Computational Neuroscience: A Comprehensive ApproachJianfeng Feng How does the brain work? After a century of research, we still lack a coherent view of how neurons process signals and control our activities. But as the field of computational neuroscience continues to evolve, we find that it provides a theoretical foundation and a set of technological approaches that can significantly enhance our understanding. |
Contents
1 A Theoretical Overview | 1 |
2 Atomistic Simulations of Ion Channels | 30 |
3 Modelling Neuronal Calcium Dynamics | 70 |
4 StructureBased Models of NO Diffusion in the Nervous System | 91 |
5 Stochastic Modelling of Single Ion Channels | 126 |
6 The Biophysical Basis of Firing Variability in Cortical Neurons | 153 |
7 Generating Quantitatively Accurate but Computationally Concise Models of Single Neurons | 185 |
8 Bursting Activity in Weakly Electric Fish | 217 |
11 Hebbian Learning and SpikeTimingDependent Plasticity | 300 |
High and LowLevel Views | 337 |
Stimulus Localisation in the Barrel Cortex | 368 |
14 Modelling Fly Motion Vision | 389 |
15 MeanField Theory of Irregularly Spiking Neuronal Populations and Working Memory in Recurrent Cortical Networks | 425 |
16 The Operation of Memory Systems in the Brain | 485 |
17 Modelling Motor Control Paradigms | 532 |
18 Computational Models for Generic Cortical Microcircuits | 570 |
9 Likelihood Methods for Neural Spike Train Data Analysis | 252 |
10 BiologicallyDetailed Network Modelling | 284 |
19 Modelling Primate Visual Attention | 604 |
| 623 | |
Other editions - View all
Computational Neuroscience: Realistic Modeling for Experimentalists Erik De Schutter Limited preview - 2000 |
Common terms and phrases
action potentials activity alamethicin amplitude analysis approximation attractor network average behavior Biophys brain burst Ca2+ calcium coding components concentration conductance connections constant continuous attractor correlation dendritic density depends detector diffusion distribution dynamics effect electrosensory Equation example excitatory experimental exponential feedback Figure filter firing rate fluctuations frequency Gaussian gramicidin head direction head direction cell hippocampal idiothetic inhibitory integration interactions interspike interval ion channels KcsA linear mechanisms membrane potential memory microcircuit model mitral cell module motion movement Neural Computation neuron model Neurophysiol Neurosci NMDA noise oscillations output oxytocin oxytocin cells parameters Poisson population population code postsynaptic potassium channel prefrontal cortex probability properties pyramidal cells readout receptive field receptor recurrent response sensory shown signal simulations single spatial spike patterns spike trains STDP stimulus stochastic structure studies synaptic input synaptic strengths synchronization temporal theory threshold trajectory variability vasopressin visual cortex voltage