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Research ArticleNew Research, Cognition and Behavior

Characterizing Population EEG Dynamics throughout Adulthood

Ali Hashemi, Lou J. Pino, Graeme Moffat, Karen J. Mathewson, Chris Aimone, Patrick J. Bennett, Louis A. Schmidt and Allison B. Sekuler
eNeuro 30 November 2016, 3 (6) ENEURO.0275-16.2016; https://doi.org/10.1523/ENEURO.0275-16.2016
Ali Hashemi
1Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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Lou J. Pino
2InteraXon Inc., Toronto, Ontario, M5V 1K4, Canada
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Graeme Moffat
2InteraXon Inc., Toronto, Ontario, M5V 1K4, Canada
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Karen J. Mathewson
1Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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Chris Aimone
2InteraXon Inc., Toronto, Ontario, M5V 1K4, Canada
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Patrick J. Bennett
1Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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Louis A. Schmidt
1Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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Allison B. Sekuler
1Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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Article Figures & Data

Figures

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  • Figure 1.
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    Figure 1.

    Average power spectra at each channel for CAL (left) and NFB (right) conditions. Frontal and temporoparietal channels are represented by black and gray lines, respectively, and left and right channels in these regions are represented by solid and dashed lines, respectively.

  • Figure 2.
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    Figure 2.

    Log10-transformed EEG power in the 0- to 30-Hz range measured in females (white) and males (gray) at each channel for NFB (left) and CAL (right), shown in the form of violin plots (Hintze and Nelson, 1998). Filled circles represent the median, and the first and third quartiles are identified by the bottom and top of the bold vertical lines, respectively. The bottom and top of the thin vertical line represent the lower and upper adjacent values, respectively. Females had slightly higher power at all channels, regardless of task.

  • Figure 3.
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    Figure 3.

    Standard deviation of the average band power across ages (x-axis) plotted with the average standard deviation of each band power across participants within each age (y-axis). Within-age SD was calculated by calculating the SD across participants at each given age. Ages 78+ all had two or fewer participants, so we grouped them into a single age bin. Mean within-age SD (y-axis) was calculated as the average within-age SD. Between-age SD (x-axis) was calculated by first computing the mean band power for each individual age, then calculating the SD across these values.

  • Figure 4.
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    Figure 4.

    Delta band power plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males (solid line) and females (dashed line), and the shaded regions represent 95% confidence intervals.

  • Figure 5.
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    Figure 5.

    Theta band power plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males and females, and the shaded regions represent 95% confidence intervals.

  • Figure 6.
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    Figure 6.

    Alpha band power plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males and females, and the shaded regions represent 95% confidence intervals.

  • Figure 7.
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    Figure 7.

    Beta band power plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males and females, and the shaded regions represent 95% confidence intervals.

  • Figure 8.
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    Figure 8.

    Alpha peak frequency plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males and females, and the shaded regions represent 95% confidence intervals.

  • Figure 9.
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    Figure 9.

    Alpha asymmetry measured at frontal (top) and temporoparietal (bottom) electrodes plotted against age for males (gray symbols) and females (white symbols). Each point represents the mean for that age; symbol size represents how many individuals were used to compute the mean. Regression was used to compute the best-fitting curves separately for males and females, and the shaded regions represent 95% confidence intervals.

Tables

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    Table 1.

    User and session distribution by age and sex.

    Age (years)MaleFemaleTotal
    18–19481765
    20–298543241178
    30–3912274191646
    40–4910593591418
    50–597083441052
    60–69400166566
    70–79772097
    ≥80617
    Total437916506029
    • For each user, data were averaged for up to five sessions.

    • View popup
    Table 2.

    Regression coefficients (rounded to nearest 0.00001) estimated for each measure and channel in the CAL condition.

    MeasureChannelInterceptAgeAge2SexAge × sexAge2 × sexR2Age (m)Age (f)Age2 (m)Age2 (f)
    δAF70.43339†–0.00152***0.00010***–0.03076*0.000280.000100.210†
    δAF80.42873†–0.00201†0.00013†–0.03468*0.001010.000090.280†
    δTP90.95463†–0.00312†0.00011†0.01803–0.000950.000040.482†
    δTP100.94772†–0.00320†0.00013†0.02609*–0.000740.000010.535†
    θAF7–0.13675†–0.00064*0.00007***0.017980.000840.00013**0.380†–0.00064*0.000210.00007***0.00020†
    θAF8–0.15823†–0.00095**0.00008***–0.000640.000910.00011*0.282†–0.00095**–0.000040.00008***0.00019†
    θTP90.43667†–0.00191†0.00006**0.011320.000250.00008*0.393†–0.00191†–0.00166***0.00006**0.00013***
    θTP100.41830†–0.00225†0.00009†0.03257***0.000180.000050.515†
    αAF7–0.32292†0.00090**0.00006**0.11225†0.00116*0.00009*0.798†0.00090***0.00206†0.00006***0.00015†
    αAF8–0.36987†0.00071*0.00007***0.07154†0.000680.00008*0.645†0.00071*0.00139**0.00007***0.00016†
    αTP90.45606†–0.00139†–0.00004*–0.015590.000400.00015***0.229†–0.00139***–0.00099–0.00004*0.00011**
    αTP100.47902†–0.00145†–0.000000.006670.000000.00012*0.228†–0.00145***–0.00144**–0.000000.00011**
    βAF7–0.08567†0.00242†0.00009**0.26647†0.000720.000010.846†
    βAF8–0.15873†0.00318†0.00008**0.20429†–0.00027–0.000000.810†
    βTP90.34545†0.00173†–0.00005**0.05945†0.000080.00009*0.608†0.00173†0.00181***–0.00005**0.00004
    βTP100.37780†0.00224†–0.000000.07855†–0.000850.000070.589†
    α PeakAF710.28787†–0.02162†0.00010–0.00010†0.001220.000020.510†
    α PeakAF810.22824†–0.01597†0.00018–0.29203***–0.003410.000240.351†
    α PeakTP99.57089†–0.01469†0.000020.02296–0.00592*–0.000100.584†–0.01469†–0.02060†0.00002–0.00008
    α PeakTP109.60727†–0.01367†–0.000040.06327–0.00426–0.000070.567†
    α AsymAF8–AF7–0.04695†–0.000180.00002–0.04071†–0.00048–0.000010.338†
    α AsymTP10–TP90.02296†–0.000060.00004†0.02225†–0.00039–0.000040.220†
    • Bolded rows indicate cases where R 2 ≥ 0.5. *p < 0.05, **p < 0.01, ***p < 0.001, †p < 0.0001.

