Action perception and motor imagery: Mental practice of action

The lateralized effects of Parkinson's Disease on motor imagery: Evidence from mental chronometry

Alterations to the content of action representations may contribute to the movement challenges that characterize Parkinson's Disease (PD). One way to investigate action representations is through motor imagery. As PD motor symptoms typically have a unilateral onset, disease-related deficits related to action representations may follow a similarly lateralized pattern. The present study examined if temporal accuracy of motor imagery in individuals with PD differed according to the side of the body involved in the task. Thirty-eight participants with PD completed a mental chronometry task using their more affected and less affected side. Participants had significantly shorter mental versus physical movement times for the more affected. Higher imagery vividness in the kinaesthetic domain predicted shorter mental versus physical movement times for the more affected side, as did lower imagery vividness in the visual domain and poorer cognitive function. These results indicate that people with PD imagine movements differently when the target actions their more affected versus less affected side. It is additionally possible that side-specific deficits in the accurate processing of kinaesthetic information lead to an increased reliance on visual processes and cognitive resources to successfully execute motor imagery involving the more affected side.

Large-Scale Cortical Network Analysis and Classification of MI-BCI Tasks Based on Bayesian Nonnegative Matrix Factorization

Motor imagery (MI) is a high-level cognitive process that has been widely applied to clinical rehabilitation and brain-computer interfaces (BCIs). However, the decoding of MI tasks still faces challenges, and the neural mechanisms underlying its application are unclear, which seriously hinders the development of MI-based clinical applications and BCIs. Here, we combined EEG source reconstruction and Bayesian nonnegative matrix factorization (NMF) methods to construct large-scale cortical networks of left-hand and right-hand MI tasks. Compared to right-hand MI, the results showed that the significantly increased functional network connectivities (FNCs) mainly located among the visual network (VN), sensorimotor network (SMN), right temporal network, right central executive network, and right parietal network in the left-hand MI at the β (13-30Hz) and all (8-30Hz) frequency bands. For the network properties analysis, we found that the clustering coefficient, global efficiency, and local efficiency were significantly increased and characteristic path length was significantly decreased in left-hand MI compared to right-hand MI at the β and all frequency bands. These network pattern differences indicated that the left-hand MI may need more modulation of multiple large-scale networks (i.e., VN and SMN) mainly located in the right hemisphere. Finally, based on the spatial pattern network of FNC and network properties, we propose a classification model. The proposed model achieves a top classification accuracy of 78.2% in cross-subject two-class MI-BCI tasks. Overall, our findings provide new insights into the neural mechanisms of MI and a potential network biomarker to identify MI-BCI tasks.

Motor cortex activation during visuomotor transformations: evoked potentials during overt and imagined movements

Despite the prevalence of visuomotor transformations in our motor skills, their mechanisms remain incompletely understood, especially when imagery actions are considered such as mentally picking up a cup or pressing a button. Here, we used a stimulus-response task to directly compare the visuomotor transformation underlying overt and imagined button presses. Electroencephalographic activity was recorded while participants responded to highlights of the target button while ignoring the second, non-target button. Movement-related potentials (MRPs) and event-related desynchronization occurred for both overt movements and motor imagery (MI), with responses present even for non-target stimuli. Consistent with the activity accumulation model where visual stimuli are evaluated and transformed into the eventual motor response, the timing of MRPs matched the response time on individual trials. Activity-accumulation patterns were observed for MI, as well. Yet, unlike overt movements, MI-related MRPs were not lateralized, which appears to be a neural marker for the distinction between generating a mental image and transforming it into an overt action. Top-down response strategies governing this hemispheric specificity should be accounted for in future research on MI, including basic studies and medical practice.

Rehabilitation Training after Spinal Cord Injury Affects Brain Structure and Function: From Mechanisms to Methods

Spinal cord injury (SCI) is a serious neurological insult that disrupts the ascending and descending neural pathways between the peripheral nerves and the brain, leading to not only functional deficits in the injured area and below the level of the lesion but also morphological, structural, and functional reorganization of the brain. These changes introduce new challenges and uncertainties into the treatment of SCI. Rehabilitation training, a clinical intervention designed to promote functional recovery after spinal cord and brain injuries, has been reported to promote activation and functional reorganization of the cerebral cortex through multiple physiological mechanisms. In this review, we evaluate the potential mechanisms of exercise that affect the brain structure and function, as well as the rehabilitation training process for the brain after SCI. Additionally, we compare and discuss the principles, effects, and future directions of several rehabilitation training methods that facilitate cerebral cortex activation and recovery after SCI. Understanding the regulatory role of rehabilitation training at the supraspinal center is of great significance for clinicians to develop SCI treatment strategies and optimize rehabilitation plans.

