Brain Activity during Lower-Limb Movement with Manual Facilitation: An fMRI Study

fMRI-Informed EEG for brain mapping of imagined lower limb movement: Feasibility of a brain computer interface

BACKGROUND

EEG and fMRI have contributed greatly to our understanding of brain activity and its link to behaviors by helping to identify both when and where the activity occurs. This is particularly important in the development of brain-computer interfaces (BCIs), where feed forward systems gather data from imagined brain activity and then send that information to an effector. The purpose of this study was to develop and evaluate a computational approach that enables an accurate mapping of spatial brain activity (fMRI) in relation to the temporal receptors (EEG electrodes) associated with imagined lower limb movement.

NEW METHOD

EEG and fMRI data from 16 healthy, male participants while imagining lower limb movement were used for this purpose. A combined analysis of fMRI data and EEG electrode locations was developed to identify EEG electrodes with a high likelihood of capturing imagined lower limb movement originating from various clusters of brain activity. This novel feature selection tool was used to develop an artificial neural network model to classify right and left lower limb movement.

RESULTS

Results showed that left versus right lower limb imagined movement could be classified with 66.5% accuracy using this approach. Comparison with existing methods: Adopting a purely data-driven approach for feature selection to use in the right/left classification task resulted in the same accuracy (66.6%) but with reduced interpretability.

CONCLUSIONS

The developed fMRI-informed EEG approach could pave the way towards improved brain computer interfaces for lower limb movement while also being applicable to other systems where fMRI could be helpful to inform EEG acquisition and processing.

Differentiating the Brain's involvement in Executed and Imagined Stepping using fMRI

The purpose of this study was to extend the extant literature regarding brain areas that are activated during executed and imagined lower limb movement. Past research suggests that stepping, as a cyclical movement, should activate the motor control areas of the brain that integrates smooth movements with spinal cord nerves. The neuronal activity needed to imagine that same activity is likely to recruit additional sensory-motor areas that provide initiation and inhibition signals, making this task take on a neuronal activity pattern that is more similar to discrete movements. To assess this research question, 16 participants took part in the current study where they executed and imagined stepping, with movement at the hip, knee, and ankle joints, while viewing a computer-generated image of a human walking. A block design with a total of 10 blocks for rest and task for each condition was used. Rest blocks lasted 18 seconds, followed by an 18-second display of the visual stimulus. Results showed that in the executed condition, areas of the brain that are most prominently associated with sensory-motor activity were activated. In the imagined condition areas of the brain associated with movement control, inhibition of movement, and the integration of sensory input and motor output (parietal and occipital) were also activated. These findings contribute to the literature identifying brain areas that are activated in lower limb locomotion.

Neurophysiological changes in the visuomotor network after practicing a motor task

Although it is well appreciated that practicing a motor task updates the associated internal model, it is still unknown how the cortical oscillations linked with the motor action change with practice. The present study investigates the short-term changes (e.g., fast motor learning) in the α- and β-event-related desynchronizations (ERD) associated with the production of a motor action. To this end, we used magnetoencephalography to identify changes in the α- and β-ERD in healthy adults after participants practiced a novel isometric ankle plantarflexion target-matching task. After practicing, the participants matched the targets faster and had improved accuracy, faster force production, and a reduced amount of variability in the force output when trying to match the target. Parallel with the behavioral results, the strength of the β-ERD across the motor-planning and execution stages was reduced after practice in the sensorimotor and occipital cortexes. No pre/postpractice changes were found in the α-ERD during motor planning or execution. Together, these outcomes suggest that fast motor learning is associated with a decrease in β-ERD power. The decreased strength likely reflects a more refined motor plan, a reduction in neural resources needed to perform the task, and/or an enhancement of the processes that are involved in the visuomotor transformations that occur before the onset of the motor action. These results may augment the development of neurologically based practice strategies and/or lead to new practice strategies that increase motor learning. NEW & NOTEWORTHY We aimed to determine the effects of practice on the movement-related cortical oscillatory activity. Following practice, we found that the performance of the ankle plantarflexion target-matching task improved and the power of the β-oscillations decreased in the sensorimotor and occipital cortexes. These novel findings capture the β-oscillatory activity changes in the sensorimotor and occipital cortexes that are coupled with behavioral changes to demonstrate the effects of motor learning.

