Modelling and dynamics of neural systems

Details


Contents

  1. Introduction.
    • Membrane potential and electrical currents.
    • Neuronal activity: generalities.
    • Nerve impulse.
    • Voltage dependent channels.
  2. Models of individual neurons.
    • Hudgkin-Huxley experiment.
    • Hudgkin-Huxley model; pulses and bursts.
    • Reduced models; Integrated & Fire, Morris Leccar, Fitzhugh Nagumo, Izhickevich, etc.
  3. Synapsis.
    • Chemical and electrical synapses.
    • Neurotransmitters and receptors.
    • Synaptic and postsynaptic conductance.
    • Short-range plasticity.
    • Dynamic of coupled neurons.
  4. Synchronization.
    • Introduction
    • Synchronization of identical systems
    • Synchronization of nonidentical systems
  5. Interacting systems.
    • Characterization of time series.
    • Calculations of autocorrelation and cross-correlation.
    • Mutual entropy.
    • Populations of neurons.
    • Neural networks.
  6. Information Encoding.
    • Temporal coding.
    • Rate Coding.
  7. Effects of noise.
    • Gaussian white noise, color noise and Poisson noise.