Video game training enhances cognitive control in older adults

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Cognitive control is defined by a set of neural processes that allow us to interact with our complex environment in a goal-directed manner1. Humans regularly challenge these control processes when attempting to simultaneously accomplish multiple goals (multitasking), generating interference as the result of fundamental information processing limitations2. It is clear that multitasking behaviour has become ubiquitous in today’s technologically dense world3, and substantial evidence has accrued regarding multitasking difficulties and cognitive control deficits in our ageing population4. Here we show that multitasking performance, as assessed with a custom-designed three-dimensional video game (NeuroRacer), exhibits a linear age-related decline from 20 to 79 years of age. By playing an adaptive version of NeuroRacer in multitasking training mode, older adults (60 to 85 years old) reduced multitasking costs compared to both an active control group and a no-contact control group, attaining levels beyond those achieved by untrained 20-year-old participants, with gains persisting for 6 months. Furthermore, age-related deficits in neural signatures of cognitive control, as measured with electroencephalography, were remediated by multitasking training (enhanced midline frontal theta power and frontal–posterior theta coherence). Critically, this training resulted in performance benefits that extended to untrained cognitive control abilities (enhanced sustained attention and working memory), with an increase in midline frontal theta power predicting the training-induced boost in sustained attention and preservation of multitasking improvement 6 months later. These findings highlight the robust plasticity of the prefrontal cognitive control system in the ageing brain, and provide the first evidence, to our knowledge, of how a custom-designed video game can be used to assess cognitive abilities across the lifespan, evaluate underlying neural mechanisms, and serve as a powerful tool for cognitive enhancement.

At a glance


  1. NeuroRacer experimental conditions and training design.
    Figure 1: NeuroRacer experimental conditions and training design.

    a, Screen shot captured during each experimental condition. b, Visualization of training design and measures collected at each time point.

  2. NeuroRacer multitasking costs.
    Figure 2: NeuroRacer multitasking costs.

    a, Costs across the lifespan (n = 174) increased (that is, a more negative percentage) in a linear fashion when participants were grouped by decade (F(1,5) = 135.7, P<0.00001) or analysed individually (F(1,173) = 42.8, r = 0.45, P<0.00001; see Supplementary Fig. 3), with significant increases in cost observed for all age groups versus the 20-year-old group (P<0.05 for each decade comparison). b, Costs before training, 1month post-training, and 6months post-training showed a session X group interaction (F(4,72) = 7.17, P<0.0001, Cohen’s d = 1.10), with follow-up analyses supporting a differential benefit for the MTT group (Cohen’s d for MTT vs STT = 1.02; MTT vs NCC = 1.20). P<0.05 within group improvement from pre to post, *P<0.05 between groups (n = 46). Error bars represent s.e.m.

  3. Change in performance across sessions on independent tests of cognition for each experimental group.
    Figure 3: Change in performance across sessions on independent tests of cognition for each experimental group.

    For each test, a group X session ANOVA revealed a significant interaction (F(2,43)>3.39, P<0.04, Cohen's d>0.73), with follow-up analyses demonstrating improvement only for MTT (n = 15). a, Response time (RT) change for a delayed-recognition working memory (WM) task with the presence of distraction (n = 46). b, Response time change for a delayed-recognition WM task without distraction. c, Response time change for the test of variables of attention (TOVA). d, Correlation between data from (a) and NeuroRacer multitasking cost improvement 1month after training for the MTT group (n = 16). P<0.05 within group improvement from pre to post, *P<0.05 between groups, - - -P = 0.08. Error bars represent s.e.m.

  4. /`Sign and drive/' midline frontal theta activity and long-range theta coherence in younger adults and older adults pre- and post-training.
    Figure 4: ‘Sign and drive’ midline frontal theta activity and long-range theta coherence in younger adults and older adults pre- and post-training.

    a, b, For older adult training assessments, a group X session X condition ANOVA for each neural measure revealed significant interactions (in each case, F(2,41)>4.98, P<0.01, Cohen's d>0.93; see Supplementary Fig. 6a, b), with follow-up analyses demonstrating improvement only for MTT during ‘sign and drive’ (n = 15). For younger (n = 18) vs older adult (n = 44) assessments, both neural measures revealed significant reductions in older adults (see Supplementary Fig. 8a, b). c, Correlation in the MTT group between the change in midline frontal theta power and multitasking behavioural gain preservation 6months later (n = 12). d, Correlation in the MTT group between the change in midline frontal (mf) theta power and behavioural improvement on the TOVA (n = 14). P<0.05 within group improvement from pre- to post-training, *P<0.05 between groups.


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Author information


  1. Department of Neurology, University of California, San Francisco, California 94158, USA

    • J. A. Anguera,
    • J. Boccanfuso,
    • J. L. Rintoul,
    • O. Al-Hashimi,
    • F. Faraji,
    • J. Janowich,
    • E. Kong,
    • Y. Larraburo,
    • C. Rolle,
    • E. Johnston &
    • A. Gazzaley
  2. Department of Physiology, University of California, San Francisco, California 94158, USA

    • J. A. Anguera,
    • O. Al-Hashimi &
    • A. Gazzaley
  3. Center for Integrative Neuroscience, University of California, San Francisco, California 94158, USA

    • J. A. Anguera,
    • J. Boccanfuso,
    • J. L. Rintoul,
    • O. Al-Hashimi,
    • F. Faraji,
    • J. Janowich,
    • E. Kong,
    • Y. Larraburo,
    • C. Rolle &
    • A. Gazzaley
  4. Department of Psychiatry, University of California, San Francisco, California 94158, USA

    • A. Gazzaley


J.A.A., J.B., J.L.R., O.A., E.J. and A.G. designed the experiments; J.A.A., J.L.R., O.A., E.J. and A.G. developed the NeuroRacer software; J.A.A., J.B., O.A., F.F., E.K., Y.L. and C.R. collected the data; J.A.A., J.B., O.A., J.J. and C.R. analysed the data; and J.A.A. and A.G. wrote the paper. All authors discussed the results.

Competing financial interests

A.G. is co-founder and chief science advisor of Akili Interactive Labs, a newly formed company that develops cognitive training software. A.G. has a patent pending for a game–based cognitive training intervention, ‘Enhancing cognition in the presence of distraction and/or interruption’, which was inspired by the research presented here.

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