Hands off, brain off? A meta-analysis of neuroimaging data during active and passive driving

BACKGROUND

Car driving is more and more automated, to such an extent that driving without active steering control is becoming a reality. Although active driving requires the use of visual information to guide actions (i.e., steering the vehicle), passive driving only requires looking at the driving scene without any need to act (i.e., the human is passively driven).

MATERIALS & METHODS

After a careful search of the scientific literature, 11 different studies, providing 17 contrasts, were used to run a comprehensive meta-analysis contrasting active driving with passive driving.

RESULTS

Two brain regions were recruited more consistently for active driving compared to passive driving, the left precentral gyrus (BA3 and BA4) and the left postcentral gyrus (BA4 and BA3/40), whereas a set of brain regions was recruited more consistently in passive driving compared to active driving: the left middle frontal gyrus (BA6), the right anterior lobe and the left posterior lobe of the cerebellum, the right sub-lobar thalamus, the right anterior prefrontal cortex (BA10), the right inferior occipital gyrus (BA17/18/19), the right inferior temporal gyrus (BA37), and the left cuneus (BA17).

DISCUSSION

From a theoretical perspective, these findings support the idea that the output requirement of the visual scanning process engaged for the same activity can trigger different cerebral pathways, associated with different cognitive processes. A dorsal stream dominance was found during active driving, whereas a ventral stream dominance was obtained during passive driving. From a practical perspective, and contrary to the dominant position in the Human Factors community, our findings support the idea that a transition from passive to active driving would remain challenging as passive and active driving engage distinct neural networks.

Evidence of motor imagery for lower limb motor function recovery after stroke: A systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

To systematically evaluate the efficacy of motor imagery (MI) on lower limb function in patients with stroke based on the existing clinical studies.

METHODS

Eight databases were searched up from the establishment of database to November 2022 to identify eligible studies. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 2 researchers used the Cochrane Systematic Review manual to independently cross-check the quality of the included literature and extract valid data. The RevMan 5.3 statistical software was used to obtain the meta-analysis, through the mean difference (MD) and 95% confidence intervals (CI).

RESULTS

A total of seventeen studies with 939 patients were included in the systematic review. The overall quality of the included studies was moderate. Meta-analysis showed that Fugl-Meyer Assessment of the lower extremity (FMA-LE) (MD = 4.86, 95%CI: 4.31, 5.42, P < .00001), berg balance scale (MD = 6.18, 95%CI: 4.57, 7.78, P < .00001), functional ambulation category (MD = 0.87, 95%CI: 0.41, 1.32, P = .0002), and the Modified Barthel Index (MD = 6.75, 95%CI: 3.23, 10.28, P = .0002) score improved significantly in the MI group compared with the control group.

CONCLUSIONS

Current evidence shows that MI could effectively improve lower limb motor function and activities of daily living in stroke patients. Due to the limitations of the number and quality of the included studies, the above conclusions need to be verified by more high-quality studies.

Neuropsychological Activations and Networks While Performing Visual and Kinesthetic Motor Imagery

This study aimed to answer the questions 'What are the neural networks and mechanisms involved in visual and kinesthetic motor imagery?', and 'Is part of cognitive processing included during visual and kinesthetic motor imagery?' by investigating the neurophysiological networks and activations during visual and kinesthetic motor imagery using motor imagery tasks (golf putting). The experiment was conducted with 19 healthy adults. Functional magnetic resonance imaging (fMRI) was used to examine neural activations and networks during visual and kinesthetic motor imagery using golf putting tasks. The findings of the analysis on cerebral activation patterns based on the two distinct types of motor imagery indicate that the posterior lobe, occipital lobe, and limbic lobe exhibited activation, and the right hemisphere was activated during the process of visual motor imagery. The activation of the temporal lobe and the parietal lobe were observed during the process of kinesthetic motor imagery. This study revealed that visual motor imagery elicited stronger activation in the right frontal lobe, whereas kinesthetic motor imagery resulted in greater activation in the left frontal lobe. It seems that kinesthetic motor imagery activates the primary somatosensory cortex (BA 2), the secondary somatosensory cortex (BA 5 and 7), and the temporal lobe areas and induces human sensibility. The present investigation evinced that the neural network and the regions of the brain that are activated exhibit variability contingent on the category of motor imagery.

