Special issue: Original articleMotor imagery: A window into the mechanisms and alterations of the motor system
Introduction
Motor imagery is a familiar aspect of most people's everyday experience. It is important for learning complex motor skills like sports (Murphy, 1994), as well as re-learning motor skills in neurological populations (Dijkerman et al., 2004, Lotze et al., 2006). The potential of motor imagery in clinical applications is broad, ranging from Brain–Computer interfacing (Pfurtscheller and Neuper, 2006) to diagnosis of vegetative state in non-communicative brain-injured patients (Owen et al., 2006).
Numerous studies have addressed behavioral and cerebral correlates of motor imagery, and its relationship with actual execution and motor planning [reviewed in Jeannerod, 2006]. Owing to this link, motor imagery paradigms have been extensively used as a tool to gain insight in the action system of both healthy and diseased populations. An important asset of motor imagery is that it allows one to investigate internal dynamics of motor control like planning and preparation, while avoiding sensory and motor confounds related to motor execution. This feature is especially important when studying motor impairments in clinical populations. In neuropsychiatric or neurological syndromes like hemiplegia, dystonia, Parkinson's disease, or a (conversive) limb paralysis, motor execution is impaired or even absent. In these cases, the (in)ability of imagining to carry out actions, and its cerebral correlates, can be used to establish at what level impairments in the action system are manifest.
The goal of this paper is threefold. Firstly, we assess how motor imagery research has advanced the knowledge of action control, reviewing behavioral and neuroimaging studies in healthy subjects. Secondly, we review the use of motor imagery in clinical populations, and its usefulness for scientific and diagnostic purposes.
Thirdly, we illustrate the use of motor imagery in a psychopathological condition: conversion paralysis (CP). In this context, we present new behavioral and neuroimaging data dealing with the cerebral implementation of imagined actions in the affected and non-affected arm, showing how manipulating the degree of action monitoring of the patient influences the imagery process.
Motor imagery paradigms come in many flavours. One variable that differs between studies is the effector(s) that are used in the imagined action (e.g., hand, foot, mouth). Also, the complexity of the action to be imagined can vary widely, ranging from simple finger tapping (Hanakawa et al., 2003) to walking (Bakker et al., 2007, Stevens, 2005) or playing tennis (Owen et al., 2006). A further important distinction can be made between tasks that explicitly ask subjects to engage in motor imagery and tasks that elicit imagined actions in an implicit fashion (Jeannerod and Frak, 1999).
During explicit imagery tasks subjects are simply asked to imagine moving their effector in a particular manner [e.g., “Imagine making repetitive brisk flexion/extension movements of the fingers”, Ehrsson et al., 2003]. Implicit imagery tasks on the other hand usually employ a task that is tangential to imagery of actions [e.g., “Is the stimulus you are looking at a left or right hand”, Parsons, 1987, Sekiyama, 1982], and infer the motoric nature of the processes involved in solving the task from the behavior of the subjects. Conceptually, implicit and explicit imagery tasks differ in terms of how vulnerable they are to criticisms of cognitive penetrability (Pylyshyn, 2002). When subjects are explicitly asked to imagine a movement, say imagining to run from A to B, they may use tacit knowledge about the time it takes to run from A to B to guide their performance, out of a desire to comply with the experimenter. This criticism applies less to implicit motor imagery tasks. In this case, subjects are not asked to engage in imagery, but to solve a tangential task (e.g., judge the laterality of a hand), and subjects are often not aware of the crucial experimental variables. In these cases, the visual or motor nature of the imagery process is inferred from behavioral and/or neural performance.
