Periods of rest in fMRI contain individual spontaneous events which are related to slowly fluctuating spontaneous activity

Authors

  • Natalia Petridou,

    Corresponding author
    1. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
    2. Rudolf Mangus Institute/Radiology, University Medical Centre Utrecht, Utrecht, Netherlands
    • UMC Utrecht, Room Q.04.4.310 (HP E.01.132), Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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  • César Caballero Gaudes,

    1. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
    2. Centre for Biomedical Imaging, Department of Radiology and Medical Informatics, Hôpitaux Universitarie de Genève, Genève, Switzerland
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  • Ian L. Dryden,

    1. Department of Statistics, University of South Carolina, Columbia, South Carolina
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  • Susan T. Francis,

    1. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
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  • Penny A. Gowland

    1. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
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Abstract

fMRI studies of brain activity at rest study slow (<0.1 Hz) intrinsic fluctuations in the blood-oxygenation-level-dependent (BOLD) signal that are observed in a temporal scale of several minutes. The origin of these fluctuations is not clear but has previously been associated with slow changes in rhythmic neuronal activity resulting from changes in cortical excitability or neuronal synchronization. In this work, we show that individual spontaneous BOLD events occur during rest, in addition to slow fluctuations. Individual spontaneous BOLD events were identified by deconvolving the hemodynamic impulse response function for each time point in the fMRI time series, thus requiring no information on timing or a-priori spatial information of events. The patterns of activation detected were related to the motor, visual, default-mode, and dorsal attention networks. The correspondence between spontaneous events and slow fluctuations in these networks was assessed using a sliding window, seed-correlation analysis, where seed regions were selected based on the individual spontaneous event BOLD activity maps. We showed that the correlation varied considerably over time, peaking at the time of spontaneous events in these networks. By regressing spontaneous events out of the fMRI signal, we showed that both the correlation strength and the power in spectral frequencies <0.1 Hz decreased, indicating that spontaneous activation events contribute to low-frequency fluctuations observed in resting state networks with fMRI. This work provides new insights into the origin of signals detected in fMRI studies of functional connectivity. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.

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