Related Experiment Video
Updated: May 21, 2026
09:47
Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
Published on: October 18, 2015
Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics
Fikret E Kapucu1, Jarno M A Tanskanen, Jarno E Mikkonen
1Department of Biomedical Engineering, Tampere University of Technology Tampere, Finland.
Frontiers in Computational Neuroscience
|June 23, 2012
Summary
We developed an adaptive algorithm using firing statistics to detect neuronal network bursts, even in complex, developing systems like human embryonic stem cell networks. This method accurately identifies burst activity for better understanding neuronal development and drug testing.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Biophysics
Background:
- Neuronal network activity analysis relies on spike and burst detection.
- Existing algorithms struggle with the complex, time-varying dynamics of developing neuronal networks, such as those derived from human embryonic stem cells (hESCs).
- Predefined criteria in common algorithms limit their adaptability to diverse neuronal network structures.
Purpose of the Study:
- To propose a novel, adaptive burst detection algorithm for neuronal networks with highly variable action potential dynamics.
- To accurately analyze the developing burst and spike activities in hESC-derived neuronal networks.
- To provide a versatile tool for studying neuronal development and for applications in drug screening and neurotoxicity assays.
Main Methods:
- Developed a firing statistics-based algorithm utilizing interspike interval (ISI) histograms.
- Calculated adaptive ISI thresholds for burst, pre-burst, and burst tail spikes using cumulative moving average (CMA) and skewness.
- Validated the algorithm on microelectrode array (MEA) data from spontaneously active hESC-derived neuronal networks.
- Compared results with two commonly employed burst detection algorithms.
Main Results:
- The proposed algorithm successfully detected burst activity in hESC-derived neuronal networks.
- Demonstrated adaptability to the network's firing statistics, outperforming traditional methods in complex scenarios.
- Illustrated significant differences in burst detection results compared to existing algorithms.
- Confirmed the algorithm's robustness across different neuronal cell network types.
Conclusions:
- The novel firing statistics-based algorithm provides adaptive and successful burst detection for developing neuronal networks.
- This method is particularly effective for analyzing hESC-derived neuronal networks, offering insights into human neuronal development.
- The algorithm serves as a valuable tool for neurodevelopmental studies, in vitro drug screening, and neurotoxicity assessments.
Related Concept Videos
01:14Action 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...
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
01:23Propagation 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...
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...
01:41Action Potentials
Overview
01:28Action Potential: Phases of Stimulation
The action potential is a complex electrical event that occurs in excitable cells, such as neurons and muscle cells. It consists of several distinct phases, each with specific characteristics.
Resting Phase:
In this phase, the cell's membrane is at its resting potential, typically around -70 millivolts (mV) for neurons. Inside the cell, there is a higher concentration of potassium ions (K+) and a lower concentration of sodium ions (Na+). Voltage-gated sodium channels are closed, and...
Resting Phase:
In this phase, the cell's membrane is at its resting potential, typically around -70 millivolts (mV) for neurons. Inside the cell, there is a higher concentration of potassium ions (K+) and a lower concentration of sodium ions (Na+). Voltage-gated sodium channels are closed, and...