Experiment protocols for brain-body imaging of locomotion: A systematic review

Abstract

IntroductionHuman locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings.MethodsThis paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols.ResultsThe findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments.DiscussionFinally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.

Neuropsychological Activations and Networks While Performing Visual and Kinesthetic Motor Imagery

“…In a study of kinesthetic imagery, the thalamus and basal ganglia were activated during imagery of an upright stance; the parahippocampal cortical areas during imagery of walking; and the vestibular and somatosensory cortex areas during imagery of running [14][15][16]. This indicates that the brain functions related to an actual motion operate similarly during kinesthetic imagery of that same motion.…”

From brain to worksite: the role of fNIRS in cognitive studies and worker safety

“…Its high spatial resolution allows for precise localization of brain activity, a valuable asset in cognitive research. However, fMRI has limitations, including the large, expensive equipment and the requirement for subjects to remain immobile within a narrow MRI machine, which can be restrictive in cognitive research related to construction worker safety (101).…”

Electrophysiological approaches to understanding brain-muscle interactions during gait: a systematic review

“…Specifically, it records the fluctuations in electrical potential generated by the collective activity of neurons through electrodes placed on the scalp. Its excellent temporal resolution allows for the real-time examination of brain activity during dynamic tasks like walking (Korivand et al, 2023; Walsh and Cowey, 2000). Recent advancements in EEG processing techniques, such as advanced artifact correction methods, have significantly enhanced the quality of recordings during movement (Zhao et al, 2021).…”

“…Additionally, the utilization of volume conduction models has contributed to improved spatial resolution (Taberna et al, 2021, 2019). Therefore, EEG is well-suited to study temporal and spatial brain dynamics during gait (Korivand et al, 2023).…”