Does Motor Simulation Theory Explain the Cognitive Mechanisms Underlying Motor Imagery? A Critical Review

Neural correlates of motor imagery and execution in real-world dynamic behavior: evidence for similarities and differences

A large body of evidence shows that motor imagery and action execution behaviors result from overlapping neural substrates, even in the absence of overt movement during motor imagery. To date it is unclear how neural activations in motor imagery and execution compare for naturalistic whole-body movements, such as walking. Neuroimaging studies have not directly compared imagery and execution during dynamic walking movements. Here we recorded brain activation with mobile EEG during walking compared to during imagery of walking, with mental counting as a control condition. We asked 24 healthy participants to either walk six steps on a path, imagine taking six steps, or mentally count from one to six. We found beta and alpha power modulation during motor imagery resembling action execution patterns; a correspondence not found performing the control task of mental counting. Neural overlap occurred early in the execution and imagery walking actions, suggesting activation of shared action representations. Remarkably, a distinctive walking-related beta rebound occurred both during action execution and imagery at the end of the action suggesting that, like actual walking, motor imagery involves resetting or inhibition of motor processes. However, we also found that motor imagery elicits a distinct pattern of more distributed beta activity, especially at the beginning of the task. These results indicate that motor imagery and execution of naturalistic walking involve shared motor-cognitive activations, but that motor imagery requires additional cortical resources.

Inequivalent and uncorrelated response priming in motor imagery and execution

Introduction

Theoretical considerations on motor imagery and motor execution have long been dominated by the functional equivalence view. Previous empirical works comparing these two modes of actions, however, have largely relied on subjective judgments on the imagery process, which may be exposed to various biases. The current study aims to re-examine the commonality and distinguishable aspects of motor imagery and execution via a response repetition paradigm. This framework aims to offer an alternative approach devoid of self-reporting, opening the opportunity for less subjective evaluation of the disparities and correlations between motor imagery and motor execution.

Methods

Participants performed manual speeded-choice on prime-probe pairs in each trial under three conditions distinguished by the modes of response on the prime: mere observation (Perceptual), imagining response (Imagery), and actual responses (Execution). Responses to the following probe were all actual execution of button press. While Experiment 1 compared the basic repetition effects in the three prime conditions, Experiment 2 extended the prime duration to enhance the quality of MI and monitored electromyography (EMG) for excluding prime imagery with muscle activities to enhance specificity of the underlying mechanism.

Results

In Experiment 1, there was no significant repetition effect after mere observation. However, significant repetition effects were observed in both imagery and execution conditions, respectively, which were also significantly correlated. In Experiment 2, trials with excessive EMG activities were excluded before further statistical analysis. A consistent repetition effect pattern in both Imagery and Execution but not the Perception condition. Now the correlation between Imagery and Execution conditions were not significant.

Conclusion

Findings from the current study provide a novel application of a classical paradigm, aiming to minimize the subjectivity inherent in imagery assessments while examining the relationship between motor imagery and motor execution. By highlighting differences and the absence of correlation in repetition effects, the study challenges the functional equivalence hypothesis of imagery and execution. Motor representations of imagery and execution, when measured without subjective judgments, appear to be more distinguishable than traditionally thought. Future studies may examine the neural underpinnings of the response repetition paradigm to further elucidating the common and separable aspects of these two modes of action.

Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents

The trend in industrial/service robotics is to develop robots that can cooperate with people, interacting with them in an autonomous, safe and purposive way. These are the fundamental elements characterizing the fourth and the fifth industrial revolutions (4IR, 5IR): the crucial innovation is the adoption of intelligent technologies that can allow the development of cyber-physical systems, similar if not superior to humans. The common wisdom is that intelligence might be provided by AI (Artificial Intelligence), a claim that is supported more by media coverage and commercial interests than by solid scientific evidence. AI is currently conceived in a quite broad sense, encompassing LLMs and a lot of other things, without any unifying principle, but self-motivating for the success in various areas. The current view of AI robotics mostly follows a purely disembodied approach that is consistent with the old-fashioned, Cartesian mind-body dualism, reflected in the software-hardware distinction inherent to the von Neumann computing architecture. The working hypothesis of this position paper is that the road to the next generation of autonomous robotic agents with cognitive capabilities requires a fully brain-inspired, embodied cognitive approach that avoids the trap of mind-body dualism and aims at the full integration of Bodyware and Cogniware. We name this approach Artificial Cognition (ACo) and ground it in Cognitive Neuroscience. It is specifically focused on proactive knowledge acquisition based on bidirectional human-robot interaction: the practical advantage is to enhance generalization and explainability. Moreover, we believe that a brain-inspired network of interactions is necessary for allowing humans to cooperate with artificial cognitive agents, building a growing level of personal trust and reciprocal accountability: this is clearly missing, although actively sought, in current AI. The ACo approach is a work in progress that can take advantage of a number of research threads, some of them antecedent the early attempts to define AI concepts and methods. In the rest of the paper we will consider some of the building blocks that need to be re-visited in a unitary framework: the principles of developmental robotics, the methods of action representation with prospection capabilities, and the crucial role of social interaction.

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.

Visualizing Compassion: Episodic Simulation as Contemplative Practice

Contemplative interventions designed to cultivate compassion are receiving increasing empirical attention. Accumulating evidence suggests that these interventions bolster prosocial motivation and warmth towards others. Less is known about how these practices impact compassion in everyday life. Here we consider one mechanistic pathway through which compassion practices may impact perception and action in the world: simulation. Evidence suggests that vividly imagining a situation simulates that experience in the brain as if it were, to a degree, actually happening. Thus, we hypothesize that simulation during imagery-based contemplative practices can construct sensorimotor patterns in the brain that prime an individual to act compassionately in the world. We first present evidence across multiple literatures in Psychology that motivates this hypothesis, including the neuroscience of mental imagery and the emerging literature on prosocial episodic simulation. Then, we examine the specific contemplative practices in compassion-based interventions that may construct such simulations. We conclude with future directions for investigating how compassion-based interventions may shape prosocial perception and action in everyday life.

Review of public motor imagery and execution datasets in brain-computer interfaces

The demand for public datasets has increased as data-driven methodologies have been introduced in the field of brain-computer interfaces (BCIs). Indeed, many BCI datasets are available in various platforms or repositories on the web, and the studies that have employed these datasets appear to be increasing. Motor imagery is one of the significant control paradigms in the BCI field, and many datasets related to motor tasks are open to the public already. However, to the best of our knowledge, these studies have yet to investigate and evaluate the datasets, although data quality is essential for reliable results and the design of subject- or system-independent BCIs. In this study, we conducted a thorough investigation of motor imagery/execution EEG datasets recorded from healthy participants published over the past 13 years. The 25 datasets were collected from six repositories and subjected to a meta-analysis. In particular, we reviewed the specifications of the recording settings and experimental design, and evaluated the data quality measured by classification accuracy from standard algorithms such as Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) for comparison and compatibility across the datasets. As a result, we found that various stimulation types, such as text, figure, or arrow, were used to instruct subjects what to imagine and the length of each trial also differed, ranging from 2.5 to 29 s with a mean of 9.8 s. Typically, each trial consisted of multiple sections: pre-rest (2.38 s), imagination ready (1.64 s), imagination (4.26 s, ranging from 1 to 10 s), the post-rest (3.38 s). In a meta-analysis of the total of 861 sessions from all datasets, the mean classification accuracy of the two-class (left-hand vs. right-hand motor imagery) problem was 66.53%, and the population of the BCI poor performers, those who are unable to reach proficiency in using a BCI system, was 36.27% according to the estimated accuracy distribution. Further, we analyzed the CSP features and found that each dataset forms a cluster, and some datasets overlap in the feature space, indicating a greater similarity among them. Finally, we checked the minimal essential information (continuous signals, event type/latency, and channel information) that should be included in the datasets for convenient use, and found that only 71% of the datasets met those criteria. Our attempts to evaluate and compare the public datasets are timely, and these results will contribute to understanding the dataset's quality and recording settings as well as the use of using public datasets for future work on BCIs.

