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. Author manuscript; available in PMC: 2021 Jul 15.
Published in final edited form as: Behav Brain Res. 2020 May 18;390:112667. doi: 10.1016/j.bbr.2020.112667

Enriching hippocampal memory function in older adults through video games

Gregory D Clemenson 1, Shauna M Stark 1, Samantha M Rutledge 1, Craig EL Stark 1,2
PMCID: PMC7286064  NIHMSID: NIHMS1595525  PMID: 32439346

Abstract

Healthy aging is accompanied by a steady cognitive decline with clear losses in memory. Animal studies have consistently demonstrated that simply modifying an animal’s living environment (known as environmental enrichment) can have a positive influence on age-related cognitive decline in the hippocampus. Previously, we showed that playing immersive 3D video games can improve hippocampal-based memory in young healthy adults, suggesting that the exploration of the large open worlds of modern-day video games may act as proxy for environmental enrichment in humans. Here, we replicated our previous video game study in healthy older adults, showing that playing video games for four weeks can improve hippocampal-based memory in a population that is already experiencing age-related decline in memory. Furthermore, we showed that the improvements last for up to four weeks past the intervention, highlighting the potential of video games as intervention for age-related cognitive decline.

Keywords: Environmental enrichment, aging, spatial exploration, pattern separation

1. Introduction

Healthy aging is closely associated with a reduction in hippocampal structure and function (Burke & Barnes, 2006; O’Shea, Cohen, Porges, Nissim, & Woods, 2016; Stark & Stark, 2017b; Wilson, Gallagher, Eichenbaum, & Tanila, 2006). Nevertheless, studies in animals have shown that the aged hippocampus still retains a certain amount of plasticity that is susceptible to influence by the surrounding environment (Lee, Clemenson, & Gage, 2012). Environmental enrichment traditionally describes an experimental manipulation where an animal’s environment is enhanced to promote cognitive, physical, social, and other sensory stimulation (van Praag, Kempermann, & Gage, 2000). Despite the simplicity of this manipulation, environmental enrichment has been repeatedly shown to provide numerous structural and functional benefits to the hippocampus (Clemenson, Gage, & Stark, 2018). Importantly, environmental enrichment has been shown to improve both structural and cognitive deficits associated with aging, such as increased neurogenesis (Kempermann, Gast, & Gage, 2002; Leal-Galicia, Castañeda-Bueno, Quiroz-Baez, & Arias, 2008; Segovia, Yagüe, García-Verdugo, & Mora, 2006; Speisman et al., 2013), dendritic branching and spine density (Darmopil, Petanjek, Mohammed, & Bogdanović, 2009), expression of presynaptic proteins (Frick & Fernandez, 2003; Leal-Galicia et al., 2008; Saito et al., 1994), neurotransmitter release (Segovia et al., 2006), enhanced long-term potentiation and depression (Kumar, Rani, Tchigranova, Lee, & Foster, 2012; Stein, O’Dell, Funatsu, Zorumski, & Izumi, 2016), and related hippocampus-dependent behaviors (Kempermann et al., 2002; Segovia et al., 2006; Speisman et al., 2013). Whether the benefits of environmental enrichment are due to physical activity (Kobilo et al., 2011; Mustroph et al., 2012; van Praag, Kempermann, & Gage, 1999), spatial exploration (Freund et al., 2013), learning (Gould, Beylin, Tanapat, Reeves, & Shors, 1999; Leuner et al., 2004), or other aspects of the environment (Birch, McGarry, & Kelly, 2013; Clemenson et al., 2015; Steiner, Zurborg, Hörster, Fabel, & Kempermann, 2008), the surrounding environment can have a significant impact on the aging hippocampus of animals.

While the effects of environmental enrichment on aging are well defined in animals, it is less clear how this manipulation relates to humans, especially considering that humans already live in an enriched environment compared to the standard laboratory rodent (Clemenson et al., 2018). It is generally thought that leading a physically and cognitively active lifestyle is critical for healthy aging (Mora, 2013). Several studies have demonstrated that engaging in novel activities (Park et al., 2014), directed cognitive training (Rebok et al., 2014), physical exercise (Bugg & Head, 2011; Erickson et al., 2011; Pereira et al., 2007), and a combination of cognitive training, physical exercise, social experience, and diet (Consortium, 2017; Lövdén et al., 2012; Ngandu et al., 2015; Rosen, Sugiura, Kramer, Whitfield-Gabrieli, & Gabrieli, 2011) can have a positive impact on age-related cognitive decline in humans. There are clear parallels between enrichment in human and animal studies, suggesting that despite the differences, interactions with the environment can have a meaningful impact on brain structure and function.

Previously, we showed that playing immersive 3D video games could improve hippocampal-based memory in young adults (Clemenson & Stark, 2015). The Mnemonic Similarity Task (MST) serves as our metric for hippocampal function as it was designed to tap into the hippocampal-dependent process of pattern separation and has previously been demonstrated to be sensitive to hippocampal function and age-related changes in the hippocampus (Stark, Kirwan, & Stark, 2019; Stark, Yassa, Lacy, & Stark, 2013; Yassa, Muftuler, & Stark, 2010; Yassa, Stark, et al., 2010). In animals it has repeatedly been shown that exposure to an enriched environment has a widespread effect on hippocampal function, consistent with an overall improvement in hippocampal memory (i.e., MST performance) in humans (Clemenson et al., 2018) following a video game intervention.