    • View popup
    Table 3.

    Regression coefficients (rounded to nearest 0.00001) estimated for each measure and channel in the NFB condition.

    MeasureChannelInterceptAgeAge2SexAge × sexAge2 × sexR 2Age (m)Age (f)Age2 (m)Age2 (f)
    δAF70.29099†–0.00202†0.00013†–0.022490.001330.000110.267†
    δAF80.28779†–0.00267†0.00013†–0.027680.001300.00012*0.319†–0.00267†–0.001370.00013†0.00025†
    δTP90.76347†–0.00388†0.00011†–0.00821–0.000210.000060.620†
    δTP100.74835†–0.00418†0.00014†0.001110.00013–0.000000.662†
    θAF7–0.24320†–0.00136†0.00008†0.02290*0.00207***0.00010*0.412†–0.00136†0.000710.00008***0.00019†
    θAF8–0.26573†–0.00146†0.00007***0.007930.00161**0.00013**0.365†–0.00146†0.000150.00007**0.00021†
    θTP90.35367†–0.00196†0.00004*–0.02996**0.000820.00014***0.373†–0.00196†–0.00113*0.00004*0.00017†
    θTP100.31149†–0.00262†0.00009†–0.004300.000870.00010*0.480†–0.00262†–0.00175***0.00009†0.00018†
    αAF7–0.39869†0.00123†0.00007***0.11474†0.00206***0.00008*0.815†0.00123†0.00329†0.00007***0.00015†
    αAF8–0.44195†0.00101**0.00006***0.08223†0.00142*0.00010*0.712†0.00101**0.00243†0.00006**0.00016†
    αTP90.48919†0.00049–0.00005*–0.02840*0.000650.00016**0.105**0.000490.00114–0.00005*0.00011**
    αTP100.47046†0.00024–0.00002–0.004980.000520.00013**0.087**0.000240.00075–0.000020.00012**
    βAF7–0.18422†0.00197†0.00011***0.26647†0.00174*0.000040.868†0.00197†0.00372†0.00011†0.00015**
    βAF8–0.23850†0.00233†0.00008**0.21553†0.000460.000030.813†
    βTP90.29314†0.00206†–0.00005**0.05542†0.000670.00012**0.669†0.00206†0.00273†–0.00005**0.00006*
    βTP100.28957†0.00216†0.000000.08575†0.000110.000070.675†
    α PeakAF79.72796†–0.03847†0.00052***–0.036510.00159–0.000280.779†
    α PeakAF89.82156†–0.03457†0.00010–0.05259–0.00074–0.000090.665†
    α PeakTP99.46783†–0.01795†0.000010.11219*–0.00647*–0.000320.723†–0.01795†–0.02442†0.00001–0.00030
    α PeakTP109.54145†–0.01891†–0.000000.06429–0.00865***0.000040.768†–0.01891†–0.02756†0.000000.00004
    α AsymAF8–AF7–0.04326†–0.00022–0.00000–0.03251†–0.000640.000020.235†
    α AsymTP10–TP9–0.01873†–0.000250.00004†0.02342†–0.00013–0.000030.246†
    • Bolded rows indicate cases where R2 ≥ 0.5. significance levels: *p < 0.05, **p < 0.01, ***p < 0.001, †p < 0.0001.

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Characterizing Population EEG Dynamics throughout Adulthood
Ali Hashemi, Lou J. Pino, Graeme Moffat, Karen J. Mathewson, Chris Aimone, Patrick J. Bennett, Louis A. Schmidt, Allison B. Sekuler
eNeuro 30 November 2016, 3 (6) ENEURO.0275-16.2016; DOI: 10.1523/ENEURO.0275-16.2016

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Characterizing Population EEG Dynamics throughout Adulthood
Ali Hashemi, Lou J. Pino, Graeme Moffat, Karen J. Mathewson, Chris Aimone, Patrick J. Bennett, Louis A. Schmidt, Allison B. Sekuler
eNeuro 30 November 2016, 3 (6) ENEURO.0275-16.2016; DOI: 10.1523/ENEURO.0275-16.2016
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