Enhancing upper-limb neurorehabilitation in chronic stroke survivors using combined action observation and motor imagery therapy

Introduction

For people who have had a stroke, recovering upper-limb function is a barrier to independence. When movement is difficult, mental practice can be used to complement physical therapy. In this within-participants study we investigated the effects of combined action observation and motor imagery (AO + MI) therapy on upper-limb recovery in chronic stroke survivors.

Methods

A Graeco-Latin Square design was used to counterbalance four mental practice conditions (AO + MI, AO, MI, Control) across four cup-stacking tasks of increasing complexity. Once a week, for five consecutive weeks, participants (n = 10) performed 16 mental practice trials under each condition. Each trial displayed a 1st person perspective of a cup-stacking task performed by an experienced model. For AO, participants watched each video and responded to an occasional color cue. For MI, participants imagined the effort and sensation of performing the action; cued by a series of still-images. For combined AO + MI, participants observed a video of the action while they simultaneously imagined performing the same action in real-time. At three time points (baseline; post-test; two-week retention test) participants physically executed the three mentally practiced cup-stacking tasks, plus a fourth unpractised sequence (Control), as quickly and accurately as possible.

Results

Mean movement execution times were significantly reduced overall in the post-test and the retention test compared to baseline. At retention, movement execution times were significantly shorter for combined AO + MI compared to both MI and the Control. Individual participants reported clinically important changes in quality of life (Stroke Impact Scale) and positive qualitative experiences of AO + MI (social validation).

Discussion

These results indicate that when physical practice is unsuitable, combined AO + MI therapy could offer an effective adjunct for neurorehabilitation in chronic stroke survivors.

TMS over dorsolateral prefrontal cortex affects the timing of motor imagery but not overt action: Further support for the motor-cognitive model

The Motor-Cognitive model suggests a functional dissociation between motor imagery and overt action, in contrast to the Functional Equivalence view of common processes between the two behaviours. According to the Motor-Cognitive model, motor imagery differs from overt action primarily through the use of executive resources to monitor and elaborate a motor image during execution, which can result in a lack of correspondence between motor imagery and its overt action counterpart. The present study examined the importance of executive resources in motor imagery by using TMS to impair the function of the dorsolateral prefrontal cortex while measuring the time to complete imagined versus overt actions. In two experiments, TMS over the dorsolateral prefrontal cortex slowed motor imagery but did not affect overt actions. TMS over the same region also interfered with performance of a mental calculation task, though it did not reliably affect less demanding cognitive tasks also thought to rely on executive functions. Taken together, these results were consistent with the Motor-Cognitive model but not with the idea of functional equivalence. The implications of these results for the theoretical understanding of motor imagery, and potential applications of the Motor-Cognitive model to the use of motor imagery in training and rehabilitation, are discussed.

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.

Enhancing motor imagery practice using synchronous action observation

In this paper, we discuss a variety of ways in which practising motor actions by means of motor imagery (MI) can be enhanced via synchronous action observation (AO), that is, by AO + MI. We review the available research on the (mostly facilitatory) behavioural effects of AO + MI practice in the early stages of skill acquisition, discuss possible theoretical explanations, and consider several issues related to the choice and presentation schedules of suitable models. We then discuss considerations related to AO + MI practice at advanced skill levels, including expertise effects, practical recommendations such as focussing attention on specific aspects of the observed action, using just-ahead models, and possible effects of the perspective in which the observed action is presented. In section "Coordinative AO + MI", we consider scenarios where the observer imagines performing an action that complements or responds to the observed action, as a promising and yet under-researched application of AO + MI training. In section "The dual action simulation hypothesis of AO + MI", we review the neurocognitive hypothesis that AO + MI practice involves two parallel action simulations, and we consider opportunities for future research based on recent neuroimaging work on parallel motor representations. In section "AO + MI training in motor rehabilitation", we review applications of AO, MI, and AO + MI training in the field of neurorehabilitation. Taken together, this evidence-based, exploratory review opens a variety of avenues for future research and applications of AO + MI practice, highlighting several clear advantages over the approaches of purely AO- or MI-based practice.

Imagining the way forward: A review of contemporary motor imagery theory

Over the past few decades, researchers have become interested in the mechanisms behind motor imagery (i.e., the mental rehearsal of action). During this time several theories of motor imagery have been proposed, offering diverging accounts of the processes responsible for motor imagery and its neural overlap with movement. In this review, we summarize the core claims of five contemporary theories of motor imagery: motor simulation theory, motor emulation theory, the motor-cognitive model, the perceptual-cognitive model, and the effects imagery model. Afterwards, we identify the key testable differences between them as well as their various points of overlap. Finally, we discuss potential future directions for theories of motor imagery.

Why motor imagery is not really motoric: towards a re-conceptualization in terms of effect-based action control

Overt and imagined action seem inextricably linked. Both have similar timing, activate shared brain circuits, and motor imagery influences overt action and vice versa. Motor imagery is, therefore, often assumed to recruit the same motor processes that govern action execution, and which allow one to play through or simulate actions offline. Here, we advance a very different conceptualization. Accordingly, the links between imagery and overt action do not arise because action imagery is intrinsically motoric, but because action planning is intrinsically imaginistic and occurs in terms of the perceptual effects one want to achieve. Seen like this, the term 'motor imagery' is a misnomer of what is more appropriately portrayed as 'effect imagery'. In this article, we review the long-standing arguments for effect-based accounts of action, which are often ignored in motor imagery research. We show that such views provide a straightforward account of motor imagery. We review the evidence for imagery-execution overlaps through this new lens and argue that they indeed emerge because every action we execute is planned, initiated and controlled through an imagery-like process. We highlight findings that this new view can now explain and point out open questions.

Mapping relational links between motor imagery, action observation, action-related language, and action execution

Actions can be physically executed, observed, imagined, or simply thought about. Unifying mental processes, such as simulation, emulation, or predictive processing, are thought to underlie different action types, whether they are mental states, as in the case of motor imagery and action observation, or involve physical execution. While overlapping brain activity is typically observed across different actions which indicates commonalities, research interest is also concerned with investigating the distinct functional components of these action types. Unfortunately, untangling subtleties associated with the neurocognitive bases of different action types is a complex endeavour due to the high dimensional nature of their neural substrate (e.g., any action process is likely to activate multiple brain regions thereby having multiple dimensions to consider when comparing across them). This has impeded progress in action-related theorising and application. The present study addresses this challenge by using the novel approach of multidimensional modeling to reduce the high-dimensional neural substrate of four action-related behaviours (motor imagery, action observation, action-related language, and action execution), find the least number of dimensions that distinguish or relate these action types, and characterise their neurocognitive relational links. Data for the model comprised brain activations for action types from whole-brain analyses reported in 53 published articles. Eighty-two dimensions (i.e., 82 brain regions) for the action types were reduced to a three-dimensional model, that mapped action types in ordination space where the greater the distance between the action types, the more dissimilar they are. A series of one-way ANOVAs and post-hoc comparisons performed on the mean coordinates for each action type in the model showed that across all action types, action execution and concurrent action observation (AO)-motor imagery (MI) were most neurocognitively similar, while action execution and AO were most dissimilar. Most action types were similar on at least one neurocognitive dimension, the exception to this being action-related language. The import of the findings are discussed in terms of future research and implications for application.

