1. Video Games and Working Memory Derek M. Ellis Chris Blais Gene A. Brewer Department of Psychology Arizona State University The Entertainment Software Rating Board (ESRB) estimates that the average U.S. household owns at least one video game console. On average people 9+ years of age play 6.5 hours of video games per week. Previous research has found a positive relationship between video game play and measures of working memory 1,2. Working memory involves the temporary storage and manipulation of information. Within the last year the statistical and methodological practices of those findings has been called to question 4. The purpose of the current study is to investigate the individual differences between video games and working memory utilizing both behavioral and neurophysiological measures. IntroductionMethods Participants: N = 109 (M age = 19.41, SD = 2.13) neurologically healthy adults who report M hours per week = 5.02 (SD = 7.83). General Demographics & Video Game Questionnaire: Age, gender, GPA, number of hours per week currently/when time allows play video games, and games they are currently playing. Hours per week were log transformed. Working Memory Capacity: Measured using Operation, Reading, and Symmetry Span tasks. All span tasks were the shortened versions. Calculated using total number of correct answers on the individual span tasks. WMC is maximum-likelihood estimation of the individual span scores creating the WMC factor score. EEG: Monster or Manipulation of Orthogonal Neural Systems Together in Electrophysiological Recordings 3. Neuroscan SynampsRT system using the 32 channel quik-cap. ICA used to remove artifacts. Grand Average ERPs represent evoked activity for all participants. Individual participants ERP analysis done using mean amplitude event window for each ERP. The windows for the C1 (40-100ms), N2PC (200-300ms), and P3 (300-600ms) occur post-stimulus. The Error-related Negativity (ERN) is 50 ms before and 100 ms after the participant respond to the stimuli. References 1) Blacker, K. J., & Curby, K. M. (2013). Enhanced visual short-term memory in action videogame players. Attention, Perception, & Psychophysics, 75, 1128-1136. 2) Green, C. S., & Bavelier, D. (2003). Action video game modifies visual selective attention. Nature, 423, 534- 537. 3) Kappenman, E. S., & Luck. S. J. (2012). Manipulation of Orthogonal Neural Systems Together in Electrophysiological Recordings: The MONSTER approach to simultaneous assessment of multiple neurocognitive dimensions. Schizophrenia Bulletin, 38(1), 92-102. 4) Unsworth, N., Redick, T. S., McMillan, B. D., Hambrick, D. Z., Kane, M. J., & Engle, R. W. (2015). Is playing video games related to cognitive abilities? Psychological Science, 26(6), 759-774. ERP Grand Average Waveforms Video Games, Working Memory, and ERPs MAClab Memory & Attention Control Laboratory Hours Per WeekO Span R Span Sym Span WMC Factor ScoreGPA Current.067.324**.317**.262**-.350** When Time Allows.153.290**.337**.304**-.334** * Indicates significant at p <.05 ** Indicates significant at p <.01 Component C1N2PCP3ERN WMC.053-.063.128.015 Current Hours Per Week -.187.054-.218*-.070 Playing Game with Violent Content -.051.131-.299**.005 Are there any causal effects of video games on working memory or is the correlation driven by self selection or some other unidentified variable? Extreme group analysis of ERP latency and WMC. Create a Violent Game Factor using hours per week and what games they are currently playing. Given the large nature of the study we have the ability to evaluate the reliability of ERP measures, i.e. split half analysis of odd vs even trials. Future Directions MONSTER Analysis Our data indicate that number of hours per week played of video games is positively correlated with WMC. Mean amplitude was measured from the difference waves for each ERP. We found no significant correlations between WMC and any of the ERP components. However, there is a significant negative correlation between hours per week and P3 amp. Individuals who reported currently playing games with violent content, realistic or cartoon, were found to have a significantly reduced P3 amplitude. + X 1 + + G 1 + + G + 2 Time ITI Participants identify target stimuli which are either letters or numbers. Target stimuli appear in an 80/20 ratio of standard/deviant. Variation in the stimuli presentation result in the different ERP components. Variations are counterbalanced across 16 blocks, with individual blocks lasting 2-3 mins in length, totaling 1600 individual trials. C1 represents early sensory processing N2PC represents shifts of covert attention P3 represents categorization Error-related Negativity (ERN) represents self-monitoring Conclusions The results of analysis support the body of literature reporting that playing video games is related to enhancements of various cognitive abilities. To be successful playing video games and span tasks an individual is required to maintain task goals in the face of distraction. We expected to find a negative correlation between P3, N2PC, ERN and WMC, but our data do not support that hypothesis. Previous research found that violent video game play mediated changes in aggression and P3 amplitude when shown violent imagery. We find a similar correlation between violent game play and P3 amplitude but to stimuli containing no violent imagery. Number of hours of video game play per week will be positively correlated with working memory capacity, as measured by the Span tasks. Working memory capacity will be negatively correlated with mean amplitude of the P3, N2PC, and ERN ERP components. No significant correlations with regards to the C1 component. Hypothesis = Upper = Lower = Contra = Ipsi = Contra-Ipsi = Incorrect = Correct = Standard = Deviant = Dev-Stand Time Potential (mV)