Neuron human brain

Just like humans, ANNs learn from examples. The examples are delivered as input data. The learning process of an ANN is called training. In the human brain, the synaptic connections, and thus the connections between the neurons. 

The human brain is comprised of many millions of interconnected units, known individually as biological neurons. Each neuron consists of a cell to which is attached several dendrites (inputs) and a single axon (output). The axon connects to many other neurons via connection points called synapses. A synapse produces a chemical reaction in response to an input. The biological neuron fires if the sum of the synaptic reactions is sufficiently large. The brain is a complex network of sensory and motor neurons that provide a human being with the capacity to remember, think, learn and reason. 

It is tempting to view ANNS as simplified versions of biological nervous systems. Yet even the most complex neurocomputers, with several million neurons, are unable to mimic the behavior of a fly, which has approximately one million nerve cells. This is because the nerve system of the fly has far more interconnections than are possible with current-day neurocomputers, and their neurons are highly specialized to perform necessary tasks. The human brain, with about 10 billion nerve cells, is still several orders of magnitude more complex. 

Perhaps the quintessential example of a complex system is the human brain, which, consisting of something on the order of 10 neurons with lO -lO coniiec-... 

The human brain is a neural net consisting of about ten billion interconnected neurons. Figure 10.1-a shows a schematic representation of a single neuron. At the ri.sk of grossly oversimplifying the brain s enormously complex physiology, we will only focus on a relatively few functional parts of a single neuron. 

Hi-receptors in the adrenal medulla stimulates the release of the two catecholamines noradrenaline and adrenaline as well as enkephalins. In the heart, histamine produces negative inotropic effects via Hr receptor stimulation, but these are normally masked by the positive effects of H2-receptor stimulation on heart rate and force of contraction. Histamine Hi-receptors are widely distributed in human brain and highest densities are found in neocortex, hippocampus, nucleus accumbens, thalamus and posterior hypothalamus where they predominantly excite neuronal activity. Histamine Hrreceptor stimulation can also activate peripheral sensory nerve endings leading to itching and a surrounding vasodilatation ( flare ) due to an axonal reflex and the consequent release of peptide neurotransmitters from collateral nerve endings. 

Neuronal NO synthase (nNOS) is constitutively expressed in neurons of the brain. Its activity is regulated by Ca2+ and calmodulin. Half-saturating L-arginine concentrations are around 2 pM. cDNAs encoding nNOS have been cloned from rat and human brain. The open reading frame of human nNOS consists of 4299 bp, corresponding to 1433 aa. This predicts a protein of 160 kDa, which is in accordance with the molecular mass of the purified protein. 

Tomassini N, Renaud F, Roy S, Loh HH (2004) Morphine inhibits Fc-mediated phagocytosis through mu and delta opioid receptors. J Neuroimmunol 147 131-133 Trillo-Pazos G, Kandanearatchi A, Eyeson J, King D, Vyakamam A, Everall IP (2004) Infection of stationary human brain aggregates with HIV-1 SF162 and IIIB results in transient neuronal damage and neurotoxicity. Neuropathol Appl Neurobiol 30 136-147... 

The neurons from which NTs are released number more than 7 billion in the human brain. Each (Fig. 1.2) consists of a cell body, the soma or perikaryon, with one major cytoplasmic process termed the axon, which projects variable distances to other neurons, e.g. from a cortical pyramidal cell to adjacent cortical neurons, or to striatal neurons or to spinal cord motoneurons. Thus by giving off a number of branches from its axon one neuron can influence a number of others. All neurons, except primary sensory neurons with cell bodies in the spinal dorsal root ganglia, have a number of other, generally shorter, projections running much shorter distances among neighbouring neurons like the branches of a tree. These processes are the dendrites. Their... 

To understand the chemical-imbalance theory, it will be helpful to first review some basic aspects of how the brain functions. The human brain contains about ioo billion nerve cells called neurons. Each neuron is like an electrical wire with many branches. When a neuron fires, electrical impulses travel along its length from one end to the other. When an impulse reaches the end of a branch, it may stimulate the next neuron, influencing whether or not it fires. 

The interconnections or communication among neurons in humans is very extensive. Imagine the complexity of the electrical activity that may occur among 100 billion neurons in the human brain where each of these neurons provides input to and receives input from hundreds of other neurons. It is the diversity of these interconnections that accounts for the uniqueness of many abstract neurological phenomena in individuals such as intellect, personality, and memory. The two types of interconnections are ... 

The third class of neurons includes the intemeurons, which lie entirely within the CNS. Because the human brain and spinal cord contain well over 100 billion neurons, interneurons account for approximately 99% of all the neurons in the body taken together. Intemeurons lie between afferent and... 

In the human brain, very large numbers of neurons are connected in a three-dimensional mesh of great complexity (Figure 2.2). Each neuron is a simple computational unit which, on its own, can accomplish little. When many of them are joined in a large-scale structure, however, the ensemble is capable of impressive feats of computation (such as making sense of the words on this page). 

Because of the scale and complexity of the brain, it will be some years before the 1011 neurons in a typical human brain and the 1015 connections between them can be fully modeled in software. Not only is the brain very complex, it is fast we can recognize the face of a friend within a few hundred milliseconds by comparing it against the many thousands of faces that we have seen in the past. It is evident, therefore, that spreading a demanding computational task across large numbers of simple units can be very efficient. 

In the human brain, it is the combined efforts of many neurons acting in concert that creates complex behavior this is mirrored in the structure of an ANN, in which many simple software processing units work cooperatively. It is not just these artificial units that are fundamental to the operation of ANNs so, too, are the connections between them. Consequently, artificial neural networks are often referred to as connectionist models. 

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