Simultaneous multimodal fNIRS-EEG recordings reveal new insights in neural activity during motor execution, observation, and imagery

Motor execution, observation, and imagery are important skills used in motor learning and rehabilitation. The neural mechanisms underlying these cognitive-motor processes are still poorly understood. We used a simultaneous recording of functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) to elucidate the differences in neural activity across three conditions requiring these processes. Additionally, we used a new method called structured sparse multiset Canonical Correlation Analysis (ssmCCA) to fuse the fNIRS and EEG data and determine the brain regions of neural activity consistently detected by both modalities. Unimodal analyses revealed differentiated activation between conditions; however, the activated regions did not fully overlap across the two modalities (fNIRS: left angular gyrus, right supramarginal gyrus, as well as right superior and inferior parietal lobes; EEG: bilateral central, right frontal, and parietal). These discrepancies might be because fNIRS and EEG detect different signals. Using fused fNIRS-EEG data, we consistently found activation over the left inferior parietal lobe, superior marginal gyrus, and post-central gyrus during all three conditions, suggesting that our multimodal approach identifies a shared neural region associated with the Action Observation Network (AON). This study highlights the strengths of using the multimodal fNIRS-EEG fusion technique for studying AON. Neural researchers should consider using the multimodal approach to validate their findings.

Neuropsychological Evidence Underlying Counterclockwise Bias in Running: Electroencephalography and Functional Magnetic Resonance Imaging Studies of Motor Imagery

We aimed to answer the question "why do people run the track counterclockwise (CCW)?" by investigating the neurophysiological differences in clockwise (CW) versus CCW direction using motor imagery. Three experiments were conducted with healthy adults. Electroencephalography (EEG) was used to examine hemispheric asymmetries in the prefrontal, frontal, and central regions during CW and CCW running imagery (n = 40). We also evaluated event-related potential (ERP) N200 and P300 amplitudes and latencies (n = 66) and conducted another experiment using functional magnetic resonance imaging (fMRI) (n = 30). EEG data indicated greater left frontal cortical activation during CCW imagery, whereas right frontal activation was more dominant during CW imagery. The prefrontal and central asymmetries demonstrated greater left prefrontal activation during both CW and CCW imagery, with CCW rotation exhibiting higher, though statistically insignificant, asymmetry scores than CW rotation. As a result of the fMRI experiment, greater activation was found during CW than during CCW running imagery in the brain regions of the left insula, Brodmann area 18, right caudate nucleus, left dorsolateral prefrontal cortex, left superior parietal cortex, and supplementary motor area. In the ERP experiment, no significant differences were found depending on direction. These findings suggest that CCW rotation might be associated with the motivational approach system, behavioral activation, or positive affect. However, CW rotation reflects withdrawal motivation, behavioral inhibition, or negative affect. Furthermore, CW rotation is understood to be associated with neural inefficiency, increased task difficulty, or unfamiliarity.

Motor imagery training to improve language processing: What are the arguments?

Studies showed that motor expertise was found to induce improvement in language processing. Grounded and situated approaches attributed this effect to an underlying automatic simulation of the motor experience elicited by action words, similar to motor imagery (MI), and suggest shared representations of action conceptualization. Interestingly, recent results also suggest that the mental simulation of action by MI training induces motor-system modifications and improves motor performance. Consequently, we hypothesize that, since MI training can induce motor-system modifications, it could be used to reinforce the functional connections between motor and language system, and could thus lead to improved language performance. Here, we explore these potential interactions by reviewing recent fundamental and clinical literature in the action-language and MI domains. We suggested that exploiting the link between action language and MI could open new avenues for complementary language improvement programs. We summarize the current literature to evaluate the rationale behind this novel training and to explore the mechanisms underlying MI and its impact on language performance.

