Chapter 1: Motor control

Motor control refers to the process by which creatures that have a nervous system are able to regulate their movements. In addition to instinctive taxis, conscious voluntary motions, subconscious muscle memory, and involuntary reflexes are also components of motor control.

It is important for the neural system to integrate multimodal sensory input (both from the outside world and from proprioception) in order to govern movement. Additionally, the nervous system must elicit the necessary signals in order to recruit muscles in order to accomplish. This pathway encompasses a wide range of fields, such as multisensory integration, signal processing, coordination, biomechanics, and cognition. The computational issues that are associated with this pathway are frequently explored under the phrase sensorimotor control. It is essential to have effective motor control in order to interact with the outside environment in order to accomplish one's goals, as well as to maintain proper posture, balance, and stability.

A number of scholars, the most of whom are neuroscientists who study movement and include Daniel Wolpert and Randy Flanagan, contend that the reason brains exist at all is because of the ability to govern movement.

The firing of action potentials by motor neurons, which leads to the contraction of muscles, is necessary for all actions, such as touching your nose using your fingers. In human beings, around 150,000 motor neurons are responsible for controlling the contraction of approximately 600 muscles. A subset of 600 muscles must contract in a temporally accurate pattern in order to carry out movements. This is necessary in order to generate the appropriate force at the appropriate time.

The term "motor unit" refers to the collection of muscle fibers that are innervated by a single motor neuron. As an illustration, the rectus femoris is associated with around one million muscle fibers, each of which is regulated by approximately one thousand motor neurons. Every single one of the innervated muscle fibers undergoes contraction as a result of activity in the motor neuron, which allows them to work together as a single unit. The action potential frequency, also known as the spike rate, in the motor neuron is increased, which results in a rise in the force of muscle fiber contraction, all the way up to the maximal force. The contractile characteristics of the muscle fibers are what determine the maximum force that can be applied. All of the muscle fibers that are contained inside a motor unit are of the same kind (for example, type I fibers, which are slow-twitch, or type II fibers, which are fast-twitch), and a particular muscle is composed of motor units that are of multiple types. The motor units that make up a particular muscle are brought together and referred to as a motor pool.

In a given muscle, the force that is produced is dependent on the following factors: 1) the number of active motor neurons and the spike rates of those neurons; 2) the contractile characteristics of the muscle fibers and the number of muscle fibers that are innervated by the active neurons. It is possible to create additional force by increasing the spike frequencies of activated motor neurons and/or by recruiting more motor units that are physically stronger. On the other hand, the manner in which the muscular force generates movement in the limbs is contingent upon the biomechanics of the limbs, such as the origin of the tendon and the muscle (which bone and at what specific place), as well as the location of the muscle's attachment to the bone that it moves.

The recruitment of motor units within a motor pool follows a conventional order, beginning with motor units that generate negligible amounts of force per spike and progressing to those that generate the greatest amount of force per spike. There is a correlation between the gradient of motor unit force and a gradient in the size of the soma of motor neurons as well as the electrical excitability of motor neurons. Henneman's size principle is a major discovery in the field of neurology and an organizing principle of motor control. It was named after the relationship that Elwood Henneman described, which is now known as Henneman's size principle.

In order to do tasks that require modest forces, such as making constant adjustments to one's posture, motor units that have fewer muscle fibers and contract slowly yet are less fatigueable are utilized. When a greater amount of force is required, motor units that include fast-twitch muscle fibers that are also fast-fatigeable are recruited.

When it comes to movement, the nervous system is responsible for determining which motor neurons are activated and at what times. It is believed that the discovery that a recruitment order exists inside a motor pool is a result of a simplification of the problem. If a specific muscle is supposed to create a specific force, then the motor pool should be activated along its recruitment hierarchy until that force is produced.

So the question is, how do you decide what kind of force to generate in each muscle? Here are some of the challenges that the nervous system must overcome in order to solve this dilemma.

There is a significant amount of ongoing research that is currently being conducted to investigate how the nervous system deals with these challenges, both at the behavioral level and how neural circuits in the brain and spinal cord represent and deal with these aspects in order to produce the fluid motions that we see in animals.

The concept of "optimal feedback control" is a significant theoretical framework that has been applied to these computation challenges.

The computational challenges described above are encountered by all organisms; hence, brain circuits for motor control have been investigated in a wide variety of organisms, including humans, primates, horses, cats, mice, fish lamprey, flies, locusts, and nematodes, amongst many others. Mice and monkeys are examples of mammalian model systems that provide the most straightforward comparative models for human health and disease (Mammal Model Systems). They are utilized extensively in the research of the function of higher brain regions that are shared by vertebrates. These regions include the cerebral cortex, the thalamus, the basal ganglia, and the deep brain medullary and reticular circuits for the control of motor functions. The genetics and neurophysiology of motor circuits in the spine have also been researched in mammalian model organisms. However, the presence of protective vertebrae makes it difficult to investigate the functional role that spinal circuits play in animals that behave. It has been found that both larval and adult fish have been helpful in determining the functional logic of the local spinal circuits that are responsible for coordinating the activity of motor neurons. The organization of arthropod nervous systems into ganglia that control each leg has enabled researchers to record from neurons that are dedicated to moving a specific leg during behavior. Although invertebrate model organisms do not have the same brain regions as vertebrates, their brains must solve similar computational issues. As a result, it is believed that their brains have brain regions that are homologous to those involved in motor control in the nervous system of vertebrates.

Additionally, the importance of central pattern generators in driving rhythmic motions has been proven by model systems. The term "central pattern generator" refers to a neural network that is capable of producing rhythmic activity even in the absence of an external control signal. This could be a signal that is transmitted from the brain or feedback signals that are received from sensors in the limbs (for example, proprioceptors). It has been demonstrated that genuine CPGs are present in a number of important locations that are responsible for motor control, including as the stomachs of arthropods and the pre-Boetzinger complex, which is responsible for controlling breathing in humans. In addition, as a theoretical idea, CPGs have shown to be helpful in illustrating the potential role that sensory feedback plays in the regulation of motor functions.

There is a progression of steps that occur throughout the process of being aware of a sensory stimulation and utilizing that knowledge to affect an action. To get insight into these stages, one can use the reaction time of basic tasks as a source of information. A person's reaction time is the amount of time that passes between the moment that the stimulus is introduced and the moment that the response is completed. The amount of time required to finish a movement is referred to as the movement time. The difference in response times to a choice task was employed by Franciscus Donders, who conducted some of the first tests on reaction time. He used this information to determine the amount of time required to process the stimuli and select the appropriate response. This method, despite the fact that it is ultimately erroneous, gave rise to the concept that reaction time was composed of the recognition of a stimulus, followed by the selection of a response, and finally culminating in the execution of the appropriate movement. Further investigation has shown evidence that these stages actually exist; nonetheless, the response selection period of any reaction time increases as the number of possible choices expands. This relationship is referred to as Hick's law, and it is a relationship that has been observed.

The definition of a closed loop system for human movement that is considered to be the most traditional comes from Jack A. Adams (1971). A reference of the desired output is compared to the actual output via the use of error detection systems; the error is...