Which part of the neuron sends signals either to other neurons or effector cells
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Neurons send signals to other cells as electrochemical waves traveling along the axons (from the Greek άξων, (axon), meaning “axis”). These signals activate the release of chemicals, called neurotransmitters, over the neurons junctions, called synapses. Neurons do not touch each other; the synapses, from the Greek συνάπις (synapsis), meaning “conjunction”, are small gaps of approximately 20–40 nm (just for the sake of comparison, a sheet of paper is about 100,000 nm thick). The signals are transferred over this gap via a chemical process, and not an electrical process. Through an impulse, the axon terminals of a neuron release neurotransmitters over the synapses. On the other side, the adjacent membrane (dendrite, muscle or gland cell), with the appropriate chemical receptors, receives the neurotransmitters. This may trigger an electrical impulse across the neighbor neuron cell. The signal starts electrical, becomes chemical and returns to be electrical over the next neuron. The time for neurotransmitter action is between 0.5 and 1 ms. Over the axon, the transmission of the electric pulse occurs by differences of potentials. Instead of passing along the entire axon, the signal jumps from one node of Ranvier to the next. Show
The soma (cell body) is the central and largest part of the neuron. It contains the nucleus of the cell, and, for this reason, it is the place where most of the protein synthesis occurs. The nucleus ranges from 3 to 18 μm in diameter. The cell body receives the signals from other neurons through the dendrites. Dendrites are cellular extensions connected to the soma. The overall shape and structure is referred to as a dendritic tree. In fact, the term “dendrite” comes from the Greek δένδρον (déndron), meaning “tree”. Our brain is constantly changing; we learn because our synaptic relations change, i.e. our neurons change [KAN 03]. If you are able to remember anything you read from this book, from more than 30 s ago (the time information is stored in the short-term memory [ATK 71]), then your brain has necessarily changed during the reading. If a synapse is used in a consistent, coherent and important way, it tends to be maintained. If 10 years from now you still remember something, anything, from this book, this means that the connections were stable and the change, in a 5 s reading of a single phrase, was preserved all this time. The neuron changes constantly; it grows, and when growing it samples the environment. For example, in case it reaches another neuron, which presents a repulsive cue, the axon abandons that direction and tries another. The search is more or less random, but there are moments where the reorientation occurs, given attractors and repellers. The axon tends to grow in the direction of attractors, and away from repulse signalings [TES 96]. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B978178548021850003X Neuromuscular SystemC.-P. Ko, in International Encyclopedia of the Social & Behavioral Sciences, 2001 The neuromuscular system is composed of a neural circuit including motor neurons, sensory neurons, and skeletal muscle fibers. The system is essential to movements of the body, the control of posture, and breathing. The motor nerve fiber makes synaptic contacts with the muscle fiber at the neuromuscular junction. The neuromuscular junction is composed of three cellular elements: the nerve terminal, glial cells (perisynaptic Schwann cells), and the muscle fiber. Inside the nerve terminal, there are numerous synaptic vesicles containing the neurotransmitter, acetylcholine. The electrical impulse at the nerve terminal increases an influx of calcium ions that trigger the exocytosis of synaptic vesicles and release of acetylcholine at the active zone. Acetylcholine binds acetylcholine receptors, which are concentrated at the neuromuscular junction, on the muscle surface. The unbound acetylcholine is rapidly removed by acetylcholinesterase. The binding of acetylcholine to the acetylcholine receptors results in membrane depolarization, which, in turn, triggers a release of calcium ions from the sarcoplasmic reticulum into muscle cytosol and initiates muscle contraction. Agrin and neuregulin play important roles in the aggregation and synthesis of acetylcholine receptors, respectively. The perisynaptic Schwann cells sprout profusely after nerve injury and the glial sprouts may lead and guide nerve terminal regeneration and sprouting. The muscle spindle and the Golgi tendon organ provide information on the muscle length and tension, respectively, to the spinal cord. The motor output and the sensory input constitute a circuit of the stretch reflex that maintains proper muscle fiber length. Neurotoxins, such as α-bungarotoxin, botulinum toxin, and nerve gases are deadly when they stop an animal's breathing by interfering with synaptic transmission in the diaphragm muscle. Diseases of the neuromuscular system include disorders affecting transmission, such as, myasthenia gravis; motor neuron degeneration, such as amyotrophic lateral sclerosis; and muscular dystrophies. