Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Action Potentials

Action Potentials

Cardiac Action Potential

Cardiac Action Potential

Cardiac action potentials are essential for proper heart function, enabling the rhythmic contractions needed for adequate blood circulation. Nodal cells and Purkinje fibers, specialized for electrical conduction, generate these action potentials.
The cardiac action potential process involves a series of phases characterized by the movement of ions across the cardiac cell membranes, leading to the depolarization and repolarization of the cardiac myocytes.
Ionic Basis of Cardiac Action Potentials

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Electrical stimulation precisely reproduces naturalistic spiking activity in complete and intermixed neural populations in the primate retina.

bioRxiv : the preprint server for biology·2026

Same author

Compression detects changes in spiking neural data from cortical lesions.

Journal of neural engineering·2026

Same author

Information-computation trade-offs in nonlinear transforms.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026

Same author

Compression Detects Changes in Spiking Neural Data from Cortical Lesions.

bioRxiv : the preprint server for biology·2026

Same author

Leveraging current steering and the biophysics of spike generation for cellular-resolution electrical stimulation of neurons.

Cell reports·2026

Same author

A Scalable 1024-Channel Ultra-Low-Power Spike Sorting Chip with Event-Driven Detection and Spatial Clustering.

IEEE journal of solid-state circuits·2025

Same journal

Use of RPNIs and Implanted Electrodes for Prosthetic Wrist and Multi-Grip Hand Control during Functional Tasks: A Case Study.

IEEE transactions on bio-medical engineering·2026

Same journal

Healthy Limb Driven Prediction for Real Time Control of Unilateral Exoskeletons in Gait Rehabilitation.

IEEE transactions on bio-medical engineering·2026

Same journal

A Miniature Wearable Ultrasound System for Continuous Bladder Monitoring with Sleeping-Position-Robust Modeling Strategies.

IEEE transactions on bio-medical engineering·2026

Same journal

A Bi-objective Array Optimization Framework for Magnetocardiographic Source Imaging.

IEEE transactions on bio-medical engineering·2026

Same journal

A Dynamic Mutual Information Measure of Phase-Amplitude Coupling with Uncertainty Quantification.

IEEE transactions on bio-medical engineering·2026

Same journal

Enhancing Communication Robustness for Leadless Pacemakers: 2-DOF Gain Compensation Across Physiologic and Pathologic Dynamics.

IEEE transactions on bio-medical engineering·2026

See all related articles

Search research articles

Home
A Framework For Compressive On-chip Action Potential Recording.

Home
A Framework For Compressive On-chip Action Potential Recording.

Related Experiment Video

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

A Framework for Compressive On-Chip Action Potential Recording.

Pumiao Yan, Dante G Muratore, E J Chichilnisky

IEEE Transactions on Bio-Medical Engineering

|September 29, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study presents an adaptive compression framework for high-bandwidth neural interfaces, significantly reducing data demands for implantable devices. The system achieves over 1000x compression while preserving 90% of neural spikes.

More Related Videos

Recording Synaptic Plasticity in Acute Hippocampal Slices Maintained in a Small-volume Recycling-, Perfusion-, and Submersion-type Chamber System

Recording Synaptic Plasticity in Acute Hippocampal Slices Maintained in a Small-volume Recycling-, Perfusion-, and Submersion-type Chamber System

Published on: January 1, 2018

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Related Experiment Videos

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

Recording Synaptic Plasticity in Acute Hippocampal Slices Maintained in a Small-volume Recycling-, Perfusion-, and Submersion-type Chamber System

Recording Synaptic Plasticity in Acute Hippocampal Slices Maintained in a Small-volume Recycling-, Perfusion-, and Submersion-type Chamber System

Published on: January 1, 2018

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Scaling neural recording systems to thousands of channels presents extreme bandwidth challenges for implantable devices.
Resource constraints in implantable devices necessitate efficient data compression for high-bandwidth neural interfaces.

Purpose of the Study:

To introduce an adaptive, multi-stage compression framework for high-bandwidth neural interfaces.
To reduce bandwidth demands for neural recording systems while preserving signal fidelity.

Main Methods:

Implemented a Wired-OR analog-to-digital compressive readout.
Developed a digital core for adaptive requantization, selective sampling, and encoding.
Utilized a mutual information-based criterion for spike sample selection.

Employed a static entropy coder optimized for neural signal statistics.

Main Results:

Achieved a 1098× total compression ratio on 512-channel macaque retina data.
Preserved 90% of recorded spikes.
Demonstrated that quantization levels can be matched to electrode SNR ($\bm {\lceil \log _{2} \rm{SNR} \rceil }$ bits) to reduce precision without degrading waveform fidelity.

Conclusions:

The adaptive compression framework effectively addresses bandwidth demands in neural recording systems.
The system successfully preserves critical neural waveform features and spike data.
This approach offers a viable solution for resource-constrained, high-channel-count implantable neural interfaces.