N400 Indexing the Motion Concept Shared by Music and Words

The two event-related potentials (ERP) studies investigated how verbs and nouns were processed in different music priming conditions in order to reveal whether the motion concept via embodiment can be stimulated and evoked across categories. Study 1 (Tasks 1 and 2) tested the processing of verbs (action verbs vs. state verbs) primed by two music types, with tempo changes (accelerating music vs. decelerating music) and without tempo changes (fast music vs. slow music) while Study 2 (Tasks 3 and 4) tested the processing of nouns (animate nouns vs. inanimate nouns) in the same priming condition as adopted in Study 1. During the experiments, participants were required to hear a piece of music prior to judging whether an ensuing word (verb or noun) is semantically congruent with the motion concept conveyed by the music. The results show that in the priming condition of music with tempo changes, state verbs and inanimate nouns elicited larger N400 amplitudes than action verbs and animate nouns, respectively in the anterior regions and anterior to central regions, whereas in the priming condition of music without tempo changes, action verbs elicited larger N400 amplitudes than state verbs and the two categories of nouns revealed no N400 difference, unexpectedly. The interactions between music and words were significant only in Tasks 1, 2, and 3. Taken together, the results demonstrate that firstly, music with tempo changes and music without tempo prime verbs and nouns in different fashions; secondly, action verbs and animate nouns are easier to process than state verbs and inanimate nouns when primed by music with tempo changes due to the shared motion concept across categories; thirdly, bodily experience differentiates between music and words in coding (encoding and decoding) fashion but the motion concept conveyed by the two categories can be subtly extracted on the metaphorical basis, as indicated in the N400 component. Our studies reveal that music tempos can prime different word classes, favoring the notion that embodied motion concept exists across domains and adding evidence to the hypothesis that music and language share the neural mechanism of meaning processing.

The promise of low-tech intervention in a high-tech era: Remodeling pathological brain circuits using behavioral reverse engineering

As an academic pursuit, neuroscience is enjoying a golden age. From a clinical perspective, our field is failing. Conventional 20th century drugs and devices are not well-matched to the heterogeneity, scale, and connectivity of neural circuits that produce aberrant mental states and behavior. Laboratory-based methods for editing neural genomes and sculpting activity patterns are exciting, but their applications for hundreds of millions of people with mental health disorders is uncertain. We argue that mechanisms for regulating adult brain plasticity and remodeling pathological activity are substantially pre-wired, and we suggest new minimally invasive strategies to harness and direct these endogenous systems. Drawing from studies across the neuroscience literature, we describe approaches that identify neural biomarkers more closely linked to upstream causes-rather than downstream consequences-of disordered behavioral states. We highlight the potential for innovation and discovery in reverse engineering approaches that refine bespoke behavioral "agonists" to drive upstream neural biomarkers in normative directions and reduce clinical symptoms for select classes of neuropsychiatric disorders.

Emerging Limb Rehabilitation Therapy After Post-stroke Motor Recovery

Stroke, including hemorrhagic and ischemic stroke, refers to the blood supply disorder in the local brain tissue for various reasons (aneurysm, occlusion, etc.). It leads to regional brain circulation imbalance, neurological complications, limb motor dysfunction, aphasia, and depression. As the second-leading cause of death worldwide, stroke poses a significant threat to human life characterized by high mortality, disability, and recurrence. Therefore, the clinician has to care about the symptoms of stroke patients in the acute stage and formulate an effective postoperative rehabilitation plan to facilitate the recovery in patients. We summarize a novel application and update of the rehabilitation therapy in limb motor rehabilitation of stroke patients to provide a potential future stroke rehabilitation strategy.

