High-intensity training enhances executive function in children in a randomized, placebo-controlled trial

  1. David Moreau  Is a corresponding author
  2. Ian J Kirk
  3. Karen E Waldie
  1. The University of Auckland, New Zealand
6 figures, 7 tables and 2 additional files

Figures

Physiological and effort-dependent measures.

(A) Violin and box plots showing change in resting heart rate (in BPM) between pretest and posttest sessions, for HIT and control groups. The dashed line shows the point of perfect equivalence between pretest and posttest measurements; values below the line indicate heart rate decreases. (B) Targeted range accuracy, defined as the ratio of maximum measured heart rate per participant (in BPM) to targeted heart rate (expected), averaged across sessions. Dark dots show accuracy based on pretest resting heart rate, whereas light dots show accuracy based on posttest resting heart rate. The blue dashed line represents the point of perfect agreement between individual targeted heart rate and maximum measured heart rate. Values above the line represent higher measured heart rate than expected from baseline. (C) Time series of the maximum heart rate (in BPM) measured for a single workout, averaged over participants, plotted across sessions. Smoothing is modeled via a non-parametric locally weighted regression using a nearest neighbor approach (i.e. local polynomial regression fitting). (D) Time series of the total number of steps for a single workout, averaged over participants, shown across sessions. Smoothing is modeled via a non-parametric locally weighted regression using a nearest neighbor approach (i.e. local polynomial regression fitting).

https://doi.org/10.7554/eLife.25062.003
Cognitive improvements.

Violin and box plots showing gains in Cognitive Control (A) and Working Memory (B) between pretest and posttest sessions, for HIT and control groups.

https://doi.org/10.7554/eLife.25062.009
Effect of BDNF allele on cognitive improvements.

μ and σ2 parameter estimates from the posterior distribution for the difference between BDNF met carriers and non-carriers (met66 – val66 homozygotes) in cognitive gains. Estimates were generated from 10,000 iterations, in one chain, with thinning interval of one (no data point discarded). (A) Trace of μ for Cognitive Control. (B) σ2 estimate for Cognitive Control. (C) Trace of μ for Working Memory. (D) σ2 estimate for Working Memory.

https://doi.org/10.7554/eLife.25062.012
Prior and posterior distributions for the comparison between Conditions (HIT vs. Control) for Cognitive Control.

The graph shows the density of each distribution as a function of effect size, with the prior centered on the null effect.

https://doi.org/10.7554/eLife.25062.013
Bayes factor robustness check for the comparison between Conditions (HIT vs. Control) for Cognitive Control.

The figure shows our default prior, as well as wide and ultrawide priors. Importantly, the curve shows stronger evidence for our hypothesis with narrower priors, indicating that our conclusions are not based on a restricted range of priors.

https://doi.org/10.7554/eLife.25062.014
Sequential analysis.

The graph shows the strength of evidence (as expressed by BF10) as N increases.

https://doi.org/10.7554/eLife.25062.015

Tables

Table 1

Exploratory factor analysis for cognitive measurements at baseline. F1 (Cognitive Control) and F2 (Working Memory) refer to the factor loadings of each measure from an exploratory factor analysis with promax rotation (N = 287). Uniqueness represents the variance of each item not accounted for by the two factors.

https://doi.org/10.7554/eLife.25062.004
MeasureCCWMUniqueness
Flanker0.890.21
Go/no-go0.710.48
Stroop0.550.71
Backward digit span0.700.51
Backward Corsi blocks0.270.91
Visual 2-back0.330.90
  1. Note: Only factor loadings greater than. 25 are included in the table.

Table 1—source data 1

Scree plot for the exploratory factor analysis on all cognitive measures.

The plot shows the eigenvalues associated with each factor plotted against each factor, and supports the decision to retain two factors.

https://doi.org/10.7554/eLife.25062.005
Table 1—source data 2

Path diagram for the exploratory factor analysis on all cognitive measures.