Unisensory and multisensory Self-referential stimulation of the lower limb: An exploratory fMRI study on healthy subjects

BACKGROUND

The holistic view of the person is the essence of the physiotherapy. Knowledge of approaches that develop the whole person promotes better patient outcomes. Multisensory Self-referential stimulation, more than a unisensory one, seems to produce a holistic experience of the Self ("Core-Self").

OBJECTIVES

(1) To analyze the somatotopic brain activation during unisensory and multisensorial Self-referential stimulus; and (2) to understand if the areas activated by multisensorial Self-referential stimulation are the ones responsible for the "Core-Self."

METHODS

An exploratory functional magnetic resonance imaging (fMRI) study was performed with 10 healthy subjects, under the stimulation of the lower limbs with three Self-referential stimuli: unisensory auditory-verbal, unisensory tactile-manual, and multisensory, applying the unisensory stimuli simultaneously.

RESULTS

Unisensory stimulation elicits bilateral activations of the temporoparietal junction (TPJ), of the primary somatosensory cortex (S1), of the primary motor cortex (BA4), of the premotor cortex (BA6) and of BA44; multisensory stimulation also elicits activity in TPJ, BA4, and BA6, and when compared with unisensory stimuli, activations were found in: (1) Cortical and subcortical midline structures-BA7 (precuneus), BA9 (medial prefrontal cortex), BA30 (posterior cingulated), superior colliculum and posterior cerebellum; and (2) Posterior lateral cortex-TPJ, posterior BA13 (insula), BA19, and BA37. Bilateral TPJ is the one that showed the biggest activation volume.

CONCLUSION

This specific multisensory stimulation produces a brain activation map in regions that are responsible for multisensory Self-processing and may represent the Core-Self. We recommend the use of this specific multisensory stimulation as a physiotherapy intervention strategy that might promote the Self-reorganization.

Brain-actuated gait trainer with visual and proprioceptive feedback

OBJECTIVE

Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension.

APPROACH

We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design. A random forest classifier was trained from the offline session and tested online with visual and proprioceptive feedback, respectively. Post-hoc classification was conducted to assess the impact of feedback modalities and learning effect (an improvement over time) on the simulated trial-based performance. Finally, we performed feature analysis to investigate the discriminant power and brain pattern modulations across the subjects.

MAIN RESULTS

(i) For real-time classification, the average accuracy was [Formula: see text]% and [Formula: see text]% for the two online sessions. The results were significantly higher than chance level, demonstrating the feasibility to distinguish between MI of leg extension and flexion. (ii) For post-hoc classification, the performance with proprioceptive feedback ([Formula: see text]%) was significantly better than with visual feedback ([Formula: see text]%), while there was no significant learning effect. (iii) We reported individual discriminate features and brain patterns associated to each feedback modality, which exhibited differences between the two modalities although no general conclusion can be drawn.

SIGNIFICANCE

The study reported a closed-loop brain-controlled gait trainer, as a proof of concept for neurorehabilitation devices. We reported the feasibility of decoding lower-limb movement in an intuitive and natural way. As far as we know, this is the first online study discussing the role of feedback modalities in lower-limb MI decoding. Our results suggest that proprioceptive feedback has an advantage over visual feedback, which could be used to improve robot-assisted strategies for motor training and functional recovery.

Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task

There is currently a void in the scientific literature on the cortical beta oscillatory activity that is associated with the production of leg motor actions. In addition, we have limited data on how these cortical oscillations may progressively change as a function of development. This study began to fill this vast knowledge gap by using high-density magnetoencephalography to quantify the beta cortical oscillatory activity over a cross-section of typically developing children as they performed an isometric knee target matching task. Advanced beamforming methods were used to identify the spatiotemporal changes in beta oscillatory activity during the motor planning and motor action time frames. Our results showed that a widespread beta event-related desynchronization (ERD) was present across the pre/postcentral gyri, supplementary motor area, and the parietal cortices during the motor planning stage. The strength of this beta ERD sharply diminished across this fronto-parietal network as the children initiated the isometric force needed to match the target. Rank order correlations indicated that the older children were more likely to initiate their force production sooner, took less time to match the targets, and tended to have a weaker beta ERD during the motor planning stage. Lastly, we determined that there was a relationship between the child's age and the strength of the beta ERD within the parietal cortices during isometric force production. Altogether our results suggest that there are notable maturational changes during childhood and adolescence in beta cortical oscillatory activity that are associated with the planning and execution of leg motor actions.