improvement in at least one of the outcome measures was observed in all the participants, while improvements approached a minimal clinically important difference (MCID) for the ARAT. The on-line CA of MI induced sensorimotor rhythm (SMR) modulation patterns in the form of lateralized event-related desynchronization (ERD) and event-related synchronization (ERS) effects, for novice participants was in a moderate range of 60-75% within the limited 12 training sessions. The ERD/ERS change from the first to the last session was statistically significant for only two participants. Overall the crucial observation is that the moderate BCI classification performance did not impede the positive rehabilitation trends as quantified with the rehabilitation outcome measures adopted in this study. Therefore it can be concluded that the BCI supported MI is a feasible intervention as part of a post-stroke rehabilitation protocol combining both PP and MI practice of rehabilitation tasks. Although these findings are promising, the scope of the final conclusions is limited by the small sample size and the lack of a control group.

An EEG-Based BCI System for 2-D Cursor Control by Combining Mu/Beta Rhythm and P300 Potential

Abstract: Two-dimensional cursor control is an important and challenging issue in EEG-based brain-computer interfaces (BCIs). To address this issue, here we propose a new approach by combining two brain signals including Mu/Beta rhythm during motor imagery and P300 potential. In particular, a motor imagery detection mechanism and a P300 potential detection mechanism are devised and integrated such that the user is able to use the two signals to control, respectively, simultaneously, and independently, the horizontal and the vertical movements of the cursor in a specially designed graphic user interface. A real-time BCI system based on this approach is implemented and evaluated through an online experiment involving six subjects performing 2-D control tasks. The results attest to the efficacy of obtaining two independent control signals by the proposed approach. Furthermore, the results show that the system has merit compared with prior systems: it allows cursor movement between arbitrary positions.

Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback

Abstract: This clinical study investigates the ability of hemiparetic stroke patients in operating EEG-based motor imagery brain-computer interface (MI-BCI). It also assesses the efficacy in motor improvements on the stroke-affected upper limb using EEG-based MI-BCI with robotic feedback neurorehabilitation compared to robotic rehabilitation that delivers movement therapy. 54 hemiparetic stroke patients with mean age of 51.8 and baseline Fugl-Meyer Assessment (FMA) 14.9 (out of 66, higher = better) were recruited. Results showed that 48 subjects (89%) operated EEG-based MI-BCI better than at chance level, and their ability to operate EEG-based MI-BCI is not correlated to their baseline FMA (r=0.358). Those subjects who gave consent are randomly assigned to each group (N=11 and 14) for 12 1-hour rehabilitation sessions for 4 weeks. Significant gains in FMA scores were observed in both groups at post-rehabilitation (4.5, 6.2; p=0.032, 0.003) and 2-month post-rehabilitation (5.3, 7.3; p=0.020, 0.013), but no significant differences were observed between groups (p=0.512, 0.550). Hence, this study showed evidences that a majority of hemiparetic stroke patients can operate EEG-based MI-BCI, and that EEG-based MI-BCI with robotic feedback neurorehabilitation is effective in restoring upper extremities motor function in stroke.

Mental Practice for Relearning Locomotor Skills

Abstract: Over the past 2 decades, much work has been carried out on the use of mental practice through motor imagery for optimizing the retraining of motor function in people with physical disabilities. Although much of the clinical work with mental practice has focused on the retraining of upper-extremity tasks, this article reviews the evidence supporting the potential of motor imagery for retraining gait and tasks involving coordinated lower-limb and body movements. First, motor imagery and mental practice are defined, and evidence from physiological and behavioral studies in healthy individuals supporting the capacity to imagine walking activities through motor imagery is examined. Then the effects of stroke, spinal cord injury, lower-limb amputation, and immobilization on motor imagery ability are discussed. Evidence of brain reorganization in healthy individuals following motor imagery training of dancing and of a foot movement sequence is reviewed, and the effects of mental practice on gait and other tasks involving coordinated lower-limb and body movements in people with stroke and in people with Parkinson disease are examined. Lastly, questions pertaining to clinical assessment of motor imagery ability and training strategies are discussed.

Cognitive neural prosthetics.

Abstract: The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded However, some cortical areas may be better than others for particular applications Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions

Mental imagery of speech and movement implicates the dynamics of internal forward models.

Abstract: The classical concept of efference copies in the context of internal forward models has stimulated productive research in cognitive science and neuroscience. There are compelling reasons to argue for such a mechanism, but finding direct evidence in the human brain remains difficult. Here we investigate the dynamics of internal forward models from an unconventional angle: mental imagery, assessed while recording high temporal resolution neuronal activity using magnetoencephalography (MEG). We compare two overt and covert tasks; our covert, mental imagery tasks are unconfounded by overt input/output demands – but in turn necessitate the development of appropriate multi-dimensional topographic analyses. Finger tapping (studies 1-2) and speech experiments (studies 3-5) provide temporally constrained results that implicate the estimation of an efference copy. We suggest that one internal forward model over parietal cortex subserves the kinesthetic feeling in motor imagery. Secondly, observed auditory neural activity ~170 ms after motor estimation in speech experiments (studies 3-5) demonstrates the anticipated auditory consequences of planned motor commands in a second internal forward model in imagery of speech production. Our results provide neurophysiological evidence from the human brain in favor of internal forward models deploying efference copies in somatosensory and auditory cortex, in finger tapping and speech production tasks, respectively, and also suggest the dynamics and sequential updating structure of internal forward models.

