Motor imagery is a mental representation of motor behavior which has been widely used to study the cognitive basis of movement. The assumption that real movements and motor imagery (virtual movements) use the same neurobiological basis has been questioned by functional magnetic resonance data. The functional similarity in the planning of real and virtual movements was studied here by analyzing event-related EEG recordings of the Mu-activity in the sensitive-motor cortex, pre-motor cortex and supplementary motor cortex. A visual stimulus (an arrow) which displayed the information needed for planning a motion (which can be executed or imaged later after the display of a second stimulus) induced a short-lasting phase-locked Mu-response (PLr) which was wider and more widespread when it was used for the motor planning of real or virtual movements than when it was passively watched. The phase-locked Mu-response was accompanied by a persistent decrease of the Mu-rhythms which were not phase-locked to stimuli (NPLr), a response which also was more marked and generalized when stimuli were used for motor planning than when they were passively observed. PLr and NPLr were similar during motor testing and imagery testing, suggesting that both tasks activated the Mu rhythms to a similar degree. This congruency between real and virtual movements was observed in the three cortical areas studied, where the amplitude, latency and duration of the phase-locked and non-phase-locked Mu response was similar in both cases. These noticeable similarities support the idea that the same cortical mechanisms are recruited during the planning of real and virtual movements, a fact that can be analyzed better when an event-related paradigm and a high time-resolution method are used.
Motor imagery (MI) is a dynamic mental representation of motor behavior which is not accompanied by real movements (virtual movement). As virtual movements show many similarities with real movements and they are not interfered with by variables involved in the execution of real movements (e.g. somatosensory stimuli) (Sabate et al., 2007 and Sabate et al., 2008), MI has been widely used to study the cognitive basis of movement. The similarity of cognitive functions involved in real and virtual movements has been supported by chronometric studies showing that both movements consume the same execution time and use the same neurobiological basis. The time needed to execute a motor pattern is similar to that needed for its MI (Abbruzzese et al., 1996, Crammond, 1997 and Sirigu et al., 1996), and this increases in both cases with the complexity and accuracy of the task (Fitts' law) (Decety and Lindgren, 1991, Dominey et al., 1995, Jeannerod and Frak, 1999 and Sirigu et al., 1996). This real–virtual congruency has been observed in normal subjects under different conditions (e.g. during ageing) (Morales et al., 2007 and Sabate et al., 2004) and in patients with different brain lesions (e.g. stroke and Parkinson disease) (Cramer et al., 1999, Dominey et al., 1995, Gonzalez et al., 2005, Morales et al., 2007, Sirigu et al., 1996 and Thobois et al., 2000). However, this real–virtual congruency decreases in some circumstances. For instance, congruency decreases occurs when movements are automatically executed without conscious supervision (Sabate et al., 2004), or when they need an “on line” adjustment during their execution (Rodriguez, Llanos, & Sabate, 2009). In addition, the real–virtual congruency of patients with brain damage may be transiently lost just after acute lesion, requiring a time interval where the motor practice (e.g. 1–2 weeks after stroke) to restore the pre-lesion congruency (Sabate et al., 2007). These data suggest that similarities between real and virtual movements could be the result of an active process (which scans the competence of elements involved in the motor behavior to adjust motor planning and virtual imagery to the real capability of the motor system) (Sabate et al., 2007) more than the result of using the same neuronal basis (the common-basis hypothesis). Thus, the functional similarity between real and virtual movements and the neuronal networks involved in each case are still a matter of debate.