F1 (Cognitive Control) and F2 (Working Memory) refer to the factors extracted from an exploratory factor analysis on all six cognitive measures, with promax rotation (N = 287).

https://doi.org/10.7554/eLife.25062.006
Table 2

Model comparisons for the Cognitive Control construct (CC) with condition as a fixed factor. The table shows the probability of each model given the data P(M | Data), the corresponding Bayes Factor, BF10 and the percentage of error. The unconditional probability for each model is 0.2.

https://doi.org/10.7554/eLife.25062.007
ModelsP(M | Data)BFMBF10Error (%)
 Null1.01e −54.05e −51-
 Session0.433.0643120.060.98
 Condition2.32e −69.28e −60.233.93
 Main effects0.110.4911143.874.52
 Interaction0.463.3843792.875.52
Table 3

Model comparisons for the Working Memory construct (WM) with condition as a fixed factor. The table shows the probability of each model given the data P(M | Data), the corresponding Bayes Factor, BF10 and the percentage of error. The unconditional probability for each model is 0.2.

https://doi.org/10.7554/eLife.25062.008
ModelsP(M | Data)BFMBF10Error (%)
 Null2.92e −131.17e −121-
 Session4.49e −401.54e + 91.23
 Condition1.84e −1317349e −130.630.69
 Main effects3.15e −401.08e + 93.13
 Interaction15232.683.42e + 122.91
Table 4

Model comparisons for the Cognitive Control construct (CC) with BDNF polymorphism as a fixed factor. The table shows the probability of each model given the data P(M | Data), the corresponding Bayes Factor, BF10 and the percentage of error. The unconditional probability for each model is 0.2.

https://doi.org/10.7554/eLife.25062.010
ModelsP(M | Data)BFMBF10Error (%)
 Null0.010.061-
 Session0.030.121.941.45
 Condition0.020.101.652.60
 Main effects0.040.193.051.71
 Interaction0.8931.1759.4924.61
Table 5

Model comparisons for the Working Memory construct (WM) with BDNF polymorphism as a fixed factor. The table shows the probability of each model given the data P(M | Data), the corresponding Bayes Factor, BF10 and the percentage of error. The unconditional probability for each model is 0.2.

https://doi.org/10.7554/eLife.25062.011
ModelsP(M | Data)BFMBF10Error (%)
 Null2.47e −59.90e −51-
 Session00.0179.860.77
 Condition3.52e −51.41e −41.420.69
 Main effects00.01155.375.84
 Interaction0.99675.9240159.393.51
Table 6

Mean cognitive scores (SDs) for the two conditions at pretest and posttest. Scores are scaled and centered for each task (z-transformed by row).

https://doi.org/10.7554/eLife.25062.016
HITControl

PretestPosttestPretestPosttest
Flanker−0.14 (1.20)0.16 (0.66)−0.06 (1.18)0.04 (0.85)
Go/no-go−0.09 (1.11)0.08 (0.96)0.01 (1.04)0.01 (0.88)
Stroop−0.11 (1.19)0.16 (0.38)−0.09 (1.31)0.04 (0.83)
Backward digit span−0.14 (1.07)0.25 (0.55)−0.13 (1.34)0.02 (0.82)
Backward Corsi blocks−0.13 (1.55)0.31 (0.35)−0.17 (0.92)0.00 (0.73)
Visual 2-back−0.24 (1.62)0.33 (0.51)−0.06 (0.74)−0.03 (0.69)
Table 7

Demographics and sample characteristics at baseline.

https://doi.org/10.7554/eLife.25062.017

HITControlsTotal
Sample (N)
Gender
152
90 f./62 m.
153
97 f./56 m.
305
187 f./118 m.
Age9.87 (1.81)9.96 (1.68)9.91 (1.74)
Handedness (LH/Ambid.)18/314/332/6
BMI 18.1 (3.92)18.51 (7.89)18.31 (6.25)
LD diagnosis131629
Previous remediation81422
Videogaming2.32 (0.95)2.43 (0.96)2.38 (0.97)
Physical exercise3.06 (0.8)2.95 (0.78)3.03 (0.81)
Happiness4.53 (1.25)4.61 (1.22)4.55 (1.27)
Sleep quality4.07 (1.36)4.11 (1.39)4.11 (1.41)
General health4.88 (1.05)4.84 (1.01)4.82 (1.06)

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  1. David Moreau
  2. Ian J Kirk
  3. Karen E Waldie
(2017)
High-intensity training enhances executive function in children in a randomized, placebo-controlled trial
eLife 6:e25062.
https://doi.org/10.7554/eLife.25062