Sources of independent mu components reveal different brain areas involved in motor imagery, motor execution, and movement observation

To answer the question of whether the same brain circuit(s) facilitates motor imagery (MI), motor execution (ME), and movement observation (MO), we conducted electroencephalography (EEG) experiment combining the three motor conditions in the same experimental runs. The EEG data were analyzed using two different independent component analysis (ICA) decomposition approaches: a single ICA decomposition on all EEG data combined and separate ICA decomposition on the EEG data obtained from the separate conditions. The results indicated that the separate ICA approach may provide a better fit to the EEG data obtained from the separate conditions to deliver specific independent right mu components with distinct topographies for each of the motor conditions. The topography of the MI condition covered the brain regions posterior to the central sulcus (P4 EEG channel); the ME condition covered the brain regions anterior to the central sulcus (C4 EEG channel), and the MO condition had broader coverage with the main activation in the premotor region (CP4 EEG channel). The source localization results also exhibited significant differences among the motor conditions. In addition, the result of single ICA decomposition resembled the result of separate ICA decomposition on the EEG data of ME with similar topographies and closely located EEG sources. This finding may further indicate that the result of single ICA decomposition may be dominated by the ME motor condition because it manifests higher data variance than the other two motor conditions.

Hand constraint reduces brain activity and affects the speed of verbal responses on semantic tasks

According to the theory of embodied cognition, semantic processing is closely coupled with body movements. For example, constraining hand movements inhibits memory for objects that can be manipulated with the hands. However, it has not been confirmed whether body constraint reduces brain activity related to semantics. We measured the effect of hand constraint on semantic processing in the parietal lobe using functional near-infrared spectroscopy. A pair of words representing the names of hand-manipulable (e.g., cup or pencil) or nonmanipulable (e.g., windmill or fountain) objects were presented, and participants were asked to identify which object was larger. The reaction time (RT) in the judgment task and the activation of the left intraparietal sulcus (LIPS) and left inferior parietal lobule (LIPL), including the supramarginal gyrus and angular gyrus, were analyzed. We found that constraint of hand movement suppressed brain activity in the LIPS toward hand-manipulable objects and affected RT in the size judgment task. These results indicate that body constraint reduces the activity of brain regions involved in semantics. Hand constraint might inhibit motor simulation, which, in turn, would inhibit body-related semantic processing.

Kinesthetic motor-imagery training improves performance on lexical-semantic access

The objective of this study was to evaluate the effect of Motor Imagery (MI) training on language comprehension. In line with literature suggesting an intimate relationship between the language and the motor system, we proposed that a MI-training could improve language comprehension by facilitating lexico-semantic access. In two experiments, participants were assigned to a kinesthetic motor-imagery training (KMI) group, in which they had to imagine making upper-limb movements, or to a static visual imagery training (SVI) group, in which they had to mentally visualize pictures of landscapes. Differential impacts of both training protocols on two different language comprehension tasks (i.e., semantic categorization and sentence-picture matching task) were investigated. Experiment 1 showed that KMI training can induce better performance (shorter reaction times) than SVI training for the two language comprehension tasks, thus suggesting that a KMI-based motor activation can facilitate lexico-semantic access after only one training session. Experiment 2 aimed at replicating these results using a pre/post-training language assessment and a longer training period (four training sessions spread over four days). Although the improvement magnitude between pre- and post-training sessions was greater in the KMI group than in the SVI one on the semantic categorization task, the sentence-picture matching task tended to provide an opposite pattern of results. Overall, this series of experiments highlights for the first time that motor imagery can contribute to the improvement of lexical-semantic processing and could open new avenues on rehabilitation methods for language deficits.

Effectiveness of mental simulation practices after total knee arthroplasty in patients with knee osteoarthritis: A systematic review and meta-analysis of randomized controlled trials

Mental simulation practices, such as motor imagery, action observation, and guided imagery, have been an intervention of interest in neurological and musculoskeletal rehabilitation. Application of such practices to postoperative patients in orthopedics, particularly after total knee arthroplasty, has resulted in favorable physical function outcomes. In this systematic review and meta-analysis, we wish to determine the effectiveness of mental simulation practices with standard physical therapy compared to standard physical therapy alone in patients who underwent total knee arthroplasty in terms of postoperative pain, physical functions, and patient-reported outcome measures. We identified randomized controlled trials from inception to August 28, 2021, by using the PubMed, Cochrane Library, EMBASE, and Scopus databases. Data collection was completed on August 28, 2021. Finally, eight articles (249 patients) published between 2014 and 2020 were included. The meta-analysis revealed that mental simulation practices caused more favorable results in pain [standardized mean difference = -0.42, 95% confidence interval (CI) (-0.80 to -0.04), P = 0.03], range of motion [0.55, 95% CI (0.06-1.04), P = 0.03], maximal strength of quadriceps [1.21, 95% CI (0.31-2.12), P = 0.009], and 36-Item Short-Form Survey [0.53, 95% CI (0.14-0.92), P = 0.007]. Our data suggest that mental simulation practices may be considered adjunctive to standard physiotherapy after total knee arthroplasty in patients with knee osteoarthritis.

Motor Imagery: How to Assess, Improve Its Performance, and Apply It for Psychosis Diagnostics

With this review, we summarize the state-of-the-art of scientific studies in the field of motor imagery (MI) and motor execution (ME). We composed the brain map and description that correlate different brain areas with the type of movements it is responsible for. That gives a more complete and systematic picture of human brain functionality in the case of ME and MI. We systematized the most popular methods for assessing the quality of MI performance and discussed their advantages and disadvantages. We also reviewed the main directions for the use of transcranial magnetic stimulation (TMS) in MI research and considered the principal effects of TMS on MI performance. In addition, we discuss the main applications of MI, emphasizing its use in the diagnostics of various neurodegenerative disorders and psychoses. Finally, we discuss the research gap and possible improvements for further research in the field.

Measuring the prediction of observed actions using an occlusion paradigm: Comparing autistic and non-autistic adults

Action prediction involves observing and predicting the actions of others and plays an important role in social cognition and interacting with others. It is thought to use simulation, whereby the observers use their own motor system to predict the observed actions. As individuals diagnosed with autism are characterized by difficulties understanding the actions of others and motor coordination issues, it is possible that action prediction ability is altered in this population. This study compared action prediction ability between 20 autistic and 22 non-autistic adults using an occlusion paradigm. Participants watched different videos of a female actor carrying out everyday actions. During each video, the action was transiently occluded by a gray rectangle for 1000 ms. During occlusions, the video was allowed to continue as normal or was moved forward (i.e., appearing to continue too far ahead) or moved backwards (i.e., appearing to continue too far behind). Participants were asked to indicate after each occlusion whether the action continued with the correct timing or was too far ahead/behind. Autistic individuals were less accurate than non-autistic individuals, particularly when the video was too far behind. A trend analysis suggested that autistic participants were more likely to judge too far behind occlusions as being in time. These preliminary results suggest that prediction ability may be altered in autistic adults, potentially due to slower simulation or a delayed onset of these processes. LAY SUMMARY: When we observe other people performing everyday actions, we use their movements to help us understand and predict what they are doing. In this study, we found that autistic compared to non-autistic adults were slightly less accurate at predicting other people's actions. These findings help to unpick the different ways that social understanding is affected in autism.