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B0080430767034823 ElectricityPaul Davidovits, in Physics in Biology and Medicine (Fifth Edition), 2019 13.1.1 The NeuronThe neurons, which are the basic units of the nervous system, can be divided into three classes: sensory neurons, motor neurons, and interneurons. The sensory neurons receive stimuli from sensory organs that monitor the external and internal environment of the body. Depending on their specialized functions, the sensory neurons convey messages about factors such as heat, light, pressure, muscle tension, and odor to higher centers in the nervous system for processing. The motor neurons carry messages that control the muscle cells. These messages are based on information provided by the sensory neurons and by the central nervous system located in the brain. The interneurons transmit information between neurons. Each neuron consists of a cell body to which are attached input ends called dendrites and a long tail called the axon which propagates the signal away from the cell (see Fig. 13.1). The far end of the axon branches into nerve endings that transmit the signal across small gaps to other neurons or muscle cells. A simple sensory-motor neuron circuit is shown in Fig. 13.2. A stimulus from a muscle produces nerve impulses that travel to the spine. Here the signal is transmitted to a motor neuron, which in turn sends impulses to control the muscle. Such simple circuits are often associated with reflex actions. Most nervous connections are far more complex.  Figure 13.1. A neuron. Figure 13.2. A simple neural circuit. The axon, which is an extension of the neuron cell, conducts the electrical impulses away from the cell body. Some axons are long indeed—in people, for example, the axons connecting the spine with the fingers and toes are more than a meter in length. Some of the axons are covered with a segmented sheath of fatty material called myelin. The segments are about 2 mm long, separated by gaps called the Nodes of Ranvier. We will show later that the myelin sheath increases the speed of pulse propagation along the axon. Although each axon propagates its own signal independently, many axons often share a common path within the body. These axons are usually grouped into nerve bundles. The ability of the neuron to transmit messages is due to the special electrical characteristics of the axon. Most of the data about the electrical and chemical properties of the axon is obtained by inserting small needlelike probes into the axon. With such probes it is possible to measure currents flowing in the axon and to sample its chemical composition. Such experiments are usually difficult as the diameter of most axons is very small. Even the largest axons in the human nervous system have a diameter of only about 20μm(20×10-4cm). The squid, however, has a giant axon with a diameter of about 500μm(0.5 mm), which is large enough for the convenient insertion of probes. Much of the information about signal transmission in the nervous system has been obtained from experiments with the squid axon. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780128137161000136 Artificial Neural Networks: NeurocomputationR.M. Golden, in International Encyclopedia of the Social & Behavioral Sciences, 2001 2.1 Quasilinear Formal Neurons and LearningBy the late 1960s, the biological assumption underlying generalized MP-neurons began to be reconsidered. First, neuroscientists such as Vernon Mountcastle had shown that the firing rate of a sensory neuron (i.e., the number of voltage pulses generated per second) in response to a stimulus could sometimes be realistically modeled as a linear function of the stimulus magnitude. Experiments of this type suggested that the ‘relevant informational state’ of a neuron might be better modeled as a continuous numeric quantity (i.e., a real number) as opposed to a categorical binary variable. Second, work by Ratliff, Hartline, and others had shown that the peripheral visual system of the horseshoe crab could be effectively modeled using linear systems theory. Research of this nature encouraged modelers to consider a ‘quasilinear’ continuous-state neuron model (as opposed to the ‘two-state’ MP-neuron model) for the purposes of neurocomputation. Figure 1 illustrates the key idea underlying the quasilinear neuron model which is essentially that the change in the model neuron's activation level can be approximately modeled as a linear transformation of the activation levels of the other model neurons in the system. In the early 1970s the quasilinear neuron model became relatively popular and researchers such as James Anderson, S. I. Amari, Stephen Grossberg, and Teuvo Kohonen independently published papers concerning Hebbian learning in networks of abstract quasilinear neurons (see Anderson and Rosenfeld 