Titlebook: Neural Modeling; Electrical Signal Pr Ronald J. MacGregor,Edwin R. Lewis Book 1977 Plenum Press, New York 1977 Nervous System.brain.neural

憂(yōu)傷

Models of Signal Generation in Neural Elementsus activity in neurons. The common feature of these three topics is the generation of signals in the nervous system. Since the nervous system generally is viewed as a processor of signals, it seems natural to present models concerning the generation of those signals early in our discussion. It is qu

agonist

Models of Distributed Passive Membraneembrane, but we have ignored gradients and flows directed tangential to its surfaces, and in doing so we have ignored mechanisms by which receptor responses and synaptic responses can spread from one region of the neuron to another. As we mentioned in Chapters 1 and 2, local regions of a neuron are

惰性氣體

陰郁

Ostrich

Stochastic Models of Neuron Activitypically tried to predict the relative occurrence of time intervals of various durations between the adjacent spikes in an output spike train which is produced by applying the threshold rule to some assumed random distribution of input events. This problem has been found to be virtually unsolvable ma

Organization

Statistical Analysis of Neuronal Spike Trainsity of a nervous network as consisting of a large number of ongoing simultaneous time series of events (spike trains) emerging from all the constituent cells. The output train of any particular cell reflects the ongoing input trains at each of some several hundred or even thousands of synapses. Vari

Cervical-Spine

Models of Neuron Poolss to thousands of neurons. The motivation behind this work is the possibility of understanding the overall dynamics of large masses of neural tissue in terms of such pools, on the one hand, and to understand the properties of such pools in terms of their individual constituent neurons, on the other.

潰爛

Models of Large Networks: Analytic Approaches1 considered techniques for analyzing up to hundreds or thousands of interconnected cells. In this and the next chapter we consider techniques for predicting the activity of vast numbers of interconnected neurons, say, from tens of thousands to millions or more. We will find that the various existin

翅膀拍動(dòng)

Tincture

Models of Field Potentials, Slow Waves, and the EEG single neurons. There exists, however, another class of recordings which measure continuous, graded and more slowly fluctuating waves of activity thought to represent the combined activity of large numbers of neurons or of large regions of neuronal tissue. Such recordings are usually made with macr