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Research ArticleResearch Article: New Research, Cognition and Behavior

Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity

Thomas Donoghue, Julio Dominguez and Bradley Voytek
eNeuro 25 September 2020, 7 (6) ENEURO.0192-20.2020; DOI: https://doi.org/10.1523/ENEURO.0192-20.2020
Thomas Donoghue
1Department of Cognitive Science, University of California, San Diego
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Julio Dominguez
1Department of Cognitive Science, University of California, San Diego
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Bradley Voytek
1Department of Cognitive Science, University of California, San Diego
2Halıcıoğlu Data Science Institute, University of California, San Diego
3Neurosciences Graduate Program, University of California, San Diego
4Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, CA 92093
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  • Figure 1.
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    Figure 1.

    Literature analysis of band ratio related articles. A, Associations between published journal articles referring to band ratio measures and cognitive and clinical associations. Each cell represents the proportion of articles referring to a specified band ratio measure that also mentions the corresponding association term. B, Total counts of the number of articles mentioning each band ratio measure.

  • Figure 2.
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    Figure 2.

    Overview of band ratio measures and spectral parameters. A, An example power spectrum in which shaded regions reflect the θ band (4–8 Hz) and β band (20–30 Hz), respectively. Band ratio measures, such as the θ/β ratio, are calculated by dividing the average power between these two bands. B, An example of a parameterized power spectrum, in which aperiodic activity is separated from measured periodic components. This is an example spectrum from EEG data, in which peaks in θ, α, and β power are present. C, Examples of simulated power spectra with and without component oscillations of the θ/β ratio. Black lines indicate the simulated data, with red line reflecting the model fit, the dashed blue line indicating the aperiodic component of the model fit, and the green lines indicating the location of canonical θ and β oscillations. Band ratio measures, although intended to measure periodic activity, will reflect power at the predetermined frequencies regardless of whether there is evidence of periodic activity at those frequencies.

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    Figure 3.

    Equivalent band ratio differences from distinct changes. Simulations demonstrating the underdetermined nature of band ratio measures. In each case, the power spectrum plotted in orange has the same difference of measured θ/β ratio, indicated as Δ TBR, from the reference spectrum, in blue. This difference in ratio can arise from changes in multiple different features of the data, including a shift in: (A) periodic parameters such as the center frequency, power, or bandwidth of oscillations, and/or from a shift in; (B) aperiodic properties of the data, in this case the aperiodic exponent. Differences in aperiodic activity can induce differences in measured band ratios, even without any periodic components present (bottom panel).

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    Figure 4.

    Single parameter simulations. Simulations of changes in measured θ/β ratio (TBR) as individual parameters are varied, including: (A) periodic parameters and (B) aperiodic parameters. Changes in θ center frequency show an increase in θ/β ratio as the heightened activity is better captured in the canonical band, then decreases as activity leaves the band. Increasing θ power and bandwidth both increase θ/β ratio while increasing β power and bandwidth decreases θ/β ratio. The center frequency and bandwidth of α peaks also influences measured θ/β ratio, although α is not supposed to be included in the measure. β parameters essentially have the inverse effect of changes in θ parameters. Changes in aperiodic exponent also substantially impact measured θ/β ratio, although offset has no effect. Note that the layout of this figure corresponds to Figure 3, in which examples of how each parameter influences measured θ/β ratio can be seen. CF: center frequency, PW: power, BW: bandwidth.

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    Figure 5.

    Interacting parameter simulations. Measured θ/β ratio values in simulations as two spectral parameters are varied together. Ratio measures are plotted in log10 space because of their skewed distributions. Combinations plotted are aperiodic exponent with low band center frequency (A), as well as with low band power (B), and high band power (C). All combinations of varying parameters influence measured band ratio values.

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    Figure 6.

    Correlations between spectral parameters and band ratio measures in EEG data. In a large EEG dataset, correlation results are reported for band ratios as compared with the periodic (left) and aperiodic (right) parameters for the (A) θ/β ratio, (B) θ/α ratio, and (C) α/β ratio. In A, these results show that the θ/β ratio is most strongly correlated with the aperiodic exponent, and less related to power in the θ or β. In contrast, B, C, show that any ratio measure that includes an α band is most strongly correlated to α power, meaning any α ratio is mostly reflecting just α power. CF: center frequency, PW: power, BW: bandwidth.

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    Figure 7.

    Topographies of band ratio measures and spectral parameters. Topographical maps of the (A) ratios measures, including the θ/β ratio, θ/α ratio and α/β ratio. For comparison, the topographies of the aperiodic exponent (B) and of α power (D) are also presented. Each topography is scaled to relative range of the data, with higher values plotted in lighter colors (yellow). C, The spatial correlation between topographies of each ratio measure to spectral parameters including power of θ, α and β, and the aperiodic exponent (EXP). TBR: theta / beta ratio, TAR: theta / alpha ratio, ABR: alpha / beta ratio.

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    Figure 8.

    Changes in ratios and spectral parameters across blocks. Each row reflects a band ratio measure and each column reflects a spectral parameter. Each point is a difference measure across blocks, the value of the measure in a block, minus the value of that measure in the prior block, collected across all subjects. Printed in the inset is the spearman correlation between the measures. Consistent with prior analyses, changes across blocks in the θ/β ratio are most correlated with changes in aperiodic exponent, and changes in θ/α and α/β are most correlated with changes in α power.

Tables

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    Table 1

    Simulated periodic parameters

    θαβ
    Default61021.5
    CFRange4–88–1313–30
    Increment0.250.251
    Default0.50.50.5
    PWRange0–1.00–1.00–1.0
    Increment0.10.10.1
    Default0.10.10.1
    BWRange0.2–0.40.2–0.40.2–0.4
    Increment0.20.20.2
    • Each parameter is given a default value, used when this parameter is included but not varied, and a range and increment, which define the range of simulated values when this parameter is systematically varied. CF: center frequency, PW: power, BW: bandwidth.

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    Table 2

    Simulated aperiodic parameters

    DefaultRangeIncrement
    Offset00–2.50.25
    Exponent10–30.2
    • Same description as Table 1, for aperiodic parameters.

Extended Data

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  • Extended Data 1

    Project code. Supplementary package of code used for simulations and analysis. Download Extended Data 1, ZIP file.

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Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity
Thomas Donoghue, Julio Dominguez, Bradley Voytek
eNeuro 25 September 2020, 7 (6) ENEURO.0192-20.2020; DOI: 10.1523/ENEURO.0192-20.2020

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Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity
Thomas Donoghue, Julio Dominguez, Bradley Voytek
eNeuro 25 September 2020, 7 (6) ENEURO.0192-20.2020; DOI: 10.1523/ENEURO.0192-20.2020
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Keywords

  • aperiodic neural activity
  • frequency band ratios
  • neural oscillations
  • spectral analyses
  • θ/β ratio

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