1988a, Grossberg 1982, Levine 1991, and Lau 1992, for relevant reviews). View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B0080430767005635 Behavioral NeuroscienceR.F. Thompson, in International Encyclopedia of the Social & Behavioral Sciences, 2001 5 Sensory ProcessesA major topic area in physiological psychology has been the study of sensory processes: sensation and perception. Indeed, this is perhaps the original field of psychology, dating back at least to Newton. Although specialization has resulted in separation between the fields of psychophysics and sensory physiology, in the sense that few individual scientists do research in both fields, they remain closely interlocked. From the beginning, explorations of sensory and perceptual phenomena have always involved hypothetical physiological mechanisms, e.g., the Young–Helmholtz 3 receptor theory of color vision and the Hering opponent process theory (see Hurvich and Jameson 1974). This has been a field of extraordinary progress in the twentieth century. Techniques have been critically important. Early in the century there were really no tools, other than rather crude anatomical methods, for analyzing the organization of sensory systems in the brain. The pioneering studies of Adrian (1940) in England and Marshall, Woolsey and Bard (1941) at Johns Hopkins were the first to record electrical evoked potentials from the somatic sensory cortex in response to tactile stimulation. Woolsey and his associates developed the detailed methodology for evoked potential mapping of the cerebral cortex. In an extraordinary series of studies, Woolsey and his colleagues determined the localization and organization of the somatic sensory areas, the visual areas and the auditory areas of the cerebral cortex in a comparative series of mammals. They initially defined two areas (I and II) for each sensory field. 5.1 Organization of the Sensory SystemsIn the 1940s and 1950s the evoked potential method was used to analyze the organization of sensory systems at all levels from the first order neurons to the cerebral cortex. The principle that emerged was strikingly clear and simple; in every sensory system the nervous system maintained a receptotopic map or projection at all levels from receptors to cerebral cortex: skin surface, retina, basilar membrane. The same organization held for the second sensory areas. The receptor maps in the brain were not one-to-one, rather they reflected the functional organization of each system: fingers, lips, and tongue areas were much enlarged in primate somatic cortex, half the primary visual cortex represented the, and so on. The evoked potential method was very well suited to analysis of the overall organization of sensory systems in the brain. However, it could reveal nothing about what the individual neurons were doing. This had to wait development of the microelectrode. Indeed, the microelectrode has been the key to analysis of the fine-grained organization and feature detector properties of sensory neurons. Metal microelectrodes were developed in the early 1950s: Davies at Hopkins developed the platinum-iridium glass coated microelectrode, Hubel and Wiesel at Harvard developed the tungsten microelectrode, and the search for feature detectors was on. The pioneering studies were those of Mountcastle and associates at Hopkins on the organization of the somatic-sensory system, those of Hubel and Wiesel at Harvard on visual system and Rose, Hind, Woolsey and associates at Wisconsin on the auditory system. Thanks to the microelectrode and to modern pathway tracing techniques, we now know that each sensory modality is represented multiply in the cerebral cortex. Meanwhile, pioneering work was being done on receptors. Hartline and Ratliff analyzed receptor responses in a simple visual system, Limulus (horseshoe crab), and discovered lateral inhibition. Von Bekesy discovered the standing wave patterns in the cochlea (working in the psychology department at Harvard). Dark adaptation was explained in biochemical terms by Wald at Harvard. The role of eye movements in visual perception was elucidated by Riggs and associates at Brown. In the recent past, progress in analysis of sensory processes has been quite remarkable. The ability to measure, with the microelectrode, the activity of single receptors or sensory neurons precisely, with tight stimulus control, has been matched by the great precision of psychophysical methods and results in humans and animals. Analysis of the physiological properties of neurons in sensory systems, and their psychophysical concomitants, has become highly productive, sophisticated, and elegant. It is without question the most advanced field in behavioral neuroscience. Many would claim it as a separate field, or more precisely, a separate set of fields, i.e., the hearing sciences and the vision sciences. This, by the way, seems characteristic of behavioral neuroscience. The great questions are first raised within the field. As techniques develop and answers begin to appear, separate fields may be created. