Subjective Vividness of Kinesthetic Motor Imagery Is Associated With the Similarity in Magnitude of Sensorimotor Event-Related Desynchronization Between Motor Execution and Motor Imagery

Abstract

In the field of psychology, it has been well established that there are two types of motor imagery such as kinesthetic motor imagery (KMI) and visual motor imagery (VMI), and the subjective evaluation for vividness of motor imagery each differs across individuals. This study aimed to examine how the motor imagery ability assessed by the psychological scores is associated with the physiological measure using electroencephalogram (EEG) sensorimotor rhythm during KMI task. First, 20 healthy young individuals evaluated subjectively how vividly they can perform each of KMI and VMI by using the Kinesthetic and Visual Imagery Questionnaire (KVIQ). We assessed their motor imagery abilities by summing each of KMI and VMI scores in KVIQ (KMI_total and VMI_total). Second, in physiological experiments, they repeated two strengths (10 and 40% of maximal effort) of isometric voluntary wrist-dorsiflexion. Right after each contraction, they also performed its KMI. The scalp EEGs over the sensorimotor cortex were recorded during the tasks. The EEG power is known to decrease in the alpha-and-beta band (7-35 Hz) from resting state to performing state of voluntary contraction (VC) or motor imagery. This phenomenon is referred to as event-related desynchronization (ERD). For each strength of the tasks, we calculated the maximal peak of ERD during VC, and that during its KMI, and measured the degree of similarity (ERD_sim) between them. The results showed significant negative correlations between KMI_total and ERD_sim for both strengths (p < 0.05) (i.e., the higher the KMI_total, the smaller the ERD_sim). These findings suggest that in healthy individuals with higher motor imagery ability from a first-person perspective, KMI efficiently engages the shared cortical circuits corresponding with motor execution, including the sensorimotor cortex, with high compliance.

Keywords: corticospinal excitability; electroencephalogram; motor imagery; sensorimotor rhythm; the Kinesthetic and Visual Imagery Questionnaire.

FIGURE 1

Experimental recordings, paradigm, and setup. (A) Electroencephalogram (EEG) channel locations used in the present study. We recorded EEG signals from five electrodes on the scalp over the sensorimotor area of right forearm. The ground electrode (GND) was placed over the forehead, and the reference electrodes (Ref) were located at the left earlobe. (B) Experimental paradigm of the neurophysiological assessment. Participants repeated pairs of isometric voluntary wrist-dorsiflexion (VC) and its kinesthetic motor imagery (KMI).

FIGURE 2

Examples of raw force and electromyogram (EMG) signals, EEG time frequency maps, and event-related desynchronization (ERD) curves. Panels (A,B) are from a single participant (Participant A, see Table 1) and panels (C,D) are from a single participant (Participant G, see Table 1). The raw force and EMG signals are from a trial and EEG time frequency map and ERD curve from average data of all trials. (A,C) Data for voluntary contraction at 40% of maximal effort (40% VC task). (B,D) Data for kinesthetic motor imagery of the 40% VC task (40% KMI task). See more detail in Supplementary Figure 1 showing ERD curves for all participants.

FIGURE 3

Relationships between the scores of the KVIQ and the degree of similarity (ERD_sim) between VC and KMI tasks. (A) Relationship between KMI_total and ERD_sim between 10% VC and 10% KMI tasks. (B) Relationship between KMI_total and ERD_sim between 40% VC and 40% KMI tasks. (C) Relationship between VMI_total and ERD_sim between 10% VC and 10% KMI tasks. (D) Relationship between VMI_total and ERD_sim between 40% VC and 40% KMI tasks. Linear regression equations, Pearson’s correlation coefficients, r, and p-values are represented in each figure, if the relationship is significant. The black lines indicate the estimated regression lines.