Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...

You might also read

Related Articles

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

Sort by
Same author

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units.

Journal of neural engineering·2022
Same author

Mathematical relationships between spinal motoneuron properties.

eLife·2022
Same author

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons.

The Journal of physiology·2022
Same author

Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task.

The Journal of physiology·2022
Same author

Reducing the Calibration Time in Somatosensory BCI by Using Tactile ERD.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2022
Same author

The control and training of single motor units in isometric tasks are constrained by a common input signal.

eLife·2022
Same journal

Ultrasound-Informed State Estimation of Wrist Tremor Dynamics via Koopman Operator for Personalized Sensory Peripheral Nerve Stimulation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Motion Intention Recognition and DDPG-Based Adaptive Impedance Control for a Robotic Upper-Limb Exoskeleton.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

CNN-Based Modelling Reveals Temporal Brain Dynamics of Auditory Intensity Processing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Pathology-Informed Augmentation Improves Cross-Cohort IMU-to-vGRF Estimation Between Healthy Adults and Adults With Osteoarthritis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Effects of task-driven head orientations on gait and balance during walking in virtual reality.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Wearable sensor-based Mild Cognitive Impairment Identification: A Multi-Domain Gait Analysis Approach with Association Rule Mining.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
See all related articles

Related Experiment Video

Updated: Jun 4, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

Spike sorting by stochastic simulation.

Di Ge1, Eric Le Carpentier, Jérôme Idier

  • 1Glaizer Groupe, 92240 Malakoff, France. ge.di@glaizer.com

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
|February 15, 2011
PubMed
Summary
This summary is machine-generated.

This study enhances automatic decomposition of multiunit signals by modeling amplitude variability and using Markov Chain Monte Carlo (MCMC) simulation. The improved method achieves over 90% accuracy in identifying neural action potentials from complex recordings.

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter
07:37

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Published on: February 13, 2014

Related Experiment Videos

Last Updated: Jun 4, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter
07:37

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Published on: February 13, 2014

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Decomposition of multiunit signals is crucial for analyzing neural and muscular activity.
  • Automatic decomposition faces challenges, particularly with temporally overlapped potentials.
  • Previous work introduced a Bayesian model with MAP estimation for multiunit signal decomposition.

Purpose of the Study:

  • To develop a more sophisticated signal model incorporating unit potential amplitude variability.
  • To implement Markov Chain Monte Carlo (MCMC) simulation and a Bayesian Minimum Mean Square Error (MMSE) estimator.
  • To mathematically prove the convergence of the proposed Bayesian approach.

Main Methods:

  • Proposed a signal model accounting for amplitude variability of individual unit potentials.
  • Utilized Markov Chain Monte Carlo (MCMC) simulation for posterior distribution approximation.
  • Implemented a Bayesian Minimum Mean Square Error (MMSE) estimator based on MCMC samples.
  • Provided mathematical proof for the convergence properties of the MCMC-MMSE method.

Main Results:

  • The enhanced method demonstrated high accuracy (>90%) in spike identification for intramuscular signals.
  • The approach successfully resolved multiunit recordings with up to 8 concurrently active units.
  • The method's convergence properties were mathematically established.

Conclusions:

  • The proposed Bayesian approach with MCMC and MMSE significantly improves automatic decomposition of multiunit signals.
  • The method is effective for intramuscular recordings and applicable to other multiunit signal types.
  • Accurate spike identification is achievable even with complex, overlapping potentials.