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Frequency and power of human alpha oscillations drift systematically with time-on-task

(2019) NEUROIMAGE. 192. p.101-114
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Organization
Abstract
Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (similar to 1 h), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8-13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (similar to 8-10 Hz), while components with unique changes oscillated primarily in the higher alpha-band (similar to 9-13 Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation.
Keywords
NEURAL OSCILLATIONS, EEG ALPHA, BRAIN OSCILLATIONS, ATTENTIONAL, MODULATION, NEURONAL MECHANISMS, BAND OSCILLATIONS, SPATIAL ATTENTION, PREDICTS, RHYTHMS, SYNCHRONIZATION, EEG, Alpha, Non-stationarity, Oscillations, Power, Frequency

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Citation

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MLA
Benwell, Christopher S. Y., et al. “Frequency and Power of Human Alpha Oscillations Drift Systematically with Time-on-Task.” NEUROIMAGE, vol. 192, 2019, pp. 101–14.
APA
Benwell, C. S. Y., London, R., Tagliabue, C. F., Veniero, D., Gross, J., Keitel, C., & Thut, G. (2019). Frequency and power of human alpha oscillations drift systematically with time-on-task. NEUROIMAGE, 192, 101–114.
Chicago author-date
Benwell, Christopher S. Y., Raquel London, Chiara F. Tagliabue, Domenica Veniero, Joachim Gross, Christian Keitel, and Gregor Thut. 2019. “Frequency and Power of Human Alpha Oscillations Drift Systematically with Time-on-Task.” NEUROIMAGE 192: 101–14.
Chicago author-date (all authors)
Benwell, Christopher S. Y., Raquel London, Chiara F. Tagliabue, Domenica Veniero, Joachim Gross, Christian Keitel, and Gregor Thut. 2019. “Frequency and Power of Human Alpha Oscillations Drift Systematically with Time-on-Task.” NEUROIMAGE 192: 101–114.
Vancouver
1.
Benwell CSY, London R, Tagliabue CF, Veniero D, Gross J, Keitel C, et al. Frequency and power of human alpha oscillations drift systematically with time-on-task. NEUROIMAGE. 2019;192:101–14.
IEEE
[1]
C. S. Y. Benwell et al., “Frequency and power of human alpha oscillations drift systematically with time-on-task,” NEUROIMAGE, vol. 192, pp. 101–114, 2019.
@article{8650867,
  abstract     = {Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (similar to 1 h), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8-13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (similar to 8-10 Hz), while components with unique changes oscillated primarily in the higher alpha-band (similar to 9-13 Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation.},
  author       = {Benwell, Christopher S. Y. and London, Raquel and Tagliabue, Chiara F. and Veniero, Domenica and Gross, Joachim and Keitel, Christian and Thut, Gregor},
  issn         = {1053-8119},
  journal      = {NEUROIMAGE},
  keywords     = {NEURAL OSCILLATIONS,EEG ALPHA,BRAIN OSCILLATIONS,ATTENTIONAL,MODULATION,NEURONAL MECHANISMS,BAND OSCILLATIONS,SPATIAL ATTENTION,PREDICTS,RHYTHMS,SYNCHRONIZATION,EEG,Alpha,Non-stationarity,Oscillations,Power,Frequency},
  language     = {eng},
  pages        = {101--114},
  title        = {Frequency and power of human alpha oscillations drift systematically with time-on-task},
  url          = {http://dx.doi.org/10.1016/j.neuroimage.2019.02.067},
  volume       = {192},
  year         = {2019},
}

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