Cortical activity during motor execution, motor imagery, and imagery-based online feedback

Abstract

Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in “high frequency” (76–100 Hz) and “low frequency” (8–32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was ∼25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

Distributed cortical adaptation during learning of a brain–computer interface task

“…During the monitoring period, these subjects participated in multiple experimental recording sessions that took place over the course of 1-3 d. The first session began with a series of two basic functional screening tasks, in which subjects performed gross motor movement or imagined motor movement in response to a visual cue. Functional screening was conducted to determine the electrodes that exhibited statistically significant increase in HG activity during actual movement or imagined movement compared with rest (9,22). The controlling electrode that was used for online control was selected from these electrodes based on the magnitude of observed power change and anatomical relevance.…”

“…This modulation can occur in the absence of overt movement (6,9) or even when overt movement is not possible (3,10). The use of these signals to control external devices for restoration of lost function or as potential feedback signals for rehabilitation holds great promise for the future; however, our understanding of the underlying processes that drive this activity modulation is incomplete.…”

“…brain-machine interface | motor learning | plasticity | electrophysiology | high gamma O ver the last 50 years, it has been demonstrated that, when given feedback, the brain can learn to volitionally modulate the activity of single neurons (1)(2)(3)(4)(5) and populations of neurons (6)(7)(8)(9). This modulation can occur in the absence of overt movement (6,9) or even when overt movement is not possible (3,10).…”

Shared electrophysiology mechanisms of body ownership and motor imagery

“…Motor imagery has been shown to exhibit lateralized effects over sensorimotor cortex, particularly in the mu-and beta-bands (Pfurtscheller and Neuper, 1997), and also in the gamma band (Miller et al, 2010;Pfurtscheller and Neuper, 2001). To verify whether our paradigm and experimental setup using automated stroking and virtual reality was also associated with these EEG changes, we analyzed LPRs in mu, beta, and gamma bands over left and right sensorimotor scalp regions (at the Table 1 Significant electrodes used in whole-scalp cluster analyses.…”

Brain-Computer Interfaces in Medicine

“…96,97 It has been shown that epidural ECoG can provide BCI control, 98 that ECoG-based BCI performance with fixed parameters is stable over at least 5 days, 99 and that motor imagery-based BCI control using locations over motor cortex can produce ECoG changes exceeding those produced by actual movements. 100 A study in monkeys found that ECoG recordings and the performance of the model used to decode movement remained stable over several months. 101,102 These results suggest that ECoG is likely to prove practical for long-term BCI use.…”