rtMEG: a real-time software interface for magnetoencephalography

  • Authors:

  • Gustavo Sudre;Lauri Parkkonen;Elizabeth Bock;Sylvain Baillet;Wei Wang;Douglas J. Weber

  • Affiliations:

  • Program in Neural Computation, Carnegie Mellon University, Pittsburgh, PA;Brain Research Unit, Low Temperature Laboratory, Aalto University School of Science, Espoo, Finland;Department of Neurology, Froedtert & The Medical College of Wisconsin, Milwaukee, WI;Departments of Neurology and Biophysics, Froedtert & The Medical College of Wisconsin, Milwaukee, WI;Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA;Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA

  • Venue:
  • Computational Intelligence and Neuroscience - Special issue on academic software applications for electromagnetic brain mapping using MEG and EEG
  • Year:
  • 2011

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Abstract

To date, the majority of studies using magnetoencephalography (MEG) rely on off-line analysis of the spatiotemporal properties of brain activity. Real-time MEG feedback could potentially benefit multiple areas of basic and clinical research: brain-machine interfaces, neurofeedback rehabilitation of stroke and spinal cord injury, and new adaptive paradigm designs, among others. We have developed a software interface to stream MEG signals in real time from the 306-channel Elekta Neuromag MEG system to an external workstation. The signals can be accessed with a minimal delay (≤45 ms) when data are sampled at 1000 Hz, which is sufficient for most real-time studies. We also show here that real-time source imaging is possible by demonstrating real-time monitoring and feedback of alpha-band power fluctuations over parieto-occipital and frontal areas. The interface is made available to the academic community as an open-source resource.