The Mirror Neuron System: A Neural Substrate for Methods in Stroke Rehabilitation:

Abstract: Mirror neurons found in the premotor and parietal cortex respond not only during action execution, but also during observation of actions being performed by others. Thus, the motor system may be activated without overt movement. Rehabilitation of motor function after stroke is often challenging due to severity of impairment and poor to absent voluntary movement ability. Methods in stroke rehabilitation based on the mirror neuron system--action observation, motor imagery, and imitation--take advantage of this opportunity to rebuild motor function despite impairments, as an alternative or complement to physical therapy. Here the authors review research into each condition of practice, and discuss the relevance of the mirror neuron system to stroke recovery.

Motor Learning Without Doing: Trial-by-Trial Improvement in Motor Performance During Mental Training

Abstract: Although there is converging experimental and clinical evidences suggesting that mental training with motor imagery can improve motor performance, it is unclear how humans can learn movements through mental training despite the lack of sensory feedback from the body and the environment. In a first experiment, we measured the trial-by-trial decrease in durations of executed movements (physical training group) and mentally simulated movements (motor-imagery training group), by means of training on a multiple-target arm-pointing task requiring high accuracy and speed. Movement durations were significantly lower in posttest compared with pretest after both physical and motor-imagery training. Although both the posttraining performance and the rate of learning were smaller in motor-imagery training group than in physical training group, the change in movement duration and the asymptotic movement duration after a hypothetical large number of trials were identical. The two control groups (eye-movement training and rest groups) did not show change in movement duration. In the second experiment, additional kinematic analyses revealed that arm movements were straighter and faster both immediately and 24 h after physical and motor-imagery training. No such improvements were observed in the eye-movement training group. Our results suggest that the brain uses state estimation, provided by internal forward model predictions, to improve motor performance during mental training. Furthermore, our results suggest that mental practice can, at least in young healthy subjects and if given after a short bout of physical practice, be successfully substituted to physical practice to improve motor performance.

Neural dissociations between action verb understanding and motor imagery

Abstract: According to embodied theories of language, people understand a verb like throw, at least in part, by mentally simulating throwing. This implicit simulation is often assumed to be similar or identical to motor imagery. Here we used fMRI to test whether implicit simulations of actions during language understanding involve the same cortical motor regions as explicit motor imagery. Healthy participants were presented with verbs related to hand actions (e.g., to throw) and nonmanual actions (e.g., to kneel). They either read these verbs (lexical decision task) or actively imagined performing the actions named by the verbs (imagery task). Primary motor cortex showed effector-specific activation during imagery, but not during lexical decision. Parts of premotor cortex distinguished manual from nonmanual actions during both lexical decision and imagery, but there was no overlap or correlation between regions activated during the two tasks. These dissociations suggest that implicit simulation and explicit imagery cued by action verbs may involve different types of motor representations and that the construct of "mental simulation" should be distinguished from "mental imagery" in embodied theories of language.

The neurophysiological foundations of mental and motor imagery

Abstract: Preface Introduction SECTION 1: THE NEURAL SUBSTRATES OF MENTAL AND MOTOR IMAGERY Multimodal Images in the Brain Neural bases of topographical representation in humans: Contribution of neuroimaging studies Contribution of the primary motor cortex to motor imagery Corticospinal facilitation during motor imagery SECTION 2: NEUROPHYSIOLOGICAL CORRELATES OF MOTOR IMAGERY EEG Characteristics during Motor Imagery Electromyographic activity during motor imagery Autonomic nervous system activities during imagined movements Neurophysiological substrates of motor imagery ability SECTION 3: MOTOR IMAGERY IN REHABILITATION Motor imagery and the rehabilitation of movement disorders: an overview An overview of the effectiveness of motor imagery after stroke: A neuroimaging approach Motor imagery for optimising the reacquisition of locomotor skills after cerebral damage Motor Imagery Practice in Individuals with Parkinson's Disease Blindness and motor imagery EEG-based brain-computer communication SECTION 4: MOTOR IMAGERY IN LEARNING PROCESSES Motor imagery and motor performance: evidence from the sport science literature Meta-imagery Processes Among Elite Sports Performers The use of motor imagery in teaching surgical skills lessons from sports training Movement Imagery, Observation, and Skill From the mental representation of pain and emotions to empathy

Fast set-up asynchronous brain-switch based on detection of foot motor imagery in 1-channel EEG