Evaluation of classification approaches for distinguishing brain states predictive of episodic memory performance from electroencephalography: Abbreviated Title: Evaluating methods of classifying memory states from EEG

Previous studies have attempted to separate single trial neural responses for events a person is likely to remember from those they are likely to forget using machine learning classification methods. Successful single trial classification holds potential for translation into the clinical realm for real-time detection of memory and other cognitive states to provide real-time interventions (i.e., brain-computer interfaces). However, most of these studies-and classification analyses in general- do not make clear if the chosen methodology is optimally suited for the classification of memory-related brain states. To address this problem, we systematically compared different methods for every step of classification (i.e., feature extraction, feature selection, classifier selection) to investigate which methods work best for decoding episodic memory brain states-the first analysis of its kind. Using an adult lifespan sample EEG dataset collected during performance of an episodic context encoding and retrieval task, we found that no specific feature type (including Common Spatial Pattern (CSP)-based features, mean, variance, correlation, features based on AR model, entropy, phase, and phase synchronization) outperformed others consistently in distinguishing different memory classes. However, extracting all of these feature types consistently outperformed extracting only one type of feature. Additionally, the combination of filtering and sequential forward selection was the optimal method to select the effective features compared to filtering alone or performing no feature selection at all. Moreover, although all classifiers performed at a fairly similar level, LASSO was consistently the highest performing classifier compared to other commonly used options (i.e., naïve Bayes, SVM, and logistic regression) while naïve Bayes was the fastest classifier. Lastly, for multiclass classification (i.e., levels of context memory confidence and context feature perception), generalizing the binary classification using the binary decision tree performed better than the voting or one versus rest method. These methods were shown to outperform alternative approaches for three orthogonal datasets (i.e., EEG working memory, EEG motor imagery, and MEG working memory), supporting their generalizability. Our results provide an optimized methodological process for classifying single-trial neural data and provide important insight and recommendations for a cognitive neuroscientist's ability to make informed choices at all stages of the classification process for predicting memory and other cognitive states.

Improving the Sensitivity of Task-Related Functional Magnetic Resonance Imaging Data Using Generalized Canonical Correlation Analysis

General Linear Modeling (GLM) is the most commonly used method for signal detection in Functional Magnetic Resonance Imaging (fMRI) experiments, despite its main limitation of not taking into consideration common spatial dependencies between voxels. Multivariate analysis methods, such as Generalized Canonical Correlation Analysis (gCCA), have been increasingly employed in fMRI data analysis, due to their ability to overcome this limitation. This study, evaluates the improvement of sensitivity of the GLM, by applying gCCA to fMRI data after standard preprocessing steps. Data from a block-design fMRI experiment was used, where 25 healthy volunteers completed two action observation tasks at 1.5T. Whole brain analysis results indicated that the application of gCCA resulted in significantly higher intensity of activation in several regions in both tasks and helped reveal activation in the primary somatosensory and ventral premotor area, theoretically known to become engaged during action observation. In subject-level ROI analyses, gCCA improved the signal to noise ratio in the averaged timeseries in each preselected ROI, and resulted in increased extent of activation, although peak intensity was considerably higher in just two of them. In conclusion, gCCA is a promising method for improving the sensitivity of conventional statistical modeling in task related fMRI experiments.

A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery based Brain-Computer Interface

The motor imagery (MI) based brain-computer interfaces (BCIs) have been proposed as a potential physical rehabilitation technology. However, the low classification accuracy achievable with MI tasks is still a challenge when building effective BCI systems. We propose a novel MI classification model based on measurement of functional connectivity between brain regions and graph theory. Specifically, motifs describing local network structures in the brain are extracted from functional connectivity graphs. A graph embedding model called Ego-CNNs is then used to build a classifier, which can convert the graph from a structural representation to a fixed-dimensional vector for detecting critical structure in the graph. We validate our proposed method on four datasets, and the results show that our proposed method produces high classification accuracies in two-class classification tasks (92.8% for dataset 1, 93.4% for dataset 2, 96.5% for dataset 3, and 80.2% for dataset 4) and multiclass classification tasks (90.33% for dataset 1). Our proposed method achieves a mean Kappa value of 0.88 across nine participants, which is superior to other methods we compared it to. These results indicate that there is a local structural difference in functional connectivity graphs extracted under different motor imagery tasks. Our proposed method has great potential for motor imagery classification in future studies.

