Frontal brain areas are more involved during motor imagery than during motor execution/preparation of a response sequence.

Results of several neuroimaging studies support the functional equivalence model, which states that motor imagery (MI) and motor execution (ME) involve the same processes, except for the final execution component. In contrast, the motor-cognitive model implies that MI additionally involves frontal executive control processes. However, according to some authors MI may actually be more comparable to motor preparation (MP). In the current electroencephalographic study, a version of the discrete sequence production paradigm was employed in which human participants initially had to prepare a sequence of five finger movements that subsequently had to be executed, imagined, or withheld. MI, ME, and MP were compared by computing event-related (de)-synchronization in the theta, alpha/mu, and beta bands. Results revealed a major increase in frontal theta power during MI as compared to ME and MP. At the end of the examined intervals, a posterior reduction in alpha power was present during ME and MP, but not during MI. Finally, above sensorimotor areas a decrease in beta power was observed that was most pronounced in the case of ME. The increase of frontal theta activity during MI may reflect increased effort, while the absence of a reduction in posterior alpha power suggests no major involvement of visuospatial attention and/or visual imagery. The present findings favor the motor-cognitive model, as it predicts extra involvement of frontal executive processes during MI.

Does Transcranial Direct Current Stimulation Affect the Learning of a Fine Sequential Hand Motor Skill with Motor Imagery?

Learning a fine sequential hand motor skill, like playing the piano or learning to type, improves not only due to physical practice, but also due to motor imagery. Previous studies revealed that transcranial direct current stimulation (tDCS) and motor imagery independently affect motor learning. In the present study, we investigated whether tDCS combined with motor imagery above the primary motor cortex influences sequence-specific learning. Four groups of participants were involved: an anodal, cathodal, sham stimulation, and a control group (without stimulation). A modified discrete sequence production (DSP) task was employed: the Go/NoGo DSP task. After a sequence of spatial cues, a response sequence had to be either executed, imagined, or withheld. This task allows to estimate both non-specific learning and sequence-specific learning effects by comparing the execution of unfamiliar sequences, familiar imagined, familiar withheld, and familiar executed sequences in a test phase. Results showed that the effects of anodal tDCS were already developing during the practice phase, while no effects of tDCS on sequence-specific learning were visible during the test phase. Results clearly showed that motor imagery itself influences sequence learning, but we also revealed that tDCS does not increase the influence of motor imagery on sequence learning.

Do musicians learn a fine sequential hand motor skill differently than non-musicians?

Do professional musicians learn a fine sequential hand motor skill more efficiently than non-musicians? Is this also the case when they perform motor imagery, which implies that they only mentally simulate these movements? Musicians and non-musicians performed a Go/NoGo discrete sequence production (DSP) task, which allows to separate sequence-specific from a-specific learning effects. In this task five stimuli, to be memorized during a preparation interval, signaled a response sequence. In a practice phase, different response sequences had to be either executed, imagined, or inhibited, which was indicated by different response cues. In a test phase, responses were required to familiar (previously executed, imagined, or inhibited) and unfamiliar sequences. In both phases, response times and response accuracy were measured while the electroencephalogram (EEG) was only registered during the practice phase to compare activity between motor imagery, motor execution, and motor inhibition for both groups. Results in the practice phase revealed that musicians learned the response sequences faster and more accurately than non-musicians although no difference in initiation time was found. EEG analyses revealed similar lateralized activity during learning a motor skill for both groups. Our results from the test phase showed better sequence-a-specific learning effects (i.e., faster response times and increased accuracy) for musicians than for non-musicians. Moreover, we revealed that non-musicians benefit more from physical execution while learning a required motor sequence, whereas sequence-specific learning effects due to learning with motor imagery were very similar for musicians and non-musicians.

How effector-specific is the effect of sequence learning by motor execution and motor imagery?

The aim of the present study was twofold. First, we wanted to examine how effector specific the effect of sequence learning by motor execution is, and second, we wanted to compare this effect with learning by motor imagery. We employed a Go/NoGo discrete sequence production task in which in each trial a spatial sequence of five stimuli was presented. After a Go signal the corresponding spatial response sequence had to be executed, while after a NoGo signal, the response sequence had to be mentally imagined. For the training phase, participants were divided into two groups. In the index finger group, participants had to respond (physically or mentally) with the left or right index finger, while in the hand group they had to respond with four fingers of the left or right hand. In a final test phase both execution modes were compared and all trials had to be executed. Response times and the percentage of correct responses were determined to establish learning effects. Results showed that sequence learning effects as assessed in the test phase were independent of the effector used during the training phase. Results revealed the presence of aspecific learning effects in the case of learning a required motor task with an index finger, but sequence-specific learning effects, both due to motor execution and to motor imagery, were not effector specific.

The influence of motor imagery on the learning of a fine hand motor skill.

Motor imagery has been argued to affect the acquisition of motor skills. The present study examined the specificity of motor imagery on the learning of a fine hand motor skill by employing a modified discrete sequence production task: the Go/NoGo DSP task. After an informative cue, a response sequence had either to be executed, imagined, or withheld. To establish learning effects, the experiment was divided into a practice phase and a test phase. In the latter phase, we compared mean response times and accuracy during the execution of unfamiliar sequences, familiar imagined sequences, and familiar executed sequences. The electroencephalogram was measured in the practice phase to compare activity between motor imagery, motor execution, and a control condition in which responses should be withheld. Event-related potentials (ERPs) and event-related lateralizations (ERLs) showed strong similarities above cortical motor areas on trials requiring motor imagery and motor execution, while a major difference was found with trials on which the response sequence should be withheld. Behavioral results from the test phase showed that response times and accuracy improved after physical and mental practice relative to unfamiliar sequences (so-called sequence-specific learning effects), although the effect of motor learning by motor imagery was smaller than the effect of physical practice. These findings confirm that motor imagery also resembles motor execution in the case of a fine hand motor skill.

To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill?

Motor imagery is generally thought to share common mechanisms with motor execution. In the present study, we examined to what extent learning a fine motor skill by motor imagery may substitute physical practice. Learning effects were assessed by manipulating the proportion of motor execution and motor imagery trials. Additionally, learning effects were compared between participants with an explicit motor imagery instruction and a control group. A Go/NoGo discrete sequence production (DSP) task was employed, wherein a five-stimulus sequence presented on each trial indicated the required sequence of finger movements after a Go signal. In the case of a NoGo signal, participants either had to imagine carrying out the response sequence (the motor imagery group), or the response sequence had to be withheld (the control group). Two practice days were followed by a final test day on which all sequences had to be executed. Learning effects were assessed by computing response times (RTs) and the percentages of correct responses (PCs). The electroencephalogram (EEG ) was additionally measured on this test day to examine whether motor preparation and the involvement of visual short term memory (VST M) depended on the amount of physical/mental practice. Accuracy data indicated strong learning effects. However, a substantial amount of physical practice was required to reach an optimal speed. EEG results suggest the involvement of VST M for sequences that had less or no physical practice in both groups. The absence of differences between the motor imagery and the control group underlines the possibility that motor preparation may actually resemble motor imagery.