Neuromorphic Engineering Book
  • Welcome
  • Preliminaries
    • About the author
    • Preface
    • A tale about passion and fear
    • Before we begin
  • I. Introduction
    • 1. Introducing the perspective of the scientist
      • From the neuron doctrine to emergent behavior
      • Brain modeling
      • Take away lessons
    • 2. Introducing the perspective of the computer architect
      • Limits of integrated circuits
      • Emerging computing paradigms
      • Brain-inspired hardware
      • Take away lessons
      • Errata
    • 3. Introducing the perspective of the algorithm designer
      • From artificial to spiking neural networks
      • Neuromorphic software development
      • Take home lessons
  • II. Scientist perspective
    • 4. Biological description of neuronal dynamics
      • Potentials, spikes and power estimation
      • Take away lessons
      • Errata
    • 5. Models of point neuronal dynamic
      • Tutorial - models of point neuronal processes
        • The leaky integrate and fire model
        • The Izhikevich neuron model
        • The Hodgkin-Huxley neuron model
      • Synapse modeling and point neurons
      • Case study: a SNN for perceptual filling-in
      • Take away lessons
    • 6. Models of morphologically detailed neurons
      • Morphologically detailed modeling
      • The cable equation
      • The compartmental model
      • Case study: direction-selective SAC
      • Take away lessons
    • 7. Models of network dynamic and learning
      • Circuit taxonomy, reconstruction, and simulation
      • Case study: SACs' lateral inhibition in direction selectivity
      • Neuromorphic and biological learning
      • Take away lessons
      • Errate
  • III. Architect perspective
    • 8. Neuromorphic Hardware
      • Transistors and micro-power circuitry
      • The silicon neuron
      • Case study: hardware - software co-synthesis
      • Take away lessons
    • 9. Communication and hybrid circuit design
      • Neural architectures
      • Take away lessons
    • 10. In-memory computing with memristors
      • Memristive computing
      • Take away lessons
      • Errata
  • IV. Algorithm designer perspective
    • 11. Introduction to neuromorphic programming
      • Theory and neuromorphic programming
      • Take away lessons
    • 12. The neural engineering framework
      • NEF: Representation
      • NEF: Transformation
      • NEF: Dynamics
      • Case study: motion detection using oscillation interference
      • Take away lessons
      • Errate
    • 13. Learning spiking neural networks
      • Learning with SNN
      • Take away lessons
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  1. II. Scientist perspective
  2. 4. Biological description of neuronal dynamics

Take away lessons

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Resting potential: Relatively static membrane potential of quiescent cells in which no net transport of ions across the membrane is apparent. Equilibrium potential is maintained by the cell as it strives to keep the concentration gradient and electrical driving forces balanced at ≈ −70 mV.

Action potential: A brief electrical activity (a spike), created by depolarizing/repolarizing currents of sodium and potassium ions across the membrane. In response to stimuli, the cell membrane is depolarized. Once a threshold voltage is reached, an action potential is initiated through the opening of Na+ channels and the diffusion of Na+ into the cell. As a result, the membrane voltage continues depolarizing until Na+ channels close and K+ channels open. K+ then diffuses out of the cell, causing re-polarization, followed by a voltage undershoot (hyper-polarization).

Spike propagation: Propagation of action potential along an axon, driven by sodium channels and prevented by activation of potassium channels. Once an action potential is generated, it propagates down the axon. When a region produces an action potential and undergoes a depolarization via an influx of Na+ ions into the cell, it serves as a stimulus for the next region of the axon. In this way, action potentials are regenerated along each small region of the axon membrane.

Synapse: A site of impulse (action potential) transmission between neurons, via neurotransmitter release. Action potentials arriving at the end of an axon trigger the uptake of Ca+ which causes synaptic vesicles to fuse with the axon terminals, releasing their encapsulated neurotransmitters. These transmitters diffuse across the synaptic gap and bind to receptors anchored on the postsynaptic membrane, inducing ion flux, which causes depolarization/hyperpolarization.