Shared mechanisms underlie mental imagery and motor planning

Many studies have associated mental imagery with motor control mechanisms by showing mutually active brain areas and functions, as well as similar temporal patterns of imagining and executing the same motor actions. One of the main conjectured mutual mechanisms is the Cerebellar forward-model, commonly believed to generate sensory predictions as part of both motor control and mental imagery processes. Nevertheless, trials to associate one’s overall individual mental and motor capacities have shown only mild and inconsistent correlations, hence challenging the mutual mechanism assumption. We hypothesized that one cause to this inconsistency is the forward-model’s dominance in the motor-planning stage only when adapting to novel sensorimotor environments, while the inverse-model is gradually taking the lead along the adaptation, and therefore biasing most attempts to measure motor-mental overlapping functions and correlate these measurements under regular circumstances. Our current study aimed to tackle and explore this gap using immersive virtual embodiment, by applying an experience of a fundamental sensorimotor conflict, thereby manipulating the sensory prediction mechanism, and presumably forcing an increased involvement of the forward-model in the motor planning stage throughout the experiment. In the study, two groups of subjects (n = 48) performed mental and manual rotation within an immersive, motion-captured, virtual reality environment, while the sensorimotor dynamics of only the test group were altered by physical-virtual speed re-mapping making the virtual hand move twice as fast as the physical hand controlling it. Individual mental imagery capacities were assessed before and after three blocks of manual-rotation, where motor planning durations were measured as the time until motion onset. The results show that virtual sensorimotor alteration extremely increases the correlation of mental imagery and motor planning (r = 0.9, p < .0001) and leads to higher mental imagery performance improvement following the physical blocks. We particularly show that virtual embodiment manipulation affects the motor planning stage to change and functionally overlap with imagery mechanisms, rather than the other way around, which supports our conjecture of an increased sensory-prediction forward-model involvement. Our results shed new light on the embodied nature of mental imagery, support the view of the predictive forward-model as a key mechanism mutually underlying motor control and imagery, and suggest virtual sensorimotor alteration as a novel methodology to increase physical-mental convergence. These findings also suggest the applicability of using existing motion-tracked virtual environments for continuous cognitive evaluation and treatment, through kinematic analysis of ongoing natural motor behaviors.

A Vexing Question in Motor Control: The Degrees of Freedom Problem

The human “marionette” is extremely complex and multi-articulated: anatomical redundancy (in terms of Degrees of Freedom: DoFs), kinematic redundancy (movements can have different trajectories, velocities, and accelerations and yet achieve the same goal, according to the principle of Motor Equivalence), and neurophysiological redundancy (many more muscles than DoFs and multiple motor units for each muscle). Although it is quite obvious that such abundance is not noxious at all because, in contrast, it is instrumental for motor learning, allowing the nervous system to “explore” the space of feasible actions before settling on an elegant and possibly optimal solution, the crucial question then boils down to figure out how the nervous system “chooses/selects/recruits/modulates” task-dependent subsets of countless assemblies of DoFs as functional motor synergies. Despite this daunting conceptual riddle, human purposive behavior in daily life activities is a proof of concept that solutions can be found easily and quickly by the embodied brain of the human cognitive agent. The point of view suggested in this essay is to frame the question above in the old-fashioned but still seminal observation by Marr and Poggio that cognitive agents should be regarded as Generalized Information Processing Systems (GIPS) and should be investigated according to three nearly independent but complementary levels of analysis: 1) the computational level, 2) the algorithmic level, and 3) the implementation level. In this framework, we attempt to discriminate as well as aggregate the different hypotheses and solutions proposed so far: the optimal control hypothesis, the muscle synergy hypothesis, the equilibrium point hypothesis, or the uncontrolled manifold hypothesis, to mention the most popular ones. The proposed GIPS follows the strategy of factoring out shaping and timing by adopting a force-field based approach (the Passive Motion Paradigm) that is inspired by the Equilibrium Point Hypothesis, extended in such a way to represent covert as well overt actions. In particular, it is shown how this approach can explain spatio-temporal invariances and, at the same time, solve the Degrees of Freedom Problem.

Examining the role of the supplementary motor area in motor imagery-based skill acquisition

Motor imagery (MI) and physical practice (PP) have been seen as parallel processes that can drive acquisition of motor skills. Emerging evidence, however, suggests these two processes may be fundamentally different, whereby MI-based motor skill acquisition relies more on effector-independent encoding of movement relative to PP. This alternate view is supported by evidence where real and virtual lesions to brain areas involved in visuospatial processing impair MI-based skill acquisition, and via behavioural studies showing perceptual, but not motor, transfer impairs skill acquisition via MI whereas this effect is reversed in PP. This study further investigated the degree to which MI utilizes effector-independent encoding of movement by investigating the role of the supplementary motor area (SMA), an area involved in perceptual to motor transformations, in MI-based motor skill acquisition. Sixty-four participants completed a serial reaction time paradigm following assignment to one of four groups based on training modality (MI or PP) and stimulation type (sham stimulation or continuous theta burst stimulation to inhibit the SMA). Faster reaction times (RTs) to elements of a repeated sequence in comparison to randomly generated elements indicated that sequence-specific learning occurred. Learning occurred in both PP and MI, with the magnitude of learning significantly smaller in MI. Inhibitory stimulation impaired learning in both modalities. In the context of a framework that distinguishes effector-independent and -dependent components of learning, these findings indicate the SMA plays a role in developing motor chunks in both PP and MI facilitating effector-independent learning in both modalities.

Spatial and Motor Aspects in the "Action-Sentence Compatibility Effect"

The Action-sentence Compatibility Effect (ACE) is often taken as supporting the fundamental role of the motor system in understanding sentences that describe actions. This effect would be related to an internal "simulation," i.e., the reactivation of past perceptual and motor experiences. However, it is not easy to establish whether this simulation predominantly involves spatial imagery or motor anticipation. In the classical ACE experiments, where a real motor response is required, the direction and motor representations are mixed. In order to disentangle spatial and motor aspects involved in the ACE, we performed six experiments in different conditions, where the motor component was always reduced, asking participants to judge the sensibility of sentences by moving a mouse, thus requiring a purely spatial representation, compatible with nonmotor interpretations. In addition, our experiments had the purpose of taking into account the possible confusion of effects of practice and of compatibility (i.e., differences in reaction times simultaneously coming from block order and opposite motion conditions). Also, in contrast to the usual paradigm, we included no-transfer filler sentences in the analysis. The ACE was not found in any experiment, a result that failed to support the idea that the ACE could be related to a simulation where spatial aspects rather than motor ones prevail. Strong practice effects were always found and were carved out from results. A surprising effect was that no-transfer sentences were processed much slower than others, perhaps revealing a sort of participants' awareness of the structure of stimuli, i.e., their finding that some of them involved motion and others did not. The relevance of these outcomes for the embodiment theory is discussed.

