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Related Concept Videos

Action Potential01:14

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...
Generation of Action Potential in Skeletal Muscles01:24

Generation of Action Potential in Skeletal Muscles

Every cell in the body maintains a membrane potential due to an uneven distribution of positive and negative charges across its plasma membrane. The membrane potential is measured in millivolts and quantifies the difference in charge across the membrane.
Like neurons, muscle cells are also regarded as excitable due to their capacity to change in response to stimuli, primarily due to voltage-gated ion channels embedded in their plasma membranes, which get activated by alterations in the cell's...
Propagation of Action Potentials01:23

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: May 12, 2026

Subtype-specific Optical Action Potential Recordings in Human Induced Pluripotent Stem Cell-derived Ventricular Cardiomyocytes
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Subtype-specific Optical Action Potential Recordings in Human Induced Pluripotent Stem Cell-derived Ventricular Cardiomyocytes

Published on: September 27, 2018

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Cell-specific models of hiPSC-CMs developed by the gradient-based parameter optimization method fitting two different

Yixin Zhang1, Futoshi Toyoda2,3, Yukiko Himeno4,5

  • 1Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan.

Scientific Reports
|June 7, 2024
PubMed
Summary
This summary is machine-generated.

Parameter optimization successfully identified cardiac action potential ionic currents when analyzing control and blocked waveforms. This method, applied to human induced pluripotent stem cell-derived cardiomyocytes, proved robust even with noisy data.

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Area of Science:

  • Cardiovascular Physiology
  • Computational Biology
  • Biophysics

Background:

  • Parameter optimization (PO) methods are used to determine ionic current composition in cardiac action potential (AP) waveforms using computational models.
  • Fitting a single AP record in PO methods can be insufficient for unique solutions due to limited information.

Purpose of the Study:

  • To enhance the accuracy and reliability of PO methods for dissecting cardiac ionic current composition.
  • To validate the PO method using experimental data from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

Main Methods:

  • Utilized a computational model of cardiac membrane excitation for initial PO method testing.
  • Applied PO to a pair of control and in silico IKr-blocked AP waveforms.
  • Tested the PO method on experimental AP recordings from hiPSC-CMs, including control and IKr-blocked states.
  • Implemented stable segment selection and iterative processing to overcome experimental data challenges.

Main Results:

  • The PO method demonstrated perfect performance when applied to in silico control and single-channel blocked AP pairs.
  • Simultaneous fitting of experimental control and IKr-blocked APs from hiPSC-CMs was initially challenging due to signal noise and variability.
  • Selecting stable recording segments and employing iterative PO processing largely resolved technical issues.
  • Quantitative ionic mechanisms derived from optimized parameters aligned with established physiological understanding.

Conclusions:

  • The PO method is highly effective for determining cardiac ionic current composition, especially when analyzing paired control and blocked AP waveforms.
  • Iterative PO with stable segment selection enhances robustness for analyzing experimental AP data from hiPSC-CMs.
  • The validated PO method provides reliable quantitative insights into cardiac electrophysiology consistent with existing knowledge.