Synchronous correlation brain and muscle oscillations during motor task execution is termed as functional coupling. Functional coupling between two signals appears with a delay time which can be used to infer the directionality of information flow. Functional coupling of brain and muscle depends on the type of muscle contraction and motor task performance. Although there have been many studies of functional coupling with types of muscle contraction and force level, there has been a lack of investigation with various motor task performances. Motor task types play an essential role that can reflect the amount of functional interaction. Thus, we examined functional coupling under four different motor tasks: real movement, intention, motor imagery and movement observation tasks. We explored interaction of two signals with linear and nonlinear information flow. The aim of this study is to investigate the synchronization between brain and muscle signals in terms of functional coupling and delay time. The results proved that brain–muscle functional coupling and delay time change according to motor tasks. Quick synchronization of localized cortical activity and motor unit firing causes good functional coupling and this can lead to short delay time to oscillate between signals. Signals can flow with bidirectionality between efferent and afferent pathways.

Correlation between brain and muscle signal is referred to as functional coupling. The amount of correlation between two signals greatly depends on the motor task performance. In this study, we designed the experimental paradigm with four types of motor tasks such as real hand grasping movement (RM), movement intention (Inten), motor imagery (MI) and only looking at virtual hand in three dimensional head mounted display (OL). We aimed to investigate EEG-EMG correlation with linear and nonlinear coupling methods. The results proved that high correlation could be occurred in RM and Inten tasks rather than MI and OL tasks in both linear and nonlinear methods. High coherence occurred in beta and gamma bands of RM and Inten tasks whereas no coherence was detected in MI and OL tasks. In terms of nonlinear correlation, the high mutual information was detected in RM and Inten tasks. There was slight mutual information in MI and OL tasks. The results showed that the coherence in the contralateral brain cortex was higher than in the ipsilateral motor cortex during motor tasks. Furthermore, the amount of EEG-EMG functional coupling changed according to the motor task executed.

The first game-based treatment for children with attention-deficit hyperactivity disorder (ADHD) was approved by the United States Food and Drug Administration (FDA) in 2020. This game was developed for use at home as part of everyday training and can be used along with one’s usual training plan. In this game, two tasks are performed in parallel: (1) a perceptual discrimination targeting task (response and not response and avoiding responding to sudden pop-up targets) and (2) a sensory-motor navigation task (players continuously adjust their location to interact with or avoid positional targets). However, the brain activity of people playing this game was not examined, and the immersive environment (3D virtual world) was not considered. Therefore, we aimed to develop a system to investigate brain activity using electroencephalography (EEG) during multitask gameplay in virtual reality (VR). In this experiment, we focused on the difference between the success and failure of the Go/No-Go task in a multitask game. We created a color discrimination task and a target tracking task in VR. The content of this game task was designed using previous multitask training. EEG and event data were recorded. Using event data, we can analyze the data in detail. We divided the trial types (Go and No-Go) and results (success and failure). We then compared the success and failure of each task. In the Go trial, the relative theta power in success at Fz was significantly higher than that of failure. However, no difference in power was observed in the No-Go trial. On the other hand, theta power was no different between success and failure in the other task. These results of the Go trial suggest that the participants were attentive to processing both tasks. Thus, it is possible that theta power in the frontal area 1 s before stimulation could predict the success or failure of the Go trial. On the other hand, the results of the No-Go trial may be due to the low number of No-Go failure trials and the fact that stimulus oversight is one of the factors for success.

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