Abstract: Bringing a Brain-Computer Interface (BCI) out of the lab one of the main problems has to be solved: to shorten the training time. Finding a solution for this problem, the use of a BCI will be open not only for people who have no choice, e.g., persons in a locked-in state, or suffering from a degenerating nerve disease. By reducing the training time to a minimum, also healthy persons will make use of the system, e.g., for using this kind of control for games. For realizing such a control, the post-movement beta rebound occurring after brisk feet movement was used to set up a classifier. This classifier was then used in a cue-based motor imagery system. After classifier adaptation, a self-paced brain-switch based on brisk foot motor imagery (MI) was evaluated. Four out of six subjects showed that a post-movement beta rebound after feet MI and succeeded with a true positive rate between 69 and 89%, while the positive predictive value was between 75 and 93%.

Temporal Coding of Brain Patterns for Direct Limb Control in Humans

Abstract: For individuals with a high spinal cord injury (SCI) not only the lower limbs, but also the upper extremities are paralyzed. A neuroprosthesis can be used to restore the lost hand and arm function in those tetraplegics. The main problem for this group of individuals, however, is the reduced ability to voluntarily operate device controllers. A Brain-Computer Interface provides a non-manual alternative to conventional input devices by translating brain activity patterns into control commands. We show that the temporal coding of individual mental imagery pattern can be used to control two independent degrees of freedom – grasp and elbow function - of an artificial robotic arm by utilizing a minimum number of EEG scalp electrodes. We describe the procedure from the initial screening to the final application. From eight naive subjects participating on-line feedback experiments, four were able to voluntarily control an artificial arm by inducing one motor imagery pattern derived from one EEG derivation only.

Mental rotation task of hands: differential influence number of rotational axes

Abstract: Various studies on the hand laterality judgment task, using complex sets of stimuli, have shown that the judgments during this task are dependent on bodily constraints. More specific, these studies showed that reaction times are dependent on the participant’s posture or differ for hand pictures rotated away or toward the mid-sagittal plane (i.e., lateral or medial rotation, respectively). These findings point to the use of a cognitive embodied process referred to as motor imagery. We hypothesize that the number of axes of rotation of the displayed stimuli during the task is a critical factor for showing engagement in a mental rotation task, with an increased number of rotational axes leading to a facilitation of motor imagery. To test this hypothesis, we used a hand laterality judgment paradigm in which we manipulated the difficulty of the task via the manipulation of the number of rotational axes of the shown stimuli. Our results showed increased influence of bodily constraints for increasing number of axes of rotation. More specifically, for the stimulus set containing stimuli rotated over a single axis, no influence of biomechanical constraints was present. The stimulus sets containing stimuli rotated over more than one axes of rotation did induce the use of motor imagery, as a clear influence of bodily constraints on the reaction times was found. These findings extend and refine previous findings on motor imagery as our results show that engagement in motor imagery critically depends on the used number of axes of rotation of the stimulus set.

Motor imagery: if you can't do it, you won't think it.

Abstract: Since long, motor imagery has been recognized as a method for studying motor representations. In the last few years, important advances regarding the use of motor imagery have been made. In particular, issues concerning the functional equivalence between imagery and action have been addressed, and how equivalence affects the use of imagery to study motor representations. In this paper, we review recent findings in order to highlight the current state of knowledge about motor imagery and its relation to motor action. Three topics are discussed: (i) the imagery perspective, (ii) task complexity, and (iii) the importance of physical experience. It is shown how theses factors are closely related and how previous studies may have underestimated to what extent these factors affect the interpretation of results. Practical implications for imagery interventions are considered. It is concluded that if you cannot perform an action physically, you cannot imagine it in a way that is necessary for a high degree of functional equivalence.

Brain oscillatory activity duringmotorimagery in EEG-fMRIcoregistration

Abstract: The purpose of the present work was to investigate the correlation between topographical changes in brain oscillatory activity and the blood oxygenation level-dependent (BOLD) signal during a motor imagery (MI) task using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) coregistration. EEG was recorded in 7 healthy subjects inside a 1.5 T MR scanner during the imagination of the kinesthetic experience of movement. A Fast Fourier Transform was applied to EEG signal in the rest and active conditions. We used the event-related-synchronization (ERS)/ desynchronization (ERD) approach to characterize where the imagination of movement produces a decrease in alpha and beta power. The mean alpha map showed ERD decrease localized over the contralateral sensory motor area (SM1c) and a light desynchronization in the ipsilateral sensory motor area (SM1i); whereas the mean beta map showed ERD decrease over the supplementary motor area (SMA). fMRI showed significant activation in SMA, SM1c, SM1i. The correlation is negative in the contralateral side and positive in the ipsilateral side. Using combined EEG-fMRI signals we obtained useful new information on the description of the changes in oscillatory activity in alpha and beta bands during MI and on the investigation of the sites of BOLD activity as possible sources in generating these rhythms. By correlating BOLD and ERD/ERS we may identify more accurately which regions contribute to changes of the electrical response.