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

Atomic Force Microscopy01:08

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...

You might also read

Related Articles

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

Sort by
Same author

Revolutionizing Pediatric Neurophysiology With Magnetoencephalography.

Psychophysiology·2026
Same author

Ictal and interictal MEG in pediatric patients with tuberous sclerosis and drug resistant epilepsy.

Epilepsy research·2018
Same author

Improving the performance of the signal space separation method by comprehensive spatial sampling.

Physics in medicine and biology·2010
Same author

Combined use of non-invasive techniques for improved functional localization for a selected group of epilepsy surgery candidates.

NeuroImage·2009
Same author

Sensory afferent inhibition within and between limbs in humans.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2009
Same author

Effects of sensor calibration, balancing and parametrization on the signal space separation method.

Physics in medicine and biology·2008

Related Experiment Video

Updated: Jul 9, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Artifact and head movement compensation in MEG.

M Medvedovsky1, S Taulu, R Bikmullina

  • 1BioMag Laboratory, HUSLAB, The Hospital District of Helsinki and Uusimaa, Helsinki, Finland. marikmedv@yahoo.com

Neurology, Neurophysiology, and Neuroscience
|December 11, 2007
PubMed
Summary

Continuous head position monitoring with movement compensation (MC) in magnetoencephalography (MEG) can be improved. Using temporal extension of signal space separation (tSSS) with MC significantly reduces noise and improves source localization accuracy compared to standard MC-SSS.

More Related Videos

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers
14:52

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers

Published on: January 13, 2018

Related Experiment Videos

Last Updated: Jul 9, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers
14:52

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers

Published on: January 13, 2018

Area of Science:

  • Neuroscience
  • Biophysics
  • Biomedical Engineering

Background:

  • Magnetoencephalography (MEG) measurements are sensitive to head movement, traditionally limiting its use.
  • Continuous head position monitoring and movement compensation (MC) using signal space separation (SSS) or its temporal extension (tSSS) offer a solution.
  • Temporal extension (tSSS) is crucial for rejecting artifacts close to sensors.

Purpose of the Study:

  • To investigate the influence of MC-SSS and MC-tSSS on MEG results.
  • To compare the effectiveness of MC-SSS versus MC-tSSS in correcting movement-related artifacts.

Main Methods:

  • Recorded somatosensory evoked MEG responses to median nerve stimulation.
  • Compared localization error, noise, goodness of fit, and confidence volume using MC-SSS and MC-tSSS.
  • Utilized data from 204 planar gradiometers and 102 magnetometers on a subject with controlled head movement.

Main Results:

  • MC-SSS showed increased stimulus artifact and random noise with head shifts exceeding 5 cm.
  • MC-SSS decreased localization error up to 5 cm but increased gradiometer noise.
  • MC-tSSS significantly reduced noise (gradiometers: 5.3 to 2.8 fT/cm; magnetometers: 1.4 to 0.8 fT), improved localization error (2.13 to 0.89 cm), and increased goodness of fit (61.5% to 76.5%).

Conclusions:

  • Head position correction requires robust artifact rejection methods.
  • MC-tSSS effectively suppresses noise and nearby artifacts, enhancing the signal-to-noise ratio.
  • Recommend limiting MC use to 3 cm head shift and employing tSSS-based MC for improved MEG accuracy.