A comparison of directed functional connectivity among fist-related brain activities during movement imagery, movement execution, and movement observation

Brain-computer interface (BCI) has been widely used in sports training and rehabilitation training. It is primarily based on action simulation, including movement imagery (MI) and movement observation (MO). However, the development of BCI technology is limited due to the challenge of getting an in-depth understanding of brain networks involved in MI, MO, and movement execution (ME). To better understand the brain activity changes and the communications across various brain regions under MO, ME, and MI, this study conducted the fist experiment under MO, ME, and MI. We recorded 64-channel electroencephalography (EEG) from 39 healthy subjects (25 males, 14 females, all right-handed) during fist tasks, obtained intensities and locations of sources using EEG source imaging (ESI), computed source activation modes, and finally investigated the brain networks using spectral Granger causality (GC). The brain regions involved in the three motor conditions are similar, but the degree of participation of each brain region and the network connections among the brain regions are different. MO, ME, and MI did not recruit shared brain connectivity networks. In addition, both source activation modes and brain network connectivity had lateralization advantages.

Motor Imagery of Walking in People Living with and without Multiple Sclerosis: A Cross-Sectional Comparison of Mental Chronometry

Motor imagery represents the ability to simulate anticipated movements mentally prior to their actual execution and has been proposed as a tool to assess both individuals’ perception of task difficulty as well as their perception of their own abilities. People with multiple sclerosis (pwMS) often present with motor and cognitive dysfunction, which may negatively affect motor imagery. In this cross-sectional study, we explored differences in motor imagery of walking performance between pwMS (n = 20, age = 57.1 (SD = 8.6) years, 55% female) and age- and sex-matched healthy controls (n = 20, age = 58.1 (SD = 7.0) years, 60% female). Participants underwent mental chronometry assessments, a subset of motor imagery, which evaluated the difference between imagined and actual walking times across four walking tasks of increasing difficulty (i.e., large/narrow-width walkway with/without obstacles). Raw and absolute mental chronometry (A-MC) measures were recorded in single- (ST) and dual-task (DT) conditions. In ST conditions, pwMS had higher A-MC scores across all walking conditions (p ≤ 0.031, η² ≥ 0.119), indicating lower motor imagery ability compared to healthy controls. During DT, all participants tended to underestimate their walking ability (3.38 ± 6.72 to 5.63 ± 9.17 s). However, after physical practice, pwMS were less able to adjust their imagined walking performance compared to healthy controls. In pwMS, A-MC scores were correlated with measures of balance confidence (ρ = −0.629, p < 0.01) and the self-reported expanded disability status scale (ρ = 0.747, p < 0.01). While the current study revealed that pwMS have lower motor imagery of walking performance compared to healthy individuals, further work is necessary to examine how the disassociation between mental chronometry and actual performance relates to quality of life and well-being.

Functional Imaging of the Cerebellum during Action Execution and Observation

We employed the ¹⁴C-deoxyglucose autoradiographic method to map the activity in the cerebellar cortex of rhesus monkeys that performed forelimb movements either in the light or in the dark and of monkeys that observed forelimb movements executed by a human experimenter. The execution of forelimb movements, both in the light and in the dark, activated the forelimb representations in the cerebellar hemispheric extensions of 1) vermian lobules IV-VI and 2) vermian lobule VIIIB, ipsilaterally to the moving forelimb. Activations in the former forelimb representation involved both a paravermal and a lateral hemispheric region. Also, Crus II posterior in the ansiform lobule (the hemispheric expansion of lobule VIIB) was activated bilaterally by execution of movements in the light but not in the dark. Action observation activated the lateral-most region of the forelimb representation in the lateral hemispheric extension of vermian lobules IV-VI, as well as the crus II posterior, bilaterally. Our results demonstrate that the cerebellar cortex, in addition to its involvement in the generation of movement, is also recruited in the perception of observed movements. Moreover, our findings suggest a modularity gradient in the primate cerebellar cortex, which progresses from unimodal (medially) to multimodal (laterally) functional areas.

