Sleep loss reduces muscle endurance by rewiring brain networks, study finds

A new small study reveals that getting less than four hours of sleep reduces physical endurance by altering how different networks in the brain communicate. Rather than muscles tiring out faster, sleep-deprived brains struggle to maintain the neural signals required to sustain a physical effort. These findings were published in the International Journal of Psychophysiology.

Physical fatigue is often viewed as a straightforward matter of muscles running out of energy and accumulating metabolic waste. Yet the brain plays a primary role in determining how long a person can sustain a physical effort. This concept is known as central fatigue. When the brain senses a lack of resources, it can prematurely reduce the electrical signals sent down the spinal cord to the muscles.

This protective mechanism causes a person to feel exhausted even if their muscle tissues are still physically capable of continuing the activity. To understand how central fatigue develops, researchers look at the brain as a collection of distinct networks rather than isolated regions. For instance, the default mode network is highly active during mind-wandering, introspection, and rest. The central executive network handles focused cognitive tasks and goal-directed attention.

The sensorimotor network manages the planning and execution of physical movements. Finally, the salience network acts as a neural switchboard, helping the brain identify important sensory information and shift attention between the inward-focused default mode and the outward-focused central executive networks. Puyan Chi and Chengcheng Zhu led a research team to investigate how a severe lack of sleep affects physical endurance and the coordination of these large-scale brain networks.

The researchers focused on a specific type of physical effort known as an isometric contraction. This occurs when a muscle generates force but does not change in length, such as when holding a heavy box directly in front of you. The team wanted to observe how acute sleep restriction changes the frequency of brain waves as participants perform an exhausting isometric task.

The researchers recruited 35 healthy male college students who regularly engaged in strength training. For the experiment, each participant completed two different sleep conditions separated by at least three days to prevent lingering fatigue. In the normal sleep condition, participants slept for more than seven hours while wearing a sleep monitor. In the restricted sleep condition, participants stayed awake until three in the morning and were woken up at seven in the morning, ensuring they slept for less than four hours.

Following each sleep condition, the participants arrived at the laboratory for testing. The researchers first recorded their brain activity while they rested quietly using an electroencephalogram. This non-invasive device measures electrical activity through dozens of sensors placed across the scalp. The researchers used software to clean the data, filtering out the electrical noise caused by blinking and minor head movements.

The participants then performed a physical task. They sat against a wall with their right arm bent at a ninety-degree angle. The researchers applied a load to their wrist equal to thirty percent of their maximum bicep strength using an elastic band. This required the participants to maintain a steady isometric contraction of their bicep muscle at a moderate intensity.

The participants held this position until they were completely exhausted, reporting a high degree of perceived exertion and eventually failing to keep their arm bent. During the physical task, the researchers continuously recorded both the participants’ brain waves and the electrical activity of their bicep muscles. The muscle activity was tracked using an electromyogram, which detects the firing rate of muscle fibers.

The researchers broke the brain wave data down into different frequency bands, such as slower theta waves and faster beta and gamma waves. By tracking these frequencies, they analyzed the strength of the neural connections between the default mode, central executive, sensorimotor, and salience networks. The sleep-restricted participants exhausted their muscles much faster than they did after a normal night of sleep. The data from the muscle sensors showed that the bicep muscles tired in a very similar manner under both sleep conditions.

The electromyogram readings revealed no statistically significant differences in the rate of peripheral muscle fatigue. Because the physiological rate of muscle exhaustion did not change, the researchers concluded that the early termination of the task stemmed from the brain prematurely halting the effort. The brain wave analysis revealed notable changes in how the participants’ neural networks communicated. While resting after restricted sleep, the participants exhibited heightened connectivity across several brain networks in the theta, beta, and gamma frequency bands.

The central executive network in particular formed stronger connections with the other regions. The researchers interpreted this as a compensatory state. The sleep-deprived brain was working harder and consuming more energy just to maintain a basic level of wakeful alertness. Once the physical task began, this neural pattern shifted.

The sleep-restricted brains showed weakened connectivity across the theta, alpha, and beta frequency bands compared to the well-rested brains. The connections between the sensorimotor network and the default mode and salience networks broke down. This breakdown made it difficult for the brain to integrate sensory feedback from the straining arm with the motor commands needed to keep the bicep contracted.

Under normal sleep conditions, the researchers observed a negative correlation between physical endurance and the connection between the sensorimotor network and the default mode network. A weaker connection meant better physical performance. This indicates that a well-rested brain efficiently suppresses the daydreaming default mode network, directing all available energy toward maintaining the physical task.

After sleep restriction, this relationship completely reversed. Higher connectivity between the sensorimotor and default mode networks correlated with the duration the participants could hold the bicep contraction. The researchers suspect that the sleep-deprived brains lost their ability to exert top-down control. Instead of suppressing the default mode network, the struggling brain attempted to recruit it to help maintain the muscle contraction, revealing a state of profound neural inefficiency.

The study relied on a small sample of young, healthy men, meaning the results might not apply to women, older adults, or clinical populations. The research only evaluated a single instance of severe sleep loss rather than chronic sleep deprivation, which might alter the brain differently over time. The experiment also tested only one type of stationary muscle contraction at a single intensity level.

Dynamic exercises like running or weightlifting could place entirely different demands on the central nervous system. Future investigations will need to track subjective factors like motivation and mood, which might influence physical performance alongside the observed neural changes. The study, “Changes in athletes’ brain network connections during isometric muscle contractions after sleep restriction,” was authored by Chengcheng Zhu, Ting Peng, Jing Song, Aiping Chi, Xin Wei, and Puyan Chi.