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B0080430767034057 Foundation of neurophysiologyZhongzhi Shi, in Intelligence Science, 2021 2.2.2 Classification of neuronsThere are many kinds of classifications for neurons, but they are usually classified according to the number and functions of neural processes. 1.Neurons can be divided into three classes according to the number of neural processes: Pseudounipolar neuron: One process arises from the cell body and then splits into a T shape with two branches at a site not far from the cell body. Thus it is called as pseudounipolar neuron. One branch with the structure similar to the axon is long and thin and extends to the periphery, which is called peripheral process, and its function is same as that of the dendrite. The peripheral process senses stimulation and conducts impulses to the cell body. The other branch, called the central process, extends to the center, and its function is equal to that of the axon, conducting impulses to another neuron, like the sensory neuron in the spinal ganglia. Bipolar neuron: The bipolar neuron erupts into two processes. One is the dendrite and the other is the axon, for example the sensory neurons in the cochlear ganglion Multipolar neuron: The multipolar neuron has one axon and multiple dendrites. Multipolar neurons are the most numerous, such as the motor neurons in cornu anterius medullae spinalis, the pyramidal cells in the cerebral cortex, and so on. Based on the length of the axons, multipolar neurons are also classified into two types: Golgi type I neuron and Golgi type II neuron. Golgi type I neurons have big cell bodies and long axons, which can extend collateral branches on their way, such as the motor neurons in cornu anterius medullae spinalis. Golgi type I neurons have small cell bodies and short axons, which extend collateral branches near the cell bodies, for example the small neurons in the cornu posterius medullae spinalis and association neurons in the cerebrum and cerebellum. 2.Based on their functions, neurons fall into three types, Sensory neurons (afferent neurons): These receive stimuli and transmit afferent impulses to the CNS, and their cell bodies are located in the cerebrum and spinal ganglia. Most of them are pseudounipolar neurons, and their processes constitute the afferent nerves of peripheral nerves. The terminals of nerve fibers form sensors (receptors) in the skin or muscles. Motor neurons (efferent neurons): These transmit efferent impulses. Most of them are multipolar neurons. Their cell bodies are located in the gray matter of the CNS or vegetative ganglia, and their processes constitute efferent nerve fibers. The terminals of the nerve fibers are located in the muscle tissues and glands to form effectors. Interneurons (association neurons): These play a role of communication between the neurons. They are multipolar neurons, and they are the most numerous in the human nervous system. Interneurons construct the complicated network of the CNS. Their cell bodies are located in the gray matter of the CNS, and their processes are generally located in the gray matter too. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780323853804000026 Biased Random-Walk Learning: A Neurobiological Correlate to Trial-and-ErrorRussell W. Anderson, in Neural Networks and Pattern Recognition, 1998 4.1 Random Structural VariationCellular events are dominated by stochastic processes. It has been shown that structural variation can be guided or influenced by chemical or neural signals. What remains to be found is whether this modulation is a local phenomenon or one mediated by higher centers. Here, I cite just two examples of experimental systems that are consistent with this view. Growth of neurites in cerebellar granule cell cultures progresses stochastically [Rashid and Cambray-Deakin 1992]. Stimulation with NMDA results in a marked increase in growth rate, while the addition of an NMDA receptor antagonist, aminophosphonovalerate (APV), causes a marked retraction of preexisting processes. Either of these effects could be directed from more distant neural structures. In another experiment, Glanzman et al. [1990] studied an in vitro coculture of Aplysia sensory neurons and their target (L7 motor) cells. The sensorimotor cocultures were grown for 5 days and observed by fluorescence video micrographs. One group of preparations was repeatedly treated with the facilitating transmitter serotonin (5-HT) for 24 hours. At the end of the experiment, the coculture was imaged again to look for structural changes. Morphological changes (changes in the size of varicosities or new processes) at the junctions between the sensory and motor cells were rated on a subjective scale. This study was significant in that the researchers were able to directly image structural changes—rather than relying on comparisons between two different populations of neurons. In the control group, morphological changes were found to be normally distributed