Motor planning can enable integration of sensory input to generate motor execution. However, how the brain analyses visual information and modulates its signals to the muscle have been not well studied in human. The aim of this study was to investigate the dimensionality effect of myoelectric-controlled interface (MCI) on motor planning and motor execution during elbow tracking movements. Twenty right-handed healthy subjects were recruited to complete tracking tasks by modulating their biceps and triceps activation within one-dimensional and two-dimensional MCI. The electromyography (EMG) signals of the biceps and triceps was recorded to calculate the normalized muscle activation, while the functional near infrared spectroscopy (fNIRS) signals of the prefrontal cortex (PFC) and bilateral motor cortex (MC) were also collected to gain the brain activation simultaneously. The results showed that the activation of antagonist muscle was significant lower within two-dimensional MCI than that within one-dimensional MCI at the muscle level. At the brain level, it was found an obvious higher activation in the PFC and the left MC within two-dimensional MCI than that within one-dimensional MCI. The current EMG-fNIRS study confirmed that visual feedback can influence motor planning and motor execution, and the PFC and bilateral MC are the likely targeted sites of the proactive inhibition of the antagonist muscle. This study adds a new perspective to possible visual regulation of neuromuscular control, which might be an effective rehabilitation method to improve abnormal muscle coordination in the clinic.
Objective. Previous neuroimaging studies mainly focused on static characteristics of brain activity, and little is known about its characteristics over time, especially in post-stroke (PS) patients. In this study, we aimed to investigate the static and dynamic characteristics of brain activity after stroke using functional magnetic resonance imaging (fMRI). Approach.Twenty ischemic PS patients and nineteen healthy controls (HCs) were recruited to receive a resting-state fMRI scanning. The static amplitude of low-frequency fluctuations (sALFF) and fuzzy entropy of dynamic ALFF (FE-dALFF) were applied to identify the stroke-induced alterations. Main results. Compared with the HCs, PS patients showed significantly increased FE-dALFF values in the right angular gyrus (ANG), bilateral precuneus (PCUN), and right inferior parietal lobule (IPL) as well as significantly decreased FE-dALFF values in the right postcentral gyrus (PoCG), right dorsolateral superior frontal gyrus (SFGdor), and right precentral gyrus (PreCG). The ROC analyses demonstrated that FE-dALFF and sALFF possess comparable sensitivity in distinguishing PS patients from the HCs. Moreover, a significantly positive correlation was observed between the FE-dALFF values and the Fugl-Meyer Assessment (FMA) scores in the right SFGdor (r =0.547), right IPL (r =0.522), and right PCUN (r =0.486). Significance. This study provided insight into the stroke-induced alterations in static and dynamic characteristics of local brain activity, highlighting the potential of FE-dALFF in understanding neurophysiological mechanisms and evaluating pathological changes.
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