Another important dimension on which imagery paradigms differ is quantifiability of performance. Given the private nature of (motor) imagery, it is inherently difficult to assess whether a subject, when asked to imagine a certain action, is indeed actively engaged in motor imagery. Whereas some studies have simply assumed task compliance (e.g., Ehrsson et al., 2003, Gerardin et al., 2000, Porro et al., 1996), others have included a behavioral component to control for task compliance and aptitude. Sirigu et al. (1996) asked subjects to mentally rehearse a finger opposition sequence to the increasing pace of a metronome (i.e., an explicit motor imagery task). Subjects had to indicate the maximal speed at which they could mentally perform these movements, a measure that could later be compared to the maximal speed of executed finger opposition sequences (Sirigu et al., 1996), making the overall motor imagery performance quantifiable. Similarly, Hanakawa et al. (2003) verified imagery performance during imagined finger tapping by asking subjects to report at unpredictable intervals which finger they were imagining to move while they were engaged in imagery of a predefined movement pattern at a predefined speed. Imagery of more complex actions has been quantified in a similar manner (Bakker et al., 2007, Decety and Jeannerod, 1995, Johnson et al., 2002a, Stevens, 2005).
An influential paradigm that implicitly evokes motor imagery and allows one to quantify performance is the hand-laterality judgment task, in which subjects have to make judgments about rotated images of hands (Parsons, 1987, Sekiyama, 1982). The presence of motor simulations of the left and right hands can be inferred from the behavioral performance. Namely, reaction times (RTs) are not linearly modulated by the rotation of the hand stimulus (as is usually the case during mental rotation paradigms: see Shepard and Cooper, 1982). Rather, RTs closely correspond to the time it would take to execute a similar movement. Biomechanically complex movements (e.g., movements away from the midline of the body) take disproportionally longer than biomechanically easier movements (e.g., movements towards the midline of the body), even if the stimulus rotation is equal (de Lange et al., 2006, Parsons, 1994, Parsons et al., 1998).
There are other examples of implicit motor imagery tasks. One is the grasp judgment task designed by Johnson et al. (2002a), in which a graspable handle is presented in various orientations. Subjects had to judge whether it would be preferable to grasp the handle using an underhand or overhand power grip. This paradigm is similar to the one designed by Frak et al. (2001), in which subjects had to judge the complexity of a grasping movement. In both cases, it is possible to use mental chronometry to quantify the imagery performance of the subject.
Using the wide variety of tasks described above, several studies have typically reported a tight correlation between imagined and executed actions along various behavioral dimensions. As already mentioned above, the time it takes to image a certain action is closely correlated with the execution time of the action (Decety and Michel, 1989, Parsons, 1994, Sirigu et al., 1996, Stevens, 2005). Furthermore, vegetative responses like cardiac and respiratory rhythms covary with the degree of imagined effort (Decety et al., 1991). Motor imagery performance is also influenced by the current state of one's own body, pointing to the embodied nature of this cognitive process. Several studies have found that changing one's body posture affects motor imagery performance (Parsons, 1994, Sirigu and Duhamel, 2001), in an effector-specific manner (de Lange et al., 2006, Shenton et al., 2004).
Several neuroimaging studies have found a host of brain regions that are active during simulated actions [for a meta-analysis, see Grezes and Decety, 2001]. The posterior parietal, premotor and supplementary motor cortex have all been implicated in motor imagery. These regions are also engaged in planning and preparation of movements (Deiber et al., 1996, Rushworth et al., 2003, Toni et al., 2001), suggesting a neural overlap between motor imagery and motor planning and preparation.