with a mean change of zero on their rating scale. In the cocultures treated with serotonin, however, structural change was shown to be highly biased toward increases in varicosities or processes. Furthermore, they showed that these structural changes corresponded to measurable changes in monosynaptic excitatory postsynaptic potential (EPSP) produced in L7 motor cells by firing the sensory neuron. Thus, they were able to show that both physical and electrophysiological facilitation can be induced in vitro by a single chemical signal—serotonin. I suggest that these random variations serve a vital role in learning, that is, generating trial connections and efficacies. Serotonin release in a cluster of neurons may serve as a local “print” (or fixing) signal to retain effective changes. However, the experiment described by Glanzman et al. was not designed to differentiate between serotonin’s putative role as a simple growth factor or a reinforcement signal. Serotonin has been shown to serve a role as a neuromodulator as well as a facilitation signal. There is evidence for a brainstem serotonergic projection to the ventrobasal thalamus, thus linking facilitory signal to higher brain centers [Eaton and Salt 1989]. Does facilitation reinforce existing changes, or does the change occur as a result of the presence of serotonin? View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780125264204500082 Arousal, Neural Basis ofB.S. Kapp, M.E. Cain, in International Encyclopedia of the Social & Behavioral Sciences, 2001 2 Brainstem Contributions to Arousal: Cholinergic, Noradrenergic, Serotonergic, and Histaminergic Neuronal Groups2.1 The Ch-5 Cholinergic Contribution to ArousalRecall that Moruzzi and Magoun (1949) reported that electrical stimulation of the reticular formation elicited neocortical arousal in the cat. Recent research has demonstrated that ACh containing neurons are located in this region. This group of neurons has been designated as the Ch-5 cholinergic cell group (Wainer and Mesulam 1990). Neurons within the region where the Ch-5 group is located project to the region of the NB, and electrical stimulation of the Ch-5 region activates neurons in the NB that demonstrate positive correlations with neocortical arousal (Detari et al. 1997). This projection, therefore, offers a pathway by which stimulation within the traditionally defined ARAS elicits neocortical arousal via an influence on the NB. Importantly, however, the majority of the neurons that project from the Ch-5 cell group to the NB are not acetylcholine containing (Jones and Cuello 1989). This suggests that the stimulation-induced neocortical activation from the Ch-5 region is not due to activation of Ch-5 cholinergic neurons but perhaps to activation of neurons containing the excitatory neurotransmitter, glutamate. While the cholinergic neurons of the Ch-5 group do not appear to contribute to neocortical arousal via an influence on the NB, they nevertheless make a significant contribution to arousal via their release of ACh on neurons of the thalamus that receive sensory information directly from the sense organs. For example, Ch-5 neurons project directly onto neurons of the dorsal lateral geniculate nucleus (dLGN) (Wainer and Mesulam 1990). The latter receive information directly from the retina and transmit that information to the visual neocortex for further processing. When active, Ch-5 neurons release ACh on to dLGN neurons which influences these neurons in a manner identical to the influence of ACh on neocortical sensory neurons. It depolarizes them, making them more sensitive to incoming sensory information (Steriade and Busaki 1990, McCormick and Bal 1997). Thus, Ch-5 ACh neurons, similar to the influence of NB ACh neurons on the neocortex, enhance the processing of incoming information in the sensory thalamus. 2.2 The Serotonergic Contributions to ArousalWhile antagonists of ACh receptors have been demonstrated to block neocortical arousal, these antagonists do not block neocortical arousal under all conditions. It has been convincingly demonstrated in the rat that the neocortical arousal that accompanies certain types of behaviors such as walking, stepping, head movements, rearing, postural adjustments or spontaneous limb movements occurs in the presence of cholinergic receptor antagonists. However, neocortical arousal that occurs during grooming, licking, chewing and immobility behaviors is lost (Dringenberg and Vanderwolf 1998). Additional research has demonstrated that antagonists of the neurotransmitter, serotonin (5-HT), block neocortical arousal accompanying the former group of behaviors (Dringenberg and Vanderwolf 1998). The raphe nuclei, a series of serotonin containing cell groups within the midbrain, provide a rich serotonergic projection to the neocortex. Electrical stimulation of the raphe nuclei produces neocortical arousal that is blocked by serotonergic receptor antagonists, whereas selective destruction of serotonergic cells in the raphe nuclei abolishes the