|
|
Attention Enhancement and its Neuroplasticity Based on Long-Term Video Game Training |
Bai Binnan1, Tian Xiaoyan2, Cui Ruifang2, Hao Xinyang2, Lin Liqi1, Gong Diankun2, Yu Zhenxia1, Gao Dongrui12#* |
1(School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China) 2(School of Life and Technology, University of Electronic Science and Technology of China, Chengdu 610054,China) |
|
|
Abstract It has been shown that action-based video game training can improve multiple cognitive abilities. However, current existing video game training games are of a single type and short duration. To fill this gap, a study was conducted to improve attention with prolonged training of multiple types of video games (GSGO, LOL and SGS). In this study, 176 healthy undergraduate students were randomly divided into 3 training groups to receive game training for a period of 5 months. Three behavioral tasks were completed every month during the training period to assess attentional capacity, and EEG data were collected once before and after the training period to calculate brain power spectrum energy to assess changes in brain functional status after long-term video game training. The results revealed that after 5 months of game training, the θ power spectrum energy significantly increased in each training group and differed significantly in the parietal lobe (F=3.13, P<0.05). α power spectrum energy in the LOL and SGS groups showed a decreasing trend in all cortices, but the CSGO group showed a decrease in frontal (t=2.43, P=0.02), parietal (t=2.28, P=0.03) and central regions (t=2.48, P=0.02) showed significant α1 synchronization. There were significant between-group differences in R3 power spectrum energy in the frontal and parietal lobes across training groups (F=3.69, P=0.03), with both the LOL and SGS groups showing a significant increase in R3 power spectrum energy compared to pre-training (P<0.05), indicating that long-term electronic training can induce an increase in the attention levels and that the effect differed after training for different types of games. The results of the behavioral task assessment supported the same findings, with all training groups showing significantly higher performance in distracted spatial attention ability after month 1 of training (P<0.05), with the CSGO group improving by 11.12% and the SGS and LOL groups improving by 9.68% and 15.66%, respectively. Multiple comparisons of LSD showed that the CSGO group performed significantly better during training than the SGS group (P=0.01) and the LOL group had significantly better focused spatial attention than the CSGO group after the first 3 months of training (P=0.02). The study demonstrated that video games causally enhanced attentional plasticity and that action video games had better attentional capacity enhancement effects compared to casual game training. The results of the study are informative for assessing the effects of video game training and intervention.
|
Received: 21 October 2022
|
|
Corresponding Authors:
*E-mail: gdr1987@126.com
|
|
|
|
[1] Dale G, Joessel A, Bavelier D, et al. A new look at the cognitive neuroscience of video game play [J]. Ann NY Acad Sci, 2020, 1464(1): 192-203. [2] Anguera JA, Boccanfuso J, Rintoul JL, et al. Video game training enhances cognitive control in older adults [J]. Nature, 2013, 501(7465): 97-101. [3] Peters JL, Crewther SG, Murphy MJ, et al. Action video game training improves text reading accuracy, rate and comprehension in children with dyslexia: a randomized controlled trial [J]. Springer Science and Business Media LLC, 20 Sept, 2018 [Epub ahead of print]. [4] Qiu Nan, Ma Weiyi, Fan Xin, et al. Rapid improvement in visual selective attention related to action video gaming experience [J]. Frontiers in Human Neuroscience, 13 Feb, 2018 [Epub ahead of print]. [5] Green CS, Bavelier D. Action video game modifies visual selective attention [J]. Nature, 2003, 423(6939): 534-537. [6] Dobrowolski P, Hanusz K, Sobczyk B, et al. Cognitive enhancement in video game players: the role of video game genre [J]. Computers in Human Behavior, 2015, 44(3): 59-63. [7] Bediou B, Adams DM, Mayer RE, et al. Meta-analysis of action video game impact on perceptual, attentional, and cognitive skills [J]. Psychol Bull, 2018, 144(1): 77-110. [8] Walter, R., Boot, Arthur F, et al. The effects of video game playing on attention, memory, and executive control [J]. Acta Psychologica, 2008, 129(3): 387-398. [9] Magosso E, Decrescenzio F, Ricci G, et al. EEG alpha power is modulated