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Action Potentials

Action Potentials

Neurons: The Axon

Neurons: The Axon

Axons are long, cytoplasmic processes of nerve cells capable of propagating electrical impulses known as action potentials. The cytoplasm or axoplasm of an axon contains neurofibrils, neurotubules, small vesicles, lysosomes, mitochondria, and various enzymes, all encased within the axolemma, the plasma membrane of the axon.
The axon attaches to the cell body at a cone-shaped elevation called the axon hillock. The initial part of the axon, closest to the hillock, is known as the initial segment....

Action Potential

Action Potential

Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...

Action Potential

Action Potential

Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...

Propagation of Action Potentials

Propagation of Action Potentials

The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...

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Related Experiment Video

Updated: Apr 12, 2026

Axon Stretch Growth: The Mechanotransduction of Neuronal Growth

Axon Stretch Growth: The Mechanotransduction of Neuronal Growth

Published on: August 10, 2011

Delayed feedback model of axonal length sensing.

Bhargav R Karamched¹, Paul C Bressloff¹

¹Department of Mathematics, University of Utah, Salt Lake City, Utah.

Biophysical Journal

|May 9, 2015

Summary

This summary is machine-generated.

This study models how neurons sense axonal length using oscillating signals. Longer axons produce lower frequency signals, with motor transport fluctuations impacting accuracy.

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Area of Science:

Cell Biology
Neuroscience
Biophysics

Background:

Cell size and organelle regulation are fundamental biological questions.
Neuronal axons present unique size homeostasis challenges due to their extreme lengths.
A proposed mechanism links axonal length to the frequency of retrograde molecular motor signals.

Purpose of the Study:

To develop a mathematical model of the proposed molecular-motor-based axonal length-sensing mechanism.
To investigate the relationship between axonal length and signal frequency.
To predict the impact of molecular motor transport dynamics on length sensing reliability.

Main Methods:

Coupling advection-diffusion equations for bidirectional motor transport with a chemical signaling network.
Analyzing emergent chemical oscillations via Hopf bifurcation analysis.
Simulating the effects of molecular motor knockdown and transport fluctuations.

Main Results:

Chemical oscillations emerge from delayed negative feedback, acting as a length-encoding signal.
Oscillation frequency is a monotonically decreasing function of axonal length.
Kinesin or dynein knockdown increases oscillation frequency, predicting longer axons.
Model predicts reduced reliability of length sensing for longer axons due to transport fluctuations.

Conclusions:

The developed mathematical model supports a frequency-based mechanism for axonal length sensing.
Delayed negative feedback in signaling networks drives emergent oscillations for length encoding.
Axonal length sensing accuracy is potentially limited by the stochasticity of molecular motor transport.