neocortical arousal that is resistant to cholinergic receptor antagonists. Additional research has demonstrated that injections of serotonergic antagonists directly into the neocortex can block neocortical arousal produced by noxious stimulation, thereby suggesting that 5-HT, similar to the actions of ACh, works directly at the level of the neocortex to elicit neocortical arousal (Dringenberg and Vanderwolf 1998). The fact that 5-HT has been reported to depolarize neocortical cells and enhance their excitability is consistent with its ability to produce neocortical arousal (McCormick 1992). It, therefore, appears that both the serotonergic and cholinergic systems contribute to neocortical arousal by direct actions on the neocortex. Indeed, it has been demonstrated that the combined application of cholinergic and serotonergic receptor antagonists completely blocks neocortical arousal accompanying all behaviors, suggesting that other areas which contribute to neocortical arousal may exert their effects via an action on either the serotonergic and/or cholinergic systems (Dringenberg and Vanderwolf 1998). One such area that appears to exert such an indirect effect is the locus coeruleus (LC), as described below. 2.3 The LC Noradrenergic Contribution to ArousalThe LC, more than any other brain structure, possesses the most extensive connections with other brain areas. It comprises a small group of neurons in the dorsal brainstem that contain the neurotransmitter, norepinephrine (NE). The widespread projections of the LC to the neocortex makes it a prime candidate for a function in arousal. Indeed, much research over the years has strongly implicated the LC in neocortical arousal. Perhaps the most compelling evidence for this function derives from the demonstration in rats that infusions into the LC of a small volume of an agent that excites LC neurons elicit a shift from neocortical high amplitude slow wave activity to LVFA (Berridge and Foote 1994). There also appeared a shift in the EEG recorded from the hippocampus to one of intense theta wave activity, an activity pattern that is observed in concert with neocortical arousal. These effects were blocked by intraperitoneal injections of a NE receptor antagonist. Contrariwise, infusions into the LC of a small volume of an agent that inhibits the activity of LC neurons produced a shift in the neocortical EEG from LVFA to high amplitude slow wave activity and abolished hippocampal theta wave activity. Infusion sites within 0.5mm of the LC were without effect. Additional research is consistent with these observations. For example, recordings taken from LC neurons in the monkey demonstrated that their activity correlated positively with neocortical arousal; that is, they showed increased activity during LVFA during waking and decreased activity during high amplitude slow wave activity during drowsiness (Aston-Jones et al. 1996). Finally, the LC is the sole source of NE in the neocortex, and NE applied to neocortical sensory neurons decreases their spontaneous firing rate while enhancing their response to sensory input; in essence, increasing the signal-to-noise-ratio of the neuron. A similar action for NE on thalamic sensory neurons has been observed (McCormick 1992). The accumulated results suggest that the LC, when active, releases NE in the neocortex which in turn elicits neocortical arousal. Recent research, however, suggests that the LC exerts its effect indirectly since antagonists of cholinergic receptors block the effects of LC electrical stimulation on neocortical arousal (Dringenberg and Vanderwolf 1998). Consistent with these findings is recent research demonstrating that the effects of NE on the neocortical EEG are exerted by an excitatory action on the cholinergic cells of the medial septum which influences neocortical arousal in as yet an unknown manner (Berridge et al. 1996). Nevertheless, the noradrenergic neurons of the LC appear to play an important role in neocortical arousal, although an indirect one. 2.4 Histaminergic Contributions to ArousalIt has long been recognized that antihistamines produce drowsiness accompanied by high amplitude slow wave activity in the EEG. Research has demonstrated that the sole source of histamine-containing neurons in the brain originates in a structure called the tuberomamillary nucleus (TM) located in the basal hypothalamus and that these neurons send widespread projections to many brain areas including the neocortex (Inagaki et al. 1988). Antihistamines are antagonists of histamine receptors, and their effects on behavioral state and the EEG strongly implicate the histamine-containing neurons of the TM in neocortical arousal. Numerous observations support this hypothesis. For example, selective activation of histaminergic receptors by intracranial injections of histamine elicits neocortical arousal whereas chemically induced inactivation of TM neurons produces high amplitude slow wave activity in the EEG and sleep (Lin et al. 1989, Tasaka et al. 1989). Finally, TM