Detecting energy
Although single-celled organisms have membrane receptors that can detect light, heat, and pressure, multicellular organisms devote large, complex cell systems for detecting these and other forms of environmental energy. Cellular systems allow the production of lenses in the visual system for seeing and mechanical amplification in the auditory system for hearing, to name but two examples. Cellular systems in multicellular organisms allow energy detection to be amplified and differentiated, which supports nuanced, complex behavioral outcomes based on the detection.
Cellular motors
Single cells move via cilia, flagella, and other mechanisms such as amoeboid movement. Multicellular organisms use cilia to move substances within the body, but moving the entire body requires other mechanisms.
Cilia and flagella
Cilia are common in multicellular organisms. Motile cilia on cells in the lungs remove debris by carrying it up the windpipe. Immotile or primary cilia have evolved in many multicellular animals into sensory receptors, such as photoreceptor outer segments where the light-absorbing photopigment molecules are located. Auditory hair cells and some olfactory receptors may also be derived from cilia. Flagella are used by sperm cells to propel themselves. However, moving an entire large body via cilia or flagella is not very effective, particularly on land.
Contraction
Animals evolved specialized cells called muscle cells, for movement. Muscle cells work by contracting. In voluntary skeletal muscle, muscle cells contract by being driven by motor neurons. A large group of contracting muscle cells pulls on a tendon that is attached to a bone, moving the joint.
Neurons accomplish their role of coordinating and communicating activity across the body though chemical communication and electricity. The electrical properties of neurons allow them to communicate information precisely across long distances to specific target cells. In the case of connections to muscles, motor neurons produce movement by inducing their target muscle cells to contract.
Coordinating responses in simple circuits
Nervous systems are complex and hard to study. The human brain has been estimated to contain about 100 billion cells (a recent estimate that used a novel method of counting neural nuclei in emulsified brains produced a figure of 86 billion). All these neurons likely have from 100 trillion to a quadrillion synapses between them. This presents the challenges that we don’t know how single cells work, really, and we don’t know or cannot even count all the connections between them. So, where do we start?
People often wonder why scientists study the nervous systems of flies, worms, and squids. The reason is that these systems often have advantages in that the cells are fewer, bigger, or more amenable to genetic manipulation. Hodgkin and Huxley won the Nobel Prize for deducing the ionic basis of the action potential in the squid giant axon, which is almost a millimeter in diameter and can be handled and impaled with microelectrodes. It is also possible to squeeze out its internal contents and replace them with a specified salt solution by which it could be determined which ions flow which way through the membrane during electrical activity.
Many invertebrates such as worms and insects have less than a few thousand neurons that are more or less the same from animal to animal. Individual neurons in specific places are even numbered and named in some species. This vastly simplifies the problem of working out a complete neural circuit, including which neurotransmitters are used by which neurons to activate other neurons, and how all the electrical activity is integrated.
Robotics and bionics
Many scientists feel that we only understand a system when we can simulate it. This involves creating an artificial nervous system that simulates some properties of real ones. In robotics, behavior is simulated. A robot may perform some task, like welding in a car factory, that is otherwise done by intelligent humans. The electronic controllers of such robots can involve the use of neuron-like elements called artificial neural nets (ANNs) that emulate biological control systems. However, most controllers are written in standard computer languages using mathematical algorithms that may function quite differently from biological organizations.
Bionics is the field of applying biological principles of operation to man-made devices. An airplane is a bionic derivative of bird flight, which, however, differs in using engines for thrust rather than flapping wings. A recent use of bionics in computation involves devices called memristors that are integrated circuit devices that act like modifiable synapses between neurons. At this point, it’s unclear whether memristors devices will have advantages for computing compared to traditional electronic computation done with transistors. They may, however, become a useful tool for simulating complex nervous systems to understand them.
Organizing the Nervous System
The study of the nervous system intrinsically involves many fields. Neurobiology, our focus here, depends on physiology, anatomy, biochemistry, molecular biology, cognitive and behavioral psychology, and artificial intelligence. The basic goals of neurobiology are to describe how the nervous system operates in terms of what the system does, how it’s built, and how it works. We try to do these things by considering first various subsystems of the brain and nervous system, and then looking carefully at function in the neural circuitry within those subsystems.
Movement basics: Muscles and motor systems
Chapter 5 deals with the main purpose of the nervous system, the production of movement. Generally, animals move and have nervous systems to control movement, whereas plants don’t. Voluntary movement, controlled by the central nervous system, involves the contraction of striated muscle triggered by the receipt of acetylcholine, a neurotransmitter released by motor neurons.
Individual muscles are made of thousands of muscle cells innervated by several different types of motor neurons. The contraction of the muscle is produced by the coordinated activity of all these motor neurons that fire in a specified sequence and rate depending on the type of movement programmed, its speed, duration, and variation in load the limb experiences as it moves. Differences or errors between the central commands and actual limb position and acceleration are reported by sensory neurons in the muscles, tendons, and joints that relay this information to the spinal cord in a feedback loop that adjusts the motor neuron output to match the upper-level command goal.
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