Neurobiology For Dummies. Frank Amthor

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external environment, but also for the internal environment created by the structure of the organism itself. Neural cells evolved as sensors, movers (muscles), and communicators.

      Detecting food, waste, and toxins

      Neurons have some functions that are like all other cells, including those of many single-celled organisms. These include taking in energy through glucose, and oxygen to fuel metabolism. Neurons also excrete metabolic waste products and carbon dioxide. Many of these functions are carried out by membrane receptors and transporters, some of which are highly conserved across the evolution of life on earth. But neurons adapted many functions that single cells use to interact with the environment in order to interact with each other.

      Detecting other cells: Hormones and neurotransmitters

      Even primitive single-celled and small multicellular organisms respond to the effects of other organisms around them. This happens via their metabolic waste products that signal overcrowding or the depletion of food resources. Neurons evolved the ability to include some specific substances in their waste excretions to signal to other neurons about the state of some part of the organism.

      

These signaling substances evolved to be secreted specifically into the extracellular space around cells in multicellular organisms as hormones. The next step was the extension of a cellular process, such as an axon, from one cell to the vicinity of several distant specific cells where a specific signaling substance, called a neurotransmitter, was released. Now, instead of a multicellular signaling soup, there are circuits.

      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

      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 are necessary for coordinated movement in multicellular animals. Different muscles must be contracted in an organized manner, and information from the senses must be sent to remote parts of the body neurons to coordinate movement.

      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.

      

Recent progress has been made in making model systems from mammals, using either brain slices or neural tissue cultures that can be mounted on a microscope and recorded and stimulated under well-controlled conditions.

      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.

      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

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