Impact Factor 3.877

The world's most-cited Neurosciences journals

Technology Report ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neurosci. | doi: 10.3389/fnins.2018.00587

BrainWave: A MATLAB Toolbox for Beamformer Source Analysis of MEG Data

  • 1Program in Neurosciences and Mental Health, Hospital for Sick Children, Canada
  • 2MEG Laboratory, Dell Children's Medical Center of Central Texas, United States
  • 3Department of Medical Imaging, University of Toronto, Canada

BrainWave is an easy-to-use Matlab toolbox for the analysis of magnetoencephalography (MEG) data. It provides a graphical user interface for performing minimum-variance beamforming analysis with rapid and interactive visualization of evoked and induced brain activity. This article provides an overview of the main features of BrainWave with a step-by-step demonstration of how to proceed from raw experimental data to group source images and time series analyses. This includes data selection and pre-processing, magnetic resonance image (MRI) co-registration and normalization procedures, and the generation of volumetric (whole-brain) or cortical surface based source images, and corresponding source time series as virtual sensor (VS) waveforms and their time-frequency representations. We illustrate these steps using example data from a recently published study on response inhibition (Isabella, et al. 2015) using the Sustained Attention to Response Task (SART) paradigm in 12 healthy adult participants. In this task participants were required to press a button with their right index finger to a rapidly presented series of numerical digits and withhold their response to an infrequently presented target digit. This paradigm elicited movement-locked brain responses, as well as task-related modulation of brain rhythmic activity in different frequency bands (e.g., theta, beta and gamma), and is used to illustrate two different types of source reconstruction implemented in the BrainWave toolbox: 1) event-related beamforming of averaged brain responses and 2) beamformer analysis of modulation of rhythmic brain activity using the Synthetic Aperture Magnetometry (SAM) algorithm. We also demonstrate the ability to generate group contrast images between different response types, using the example of frontal theta activation patterns during error responses (failure to withhold on target trials). BrainWave is free academic software available for download at along with supporting software and documentation. The development of the BrainWave toolbox was supported by grants from the Canadian Institutes of Health Research, the National Research and Engineering Research Council of Canada, and the Ontario Brain Institute.

Keywords: matlab toolbox, Source analysis, Magnetoencephalography (MEG), beamforming, Group analysis, response inhibition

Received: 13 Jan 2018; Accepted: 06 Aug 2018.

Edited by:

Vladimir Litvak, Institute of Neurology, University College London, United Kingdom

Reviewed by:

Heinrich R. Liesefeld, Ludwig-Maximilians-Universität München, Germany
Robert A. Seymour, Aston University, Birmingham, United Kingdom  

Copyright: © 2018 Jobst, Ferrari, Isabella and Cheyne. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Douglas O. Cheyne, Hospital for Sick Children, Program in Neurosciences and Mental Health, Toronto, Canada,