Understanding the way in which the brain interacts with the rest of the body, and consequently how it interacts with the environment, is a process that is a huge focus in neurotechnology. Thus, in order to understand how neurotech is intended to assist people who have neuromuscular disorder, one must understand the mechanism that explains how the nervous system relays information to the muscles. Starting at the most fundamental level is the motor unit. This is essentially a combination of the motor neuron and however many muscles it innervates. When an action potential occurs at the motor neuron, it allows for the excretion of acetylcholine across the neuromuscular junction to cause constriction of the muscle fibers it innervates. This motor unit action potential is a very useful tool in neurotechnology as it can be read with the use of electromyography (EMG). This process is considered the “gold standard” of neurophysiological assessment of the neuromuscular junction and it involves passing a small needle directly through the skin and into the muscle (Article 3). After doing so, one can observe the oscillations that occur through different levels of electrical activity in the motor unit (like the difference between slight and forceful contraction). In fact, an EMG can even be used to identify when children have disorders that affect their neuromuscular junction. In one study of 878 different children, all of which had been referred for suspected myasthenia (weakness caused by inefficient ability for muscles to receive acetylcholine) or an unexplained weakness, the EMG was 84% sensitive and 71% specific for the identification of primary neuromuscular junction disorders. From this study, it was further concluded that the use of an EMG was a safe test that could be successfully undertaken without sedation in children with a highly predictive power (article 3). There are several factors that play into what occurs in the muscle after acetylcholine is transmitted to it. To begin, there is a whole cascade of recruitment. The muscle fibers are recruited smallest to largest. When the first muscle fiber is recruited, it will receive that action potential over and over again until the strength of the contraction has been reached. If that fiber is unable to achieve the contraction necessary, the motor neuron will signal the next largest fiber while continuing to increase the signal to the first small fiber. This process will repeat until the proper contraction occurs. This mechanism has been a difficult one to incorporate into the neurotechnologies that are meant to rehabilitate individuals who have lost motor function. One possible approach that has been explored is the use of electrode arrays to non-invasively stimulate muscles. However, this specific technology had a problem that was named “overflow,” which was essentially that the electrodes would accidentally target many of the surrounding muscles as opposed to the individual one they wanted to target first. One idea that has shown some promise in this area is the use of what they call “multipads” to have a more specified area of target, and when needed the system can have gaps that aren’t necessary to the function they are attempting to stimulate. The other problem these kinds of technologies often ran into was the idea of fatigue. Muscle fibers often fall into two different categories: fast twitch and slow twitch. These are measures of how quickly the muscles can contract, but consequently it is also the speed at which they become fatigued. If a muscle fiber is fast twitch, it will contract very quickly after stimulation, but it will also fatigue faster and lose its ability to exert force. The opposite is true for slow twitch fibers, which can exert a smaller force over a longer period of time. This fatigue made it very difficult for the functional electrical stimulation systems using electrode arrays to operate as they were not highly selective in their recruitment and repeatedly activated muscles that normally wouldn’t be targeted for a particular function. To circumvent this, researchers have recently focused on either varying the pulse’s temporal characteristics or using predictive models that account for fatigue to control the stimulation. These kinds of changes include closed-loop control strategies, adaptive control, neural networks, and the use of proportional integral derivative control (article 1 for like all of this paragraph). Taking one step further out from the motor unit takes us to the spinal cord. It, and the nerves contained within it, serve as the primary form of communication between the brain and the peripheral nervous system. As such, any kind of problem that occurs here can be very debilitating. A person can lose function of extremities, both in feeling and motor control. Fixing damage in the spinal cord has of course has become a huge focus in neurotechnology. One recent study (2021) that was permitted as a clinical trial by the FDA was the use of a brain-computer interface on a tetraplegic patient. The brain computer interfaced worked to transfer synaptic signals to control a prosthetic arm that had intracortical microstimulation. This intracortical microstimulation was essentially 88 wired electrodes that were implanted in the area of the motor cortex that decodes movement intent, and with it, the patient was able to have tactile sensation through the prosthetic arm. In fact, they reported that the sensations that came from use of the prosthetic arm felt as though they came from the patient’s own hand. This study has helped solve one of the major setbacks for prosthetics, which was the loss of tactile sensation (article 2). Without it, movements were clumsy and inaccurate. The brain needs these sensations in order to command the fine motor system how to respond. Finally, the last aspect to examine in motor systems is the motor cortex itself. It is split into two different sections: the premotor cortex and the primary motor cortex. The premotor cortex is in control of kinematic processes, context dependent processes, and relies heavily on input from the surrounding sensory areas. The primary motor cortex controls kinetics, plans muscle movements, and relies heavily on input from the premotor cortex. These functions have been very important for the development of neurotechnologies and have become all the more clear through electroencephalography (EEG). In one study, they utilized movement-related cortical potential (MRCP), which is a low-frequency negative shift in an EEG recording that takes place about 2 seconds prior to voluntary movement production, to predict and quantify an upcoming real or imaginary movement (article 4). This “intention of movement” information could help to make prosthetics far more accurate as they could operate as fast as a nervous system signal normally would with the extra 2 seconds of preparation. This shows the impact that using EEG on the motor cortex can bring, and how understanding these processes can further the technological advancements within neurotechnology.