In view of the tight link between imagined and executed actions, it has been proposed that the primary motor cortex (M1) may also have a critical role in motor imagery. Several studies have indeed implicated M1 in motor imagery, but this is still an ongoing topic of debate. Neuropsychological studies have found behavioral disturbances during imagined actions in patients with lesions in M1 (Sirigu et al., 1995, Tomasino et al., 2005b). Two transcranial magnetic stimulation (TMS) studies have also found that disruption of M1 selectively interfered with motor imagery performance (Ganis et al., 2000, Tomasino et al., 2005a), although a recent study did not find an involvement of M1 in motor imagery (Sauner et al., 2006). Together, these studies provide some support for a role of M1 in motor imagery, although it should be kept in mind that M1 operates within an interconnected cerebral network, and the effects of a perturbation delivered at one node of a network may influence behavior through changes in other nodes. This consideration applies both to TMS studies (Ruff et al., 2006, Strafella and Paus, 2001) and patient studies (Price and Friston, 2002a, Young et al., 2000). Several electrophysiological studies in humans have also involved motor cortex in motor imagery (Caldara et al., 2004, Carrillo-de-la-Pena et al., 2006, McFarland et al., 2000, Pfurtscheller et al., 2006). Neuroimaging methods with higher spatial resolution (like fMRI) have, however, been divided on the issue. While several studies have observed (attenuated) M1 activity during imagery (Dechent et al., 2004, Lacourse et al., 2005, Lotze et al., 1999, Porro et al., 1996, Rodriguez et al., 2004) other studies did not find any M1 activation as a function of imagery, but only M1 activity related to the actual motor response at the end of a trial (de Lange et al., 2005, Richter et al., 2000). Possibly, a host of factors like paradigm choice (e.g., implicit or explicit, simple or complex movements), and subject instructions may contribute to whether or not M1 plays a role during motor imagery (Lotze and Halsband, 2006). Future studies that experimentally manipulate these factors within one design may be of great help to solve this debate.
Given the behavioral and neural correlations between imagined actions and actually performed actions, it has been suggested that these processes (at least partly) rely on common mechanisms. More precisely, some authors have suggested that motor imagery relies on the generation of a complete motor plan that is prevented from operating on the body (Grush, 2004, Jeannerod, 1994). However, other authors have suggested that motor imagery relies on processes involved in planning, but not control of movements (Glover, 2004, Johnson et al., 2002b). According to this latter view, there is a dichotomy between the planning system, dealing with action selection before movement onset on the basis of cognitive and visual factors; and the control system, dealing with on-line supervision of movement execution on the basis of motor variables. Therefore, these two frameworks posit that different processes are underlying motor imagery. According to the planning–control framework (Glover, 2004, Johnson et al., 2002b), motor imagery relies on general representations, rather than specific motor representations. An implication of this is that the neural computations that operate on such representations should not be influenced by the current state of one's body. In contrast, according to the simulation/emulation framework (Grush, 2004, Jeannerod, 1994), motor imagery relies on embodied motor representations. Therefore, motor imagery should depend not only on the desired end-state but also on the current configuration of the limb.
Previous reports have provided evidence supporting either claim. On the one hand, some psychophysical studies failed to find a significant difference in the time required to solve a hand-laterality judgment task by densely hemiplegic and by recovered hemiplegic patients, irrespectively of whether the task involved their paralyzed or their unaffected hand (Johnson, 2000, Johnson et al., 2002b). Furthermore, the patients were as accurate in motor imagery as control subjects that fully recovered from hemiparesis. These results have been taken as evidence that action representations can be independent of one's own body. On the other hand, Nico et al. (2004) showed that the loss of one limb significantly increased the difficulty of performing hand-laterality judgments, notably if the amputated limb was the dominant limb. Similarly, behavioral (Parsons, 1987, Shenton et al., 2004, Sirigu and Duhamel, 2001) and neural (de Lange et al., 2006, Vargas et al., 2004) studies have showed that there is a clear proprioceptive influence on motor imagery performance in healthy subjects, favouring the view that motor imagery relies on the generation of a complete motor plan that is prevented from operating on the body.
Motor imagery tasks have been widely used in clinical populations to investigate cognitive aspects of motor dysfunction. For instance, motor imagery impairments have been found in neglect patients (Coslett, 1998), patients with lesions in parietal (Danckert et al., 2002, Sirigu et al., 1996) and motor cortex (Sirigu et al., 1995, Tomasino et al., 2005b), Parkinson's disease (Dominey et al., 1995, Helmich et al., 2007), chronic fatigue syndrome (de Lange et al., 2004), hand dystonia (Fiorio et al., 2006) and patients with peripheral disturbances such as upper limb amputees (Nico et al., 2004), chronic pain patients (Schwoebel et al., 2001) and people with congenital absence of limbs (Funk and Brugger, 2002). There are at least two rationales for using motor imagery paradigms in patient populations. First, one can test whether a given impairment affects motor processing beyond simple execution [see for instance, Schwoebel et al., 2001]. Second, for motor disorders that do not impair motor imagery performance, one can probe movement-related processes using a task that the patient can perform, while allowing for objective measures of patients' performance and strategies. This is a necessary requirement if one wants to attribute behavioral performance and/or cerebral activity to pathological mechanisms (Price and Friston, 2002b), rather than unspecific factors related to impaired performance.