Brain connectivity during simulated balance in older adults with and without Parkinson's disease

Individuals with Parkinson's disease often experience postural instability, a debilitating and largely treatment-resistant symptom. A better understanding of the neural substrates contributing to postural instability could lead to more effective treatments. Constraints of current functional neuroimaging techniques, such as the horizontal orientation of most MRI scanners (forcing participants to lie supine), complicates investigating cortical and subcortical activation patterns and connectivity networks involved in healthy and parkinsonian balance control. In this cross-sectional study, we utilized a newly-validated MRI-compatible balance simulator (based on an inverted pendulum) that enabled participants to perform balance-relevant tasks while supine in the scanner. We utilized functional MRI to explore effective connectivity underlying static and dynamic balance control in healthy older adults (n = 17) and individuals with Parkinson's disease while on medication (n = 17). Participants performed four tasks within the scanner with eyes closed: resting, proprioceptive tracking of passive ankle movement, static balancing of the simulator, and dynamic responses to random perturbations of the simulator. All analyses were done in the participant's native space without spatial transformation to a common template. Effective connectivity between 57 regions of interest was computed using a Bayesian Network learning approach with false discovery rate set to 5%. The first 12 principal components of the connection weights, binomial logistic regression, and cross-validation were used to create 4 separate models: contrasting static balancing vs {rest, proprioception} and dynamic balancing vs {rest, proprioception} for both controls and individuals with Parkinson's disease. In order to directly compare relevant connections between controls and individuals with Parkinson's disease, we used connections relevant for predicting a task in either controls or individuals with Parkinson's disease in logistic regression with Least Absolute Shrinkage and Selection Operator regularization. During dynamic balancing, we observed decreased connectivity between different motor areas and increased connectivity from the brainstem to several cortical and subcortical areas in controls, while individuals with Parkinson's disease showed increased connectivity associated with motor and parietal areas, and decreased connectivity from brainstem to other subcortical areas. No significant models were found for static balancing in either group. Our results support the notion that dynamic balance control in individuals with Parkinson's disease relies more on cortical motor areas compared to healthy older adults, who show a preference of subcortical control during dynamic balancing.

Mental rotation performance in young adults with and without developmental coordination disorder

While there have been consistent behavioural reports of atypical hand rotation task (HRT) performance in adults with developmental coordination disorder (DCD), this study aimed to clarify whether this deficit could be attributed to specific difficulties in motor imagery (MI), as opposed to broad deficits in general mental rotation. Participants were 57 young adults aged 18-30 years with (n = 22) and without DCD (n = 35). Participants were compared on the HRT, a measure of MI, and the letter number rotation task (LNRT), a common visual imagery task. Only participants whose behavioural performance on the HRT suggested use of a MI strategy were included in group comparisons. Young adults with DCD were significantly less efficient compared to controls when completing the HRT yet showed comparable performance on the LNRT relative to adults with typical motor ability. Our data are consistent with the view that atypical HRT performance in adults with DCD is likely to be attributed to specific difficulties engaging in MI, as opposed to deficits in general mental rotation. Based on the theory that MI provides insight into the integrity of internal action representations, these findings offer further support for the internal modelling deficit hypothesis of DCD.

Characterization of kinesthetic motor imagery compared with visual motor imageries

Motor imagery (MI) is the only way for disabled subjects to robustly use a robot arm with a brain-machine interface. There are two main types of MI. Kinesthetic motor imagery (KMI) is proprioceptive (OR somato-) sensory imagination and Visual motor imagery (VMI) represents a visualization of the corresponding movement incorporating the visual network. Because these imagery tactics may use different networks, we hypothesized that the connectivity measures could characterize the two imageries better than the local activity. Electroencephalography data were recorded. Subjects performed different conditions, including motor execution (ME), KMI, VMI, and visual observation (VO). We tried to classify the KMI and VMI by conventional power analysis and by the connectivity measures. The mean accuracies of the classification of the KMI and VMI were 98.5% and 99.29% by connectivity measures (alpha and beta, respectively), which were higher than those by the normalized power (p < 0.01, Wilcoxon paired rank test). Additionally, the connectivity patterns were correlated between the ME-KMI and between the VO-VMI. The degree centrality (DC) was significantly higher in the left-S1 at the alpha-band in the KMI than in the VMI. The MI could be well classified because the KMI recruits a similar network to the ME. These findings could contribute to MI training methods.

Leveraging the effector independent nature of motor imagery when it is paired with physical practice

While considered analogous to physical practice, the nature of imagery-based skill acquisition—specifically whether or not both effector independent and dependent encoding occurs through motor imagery—is not well understood. Here, motor imagery-based training was applied prior to or after physical practice-based training to probe the nature of imagery-based skill acquisition. Three groups of participants (N = 38) engaged in 10 days of training of a dart throwing task: 5 days of motor imagery prior to physical practice (MIP-PP), motor imagery following physical practice (PP-MIP), or physical practice only (PP-PP). Performance-related outcomes were assessed throughout. Brain activity was measured at three time points using fMRI (pre/mid/post-training; MIP-PP and PP-MIP groups). In contrast with physical practice, motor imagery led to changes in global versus specific aspects of the movement. Following 10 days of training, performance was greater when motor imagery preceded physical practice, although remained inferior to performance resulting from physical practice alone. Greater activation of regions that support effector dependent encoding was observed mid-, but not post-training for the PP-MIP group. Findings indicate that changes driven by motor imagery reflect effector independent encoding, providing new information regarding how motor imagery may be leveraged for skill acquisition.

Systematic Review and Meta-Analysis of the Effectiveness of Mental Practice for the Upper Limb After Stroke: Imagined or Real Benefit?

OBJECTIVES

This systematic review sought to determine the effectiveness of mental practice (MP) on the activity limitations of the upper limb in individuals after stroke, as well as when, in whom, and how MP should be delivered.

DATA SOURCES

Ten electronic databases were searched from November 2009 to May 2020. Search terms included: Arm, Practice, Stroke rehabilitation, Imagination, Paresis, Recovery of function, and Stroke. Studies from a Cochrane review of MP (up to November 2009) were automatically included. The review was registered with the PROSPERO database of systematic reviews (reference no.: CRD42019126044).

STUDY SELECTION

Randomized controlled trials of adults after stroke using MP for the upper limb were included if they compared MP to usual care, conventional therapy, or no treatment and reported activity limitations of the upper limb as outcomes. Independent screening was conducted by 2 reviewers.

DATA EXTRACTION

One reviewer extracted data using a tool based on the Template for Intervention Description and Replication. Data extraction was independently verified by a second reviewer. Quality was assessed using the PEDro tool.

DATA SYNTHESIS

Fifteen studies (n=486) were included and 12 (n=328) underwent meta-analysis. MP demonstrated significant benefit on upper limb activities compared with usual treatment (standardized mean difference [SMD], 0.6; 95% confidence interval [CI], 0.32-0.88). Subgroup analyses demonstrated that MP was most effective in the first 3 months after stroke (SMD, 1.01; 95% CI, 0.53-1.50) and in individuals with the most severe upper limb deficits (weighted mean difference, 7.33; 95% CI, 0.94-13.72).

CONCLUSIONS

This review demonstrates that MP is effective in reducing activity limitations of the upper limb after stroke, particularly in the first 3 months after stroke and in individuals with the most severe upper limb dysfunction. There was no clear pattern of the ideal dosage of MP.

