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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...

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Updated: Jun 3, 2025

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear Model.

Qing Qin¹, Kaiyue Zhang¹, Yanqiu Che¹

¹Tianjin Key Laboratory of Information Sensing & Intelligent Control, Tianjin University of Technology and Education, Tianjin 300222, China.

Entropy (Basel, Switzerland)

|January 8, 2025

Summary

Acupuncture stimulation at the ST36 acupoint activates spinal neurons. Neuronal spiking activity is primarily influenced by the activity of other neurons, not just the acupuncture itself.

Keywords:

acupuncture coupling generalized linear model maximum likelihood estimation spike history

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Last Updated: Jun 3, 2025

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Published on: December 22, 2016

Area of Science:

Neuroscience
Acupuncture Research
Computational Biology

Background:

Acupuncture stimulation, specifically at the ST36 acupoint, is known to elicit neural responses in the spinal dorsal root ganglia.
Understanding the precise mechanisms underlying these neural responses to different acupuncture manipulations is crucial for its scientific application.

Purpose of the Study:

To investigate the neural mechanisms of acupuncture manipulations using computational modeling.
To identify the key factors influencing neuronal spiking activity during acupuncture stimulation.

Main Methods:

Utilized a coupling generalized linear model (GLM) to encode neuronal spiking activity.
Employed maximum likelihood estimation to fit model parameters, including stimulus, self-coupling, and cross-coupling parameters.
Validated the estimation algorithm using simulation data.

Main Results:

Acupuncture stimulus acts as an initial trigger for neuronal spiking activity.
The cross-coupling of other neurons' spike history emerged as the dominant factor influencing neuronal activity.
A positive correlation was observed between neuronal spiking waveform amplitude and the cross-coupling parameter.

Conclusions:

The study provides a computational framework for analyzing acupuncture's neural effects.
Neuronal network interactions, rather than solely direct stimulus, are key drivers of responses to acupuncture.
Findings support the theoretical basis for acupuncture's therapeutic efficacy through modulation of neural networks.