Recently, the study of motor cognitive impairments has been extended to psychopathological conditions. For instance, some authors have tested the hypothesis that the motor passivity of some schizophrenic patients might be linked to altered generation of forward models in the parietal cortex (Danckert et al., 2004, Maruff et al., 2003). CP is another psychopathological condition for which motor imagery is a viable tool to gain insight in the underlying pathological mechanisms. CP is a syndrome characterized by a loss of motor function without apparent ‘organic’ cause. There are competing theories about the functional mechanisms behind this syndrome. Some studies suggest the disorder is characterized by inhibition of movement plans (Halligan et al., 2000, Marshall et al., 1997). Other studies claim that the disorder is associated with heightened self-monitoring during actions (Roelofs et al., 2006, Vuilleumier et al., 2001). Recently, we have used an implicit and explicit motor imagery paradigm in order to test the predictions of these competing theories.
CP is a mental disorder characterized by loss of voluntary motor functioning. Although the symptoms may suggest a neuropathological condition, they cannot be adequately explained by known neurological or other organic disorders (American Psychiatric Association, 1994). Moreover, there is an exacerbation of symptoms at times of psychological stress, which suggests that psychological mechanisms play a role. Conversion disorder and related disorders are common in clinical practice. About one third of new neurological outpatients exhibit medically unexplained symptoms (Carson et al., 2000, Stone et al., 2005). Despite its high prevalence among neurological outpatients, little is known about the neurobiological basis of this motor dysfunction, and its functional neuro-anatomy is controversial. Several studies have investigated the functional neuro-anatomy of CP by recording brain activity during attempted movement of the paralyzed limb (Burgmer et al., 2006, Marshall et al., 1997, Spence et al., 2000) but different studies obtained conflicting results. One of the reasons for the inconsistency may be that patients were asked to carry out a task (“move/try to move your affected limb”) that they could not appropriately perform due to their condition. Accordingly, it is conceivable that these results reveal cerebral effects related to the cognitive consequences of a failed movement (like altered effort, motivation, or error processing), rather than impaired formation of action representations. Motor imagery can overcome some of these interpretational issues, since it does not rely on actual motor execution but still taps into the motor system. Previous behavioral studies have used motor imagery tasks to reveal impairments in motoric simulations of the affected limb in patients with CP (Maruff and Velakoulis, 2000, Roelofs et al., 2001).
We recently tested the hypothesis that CP can be linked to heightened self-monitoring. Heightened self-monitoring is associated with increased behavioral inhibition in patients with anxiety disorders (Gehring et al., 2000, Hajcak and Simons, 2002, Ursu et al., 2003). In view of the stress-induced immobility observed in CP, we hypothesized that heightened self-monitoring may play a functional role also in this disorder (Roelofs et al., 2006). We found that implicit motor imagery of the affected hand leads to stronger responses in the superior temporal and ventromedial prefrontal cortex (de Lange et al., 2007) compared to the unaffected hand. These regions have been associated with self-reflexive processing (Goldberg et al., 2006), as well as observation and awareness of actions (Castelli et al., 2000, Frith et al., 2000), substantiating the link between CP and heightened self-monitoring during actions with the affected arm.
In the current study, we have tested a prediction of this interpretation. Namely, if the altered pattern of activity of those regions is related to increased self-monitoring for imagined actions of the affected hand, then inducing self-monitoring of actions of the unaffected limb (by means of explicitly cued motor imagery) should abolish the activation differences observed during implicit motor imagery.
