Author | Holden, Arun Vivian. author |
---|---|
Title | Models of the Stochastic Activity of Neurones [electronic resource] / by Arun Vivian Holden |
Imprint | Berlin, Heidelberg : Springer Berlin Heidelberg, 1976 |
Connect to | http://dx.doi.org/10.1007/978-3-642-46345-7 |
Descript | VIII, 370 p. online resource |
1. Stochastic fluctuations in membrane potential -- 1.1 Thermal or Johnson-Nyquist Noise -- 1.2 Shot Noise -- 1.3 Flicker Noise -- 1.4 Conductance fluctuations -- 1.5 References -- 2. Quantal Fluctuations in Generator Potential -- 2.1 Psychophysical Evidence for Quantal Sensitivity in Vision -- 2.2 Some Neural Machines -- 2.3 Fluctuations in the Limulus Eccentric Cell Generator Potential -- 2.4 References -- 3. Models of Action Potential Initiation -- 3.1 The Logical Neurone -- 3.2 The Perfect Integrator Model -- 3.3 The Leaky Integrator Model -- 3.4 Two-Time Constant Models -- 3.5 The Hodgkin-Huxley Equations -- 3.6 Reduced Hodgkin-Huxley Equations -- 3.7 References -- 4. Fluctuations in Excitability -- 4.1 Single Time Constant Models with Fluctuating Threshold -- 4.2 Two-Time Constant Models with Fluctuating Threshold -- 4.3 Fluctuations in Hodgkin-Huxley variables -- 4.4 Models with Time-varying Threshold -- 4.5 References -- 5. Statistical Properties of a Spike Train -- 5.1 Stationarity -- 5.2 Interval Densities and Distributions -- 5.3 Spectral Densities of Point Processes -- 5.4 Input-Output Relations -- 5.5 References -- 6. Random Walk Models -- 6.1 The Random Walk Model -- 6.2 The Probability of First Passage -- 6.3 The Interval Probability Density -- 6.4 A Diffusion Approximation -- 6.5 Introduction of a Reflecting Barrier -- 6.6 Generalization of the Random Walk as a Birth and Death Process -- 6.7 Birth and Death Process Model of the Leaky Integrator -- 6.8 More Complex Random Walks -- 6.9 Some Comments on the Random Walk Models -- 6.10 References -- 7. Diffusion Models -- 7.1 The Input Process -- 7.2 The Wiener Process -- 7.3 The Ornstein-Uhlenbeck Process -- 7.4 The Diffusion Equations -- 7.5 The First Passage Time Distribution -- 7.6 The SIPIT Model -- 7.7 The SILIT Model -- 7.8 The Inverse Approach to Diffusion Models -- 7.9 References -- 8. Superposition Models -- 8.1 Some General Properties of Superposed Processes -- 8.2 Superposition of Regular Generator Trains -- 8.4 Some Applications of Superposition Theory -- 8.5 References -- 9. Collision Models -- 9.1 The Mechanism of Collision -- 9.2 The Geometry of Collision -- 9.3 Mutual Interaction Between Two Non-adjacent Generator Sites -- 9.4 The Biology of Collision -- 9.5 References -- 10. Gating and Selective Interaction Models -- 10.1 Compound Exponential Distributions and Gating Models -- 10.2 Selective Interaction Models -- 10.3 Models with Sub-threshold Interactions -- 10.4 Neural Micro-nets with Reciprocal Inhibition -- 10.5 References -- 11. Models of Synaptic Transmission -- 11.1 The neuro-muscular junction -- 11.2 Spontaneous miniature end-plate potentials -- 11.3 Presynaptic depolarization enhanced release -- 11.4 Models of facilitation and depression -- 11.5 Transmitter induced fluctuations in conductance -- 11.6 Dynamics of signal transfer across a synapse -- 11.7 References -- 12. Models of the stochastic activity of neural aggregates -- 12.1 Nets of logical neurones -- 12.2 Networks continuous in time and space: a field approach -- 12.3 Temporal behaviour of nets of excitatory and inhibitory neurones -- 12.4 Spatially distributed excitatory and inhibitory subpopulations -- 12.5 Some qualitative speculations -- 12.6 References -- 13. Information transmission by model neurones -- 13.1 The axon as a channel -- 13.2 Information preservation in a neural chain -- 13.3 Signal detection -- 13.4 Tranmission of steady signals using a rate code -- 13.5 Information transmission of periodic signals -- 13.6 Transmission of stochastic, time-varying signals -- 13.7 Transinformations of different codes -- 13.8 References