by attentional changes during cognitive tasks and virtual reality immersion [J]. Computational Intelligence and Neuroscience, 25 Jun, 2019 [Epub ahead of print]. [10] Gentili RJ, Bradberry TJ, Oh H, et al. Cerebral cortical dynamics during visuomotor transformation: adaptation to a cognitive-motor executive challenge [J]. Psychophysiology, 2011, 48(6): 813-824. [11] Foxe JJ, Snyder AC. The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention [J]. Front Psychol, 2011, 2(1): 154-167. [12] Emami Z, Chau T. The effects of visual distractors on cognitive load in a motor imagery brain-computer interface [J]. Behavioural Brain Research, 12 Oct, 2019 [Epub ahead of print]. [13] Beck AT. An inventory for measuring depression[J]. Arch Gen Psychiatry, 1961, 4(6):561-571. [14] Kvaal K, Ulstein I, Nordhus IH, et al. The spielberger state-trait anxiety inventory (stai): the state scale in detecting mental disorders in geriatric patients.[J]. International Journal of Geriatric Psychiatry, 2010, 20(7):629-634. [15] Yao Dezhong. A method to standardize a reference of scalp eeg recordings to a point at infinity [J]. Physiological Measurement, 2001, 22(4): 693-711. [16] Dong Li, Zhao Lingling, Zhang Yufan, et al. Reference electrode standardization interpolation technique (resit): a novel interpolation method for scalp eeg [J]. Brain Topography, 5 May, 2021 [Epub ahead of print]. [17] Dong li, Li Fali, Liu Qiang, et al. MATLAB toolboxes for reference electrode standardization technique (rest) of scalp EEG [J]. Frontiers in Neuroscience, 30 Oct, 2017 [Epub ahead of print]. [18] Hockey G, Nickel P, Roberts AC, et al. Sensitivity of candidate markers of psychophysiological strain to cyclical changes in manual control load during simulated process control [J]. Applied Ergonomics, 2009, 40(6): 1011-1018. [19] Akizuki K, Ohashi Y. Measurement of functional task difficulty during motor learning: what level of difficulty corresponds to the optimal challenge point? [J]. Human Movement Science, 2015, 43(1): 107-117. [20] Postma MA, Schellekens J, Hanson E, et al. Fz theta divided by Pz alpha as an index of task load during a pc-based air traffic control simulation [J]. Human Factors in Design Safety & Management, 2005, 1(1): 465-469. [21] Oei AC, Patterson MD. Enhancing cognition with video games: a multiple game training study [J]. PLoS ONE, 13 Mar, 2013 [Epub ahead of print]. [22] Jaquess KJ, Lo LC, Oh H, et al. Changes in mental workload and motor performance throughout multiple practice sessions under various levels of task difficulty [J]. Neuroscience, 2018, 393(1): 305-318. [23] Xie Jiaxing, Cui Ruifang, Ma Weiyi, et al. Information transmission in action video gaming experts: Inferences from the lateralized readiness potential [J]. Frontiers in Human Neuroscience, 25 Jul, 2022 [Epub ahead of print]. [24] Salmelin R, Hari R. Characterization of spontaneous MEG rhythms in healthy adults [J]. Electroencephalography & Clinical Neurophysiology, 1994, 91(4): 237-248. [25] Menoret M, Varnet L, Fargier R, et al. Neural correlates of non-verbal social interactions: a dual-EEG study [J]. Neuropsychologia, 2014, 55(1): 85-97. [26] Schuch S, Bayliss AP, Klein C, et al. Attention modulates motor system activation during action observation: evidence for inhibitory rebound [J]. Experimental Brain Research, 2010, 205(2): 235-249. [27] Jensen O, Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition [J]. Frontiers in Human Neuroscience, 4 Nov, 2010 [Epub ahead of print]. [28] Gevins A, Smith ME, Mcevoy L, et al. High-resolution EEG mapping of cortical activation related to working memory: Effects of task difficulty, type of processing, and practice [J]. Cerebral Cortex, 1997, 7(4): 374-385. [29] Fantino E, Kasdon D, Stringer N. The yerkes-dodson law and alimentary motivation [J]. Canadian Journal of Psychology, 1970, 24(2): 77-84. [30] Rahman ML, Files BT, OIknine AH, et al. Combining neural and behavioral measures enhances adaptive training [J]. Frontiers in Human Neuroscience, 14 Feb, 2022 [Epub ahead of print]. |
[1] |
Xiong Xin, Yang Xinliang, Luo Jianhua, Yi Sanli, He Jianfeng. Changes of EEG Microstate in Patients with Sleep Apnea Syndrome[J]. Chinese Journal of Biomedical Engineering, 2023, 42(5): 563-571. |
[2] |
Liu Shuang, Liao Jingmeng, Wang Xiaojuan, Li Meijuan, Gao Ying, Li Jie, Ming Dong. Analysis of Resting-State EEG Specific Characteristics in Schizophrenic with RefractoryAuditory Hallucination[J]. Chinese Journal of Biomedical Engineering, 2023, 42(5): 513-519. |
|
|
|
|