Next Article in Journal
Toward a Multifactorial Conception of the Gilles de la Tourette Syndrome and Persistent Chronic Tic Disorder
Previous Article in Journal
Acute Regression in Young People with Down Syndrome
Previous Article in Special Issue
How Does Psychosocial Behavior Contribute to Cognitive Health in Old Age?
Article Menu

Export Article

Open AccessReview
Brain Sci. 2017, 7(6), 58; doi:10.3390/brainsci7060058

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies

1
Psychological & Brain Sciences, Indiana University, 1101 East 10th St, Bloomington, IN 47405, USA
2
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Stephanie Caccioppo
Received: 3 April 2017 / Revised: 23 May 2017 / Accepted: 25 May 2017 / Published: 31 May 2017
(This article belongs to the Special Issue Best Practices in Social Neuroscience)
View Full-Text   |   Download PDF [6603 KB, uploaded 31 May 2017]   |  

Abstract

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed. View Full-Text
Keywords: EEG; MEG; artifacts; data acquisition; reference electrode; data analysis; sensor space; source space EEG; MEG; artifacts; data acquisition; reference electrode; data analysis; sensor space; source space
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Puce, A.; Hämäläinen, M.S. A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies. Brain Sci. 2017, 7, 58.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Brain Sci. EISSN 2076-3425 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top