The relationship between functional MRI (fMRI)-measured brain signal and muscle force and or electromyogram (EMG) is critical in interpreting fMRI data and understanding the control mechanisms of voluntary motor actions. We designed a system that could record joint force and surface EMG online with fMRI data. High-quality force and EMG data were obtained while maintaining the quality of the fMRI brain images. Using this system, we determined the relationship between fMRI-measured brain activation and handgrip force and between fMRI-measured brain signal and EMG of extrinsic finger muscles. Ten volunteers participated in the experiments (only seven subjects' data were analyzed due to excessive noise in the fMRI data of three subjects). The participants exerted 20%, 35%, 50%, 65%, and 80% of the maximal force. During each contraction period, handgrip force, surface EMG of the finger flexor and extensor muscles, and fMRI brain images were acquired. The degree of muscle activation (force and EMG) was directly proportional to the amplitude of the brain signal determined by fMRI in the entire brain and in a number of motor function-related cortical fields, including primary motor, sensory regions, supplementary motor area, premotor, prefrontal, parietal and cingulate cortices, and cerebellum. All the examined brain areas demonstrated a similar relationship between the fMRI signal and force. A stronger fMRI signal during higher force indicates that more cortical output neurons and/or interneurons may participate in generating descending commands and/or processing additional sensory information. The similarity in the relationship between muscle output and fMRI signal in the cortical regions suggests that correlated or networked activation among a number of cortical fields may be necessary for controlling precise static force of finger muscles.

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During prolonged submaximal muscle contractions, electromyographic (EMG) signals typically increase as a result of increasing motor unit activities to compensate for fatigue-induced force loss in the muscle. It is thought that cortical signals driving the muscle to higher activation levels also increases, but this has never been experimentally demonstrated. The purpose of this study was to quantify brain activation during submaximal fatigue muscle contractions using functional magnetic resonance imaging (fMRI). Twelve volunteers performed a sustained handgrip contraction for 225 s and 320 intermittent handgrip contractions ( approximately 960 s) at 30% maximal level while their brain was imaged. For the sustained contraction, EMG signals of the finger flexor muscles increased linearly while the target force was maintained. The fMRI-measured cortical activities in the contralateral sensorimotor cortex increased sharply during the first 150 s, then plateaued during the last 75 s. For the intermittent contractions, the EMG signals increased during the first 660 s and then began to decline, while the handgrip force also showed a sign of decrease despite maximal effort to maintain the force. The fMRI signal of the contralateral sensorimotor area showed a linear rise for most part of the task and plateaued at the end. For both the tasks, the fMRI signals in the ipsilateral sensorimotor cortex, prefrontal cortex, cingulate gyrus, supplementary motor area, and cerebellum exhibited steady increases. These results showed that the brain increased its output to reinforce the muscle for the continuation of the performance and possibly to process additional sensory information.

A dynamical model is presented as a framework for muscle activation, fatigue, and recovery. By describing the effects of muscle fatigue and recovery in terms of two phenomenological parameters (F, R), we develop a set of dynamical equations to describe the behavior of muscles as a group of motor units activated by voluntary effort. This model provides a macroscopic view for understanding biophysical mechanisms of voluntary drive, fatigue effect, and recovery in stimulating, limiting, and modulating the force output from muscles. The model is investigated under the condition in which brain effort is assumed to be constant. Experimental validation of the model is performed by fitting force data measured from healthy human subjects during a 3-min sustained maximal voluntary handgrip contraction. The experimental results confirm a theoretical inference from the model regarding the possibility of maximal muscle force production, and suggest that only 97% of the true maximal force can be reached under maximal voluntary effort, assuming that all motor units can be recruited voluntarily. The effects of different motor unit types, time-dependent brain effort, sources of artifacts, and other factors that could affect the model are discussed. The applications of the model are also discussed.