neurons in the cat have been observed to be most active in the aroused, awake, state but demonstrate decreased activity during high amplitude slow wave activity indicative of slow wave sleep (Vanni-Mercier et al. 1984). Histamine has been shown to depolarize neurons, rendering them more likely to fire in response to incoming information (McCormick 1992). This action is similar to that observed for ACh and 5-HT and could result in neocortical arousal. Some recent evidence, however, suggests that histamine's effect on neocortical arousal, like the effect of NE, may be indirect. For example, neocortical arousal is still present after large depletions of brain histamine, suggesting that histamine is not essential for neocortical arousal (Dringenberg and Vanderwolf 1998). This observation has led to the suggestion that histamine may exert its effects on neocortical arousal via modulation of the cholinergic or seronergic arousal systems (Dringenberg and Vanderwolf 1998). View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B0080430767035476 Electrical TechnologyPaul Davidovits, in Physics in Biology and Medicine (Fifth Edition), 2019 14.5 Control SystemsMany of the processes in living systems must be controlled to meet the requirements of the organism. We have already encountered a few examples of controlled processes in our earlier discussions. Temperature control in the body and the growth of bones were two cases where various processes had to be regulated in order to achieve the desired condition. In this section, we will describe briefly a useful general method of analyzing such control systems. Features common to all control systems are shown in Fig. 14.6. Each block represents an identifiable function within the control system. The control process consists of: Figure 14.6. Control of a biological process. 1.The parameter to be controlled. This may be the temperature of the skin, the movement of muscles, the rate of heart beat, the size of the bone, and so on. 2.A means of monitoring the parameter and transmitting information about its state to some decision-making center. This task is usually performed by the sensory neurons. 3.Some reference value to which the controlled parameters are required to comply. The reference value may be in the central nervous system in the form of a decision, for example, about the position of the hand. In this case, the reference value is changeable and is set by the central nervous system. Many references for body functions are autonomous, however, not under the cognitive control of the brain. 4.A method for comparing the state of the parameter with the reference value and for transmitting instructions to bring the two into accord. The instructions may be transmitted by nerve impulses or in some cases by chemical messengers called hormones, which diffuse through the body and control various metabolic functions. 5.A mechanism for translating the messages into actions that alter the state of the controlled parameter. In the case of the hand position, for example, this is the contraction of a set of muscle fibers. We will now illustrate these concepts with a concrete example of the control of the light intensity reaching the retina of the eye (see Fig. 14.7). Light enters the eye through the pupil, which is the dark opening in the center of the iris. (The iris is the colored disk in the eyeball.) The size of the opening decreases as the light intensity increases. Thus, the iris acts somewhat like the automatic diaphragm in a camera. Clearly this action must be governed by a control system. Figure 14.7. Control of the light intensity reaching the retina. Light reaching the retina is converted to neural impulses, which are generated at a frequency proportional to the light intensity. At some place along the nervous system of vision, this information is interpreted and compared to a preset reference value stored probably in the brain. The reference itself can be altered by hormones and various emotional stimuli. The result of this comparison is transmitted by means of nerve impulses to the muscles of the iris which then adjust the size of the opening in response to this signal. What neurons send signals to effectors?Efferent, or motor, neurons transmit impulses from the CNS to effector organs such as muscles and glands. Efferent neurons usually have short dendrites and long axons.
What neuron sends signals to other neurons?A neuron sending a signal (i.e., a presynaptic neuron) releases a chemical called a neurotransmitter, which binds to a receptor on the surface of the receiving (i.e., postsynaptic) neuron. Neurotransmitters are released from presynaptic terminals, which may branch to communicate with several postsynaptic neurons.
Which part of the neuron sends signals to other cells?Specialized projections called axons allow neurons to transmit electrical and chemical signals to other cells. Neurons can also receive these signals via rootlike extensions known as dendrites.
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