The Functioning of Neurons: University of Auckland Module 5

Overview of Neuron Structure and Function

  • The Neuron as an Information Processor

    • Neurons are specialized cells that process information by receiving signals from multiple sources.
    • They integrate these signals to determine whether or not to generate an output.
    • The resulting signal is sent to other neurons or to muscles.
  • Key Components of a Neuron

    • Dendrites: These serve as the receptive area of the neuron. Signals from other neurons are received here.
    • Cell Body: This is the site where all incoming signals are added together (integrated) to generate a final output.
    • Axon: This acts as the output pathway of the neuron, conducting the signal away from the cell body.
    • Axon Terminal: This is located at the furthest end of the axon.
    • Synapses: These are the junctions where the neuron connects with other cells.
  • Functional Stages

    • Inputs: Received via dendrites.
    • Processing: Occurs in the cell body.
    • Transmission: Conducted via the axon to the synapses.

Neural Signaling and the Action Potential

  • Nature of the Signal

    • Signals within neurons are electrical in nature and are known as action potentials.
    • An action potential is defined as a pulse of electrical activity that travels down the neuron in a wave-like motion.
  • The Role of the Cell Membrane

    • The cell membrane acts as a physical barrier to ions.
    • Ions are atoms that carry an electrical charge.
    • The membrane allows the cell to create and maintain different environments inside versus outside the cell.
  • Ion Channels

    • These are special proteins embedded in the membrane that can open and close.
    • They allow specific ions, such as Sodium (Na+Na^+) and Potassium (K+K^+), to cross the membrane only when an action potential is occurring.

Physical Principles Governing Ion Flow

  • Two Primary Forces

    • Two physical principles determine how ions move across the membrane when a channel opens: concentration and charge.
  • Concentration (Chemical Gradient)

    • Definition: Concentration refers to the amount of a substance present in a liquid.
    • Movement Principle: Substances tend to move from areas of high concentration to areas of low concentration until the concentration becomes even.
    • Analogies provided:
      • Salt: Moving from a "saltier" area to a "less salty" area.
      • Dye: Moving from a "darker" area to a "clearer" area.
  • Charge (Electrical Gradient)

    • Electrical charges can be either positive (++) or negative (-).
    • Principles of Attraction and Repulsion:
      • Opposite charges (++ and -) attract each other.
      • Like charges (e.g., ++ and ++) repel each other.
    • Examples provided:
      • Balloon and Water: Rubbing a balloon on a cloth makes it negatively charged, allowing it to attract water (which contains positive charges).
      • Trampoline Hair: Bouncing on a trampoline can create an uneven (usually positive) charge in a person's hair. Because the hairs then have the same charge, they repel each other and stand up.

Electrical Potentials and Voltages in Neurons

  • Understanding Voltage

    • Voltage, or electrical potential, is related to the amount of energy a charge has as it travels between two terminals.
    • Battery Comparisons:
      • A standard heavy-duty battery shown in the example has a voltage of 9.00V9.00\,V.
      • An AA battery has a voltage of 1.5V1.5\,V.
  • Neuron Membrane Potentials

    • Neurons maintain a similar, though much smaller, electrical potential between the inside and outside of the membrane.
    • Resting Potential: At rest, the potential is typically 70mV-70\,mV.
    • Action Potential Peak: During an action potential, the potential reaches approximately +40mV+40\,mV.

The Mechanism of the Action Potential

  • Voltage-Sensing Channels

    • Ion channels in the membrane sense changes in voltage. At rest, Sodium (Na+Na^+) and Potassium (K+K^+) channels are closed.
  • Current Flow and Membrane Reversal

    • The process begins when the membrane potential becomes less negative.
    • Sodium (Na+Na^+) Influx: The Na+Na^+ channels open. Na+Na^+ ions flow into the cell because they are moving from a high to low concentration and are attracted to the negative charge inside the neuron.
    • The Spike: The inward flow of positive Na+Na^+ ions causes the membrane potential to become more positive, resulting in the "spike" of the action potential.
    • Potassium (K+K^+) Efflux: Shortly after, K+K^+ ions flow through Potassium channels to move out of the cell. This causes the membrane potential to return to its resting state of 70mV-70\,mV.

Propagation of the Action Potential

  • Travel Down the Axon

    • Action potentials originate at the cell body.
    • When Na+Na^+ ions flow in, they spread to neighboring sections of the axon.
    • This makes the adjacent sections more positive, triggering an action potential there.
    • This cycle repeats sequentially down the entire length of the axon until it reaches the terminals.
  • Biological Variation

    • In giraffes, axons can be several meters long.
    • Despite the length, the mechanism of action potential propagation works exactly the same way as in shorter axons.

Synaptic Transmission and Networking

  • The Synaptic Junction

    • Synapses are the connections between neurons located at the end of the axon.
    • Transmission is chemical rather than purely electrical.
  • Neurotransmitters and Receptors

    • Information is sent to the next neuron via chemicals called neurotransmitters.
    • These chemicals are released into the small space (synaptic cleft) between neurons.
    • Special proteins called receptors on the membrane of the receiving neuron capture these neurotransmitters.
  • Signal Integration and Summation

    • The activation of receptors causes very small changes in the membrane potential of the receiving neuron.
    • Summation: When enough of these small changes occur close together in time and space on the neuron, they add up.
    • If the sum is sufficient, it triggers a new action potential in the next neuron, restarting the process.
  • Complexity of Neural Networks

    • Neurons do not exist in isolation but form complicated networks.
    • Each individual neuron may receive tens of thousands of different inputs.