Cerebral hemodynamic response during a live action-observation and action-execution task: A fNIRS study

Although many studies have examined the location of the action observation network (AON) in human adults, the shared neural correlates of action-observation and action-execution are still unclear partially due to lack of ecologically valid neuroimaging measures. In this study, we aim to demonstrate the feasibility of using functional near infrared spectroscopy (fNIRS) to measure the neural correlates of action-observation and action execution regions during a live task. Thirty adults reached for objects or observed an experimenter reaching for objects while their cerebral hemodynamic responses including oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) were recorded in the sensorimotor and parietal regions. Our results indicated that the parietal regions, including bilateral superior parietal lobule (SPL), bilateral inferior parietal lobule (IPL), right supra-marginal region (SMG) and right angular gyrus (AG) share neural activity during action-observation and action-execution. Our findings confirm the applicability of fNIRS for the study of the AON and lay the foundation for future work with developmental and clinical populations.

Action Observation Responses Are Influenced by Movement Kinematics and Target Identity

In order to inform the debate whether cortical areas related to action observation provide a pragmatic or a semantic representation of goal-directed actions, we performed 2 functional magnetic resonance imaging (fMRI) experiments in humans. The first experiment, involving observation of aimless arm movements, resulted in activation of most of the components known to support action execution and action observation. Given the absence of a target/goal in this experiment and the activation of parieto-premotor cortical areas, which were associated in the past with direction, amplitude, and velocity of movement of biological effectors, our findings suggest that during action observation we could be monitoring movement kinematics. With the second, double dissociation fMRI experiment, we revealed the components of the observation-related cortical network affected by 1) actions that have the same target/goal but different reaching and grasping kinematics and 2) actions that have very similar kinematics but different targets/goals. We found that certain areas related to action observation, including the mirror neuron ones, are informed about movement kinematics and/or target identity, hence providing a pragmatic rather than a semantic representation of goal-directed actions. Overall, our findings support a process-driven simulation-like mechanism of action understanding, in agreement with the theory of motor cognition, and question motor theories of action concept processing.

Characterizing the Action-Observation Network Through Functional Near-Infrared Spectroscopy: A Review

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that has undergone tremendous growth over the last decade due to methodological advantages over other measures of brain activation. The action-observation network (AON), a system of brain structures proposed to have “mirroring” abilities (e.g., active when an individual completes an action or when they observe another complete that action), has been studied in humans through neural measures such as fMRI and electroencephalogram (EEG); however, limitations of these methods are problematic for AON paradigms. For this reason, fNIRS is proposed as a solution to investigating the AON in humans. The present review article briefly summarizes previous neural findings in the AON and examines the state of AON research using fNIRS in adults. A total of 14 fNIRS articles are discussed, paying particular attention to methodological choices and considerations while summarizing the general findings to aid in developing better protocols to study the AON through fNIRS. Additionally, future directions of this work are discussed, specifically in relation to researching AON development and potential multimodal imaging applications.

Why brain-controlled neuroprosthetics matter: mechanisms underlying electrical stimulation of muscles and nerves in rehabilitation

Delivering short trains of electric pulses to the muscles and nerves can elicit action potentials resulting in muscle contractions. When the stimulations are sequenced to generate functional movements, such as grasping or walking, the application is referred to as functional electrical stimulation (FES). Implications of the motor and sensory recruitment of muscles using FES go beyond simple contraction of muscles. Evidence suggests that FES can induce short- and long-term neurophysiological changes in the central nervous system by varying the stimulation parameters and delivery methods. By taking advantage of this, FES has been used to restore voluntary movement in individuals with neurological injuries with a technique called FES therapy (FEST). However, long-lasting cortical re-organization (neuroplasticity) depends on the ability to synchronize the descending (voluntary) commands and the successful execution of the intended task using a FES. Brain-computer interface (BCI) technologies offer a way to synchronize cortical commands and movements generated by FES, which can be advantageous for inducing neuroplasticity. Therefore, the aim of this review paper is to discuss the neurophysiological mechanisms of electrical stimulation of muscles and nerves and how BCI-controlled FES can be used in rehabilitation to improve motor function.

