Hodgkin Huxley
Hodgkin Huxley - Related Videos
08:53
Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma
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Cited by 9 •
2017
Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).
09:16
An Introduction to Neurophysiology
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2023
Neurophysiology is broadly defined as the study of nervous system function. In this field, scientists investigate the central and peripheral nervous systems at the level of whole organs, cellular networks, single cells, or even subcellular compartments. A unifying feature of this wide-ranging discipline is an interest in the mechanisms that lead to the generation and propagation of electrical impulses within and between neurons. This subject is important not only for our understanding of the...
11:56
Historical View and Physiology Demonstration at the NMJ of the Crayfish Opener Muscle
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Cited by 33 •
2009
The opener muscle of the crayfish leg is presented for its historical importance and experimental versatility in muscle phenotype, synaptic physiology and plasticity.
FAQs
Membrane capacitance represents the ability of the cell membrane to store electrical charge. When ion-channel conductances change, the membrane potential does not adjust independently of that stored charge; the capacitance contributes to the voltage dynamics in the coupled equations. Including it allows the model to relate changing ionic currents to the timing and shape of electrical signals.
These processes occur in a defined sequence with different effects on membrane voltage. Sodium-channel activation supports depolarization, sodium-channel inactivation limits that inward influence, and delayed potassium-channel opening promotes repolarization. Representing them separately allows the model to reproduce the changing balance of ionic currents that determines the progression of an action potential.
The predicted outcome depends on the interaction between membrane potential, membrane capacitance, and voltage- and time-dependent ion-channel conductances. Their combined dynamics determine whether depolarization develops into a spike, how rapidly the voltage changes, and how the signal repolarizes. These relationships allow threshold and spike shape to emerge from the modeled electrical properties rather than being imposed separately.
Coupled differential equations connect changes in membrane potential with the changing conductances and ionic currents that produce them. This relationship makes it possible to examine electrical events as a time-dependent process instead of treating each current independently. As a result, the framework can predict measurable features such as threshold, action-potential shape, and propagation.
Researchers can use the framework to interpret electrophysiology measurements by relating observed membrane-voltage changes to modeled ionic currents and conductance changes. They can examine whether the predicted threshold, spike shape, or propagation behavior is consistent with experimental recordings. This provides a mathematical connection between electrical measurements and the underlying sequence of membrane processes described by the model.
The model provides predictions about when an excitable cell reaches threshold, how an action potential develops and repolarizes, and how electrical activity propagates. These outputs help organize observations from neural signaling experiments and support analysis of how membrane properties influence communication. Its predictions also provide a foundation for computational studies of brain function.
In computational biology and neuroscience, the framework supplies a mechanistic way to represent neural electrical activity through membrane capacitance, ionic currents, and changing conductances. It therefore supports models that connect cellular processes with signaling behavior. The same structure helps researchers study neural communication, interpret electrophysiology, and develop computational descriptions of brain function.