Titlebook: Stochastic Models for Spike Trains of Single Neurons; G. Sampath,S. K. Srinivasan Book 1977 Springer-Verlag Berlin · Heidelberg 1977 Aktio

无能性

Counter Models,r is for sometime thereafter unable to register an arrival. This period of inactivity is called .: the counter goes ‘dead’. Immediately after this dead time, the counter is able to register arrivals. The similarity of the dead time effect with refractoriness in a neuron is at once obvious. This has

lethargy

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Continuous State Models,membrane potential therefore does not change in steps of constant size but executes a random walk in continuous state space. This property introduces further variability into the spontaneous activity of neurons. The membrane potential therefore cannot be considered a discrete process like the birth-

飞来飞去真休

Real Neurons and Mathematical Models, of inputs to a neuron that are also stochastic processes. First related theory on which the models are based is presented and these are then enlarged in stages. Thus models with only one kind of input-excitatory — (Models 8.1, 8.2, 9.1 and 9.2) are frequently studied first before constructing more

极为愤怒

Book 1977f neurons 2 Signals in the nervous system 14 2. 1 Action potentials as point events - point processes in the nervous system 15 18 2. 2 Spontaneous activi~ in neurons 3 Stochastic modelling of single neuron spike trains 19 3. 1 Characteristics of a neuron spike train 19 3. 2 The mathematical neuron 2

吗啡

0341-633X 2 Types of neurons 2 Signals in the nervous system 14 2. 1 Action potentials as point events - point processes in the nervous system 15 18 2. 2 Spontaneous activi~ in neurons 3 Stochastic modelling of single neuron spike trains 19 3. 1 Characteristics of a neuron spike train 19 3. 2 The mathematica

Maximizer

Superposition Models, point processes that are superposed is considered. The subject of superposition is fairly advanced, but here only some basic concepts and results are presented. The treatment follows for the greater part Cox (1962) and Khintchine (1960). Section 4.3 discusses some models based on superposition.

Occlusion

NAVEN

强行引入

Counter Models,d time, the counter is able to register arrivals. The similarity of the dead time effect with refractoriness in a neuron is at once obvious. This has motivated the use of counter theory in modelling neuron spike trains.