Section snippets
Participants
We studied seven patients (mean age of 31.6 years, range 18–48, SD = 10.8) diagnosed with conversion disorder according to the DSM-IV criteria (American Psychiatric Association, 1994) and showing a full or partial paralysis lateralized to one arm as a major symptom. For a full description of inclusion criteria and diagnosis procedure, see (de Lange et al., 2007). Four patients showed conversion paresis to the right arm and three patients showed conversion paresis to the left arm. Lateralization
Behavioral results
RTs of the participants for each task are shown in Fig. 1. Subjects were overall slower for explicit motor imagery than for implicit motor imagery (main effect of task: F(1,5) = 16.7; p = .009). RTs were modulated by stimulus rotation (main effect of rotation: F(4,20) = 18.6; p < .001). A trend analysis showed that RTs were linearly modulated by stimulus rotation (F(1,5) = 42.3; p < .001). Although RTs appeared slightly longer for the affected hand than for the unaffected hand in both tasks, this effect
Discussion
In this paper, we have reviewed different approaches and rationales for using motor imagery to study motor cognition in humans, as well as its application to neurological and neuropsychiatric disorders. We have illustrated how the application of motor imagery in conjunction with neuroimaging methods has been used to shed light on an ill-understood neuropsychiatric condition, CP. This approach has generated a specific prediction on the behavioral and cerebral effects of implicitly or explicitly
Conclusions
There is abundant evidence from psychophysical and neuroimaging studies, as well as from patient studies in neurological and psychiatric populations that motor imagery can provide a window into the mechanisms and alterations of motor cognition (Jeannerod, 2006). Although the behavioral and neural signature of motor imagery in the healthy brain, as well as its possible disturbances, has been investigated in detail, this has not yet led to a wide use of motor imagery as a diagnostic tool. The
Acknowledgments
FdL and IT were supported by Dutch Science Foundation (NWO: VIDI grant no. 452-03-339). KR was supported by Dutch Science Foundation (NWO VENI grant no. 451-02-115). This study was supported by the Dutch Brain Foundation (Hersenstichting Nederland, grant number 12F04(2).19) awarded to KR and FdL. The authors would like to thank Marije van Beilen for her generous assistance in recruiting patients, and Paul Gaalman for expert assistance during scanning.
References (100)
- et al.
Abnormal brain activation during movement observation in patients with conversion paralysis
NeuroImage
(2006) - et al.
Movement and mind: a functional imaging study of perception and interpretation of complex intentional movement patterns
NeuroImage
(2000) Evidence for a disturbance of the body schema in neglect
Brain and Cognition
(1998)- et al.
Attention, motor control and motor imagery in schizophrenia: implications for the role of the parietal cortex
Schizophrenia Research
(2004) - et al.
Mentally simulated movements in virtual reality: does Fitts's law hold in motor imagery?
Behavioural Brain Research
(1995) - et al.
Vegetative response during imagined movement is proportional to mental effort
Behavioural Brain Research
(1991) - et al.
Comparative analysis of actual and mental movement times in two graphic tasks
Brain and Cognition
(1989) - et al.
Is the human primary motor cortex involved in motor imagery?
Cognitive Brain Research
(2004) - et al.
Motor imagery of a lateralized sequential task is asymmetrically slowed in hemi-Parkinson's patients
Neuropsychologia
(1995) - et al.
