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

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences01:17

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences

790
A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
790
Muscle Stimulation Frequency01:22

Muscle Stimulation Frequency

2.1K
The contraction strength of muscles is regulated by motor neurons, which modulate the frequency of action potentials dispatched to the motor units based on the body's requirements. This process of varying the muscle stimulation frequency allows muscles to contract with a force that is precisely tailored to the needs of the moment, whether lifting a feather or a heavy box.
Wave summation
At low firing rates, motor neurons induce individual twitch contractions in muscle fibers. These twitches...
2.1K

You might also read

Related Articles

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

Sort by
Same author

Gamma suppression correlates with thalamic stimulation therapeutic response in intractable epilepsy.

Epilepsia·2026
Same author

A computationally efficient adaptive phase response curve estimator for real-time closed-loop neuromodulation.

Journal of neural engineering·2026
Same author

Parkinsonism disrupts the population-level organization of cortical dynamics.

bioRxiv : the preprint server for biology·2026
Same author

Metric validation for detection of delayed and directed coupling.

Journal of neural engineering·2026
Same author

A novel methodology for localizing pallidal deep brain stimulation leads.

Frontiers in neuroanatomy·2026
Same author

Sleep firing rate homeostasis is disrupted in mild parkinsonism.

NPJ Parkinson's disease·2026
Same journal

Cortex-anchored sensor-space harmonics for event-related EEG.

Journal of neural engineering·2026
Same journal

Neural mechanisms of mixed speech and grasp representation in sensorimotor cortices.

Journal of neural engineering·2026
Same journal

Developing a binary communication protocol between biological neural networks using virtual white matter.

Journal of neural engineering·2026
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
See all related articles

Related Experiment Video

Updated: Jun 24, 2025

Deep Brain Stimulation with Simultaneous fMRI in Rodents
11:09

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Published on: February 15, 2014

14.0K

Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activity.

Hafsa Farooqi1, Jerrold L Vitek1, David Escobar Sanabria2

  • 1Department of Neurology, Medical School, University of Minnesota, Minneapolis, MN 55455, United States of America.

Journal of Neural Engineering
|June 6, 2024
PubMed
Summary
This summary is machine-generated.

Researchers optimized brain stimulation pulse patterns to precisely control neural activity. This computational study identified modulation strategies for suppressing or amplifying brain oscillations, crucial for developing targeted therapies for neurological disorders.

Keywords:
Parkinson’s diseasedeep brain stimulationmathematical modelsneuromodulationoptimizationstimulation-evoked neural responses

More Related Videos

Analysis of Gene Expression Changes in the Rat Hippocampus After Deep Brain Stimulation of the Anterior Thalamic Nucleus
09:46

Analysis of Gene Expression Changes in the Rat Hippocampus After Deep Brain Stimulation of the Anterior Thalamic Nucleus

Published on: March 8, 2015

10.9K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K

Related Experiment Videos

Last Updated: Jun 24, 2025

Deep Brain Stimulation with Simultaneous fMRI in Rodents
11:09

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Published on: February 15, 2014

14.0K
Analysis of Gene Expression Changes in the Rat Hippocampus After Deep Brain Stimulation of the Anterior Thalamic Nucleus
09:46

Analysis of Gene Expression Changes in the Rat Hippocampus After Deep Brain Stimulation of the Anterior Thalamic Nucleus

Published on: March 8, 2015

10.9K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K

Area of Science:

  • Computational neuroscience
  • Neuromodulation systems engineering
  • Biomedical signal processing

Background:

  • Precise neuromodulation is essential for understanding brain function and developing personalized brain stimulation therapies.
  • Low-frequency local field potentials (LFPs) are key biomarkers reflecting synaptic inputs and are suitable for chronic human recording.
  • Current methods lack optimal pulse patterns for real-time neural activity control.

Purpose of the Study:

  • To computationally identify optimal stimulation pulse patterns for maximizing the suppression or amplification of specific neural oscillations.
  • To investigate the role of different pulse modulation strategies (phase, amplitude, frequency) in controlling neural activity.
  • To develop advanced closed-loop brain stimulation strategies for precise, real-time neural control.

Main Methods:

  • Derived deep brain stimulation (DBS) pulse patterns using a generalized mathematical model of LFP activity.
  • Employed subject-specific neural dynamics models from Parkinson's disease patients.
  • Utilized convex and mixed-integer optimization tools with safety constraints on pulse parameters.

Main Results:

  • Optimal suppression or amplification requires a combination of phase, amplitude, and frequency pulse modulation.
  • Phase modulation alone suffices for constant amplitude oscillations; amplitude-frequency trade-offs are needed for time-varying envelopes.
  • Optimized pulse sequences demonstrated robustness against variations in stimulation-evoked neural activity dynamics.

Conclusions:

  • The study provides insight into the structure of pulse patterns for advanced closed-loop brain stimulation.
  • Identified modulation strategies enable precise, real-time control of neural activity.
  • Findings pave the way for more effective, personalized neuromodulation therapies.