The role of transient spectral ‘bursts’ in functional connectivity: A magnetoencephalography study
Zelekha A. Seedat,
Andrew J. Quinn,
Diego Vidaurre,
Lucrezia Liuzzi,
Lauren E. Gascoyne,
Benjamin A.E. Hunt,
George C. O’Neill,
Daisie O. Pakenham,
Karen J. Mullinger,
Peter G. Morris,
Mark W. Woolrich,
Matthew J. Brookes
Affiliations
Zelekha A. Seedat
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
Andrew J. Quinn
Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK
Diego Vidaurre
Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK; Department of Clinical Medicine, Palle Juul-Jensens Boulevard 82, Building 2, Incuba/Skejby, 8200 Aarhus N, Denmark
Lucrezia Liuzzi
Mood Brain and Development Unit, Emotion and Development Branch, NIH/NIMH, Bethesda, MD 20892, USA
Lauren E. Gascoyne
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
Benjamin A.E. Hunt
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; Diagnostic Imaging, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada
George C. O’Neill
Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N 3AR, UK
Daisie O. Pakenham
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
Karen J. Mullinger
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
Peter G. Morris
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
Mark W. Woolrich
Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK
Matthew J. Brookes
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; Corresponding author.
Neural oscillations dominate electrophysiological measures of macroscopic brain activity and fluctuations in these rhythms offer an insightful window on cortical excitation, inhibition, and connectivity. However, in recent years the ‘classical’ picture of smoothly varying oscillations has been challenged by the idea that many ‘oscillations’ may actually be formed from the recurrence of punctate high-amplitude bursts in activity, whose spectral composition intersects the traditionally defined frequency ranges (e.g. alpha/beta band). This finding offers a new interpretation of measurable brain activity, however neither the methodological means to detect bursts, nor their link to other findings (e.g. connectivity) have been settled. Here, we use a new approach to detect bursts in magnetoencephalography (MEG) data. We show that a time-delay embedded Hidden Markov Model (HMM) can be used to delineate single-region bursts which are in agreement with existing techniques. However, unlike existing techniques, the HMM looks for specific spectral patterns in timecourse data. We characterise the distribution of burst duration, frequency of occurrence and amplitude across the cortex in resting state MEG data. During a motor task we show how the movement related beta decrease and post movement beta rebound are driven by changes in burst occurrence. Finally, we show that the beta band functional connectome can be derived using a simple measure of burst overlap, and that coincident bursts in separate regions correspond to a period of heightened coherence. In summary, this paper offers a new methodology for burst identification and connectivity analysis which will be important for future investigations of neural oscillations.