Origami folding: Taxing resources necessary for the acquisition of sequential skills

Sequential skill learning with practice is fundamental to human activity (e.g., tying shoes). Given the lack of prior knowledge in most participants, Origami folding is a promising task to study the acquisition of a sequential skill. While previous Origami folding studies mainly dealt with the question, which forms of instruction can lead to better learning outcomes, we employ a dual-task approach to test which resources are necessary for folding and for improvement with practice. Participants (N = 53) folded five Origami figures for four times each, which were randomly paired with five types of secondary tasks to cause either cognitive (verbal vs. visuospatial) or motoric (isochronous vs. non-isochronous tapping) memory load or none (control condition). Origami performance showed a typical learning curve from Trial 1 (first run of folding the figure) to Trial 4 (fourth run of folding the same figure). We tested for a dissociation between variants of memory load influencing Origami folding performance vs. the variants influencing learning (i.e. change in performance across practice). In line with theories suggesting that learning operates on the level that (at a given point in practice) demands the most control, we did not observe cases where a dual-task variant influenced performance while it did not affect learning. Memory load from the cognitive visuospatial secondary task as well as the isochronous tapping secondary task interfered with improvement in Origami folding with practice. This might be due to the use of visuospatial sketchpad and absolute timing mechanism during the acquisition of Origami folding.

Why Language Processing Recruits Modality Specific Brain Regions: It Is Not About Understanding Words, but About Modelling Situations

Whether language comprehension requires the participation of brain structures that evolved for perception and action has been a subject of intense debate. While brain-imaging evidence for the involvement of such modality-specific regions has grown, the fact that lesions to these structures do not necessarily erase word knowledge has invited the conclusion that language-induced activity in these structures might not be essential for word recognition. Why language processing recruits these structures remains unanswered, however. Here, we examine the original findings from a slightly different perspective. We first consider the 'original' function of structures in modality-specific brain regions that are recruited by language activity. We propose that these structures help elaborate 'internal forward models' in motor control (c.f. emulators). Emulators are brain systems that capture the relationship between an action and its sensory consequences. During language processing emulators could thus allow accessing associative memories. We further postulate the existence of a linguistic system that exploits, in a rule-based manner, emulators and other nonlinguistic brain systems, to gain complementary (and redundant) information during language processing. Emulators are therefore just one of several sources of information. We emphasize that whether a given word-form triggers activity in modality-specific brain regions depends on the linguistic context and not on the word-form as such. The role of modality-specific systems in language processing is thus not to help understanding words but to model the verbally depicted situation by supplying memorized context information. We present a model derived from these assumptions and provide predictions and perspectives for future research.

An Episodic Model of Task Switching Effects: Erasing the Homunculus from Memory

The Parallel Episodic Processing (PEP) model is a neural network for simulating human performance in speeded response time tasks. It learns with an exemplar-based memory store and it is capable of modelling findings from various subdomains of cognition. In this paper, we show how the PEP model can be designed to follow instructions (e.g., task rules and goals). The extended PEP model is then used to simulate a number of key findings from the task switching domain. These include the switch cost, task-rule congruency effects, response repetition asymmetries, cue repetition benefits, and the full pattern of means from a recent feature integration decomposition of cued task switching (Schmidt & Liefooghe, 2016). We demonstrate that the PEP model fits the participant data well, that the model does not possess the flexibility to match any pattern of results, and that a number of competing task switching models fail to account for key observations that the PEP model produces naturally. Given the parsimony and unique explanatory power of the episodic account presented here, our results suggest that feature-integration biases have a far greater power in explaining task-switching performance than previously assumed.

Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling

Motor imagery-based brain–computer interfaces (MI-BCIs) send commands to a computer using the brain activity registered when a subject imagines—but does not perform—a given movement. However, inconsistent MI-BCI performance occurs in variations of brain signals across subjects and experiments; this is considered to be a significant problem in practical BCI. Moreover, some subjects exhibit a phenomenon referred to as “BCI-inefficiency,” in which they are unable to generate brain signals for BCI control. These subjects have significant difficulties in using BCI. The primary goal of this study is to identify the connections of the resting-state network that affect MI performance and predict MI performance using these connections. We used a public database of MI, which includes the results of psychological questionnaires and pre-experimental resting-state taken over two sessions on different days. A dynamic causal model was used to calculate the coupling strengths between brain regions with directionality. Specifically, we investigated the motor network in resting-state, including the dorsolateral prefrontal cortex, which performs motor planning. As a result, we observed a significant difference in the connectivity strength from the supplementary motor area to the right dorsolateral prefrontal cortex between the low- and high-MI performance groups. This coupling, measured in the resting-state, is significantly stronger in the high-MI performance group than the low-MI performance group. The connection strength is positively correlated with MI-BCI performance (Session 1: r = 0.54; Session 2: r = 0.42). We also predicted MI performance using linear regression based on this connection (r-squared = 0.31). The proposed predictors, based on dynamic causal modeling, can develop new strategies for improving BCI performance. These findings can further our understanding of BCI-inefficiency and help BCI users to lower costs and save time.

Improving Real-Time Brain State Classification of Motor Imagery Tasks During Neurofeedback Training

In this study, we investigated the effect of the dynamic changes in brain activation during neurofeedback training in the classification of the different brain states associated with the target tasks. We hypothesized that ongoing activation patterns could change during neurofeedback session due to learning effects and, in the process, could affect the performance of brain state classifiers trained using data obtained prior to the session. Using a motor imagery paradigm, we then examined the application of an incremental training approach where classifiers were continuously updated in order to account for these activation changes. Our results confirmed our hypothesis that neurofeedback training could be associated with dynamic changes in brain activation characterized by an initially more widespread brain activation followed by a more focused and localized activation pattern. By continuously updating the trained classifiers after each feedback run, significant improvement in accurately classifying the different brain states associated with the target motor imagery tasks was achieved. These findings suggest the importance of taking into account brain activation changes during neurofeedback in order to provide more reliable and accurate feedback information to the participants, which is critical for an effective neurofeedback application.

Accuracy and Vividness in Motor Imagery Ability: Differences between Children and Young Adults

Motor imagery (MI) refers to the imagination of a motor task without actual movement execution. The purpose of this study was to compare MI accuracy and vividness, and motor proficiency between children (n = 101; 7-12 years) and young adults (n = 140; 18-25 years). Results indicated that young adults were significantly more accurate and rated their MI significantly more vivid than children. For MI accuracy, between-subject effects showed that young adults had higher scores than children on three of the four subscales and the action subscale significantly predicted motor proficiency. These findings indicate that MI ability continues to develop into adulthood.

Increased Time Difference between Imagined and Physical Walking in Older Adults at a High Risk of Falling

Walking motor imagery ability is thought to be associated with a fear of falling; however, no studies have compared fall risk and motor imagery ability. This study aimed to ascertain the time difference between imagined and physical walking in older adults at low and high risks of falling. Motor imagery ability was assessed using mental chronometry, which measures the imagined time required for movement. Participants included 31 older adults classified as having a high (n = 15) or low (n = 16) risk of falling based on single leg stance time. The time required for imagined and physical walking was measured using 5 m long walkways with three different widths (15, 25, and 50 cm), and the temporal errors (absolute and constant error) were compared. Physical walking time was significantly longer in the high-risk group than in the low-risk group for the 15 and 25 cm wide walkways. The absolute error between the imagined and physical walking times was significantly larger in the high-risk group than in the low-risk group for the 15 and 25 cm wide walkways. There was also a significant difference in the constant error between the high- and low-risk groups between the imagined and physical walking times for all three walkways. Older adults who may be at a higher risk of falling showed longer walking times during action execution but overestimated their performance (i.e., they believe they would be faster) during motor imagery. Therefore, the time difference between imagined and physical walking could, in part, be useful as a tool for assessing fall risk based on motor imagery.