Phase dependent modulation of cortical activity during action observation and motor imagery of walking: An EEG study

Action observation (AO) and motor imagery (MI) are motor simulations which induce cortical activity related to execution of observed and imagined movements. Neuroimaging studies have mainly investigated where the cortical activities during AO and MI of movements are activated and if they match those activated during execution of the movements. However, it remains unclear how cortical activity is modulated; in particular, whether activity depends on observed or imagined phases of movements. We have previously examined the neural mechanisms underlying AO and MI of walking, focusing on the combined effect of AO with MI (AO+MI) and phase dependent modulation of corticospinal and spinal reflex excitability. Here, as a continuation of our previous studies, we investigated cortical activity depending on gait phases during AO and AO+MI of walking by using electroencephalography (EEG); 64-channel EEG signals were recorded in which participants observed walking with or without imagining it, respectively. EEG source and spectral analyses showed that, in the sensorimotor cortex during AO+MI and AO, the alpha and beta power were decreased, and power spectral modulations depended on walking phases. The phase dependent modulations during AO+MI, but not during AO, were like those which occur during actual walking as reported by previous walking studies. These results suggest that combinatory effects of AO+MI could induce parts of the phase dependent activation of the sensorimotor cortex during walking even without any movements. These findings would extend understanding of the neural mechanisms underlying walking and cognitive motor processes and provide clinically beneficial information towards rehabilitation for patients with neurological gait dysfunctions.

Proactive gaze is present during biological and non-biological motion observation

Others' action observation activates in the observer a coordinated hand-eye motor program, covert for the hand (i.e. motor resonance), and overt for the eye (i.e. proactive gaze), similar to that of the observed agent. The biological motion hypothesis of action anticipation claims that proactive gaze occurs only in the presence of biological motion, and that kinematic information is sufficient to determine the anticipation process. The results of the present study did not support the biological motion hypothesis of action anticipation. Specifically, proactive gaze was present during observation of both a biological accelerated-decelerated motion and a non-biological constant velocity motion (Experiment 1), in the presence of a barrier able to restrict differences between the two kinematics to the motion profile of individual markers prior to contact (Experiment 2), but only if an object was present at the end point of the movement trajectory (Experiment 3). Furthermore, proactive gaze was found independently of the presence of end effects temporally congruent with the instant in which the movement stopped (Experiments 4, and 5). We propose that the involvement of the observer's motor system is not restricted to when the agent moves with natural kinematics, and it is mandatory whenever the presence of an agent or a goal is evident, regardless of physical appearance, natural kinematics, and the possibility to identify the action behind the stimulus.

Towards a conscious model of consciousness

Several thousand years ago, our human ancestors realized that the brain was the organ of the mind and movement. But, how does the brain generate a voluntary movement and adds consciousness to it? Here, we assume that these two processes can be explained by neuroscience, but a large proportion of our society -including some scientists- considers consciousness as some immaterial substance that dwells in our body. As consequence of these divided opinions, several theories have recently emerged with the aim of explaining consciousness. These theories in no order of importance, but definitely in the order of complexity, are the global workspace (GWT), attention schema (AST), higher order-thought (HOT) and illusionist (IT) theories. All these theories originate from different backgrounds, and each tries to explain different components of consciousness: from a pure neurobiological (GWT) interpretation to a pure psychological-folk interpretation (IT).

Neuromuscular electrical stimulation-promoted plasticity of the human brain

The application of neuromuscular electrical stimulation (NMES) to paretic limbs has demonstrated utility for motor rehabilitation following brain injury. When NMES is delivered to a mixed peripheral nerve, typically both efferent and afferent fibres are recruited. Muscle contractions brought about by the excitation of motor neurons are often used to compensate for disability by assisting actions such as the formation of hand aperture, or by preventing others including foot drop. In this context, exogenous stimulation provides a direct substitute for endogenous neural drive. The goal of the present narrative review is to describe the means through which NMES may also promote sustained adaptations within central motor pathways, leading ultimately to increases in (intrinsic) functional capacity. There is an obvious practical motivation, in that detailed knowledge concerning the mechanisms of adaptation has the potential to inform neurorehabilitation practice. In addition, responses to NMES provide a means of studying CNS plasticity at a systems level in humans. We summarize the fundamental aspects of NMES, focusing on the forms that are employed most commonly in clinical and experimental practice. Specific attention is devoted to adjuvant techniques that further promote adaptive responses to NMES thereby offering the prospect of increased therapeutic potential. The emergent theme is that an association with centrally initiated neural activity, whether this is generated in the context of NMES triggered by efferent drive or via indirect methods such as mental imagery, may in some circumstances promote the physiological changes that can be induced through peripheral electrical stimulation.