Biological neuron

Departments of Neurology, Pathology, and Cell Biology Center for Neurobiology and Behavior Center for Motor Neuron Biology and Diseases Columbia University New York, NY, USA... 

Staining Applications Brainstem cortex neurons" Biological Applications Measuring membrane potential " probes for Na, K-ATPase reaction mechanism examining activity of ion channels ... 

Morphine and its salts are very valuable analgesic drugs but are highly addictive. In addition to suppression of pain, morphine causes constipation, decreases pupillary size and depresses respiration. Only the (-l-)-stereoisoraer is biologically active. They appear to produce their effects on the brain by activating neuronal mechanisms normally activated by... 

Modeling the Brain Biological Neurons versus Artificial Neurons... 

The nervous systems and especially the brains of animals and humans work very fast, efficiently, and highly in parallel. They consist of networked neurons which work together and interchange signals with one another. This section describes the functionality of a biological neuron and explains the model of an artificial neuron. 

Artificial Neural Networks (ANNs) are information processing imits which process information in a way that is motivated by the functionality of the biological nervous system. Just as the brain consists of neurons which are connected with one another, an ANN comprises interrelated artificial neurons. The neurons work together to solve a given problem. 

Figure 9-12. Biological neuron the dendrites receive the incoming information and send it to the cell body, The axon carries the information produced in the cell body to neighboring neurons.

Rather than making this statement, one should consider first whether the representation of the Y-variablc is appropriate. What wc did here was to take categorical information as a quantitative value. So if wc have, for instance, a vector of class 1 and one of c lass 9 falling into the same neuron, the weights of the output layer will be adapted to a value between 1 and 9, which docs not make much sense. Thus, it is necessary to choose another representation with one layer for each biological activity. The architecture of such a counter-propagation network is shown in Figure 10.1 -11. Each of the nine layers in the output block corresponds to a different MOA. 

The chromaffin cells of the adrenal medulla may be considered to be modified sympathetic neurons that are able to synthesize E from NE by /V-methylation. In this case the amine is Hberated into the circulation, where it exerts effects similar to those of NE in addition, E exhibits effects different from those of NE, such as relaxation of lung muscle (hence its use in asthma). Small amounts of E are also found in the central nervous system, particularly in the brain stem where it may be involved in blood pressure regulation. DA, the precursor of NE, has biological activity in peripheral tissues such as the kidney, and serves as a neurotransmitter in several important pathways in the brain (1,2). 

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. 

Artificial Neural Networks (ANNs) attempt to emulate their biological counterparts. McCulloch and Pitts (1943) proposed a simple model of a neuron, and Hebb (1949) described a technique which became known as Hebbian learning. Rosenblatt (1961), devised a single layer of neurons, called a Perceptron, that was used for optical pattern recognition. 

The computational paradigm in an ANN is based on an idealized model of a biological unit called a neuron. The unique characteristics of this ANN model are the inputs of signal from stimulus in a training environment. It is important to note that each neuron works independently of the other neurons. The specific characteristics of ANN models that attract industrial application are ... 

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. 

Fig. 10.1 Schematic representations of (a) a biological neuron, and (b) a McCulloch-Pitts artificial neuron.

The biological actions of adrenaline and noradrenaline are mediated via nine different G-protein-coupled receptors, which are located in the plasma membrane of neuronal and nonneuronal target cells. These recqrtors are divided into two different groups, a-adrenergic receptors and P-adrenergic recqrtors (see P-adrenergic system). 

NPY is primarily (but not exclusively) synthesised and released by neurons, which in the peripheral nervous system are predominantly sympathetic neurons [1]. In most cases, NPY acts as a co-transmitter that is preferentially released upon high frequency nerve stimulation. NPY can be metabolised by the enzyme dipeptidylpeptidase IV (also known as CD26) to generate the biologically active fragment NPY3 36. 

Enterochromaffin cells are interspersed with mucosal cells mainly in the stomach and small intestine. In the blood, serotonin is present at high concentrations in platelets, which take up serotonin from the plasma by an active transport process. Serotonin is released on platelet activation. In the central nervous system, serotonin serves as a transmitter. The main serotonin-containing neurons are those clustered in form of the Raphe nuclei. Serotonin exerts its biological effects through the activation of specific receptors. Most of them are G-protein coupled receptors (GPCRs) and belong to the 5-HTr, 5-HT2-, 5-HT4-, 5-HTs-, 5-HT6-, 5-HT7-receptor subfamilies. The 5-HT3-receptor is a ligand-operated ion channel. 

The presence of polymer, solvent, and ionic components in conducting polymers reminds one of the composition of the materials chosen by nature to produce muscles, neurons, and skin in living creatures. We will describe here some devices ready for commercial applications, such as artificial muscles, smart windows, or smart membranes other industrial products such as polymeric batteries or smart mirrors and processes and devices under development, such as biocompatible nervous system interfaces, smart membranes, and electron-ion transducers, all of them based on the electrochemical behavior of electrodes that are three dimensional at the molecular level. During the discussion we will emphasize the analogies between these electrochemical systems and analogous biological systems. Our aim is to introduce an electrochemistry for conducting polymers, and by extension, for any electrodic process where the structure of the electrode is taken into account. 

The Nernst equation is widely used to estimate the emf of cells under nonstandard conditions. In biology it is used, among other things, to estimate the potential difference across biological cell membranes, such as those of neurons. 

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