Abstract

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue comprising a central and peripheral component, which demands a gradually increasing effort. However, the brain contribution to the enhancement of effort to cope with progressing fatigue lacks a complete understanding. The intermittent motor tasks (IMTs) closely resemble many activities of daily living (ADL), thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects performing IMT until self-perceived exhaustion. Fourteen participants (median age 51.5 years; age range 26−72 years; 6 males) repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted ≈5 s with a 2-s rest between trials. The force, EEG, and surface EMG (from elbow joint muscles) data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency (TF) characteristics across the conditions. The outcome of channel- and source-level TF analyses reveals that the theta, alpha, and beta power spectral densities vary in proportion to fatigue levels in cortical motor areas. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post-contraction EEG data. The findings would enhance our understanding on the etiology and physiology of voluntary motor-action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks, evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies, and develop therapeutic strategies for restoring the patients' ability to participate in ADL by mitigating the central and muscle fatigue.

Highlights

  • Fatigue interferes with task performance in multiple ways—slowing down, improper execution, or failure to accomplish

  • Out of 124 EEG channels, we selected six channels, namely FC3, C1, C3, C5, CP1, and CP3, corresponding to the scalp electrodes mounted over the contralateral cortical regions associated with the intermittent motor tasks (IMTs) for the channel-level analysis

  • To perform the source-level analysis, first, the independent component (IC) were estimated from the multichannel EEG signals by the Independent Component Analysis (ICA) algorithm and fitted with the equivalent dipoles via DIPFIT toolbox

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Summary

Introduction

Fatigue interferes with task performance in multiple ways—slowing down, improper execution, or failure to accomplish. Unpleasant sensations such as pain, discomfort, and increased effort can accompany the muscle fatigue. Physical fatigue can be viewed as the decline in the voluntaryforce-generating capacity of the neuromuscular system induced by a physical activity (Fry et al, 2017). It stems from active skeletal muscles that are involved in the peripheral processes as well as supraspinal mechanisms within the brain, comprising physiological and psychological aspects (Gandevia, 2001; Berchicci et al, 2013). The fatigue processes at or distal to the neuromuscular junction is referred to as peripheral fatigue and those attributed to the central nervous system affecting the neural drive to the muscle as central fatigue (Bigland-Ritchie et al, 1978)

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