Can we decode phonetic features in inner speech using surface electromyography?

Although having a long history of scrutiny in experimental psychology, it is still controversial whether wilful inner speech (covert speech) production is accompanied by specific activity in speech muscles. We present the results of a preregistered experiment looking at the electromyographic correlates of both overt speech and inner speech production of two phonetic classes of nonwords. An automatic classification approach was undertaken to discriminate between two articulatory features contained in nonwords uttered in both overt and covert speech. Although this approach led to reasonable accuracy rates during overt speech production, it failed to discriminate inner speech phonetic content based on surface electromyography signals. However, exploratory analyses conducted at the individual level revealed that it seemed possible to distinguish between rounded and spread nonwords covertly produced, in two participants. We discuss these results in relation to the existing literature and suggest alternative ways of testing the engagement of the speech motor system during wilful inner speech production.

Neural and Behavioral Outcomes Differ Following Equivalent Bouts of Motor Imagery or Physical Practice

Despite its reported effectiveness for the acquisition of motor skills, we know little about how motor imagery (MI)-based brain activation and performance evolves when MI (the imagined performance of a motor task) is used to learn a complex motor skill compared to physical practice (PP). The current study examined changes in MI-related brain activity and performance driven by an equivalent bout of MI- or PP-based training. Participants engaged in 5 days of either MI or PP of a dart-throwing task. Brain activity (via fMRI) and performance-related outcomes were obtained using a pre/post/retention design. Relative to PP, MI-based training did not drive robust changes in brain activation and was inferior for realizing improvements in performance: Greater activation in regions critical to refining the motor program was observed in the PP versus MI group posttraining, and relative to those driven via PP, MI led only to marginal improvements in performance. Findings indicate that the modality of practice (i.e., MI vs. PP) used to learn a complex motor skill manifests as differences in both resultant patterns of brain activity and performance. Ultimately, by directly comparing brain activity and behavioral outcomes after equivalent training through MI versus PP, this work provides unique knowledge regarding the neural mechanisms underlying learning through MI.

Inhibitory mechanisms in motor imagery: disentangling different forms of inhibition using action mode switching

In motor imagery, probably several inhibitory mechanisms prevent actual movements: global inhibition, effector-specific inhibition, and inhibition retrieved during target processing. We investigated factors that may influence those mechanisms. In an action mode switching paradigm, participants imagined and executed movements from home buttons to target buttons. We analysed sequential effects. Activation (due to execution) or inhibition (due to imagination) in the previous trial should affect performance in the subsequent trial, enabling conclusions about inhibitory mechanisms in motor imagery. In Experiment 1, evidence for global and effector-specific inhibition was observed. Evidence for inhibition retrieved during target processing was inconclusive. Data patterns were similar when start and end of the imagined movements were indicated with an effector that was part of the imagined movement (hand) and with a different effector (feet). In Experiment 2, we ruled out that the use of biological stimuli (left/right hands in Experiment 1) to indicate the effector causes sequential effects attributed to effector-specific inhibition, by using uppercase letters (R, L). As in Experiment 1, evidence for effector-specific inhibition was observed. In conclusion, we could reliably disentangle several inhibitory mechanisms in motor imagery.

Acute Effects of High-Definition Transcranial Direct Current Stimulation on Foot Muscle Strength, Passive Ankle Kinesthesia, and Static Balance: A Pilot Study

This study aimed to examine the effects of single-session anodal high-definition transcranial direct current stimulation (HD-tDCS) on the strength of intrinsic foot muscles, passive ankle kinesthesia, and static balance. Methods: In this double-blinded self-controlled study, 14 healthy younger adults were asked to complete assessments of foot muscle strength, passive ankle kinesthesia, and static balance before and after a 20-minute session of either HD-tDCS or sham stimulation (i.e., control) at two visits separated by one week. Two-way repeated-measures analysis of variance was used to examine the effects of HD-tDCS on metatarsophalangeal joint flexor strength, toe flexor strength, the passive kinesthesia threshold of ankle joint, and the average sway velocity of the center of gravity. Results: All participants completed all study procedures and no side effects nor risk events were reported. Blinding was shown to be successful, with an overall accuracy of 35.7% in the guess of stimulation type (p = 0.347). No main effects of intervention, time, or their interaction were observed for foot muscle strength (p > 0.05). The average percent change in first-toe flexor strength following anodal HD-tDCS was 12.8 ± 24.2%, with 11 out of 14 participants showing an increase in strength, while the change following sham stimulation was 0.7 ± 17.3%, with 8 out of 14 participants showing an increase in strength. A main effect of time on the passive kinesthesia threshold of ankle inversion, dorsiflexion, and anteroposterior and medial–lateral average sway velocity of the center of gravity in one-leg standing with eyes closed was observed; these outcomes were reduced from pre to post stimulation (p < 0.05). No significant differences were observed for other variables between the two stimulation types. Conclusion: The results of this pilot study suggested that single-session HD-tDCS may improve the flexor strength of the first toe, although no statistically significant differences were observed between the anodal HD-tDCS and sham procedure groups. Additionally, passive ankle kinesthesia and static standing balance performance were improved from pre to post stimulation, but no significant differences were observed between the HD-tDCS and sham procedure groups. This may be potentially due to ceiling effects in this healthy cohort of a small sample size. Nevertheless, these preliminary findings may provide critical knowledge of optimal stimulation parameters, effect size, and power estimation of HD-tDCS for future trials aiming to confirm and expand the findings of this pilot study.

The Role of Primary Motor Cortex: More Than Movement Execution

The predominant role of the primary motor cortex (M1) in motor execution is well acknowledged. However, additional roles of M1 are getting evident in humans owing to advances in noninvasive brain stimulation (NIBS) techniques. This review collates such studies in humans and proposes that M1 also plays a key role in higher cognitive processes. The review commences with the studies that have investigated the nature of connectivity of M1 with other cortical regions in light of studies based on NIBS. The review then moves on to discuss the studies that have demonstrated the role of M1 in higher cognitive processes such as attention, motor learning, motor consolidation, movement inhibition, somatomotor response, and movement imagery. Overall, the purpose of the review is to highlight the additional role of M1 in motor cognition besides motor control, which remains unexplored.

Investigating Priming Effects of Physical Practice on Motor Imagery-Induced Event-Related Desynchronization

For motor imagery (MI) to be effective, an internal representation of the to-be-imagined movement may be required. A representation can be achieved through prior motor execution (ME), but the neural correlates of MI that are primed by ME practice are currently unknown. In this study, young healthy adults performed MI practice of a unimanual visuo-motor task (Group MI, n = 19) or ME practice combined with subsequent MI practice (Group ME&MI, n = 18) while electroencephalography (EEG) was recorded. Data analysis focused on the MI-induced event-related desynchronization (ERD). Specifically, changes in the ERD and movement times (MT) between a short familiarization block of ME (Block pre-ME), conducted before the MI or the ME combined with MI practice phase, and a short block of ME conducted after the practice phase (Block post-ME) were analyzed. Neither priming effects of ME practice on MI-induced ERD were found nor performance-enhancing effects of MI practice in general. We found enhancements of the ERD and MT in Block post-ME compared to Block pre-ME, but only for Group ME&MI. A comparison of ME performance measures before and after the MI phase indicated however that these changes could not be attributed to the combination of ME and MI practice. The mixed results of this study may be a consequence of the considerable intra- and inter-individual differences in the ERD, introduced by specifics of the experimental setup, in particular the individual and variable task duration, and suggest that task and experimental setup can affect the interplay of ME and MI.

