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.
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We thank J. Avila, N. Barbahiya, M. Gugel, B. Jensen, R. Moustafa, Y. Rezaeihaghighi, P. Sztybel, C. Vong, A. Wang, B. Yang and D. Yerukhimov for their help with data collection and analyses, and B. Benson for assistance with the NeuroRacer behavioral analysis stream. Thanks to D. Ellingson, N. Falstein, and M. Omernick for insights and support of NeuroRacer development. Thanks to J. Bollinger, J. Kalkstein, J. Mishra, B. Voytek and T. Zanto for support on ERSP and coherence analyses, and Z. Chadick, W. Clapp, J. Fung, M. Hough, E. Morsella, J. Pa, M. Rubens, P. Wais, C. Walsh, and D. Ziegler for helpful discussions. Thanks to all of our participants whose time and efforts made this work possible, and Apple who generously loaned the Gazzaley laboratory all of the MacBook Pro laptops used in this study. Support for this research was provided by the Robert Wood Johnson Foundation's Pioneer Portfolio through a grant from its national program, ‘Health Games Research: Advancing Effectiveness of Interactive Games for Health’ (A.G.) and the National Institute of Aging (A.G.). J.A.A. was supported by a UCSF Institutional Research and Career Development Award (IRACDA).
This file contains Supplementary Figures 1-18, Supplementary Tables 1-3, Supplementary Materials and Supplementary References.
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Functional brain changes associated with cognitive training in healthy older adults: A preliminary ALE meta-analysis
Brain Imaging and Behavior (2019)