Neurons defined

Troemel E. R., Kimmel B. E. and Bargmann C. I. (1997) Reprogramming chemotaxis responses sensory neurons define olfactory preferences in C. elegans. Cell 91, 161— 169. 

Fig. 1.7. Comparison of the map based neurons (defined by equation (1.15)) (A) to an equivalent Hodgkin-Huxley type model (details in (Nowotny et al. 2005)) (B). The response time to an EPSP (which is the most important parameter within this context) is almost identical for both (C). The inset shows the corresponding response curve of the honeybee KC model of (Wustenberg et al. 2004) which is also virtually identical. (Modified from (Nowotny et al. 2005)).

Lamas, N.J., Johnson-Kemer, B., Roybon, L., Kim, Y.A., Garcia-Diaz, A., Wichterle, H., Henderson, C.E., 2014. Neurotrophic requirements of human motor neurons defined using amplified and purified stem cell-derived cultures. PLoS One 9 (10), el 10324. 

Alkondon, M., Pereira, E. F. R., Wonnacott, S., and Albuquerque, E. X. 1992. Blockage of Nicotinic Currents in Hippocampal Neurons Defines Methyllycaconitine as a Potent and Specific Receptor Antagonist. 

Neurons have three parts the cell body and dendrites, the axon, and axon terminals. The cell body contains the nucleus and the organelles needed for metabolism, growth, and repair. The dendrites are branched extensions of the cell body membrane. The axon is a long, thin structure which transfers electrical impulses down to the terminals. The axon divides into numerous axon terminals and it is in this specialized region that neurotransmitters are released to transmit information from one neuron to its neighbors. The synapse has been defined as the space between two subsequent interrelated neurons. ... 

Now, to be sure, McCulloch-Pitts neurons are unrealistically rendered versions of the real thing. For example, the assumption that neuronal firing occurs synchronously throughout the net at well defined discrete points in time is simply wrong. The tacit assumption that the structure of a neural net (i.e. its connectivity, as defined by the set of synaptic weights) remains constant over time is known be false as well. Moreover, while the input-output relationship for real neurons is nonlinear, real neurons are not the simple threshold devices the McCulloch-Pitts model assumes them to be. In fact, the output of a real neuron depends on its weighted input in a nonlinear but continuous manner. Despite their conceptual drawbacks, however, McCulloch-Pitts neurons are nontrivial devices. McCulloch-Pitts were able to show that for a suitably chosen set of synaptic weights wij, a synchronous net of their model neurons is capable of universal computation. This means that, in principle, McCulloch-Pitts nets possess the same raw computational power as a conventional computer (see section 6.4). 

We now need to define the. set of symmetric weights, Wij wji. Given that we want our net to act as a content-associative memory, this set of weights must satisfy two conditions (1) if the net is presented with a pattern in the stored set, that set of encoded neuronal values representing that stored pattern should remain unclianged - i.e. stored patterns must be stable (2) if the net is presented with a pattern not in the stored set, the net should evolve according to equation 10.7 to the pattern that is closest to it. 

Step 1 For a given set of patterns Pi,P2,..., Vn, where the pattern is encoded by the neuronal values, .., define the synaptic-weight matrix... 

Kolmogorov s Theorem (Reformulated by Hecht-Nielson) Any real-valued continuous function f defined on an N-dimensional cube can be implemented by a three layered neural network consisting of 2N -)-1 neurons in the hidden layer with transfer functions from the input to the hidden layer and (f> from all of... 

Fremeau RT Jr, Voglmaier S, Seal RP et al (2004) VGLUTs define subsets of excitatory neurons and suggest novel roles for glutamate. Trends Neurosci 27(2) 98—103... 

The basic component of the neural network is the neuron, a simple mathematical processing unit that takes one or more inputs and produces an output. For each neuron, every input has an associated weight that defines its relative importance, and the neuron simply computes the weighted sum of all the outputs and calculates an output. This is then modified by means of a transformation function (sometimes called a transfer or activation function) before being forwarded to another neuron. This simple processing unit is known as a perceptron, a feed-forward system in which the transfer of data is in the forward direction, from inputs to outputs, only. 

Lieberam I, Agalliu D, Nagasawa T, Eiicson J, Jessell TM (2005) A Cxcll2-CXCR4 chemokine signaling pathway defines the initial trajectory of mammalian motor axons. Neuron 47 667-679... 

This finding suggests that the fast calcium events we have recently identified are not a peculiarity of astrocytes in cell culture but may correspond to events taking place in astrocytes of the living brain. Establishing whether fast calcium events in vivo are associated to transmitter release via SLMV exocytosis, becomes, therefore, of the outmost importance in order to define the type of modulatory influence exerted by astrocytes on neighboring neuronal circuits. 

Much remains to be learned about the neurochemical regulation of noradrenergic transmission and even more research is required before we can define the role(s) of this neurotransmitter in the brain. Nevertheless, it is evident that these neurons are a crucial component of the network of monoamine influences on the limbic system and that they... 

---