Time-resolved fMRI of mental rotation revisited-dissociating visual perception from mental rotation in female subjects
NeuroImage
(2006)
Visual recognition of hands by persons born with only one hand
Cortex
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
NeuroImage
When the brain loses its self: prefrontal inactivation during sensorimotor processing
Neuron
Error-related brain activity in obsessive–compulsive undergraduates
Psychiatry Research
Imaging hypnotic paralysis: implications for conversion hysteria
Lancet
Cerebral compensation during motor imagery in Parkinson's disease
Neuropsychologia
Mental imaging of motor activity in humans
Current Opinion in Neurobiology
Selective activation of a parietofrontal circuit during implicitly imagined prehension
NeuroImage
Distinct neural correlates underlying two- and three-dimensional mental rotations using three-dimensional objects
Brain Research
Brain activation during execution and motor imagery of novel and skilled sequential hand movements
NeuroImage
Posture influences motor imagery: an fMRI study
NeuroImage
Increased self-monitoring during imagined movements in conversion paralysis
Neuropsychologia
Motor imagery
Journal of Physiology (Paris)
The functional anatomy of a hysterical paralysis
Cognition
The voluntary control of motor imagery. Imagined movements in individuals with feigned motor impairment and conversion disorder
Neuropsychologia
Abnormalities of motor imagery associated with somatic passivity phenomena in schizophrenia
Schizophrenia Research
Imagined spatial transformations of one's hands and feet
Cognitive Psychology
Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks
NeuroImage
Future prospects of ERD/ERS in the context of brain–computer interface (BCI) developments
Progress in Brain Research
Degeneracy and cognitive anatomy
Trends in Cognitive Science
Hand movement distribution in the motor cortex: the influence of a concurrent task and motor imagery
NeuroImage
Hyperactive action monitoring during motor-initiation in conversion paralysis: an event-related potential study
Biological Psychology
Concurrent TMS–fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex
Current Biology
The left parietal and premotor cortices: motor attention and selection
NeuroImage
Mental motor imagery and the body schema: evidence for proprioceptive dominance
Neuroscience Letters
Discrete neurophysiological correlates in prefrontal cortex during hysterical and feigned disorder of movement
Lancet
Interference effects demonstrate distinct roles for visual and motor imagery during the mental representation of human action
Cognition
Movement preparation and motor intention
NeuroImage
Hysterical conversion and brain function
Progress in Brain Research
Diagnostic and Statistical Manual of Mental Disorders
Motor imagery of gait: a quantitative approach
Experimental Brain Research
Actual and mental motor preparation and execution: a spatiotemporal ERP study
Experimental Brain Research
Limb (hand vs. foot) and response conflict have similar effects on event-related potentials (ERPs) recorded during motor imagery and overt execution
European Journal of Neuroscience
Do medically unexplained symptoms matter? A prospective cohort study of 300 new referrals to neurology outpatient clinics
Journal of Neurology Neurosurgery and Psychiatry
Orbitofrontal sulci of the human and macaque monkey brain
Journal of Comparative Neurology
Selective, non-lateralized impairment of motor imagery following right parietal damage
Neurocase
Cerebral structures participating in motor preparation in humans: a positron emission tomography study
Journal of Neurophysiology
Does motor imagery training improve hand function in chronic stroke patients? A pilot study
Clinical Rehabilitation
Imagery of voluntary movement of fingers, toes, and tongue activates corresponding body-part-specific motor representations
Journal of Neurophysiology
Selective impairment of hand mental rotation in patients with focal hand dystonia
Brain
Cited by (160)
A multi-classification algorithm based on multi-domain information fusion for motor imagery BCI
2023, Biomedical Signal Processing and ControlCitation Excerpt :By comparing with the F3 feature extraction method, it is found that the fused features after adding Mu and Beta rhythm window energy can effectively improve the classification performance. A large number of studies([29,30,31]) have proved that people will induce EEG signals in the brain area near the cerebral motor cortex according to performing different motor imagery tasks. To verify whether the channel selection strategy combining time-frequency-space information is consistent with neurophysiological characteristics, we use brain topology maps to confirm whether the selected optimal channel group distribution and the weight of each channel in the motor imagery tasks are consistent with the neurophysiological knowledge.
Self-perception in anorexia nervosa: When the body becomes an object
2022, NeuropsychologiaUsing motor imagery practice for improving motor performance – A review
2021, Brain and CognitionBiomarkers of Pathological Dissociation: A Systematic Review
2021, Neuroscience and Biobehavioral ReviewsCharacterizing the supraspinal sensorimotor control of walking using MRI-compatible system: a systematic review
2024, Journal of NeuroEngineering and Rehabilitation