There are long-standing relationships between the hippocampus and spatial memory (O’Keefe & Dostrovsky, 1971; Tolman, 1948) and between spatial exploration and environmental enrichment in animals (Freund et al., 2013). In our prior work (Clemenson & Stark, 2015), we capitalized on these to hypothesize that the spatial exploration provided by the vast open worlds of modern day video games can provide a human proxy for environmental enrichment. The goal of the present study was to determine if the improvements in hippocampal-based memory we observed with video game training in young adults would translate to an aged population, whom already experience age-related decline in hippocampal function.

We made several modifications to the current intervention to adapt to an older population. Similar to our previous study (Clemenson & Stark, 2015), participants played Angry Birds or Super Mario 3D World on a Nintendo Wii U. However, in place of a no-contact control, we employed an active control condition of playing computer-based Solitaire. Even though we did not observe an effect of playing Angry Birds in a younger population, we suspected that this condition might produce a benefit simply because the older adults in this study had no prior experience with modern video games or use a Nintendo Wii U. One element of enrichment that has been described in the animal literature is the fact that enriched environments provide a certain amount of novelty and learning experiences to the animal that can influence the hippocampus (Gould et al., 1999; Leuner et al., 2004). Thus, there was a possibility that we would observe effects of learning within our Angry Birds group simply by virtue that playing any video game could provide a rich, novel experience for them. For this reason, the Solitaire condition provided us with a control where participants actively played a game that they were familiar with. Thus, we examined the effect of playing Super Mario 3D or Angry Birds compared to the active control condition of playing Solitaire. In addition, to allow for the potentially slower learning of the game dynamics in older adults, we extended the amount of video game play from 2 to 4 weeks based on previous work suggesting that 10-20 hours of gameplay was needed to observe effects on cognition.

2. Materials and methods

2.1. Participants

We initially recruited 56 older adults (60-80 years of age) to participate in our intervention. Of these, five participants were excluded prior to the analysis: three participants scored more than three standard deviations below the average on the recognition metric of the MST (prior to condition assignment) and two did not play the video game for the entire duration of the study (one from Angry Birds and one from Super Mario) as determined by the Wii U which kept track of playing time. In total, 51 cognitively normal older adults (38 female, 13 male; mean age: 68.52 years, SD: 5.87; mean education: 16.53 years, SD: 2.25) completed the study. We established that all participants scored within the normal range for their age (all scores of 25 or higher) on the Mini-Mental State Examination (Folstein, Folstein, & McHugh, 1975), a standardized assessment of general cognitive status. Participants were recruited through local flyers and UCI affiliated groups, such as UCI MIND and the Alzheimer’s Disease Research Center. While participants knew they would be playing video games, they were blind to our expectations based on the specific game. At the end of the study, all participants were compensated for their participation. All participants were screened for prior experience with modern video games using a modified version of the video game questionnaire used previously (Clemenson & Stark, 2015). This questionnaire was designed to assess participant’s familiarity with video games in general, including questions of prior experience and specific video games they have played or currently play. Exclusion criteria included whether they had experience with either Super Mario 3D World or Angry Birds, on a console or PC machine, and if they currently played a 3D video game (greater than one hour per week), on a console or PC machine. We did not exclude participants for experience with Solitaire as everyone was familiar with the game and this was our active control group. No participants were excluded from the study based on their video game experience. Upon completion of a neuropsychological assessment, participants were pseudo-randomly assigned to one of three intervention groups: Solitaire (10 female, 5 male; mean age: 68.73 years, SD 5.98; mean education: 17.33 years, SD: 1.23), Angry Birds (14 female, 4 male; mean age: 70.83 years, SD: 5.98; mean education: 15.94, SD: 2.65) or Super Mario (13 female, 5 male; mean age: 67.5 years, SD: 5.02; mean education: 16.2, SD: 2.3). All participants gave voluntary consent to participate and the study was conducted in compliance with the Institutional Review Board (IRB) of the University of California at Irvine.

2.2. Experimental Design

The entire intervention spanned eight weeks, including two neuropsychological assessments, four presentations of the Mnemonic Similarity Task (MST) using four distinct image sets, and four weeks of video game training (Figure 1A). Neuropsychological assessments occurred pre (week 0) and post video game training (end of week 4). Administration of the MST occurred at both of these time points, as well as midway through the video game training (end of week 2) and four weeks after completion of the video game training (week 8) to assess any lasting effects of the intervention.

Figure 1.

Figure 1.

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Experimental design and hippocampal-based memory performance. (A) Images of the three video games used and a schematic of the experimental design. (B) Performance in the hippocampal-mediated lure discrimination index (LDI) at pre-test (0-week) and post-test time points (2-week, 4-week, and 8-week), for all groups. (C) Performance in the general recognition memory (REC) at pre-test (0-week) and post-test (2-week, 4-week, and 8-week) time points, for all groups. All data are presented as mean ± SEM, *p < 0.05, ****p < 0.0001.