Nodding and shaking of the head as simulated approach and avoidance responses

Our recent study within the embodiment perspective showed that the evaluation of true and false information activates the simulation of vertical and horizontal head movements involved in nodding and shaking of the head (Moretti & Greco, 2018). This result was found in an explicit evaluation task where motion detection software was deployed to enable participants to assess a series of objectively true or false statements by moving them with the head vertically and horizontally on a computer screen, under conditions of compatibility and incompatibility between simulated and performed action. This study replicated that experiment, but with subjective statements about liked and disliked food, in both explicit and implicit evaluation tasks. Two experiments, plus one control experiment, were devised to test the presence of a motor-affective compatibility effect (vertical-liked; horizontal-disliked) and whether the motor-semantic compatibility found with objective statements (vertical-true; horizontal-false) could be a sub-effect of a more general and automatic association (vertical-accepted; horizontal-refused). As expected, response times were shorter when statements about liked foods and disliked foods were moved vertically and horizontally respectively by making head movements, even when participants were not explicitly required to evaluate them. In contrast, the truth compatibility effect only occurred in the explicit evaluation task. Overall results support the idea that head-nodding and shaking are simulated approach-avoidance responses. Different aspects of the meaning of these gestures and the practical implications of the study for cognitive and social research are discussed.

A general theory of consciousness I: Consciousness and adaptation

This paper examines how cognitive processes in living beings become conscious. Consciousness is often assumed to be a human quality only. While the basis of this paper is that consciousness is as much present in animals as it is in humans, the human form is shown to be fundamentally different. Animal consciousness expresses itself in sensory images, while human consciousness is largely verbal. Because spoken language is not an individual quality - thoughts are shared with others via communication - consciousness in humans is complex and difficult to understand. The theory proposed postulates that consciousness is an inseparable part of the body's adaptation mechanism. In adaptation to a new environmental disturbance, the outcome of the neural cognitive process - a possible solution to the problem posed by the disturbance - is transformed into a sensory image. Sensory images are essentially conscious as they are the way living creatures experience new environmental information. Through the conversion of neural cognitive activity - thoughts - about the state of the outside world into the way that world is experienced through the senses, the thoughts gain the reality that sensory images have. The translation of thoughts into sensory images makes them real and understandable which is experienced as consciousness. The theory proposed in this paper is corroborated by functional block diagrams of the processes involved in the complex regulated mechanism of adaptation and consciousness during an environmental disturbance. All functions in this mechanism and their interrelations are discussed in detail.

The Sensitivity of Single-Trial Mu-Suppression Detection for Motor Imagery Performance as Compared to Motor Execution and Motor Observation Performance

Motor imagery (MI) has been widely used to operate brain-computer interface (BCI) systems for rehabilitation and some life assistive devices. However, the current performance of an MI-based BCI cannot fully meet the needs of its in-field applications. Most of the BCIs utilizing a generalized feature for all participants have been found to greatly hamper the efficacy of the BCI system. Hence, some attempts have made on the exploration of subject-dependent parameters, but it remains challenging to enhance BCI performance as expected. To this end, in this study, we used the independent component analysis (ICA), which has been proved capable of isolating the pure motor-related component from non-motor-related brain processes and artifacts and extracting the common motor-related component across MI, motor execution (ME), and motor observation (MO) conditions. Then, a sliding window approach was used to detect significant mu-suppression from the baseline using the electroencephalographic (EEG) alpha power time course and, thus, the success rate of the mu-suppression detection could be assessed on a single-trial basis. By comparing the success rates using different parameters, we further quantified the extent of the improvement in each motor condition to evaluate the effectiveness of both generalized and individualized parameters. The results showed that in ME condition, the success rate under individualized latency and that under generalized latency was 90.0% and 77.75%, respectively; in MI condition, the success rate was 74.14% for individual latency and 58.47% for generalized latency, and in MO condition, the success rate was 67.89% and 61.26% for individual and generalized latency, respectively. As can be seen, the success rate in each motor condition was significantly improved by utilizing an individualized latency compared to that using the generalized latency. Moreover, the comparison of the individualized window latencies for the mu-suppression detection across different runs of the same participant as well as across different participants showed that the window latency was significantly more consistent in the intra-subject than in the inter-subject settings. As a result, we proposed that individualizing the latency for detecting the mu-suppression feature for each participant might be a promising attempt to improve the MI-based BCI performance.

A Novel MRI Compatible Balance Simulator to Detect Postural Instability in Parkinson's Disease

Background: Postural instability is a debilitating and largely treatment-resistant symptom of Parkinson's disease (PD). A better understanding of the neural substrates contributing to postural instability could lead to new targets for improved pharmacological and neurosurgical interventions. However, investigating these neural substrates necessitates the use of functional MRI scanners, which are almost exclusively horizontally-based. Objective: We aimed to develop, and validate the use of, an MRI compatible balance simulator to study static and dynamic balance control in PD patients and elderly controls. Methods: Our MRI compatible balance simulator allowed participants to actively balance an inverted pendulum by activating postural muscles around the ankle joint while supine. Two studies were performed to compare static and dynamic balance performance between upright stance and simulated stance in PD patients and controls. Study 1 (14 PD; 20 controls) required participants to maintain static balance during upright and simulated stance for 120 s with eyes open and closed. In study 2 (20 PD; 22 controls) participants repeated the static balance task (80 s, eyes closed only), and also completed a dynamic balance task which required maintaining balance while experiencing random anterior-posterior perturbations applied to the trunk/pendulum. Postural sway of the body/pendulum was measured using an angular velocity sensor (SwayStar^TM, study 1) and Optotrak motion capture (study 2). Outcome measures were amplitude and frequency of center of mass sway for static balance, and peak and time-to-peak of center of mass displacement and velocity for dynamic balance. Results: PD patients had larger sway amplitude during both upright and simulated static balance compared to controls. PD patients had larger peak and time-to-peak sway, and larger time-to-peak sway velocity, during simulated, but not upright, dynamic balance compared to controls. Conclusions: Deficits in static and dynamic balance control can be detected in PD patients using a novel MRI compatible balance simulator. This technique allows for functional neuroimaging to be combined with balance-relevant tasks, and provides a new means to create insights into the neural substrates contributing to postural instability in PD.

Motor imagery entails task-set inhibition

Motor imagery requires the covert execution of a movement without any overt motor output. Previous studies indicated that motor imagery results in the prolonged inhibition of motor commands. In the present study, we investigated whether motor imagery also leads to the inhibition of more abstract task representations. To do so, we investigated the effect of motor imagery on n - 2 repetition costs, which offer an index of the extent to which task representations are inhibited. Participants switched among three tasks and among two response modes: overt and covert responding (i.e., motor imagery). N - 2 repetition costs were present when the current trial required an overt response but absent when the current trial required a covert response. Furthermore, n - 2 repetition costs were more pronounced when trial n - 1 required a covert response rather than an overt response. This pattern of results suggests that motor imagery also leads to the inhibition of abstract task representations. We discuss our findings in view of current conceptualizations of motor imagery and argue that the inhibitory mechanism entailed by motor imagery targets more than motor commands alone. Finally, we also relate our findings to the mechanisms underlying the inhibition of task representations.