Motor imagery ability scores are related to cortical activation during gait imagery.

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the θ, α, and ß band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). Positive correlations were identified between VMIQ and avgERD of the middle cingulum in the ß band and with avgERD of the left insula, right precentral area, and right middle occipital region in the θ band. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

Are Motor Imagery Ability scores related to cortical activity during gait imagery?

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography (hdEEG) in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the ß band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). VMIQ was positively correlated with avgERD of frontal and cingulate areas, whereas IA SCORE was positively correlated with avgERD of left inferior frontal and superior temporal regions. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

Neural oscillations during motor imagery of complex gait: an HdEEG study.

The aim of this study was to investigate differences between usual and complex gait motor imagery (MI) task in healthy subjects using high-density electroencephalography (hdEEG) with a MI protocol. We characterized the spatial distribution of α- and ß-bands oscillations extracted from hdEEG signals recorded during MI of usual walking (UW) and walking by avoiding an obstacle (Dual-Task, DT). We applied a source localization algorithm to brain regions selected from a large cortical-subcortical network, and then we analyzed α and ß bands Event-Related Desynchronizations (ERDs). Nineteen healthy subjects visually imagined walking on a path with (DT) and without (UW) obstacles. Results showed in both gait MI tasks, α- and ß-band ERDs in a large cortical-subcortical network encompassing mostly frontal and parietal regions. In most of the regions, we found α- and ß-band ERDs in the DT compared with the UW condition. Finally, in the ß band, significant correlations emerged between ERDs and scores in imagery ability tests. Overall we detected MI gait-related α- and ß-band oscillations in cortical and subcortical areas and significant differences between UW and DT MI conditions. A better understanding of gait neural correlates may lead to a better knowledge of pathophysiology of gait disturbances in neurological diseases.

Consolidation and retention of motor skill after motor imagery training.

Complex motor tasks are learned through training which results in lasting improvement in sensorimotor performance and accuracy. Learning a motor skill is commonly attained via physical execution. However, research has shown that cognitive training, such as motor imagery (MI), effectively facilitates skill learning. Neurophysiological findings suggest that learning-induced plasticity in the human motor cortex, subserving consolidation and retention of motor skills, is stronger after movement execution (ME) than after MI training. Here, we designed an experimental task able to test for the fast and slow learning phases and for retention of motor skills for both MI and ME. We hypothesize that differences between MI and ME training would emerge in terms of reduced consolidation and retention of motor skills. Twenty-four young healthy subjects were divided into two groups, performing MI or ME training. Participants wore sensor-engineered gloves and their sensorimotor performance was assessed over a period of 15 days with 4-days training. We analysed the touch duration (TD), the inter-tapping interval (ITI), movement rate and accuracy. Results showed that (i) during the first phase of acquisition of motor skills, sensorimotor performance improved similarly in MI and ME groups; (ii) during the second learning phase movement rate increased more in ME than MI group and this difference was mainly driven by differences in the duration of TD; (iii) consolidation deficits with MI training reflected in impaired retention of the acquired skills, as TD and ITI were larger and movement rate was lower in the MI group with respect to the ME, till to 10 days after the last training session. Explicit component of motor learning, accuracy, was maintained in retention phase in both groups. Following our hypothesis, our findings show that MI training is as effective as ME within the first learning phase, but consolidation and retention of motor skills are less effective following MI training. This study highlights MI limitations and suggests option to enhance MI, as by providing an external sensory feedback.

Selective sensorimotor modulation operates during cognitive representation of movement.

Before movement onset, during the reaction time, excitability of M1 is selectively modulated by somatosensory inputs, only in the movement-related muscle. If a similar mechanism operates before the onset of mental movements, then somatosensory afferent inputs are exploited during cognitive representation of movement. We assessed sensorimotor modulation through short latency afferent inhibition (SAI) paradigm before the onset of executed and imagined movements. Participants performed or imagined an abduction of index or little finger, in response to an acoustic signal. SAI was evaluated between a Warning and a Go signal and 100 ms after the Go signal, before the real or expected EMG activity. Results showed a reduction of SAI after the Go signal, in the movement-related muscle, during motor imagery as well as movement execution. There was a positive correlation between the individual degree of sensorimotor modulation during executed and mental movements and between the sensorimotor modulation during mental movements and motor imagery ability. Sensorimotor modulation operates during the cognitive representation of movement with selective disinhibition of the cortical representation of the muscle involved in the task. Sensorimotor modulation mechanisms prior to mental and executed movements likely share overlapping circuits.

Provision of somatosensory inputs during motor imagery enhances learning-induced plasticity in human motor cortex.

Motor learning via physical practice leads to long-term potentiation (LTP)-like plasticity in motor cortex (M1) and temporary occlusion of additional LTP-like plasticity. Motor learning can be achieved through simulation of movement, namely motor imagery (MI). When combined with electrical stimulation, MI influenced M1 excitability to a larger extent than MI itself. We explored whether a training based on the combination of MI and peripheral nerve stimulation (ESMI) modulates M1 LTP-like plasticity inducing retention of a new acquired skill. Twelve subjects mentally performed thumb-index movements, with synchronous electrical nerve stimulation, following an acoustic cue, in order to increase movement speed. Two control groups physically performed or imagined the same number of finger movements following the acoustic cue. After each training session, M1 LTP-like plasticity was assessed by using PAS25 (paired associative stimulation) technique. Performance was tested before and after training and 24 hours after training. Results showed that physical practice and ESMI training similarly increased movement speed, prevented the subsequent PAS25-induced LTP-like plasticity, and induced retention of motor skill the following day. Training with MI had significant, but minor effects. These findings suggest that a training combining MI with somatosensory input influences motor performance through M1 plasticity similarly to motor execution.