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

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

Multichannel Extracellular Recording in Freely Moving Mice

Multichannel Extracellular Recording in Freely Moving Mice

Published on: May 26, 2023

Real-time multichannel neural spike recognition with DSPs.

D A Willming¹, B C Wheeler

¹Dept. of Electr. and Comput. Eng., Illinois Univ., Urbana, IL.

IEEE Engineering in Medicine and Biology Magazine : the Quarterly Magazine of the Engineering in Medicine & Biology Society

|January 1, 1990

Summary

This study explored inexpensive digital signal processor (DSP) technology for rapid neuronal action potential (spike) data acquisition. Peak windowing, RMS error, and principal component analysis were evaluated for spike sorting accuracy.

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Stimulus-artifact elimination in a multi-electrode system.

IEEE transactions on biomedical circuits and systems·2013

Same author

Chronic network stimulation enhances evoked action potentials.

Journal of neural engineering·2010

Same author

Neuron network activity scales exponentially with synapse density.

Journal of neural engineering·2008

Same author

Patterning to enhance activity of cultured neuronal networks.

IEE proceedings. Nanobiotechnology·2006

Same author

A two-microphone dual delay-line approach for extraction of a speech sound in the presence of multiple interferers.

The Journal of the Acoustical Society of America·2002

Same author

Modulation of neural network activity by patterning.

Biosensors & bioelectronics·2001

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Rapid acquisition of neuronal action potential (spike) data is crucial for understanding neural activity.
Existing data acquisition technologies can be expensive and complex.
Digital Signal Processors (DSPs) offer a potential solution for cost-effective and rapid data acquisition.

Purpose of the Study:

To investigate data acquisition technology using inexpensive DSPs for rapid neuronal spike data collection.
To evaluate and compare three distinct spike sorting techniques for their efficacy.

Main Methods:

Developed a test system utilizing DSPs for neuronal spike data acquisition.
Implemented and assessed three spike sorting algorithms: peak windowing, Root Mean Square (RMS) error comparison, and principal component analysis.

More Related Videos

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Related Experiment Videos

Last Updated: Jul 7, 2026

Multichannel Extracellular Recording in Freely Moving Mice

Multichannel Extracellular Recording in Freely Moving Mice

Published on: May 26, 2023

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Compared the performance and accuracy of each spike sorting method.

Main Results:

Peak windowing provided a simple classification method based on spike amplitude.
RMS error calculation allowed spike classification by comparing waveform similarity to stored templates.
Principal component analysis utilized computed vectors for classifying spike waveforms based on extracted features.
The study details the constructed test system and presents comparative results for each algorithm.

Conclusions:

DSP-based data acquisition offers a viable and cost-effective approach for neuronal spike analysis.
The choice of spike sorting technique impacts the accuracy and efficiency of neuronal data analysis.
Principal component analysis demonstrated a sophisticated method for waveform classification, potentially offering higher accuracy.