2.3. Neuropsychological assessment

All participants were given a neuropsychological assessment both prior-to and immediately following the video game intervention by a tester naive to condition. The neuropsychological battery included tests for general cognition: Mini-Mental State Examination (MMSE) (Folstein et al., 1975); memory: Rey Auditory Verbal Learning Test (RAVLT) (Rey, 1941) and Rey-Osterrieth (Rey-O) (Meyers & Meyers, 1995); executive functioning: Trails A & B (Tombaugh, 2004), Wechsler Adult Intelligence Scale (WAIS) Letter-Number sequence (Wechsler, 1997) and the Stroop Color and Word Test (Golden, 1978); and depression: Beck Depression Inventory (BDI) (Beck, 1972). We used two different word sets for the RAVLT and two different figure drawings for the Rey-O, pre and post intervention.

2.4. Mnemonic Similarity Task (MST)

The MST is a recognition memory task designed to tax the process of pattern separation (Kirwan & Stark, 2007). It consists of two phases, an incidental study phase and a test phase. In the first phase, participants were shown 128 pictures of everyday objects (2s duration) and made simple indoor/outdoor judgement about each object. The second phase consists of a modified recognition test in which participants are shown Targets (previously seen items), Lures (items very similar to previously seen objects), or Novel foils (new items) and tasked with responding ‘Old’, ‘Similar’, or ‘New’ respectively (64 objects per condition, 192 total trials, 2s duration). In both phases, to better accommodate older participants, while the image disappeared from the screen after 2s, responses were self-paced. This allows for slower response times but prohibits excessive studying or scrutiny of the image that might lead to an altered strategy.

There are two metrics for assessing performance on the MST. The lure discrimination index (LDI) assesses hippocampal mnemonic discrimination (or “behavioral pattern separation”) and is calculated as the probability of correctly identifying a ‘lure’ item as ‘similar’ minus incorrectly identifying a ‘foil’ item as ‘similar’ (lure|similar – new|similar). In addition to the LDI, a traditional recognition index (REC) serves as a measure of general recognition memory. REC is calculated as the probability of correctly identifying a ‘target’ item as ‘old’ minus incorrectly identifying a ‘new’ item as ‘old’ (target|old – foil|old). Importantly, the LDI metric is specifically sensitive to age-related changes in the hippocampus and cognitive decline whereas the REC metric is not (Kirwan et al., 2012; Stark, Stevenson, Wu, Rutledge, & Stark, 2015; Stark et al., 2013; Yassa & Stark, 2011). Completely independent, but evenly matched in difficulty, stimulus sets were used for the pre-test and three post-tests (in a counter balanced manner) to eliminate any interference or practice effects. In addition, we have previously performed the MST on participants up to four times (using different image sets) and found the LDI scores to be highly consistent (Clemenson & Stark, 2015) with no evidence of test-retest effects (Stark et al., 2015).

2.5. Video game intervention

Participants were pseudo-randomly assigned to train in one of three video games (Solitaire, Angry Birds, and Super Mario Bros 3D World) for 4 weeks, 30 minutes/day (max of 45 minutes/day). Participants were pseudo-randomly assigned based on gender, age, education, and initial MST scores, to ensure an even distribution between groups. The duration of the intervention was based on prior work suggesting that 10-20 hours of video game play is sufficient to observe effects on cognition (Clemenson & Stark, 2015; Clemenson, Henningfield, & Stark, 2019; C. S. Green & Bavelier, 2006; C. Shawn Green & Bavelier, 2003; Kuhn, Gleich, Lorenz, Lindenberger, & Gallinat, 2014). Participants were told to play at least 30 minutes/day (average time: 37.58 minutes/day, SD = 8.09 minutes). However, if at 30 minutes they were in the middle of a level/game, they were allowed to continue until completion of the level/game. Both Angry Birds and Super Mario 3D World groups played on the Nintendo Wii U, while Solitaire was played on the participant’s personal computer. Klondike Solitaire (GemMineMedia, www.gemmine.de/) was downloaded as an asset using the Unity 3D Engine (www.unity3d.com, Unity Technologies) and further modified (by G.D.C) to record the score and gameplay of the participants.

Solitaire is a card game in which the goal is to organize the playing cards from Ace to King, within suits, while using a limited number of positions that cards can occupy. Angry Birds is a video game in which the goal is to knock down a structure by flinging birds at it. It is a 2D video game where the main decision by the user is to determine the ideal trajectory (power and angle) of the bird to successful destroy the structure. Super Mario, on the other hand, is a 3D video game, in which the goal is to simply navigate to the end of the level. Levels contain numerous obstacles to maneuver and puzzles to solve. Importantly, while both Angry Birds and Super Mario have been shown to be engaging (by virtue of success of the companies/games), Super Mario is significantly more spatial in nature.

All video game training occurred remotely at the participants’ homes. On the first day of video game training, an experimenter visited the residence of the participant to teach them how to set-up and play their respective game. A Nintendo Wii U was provided for participants to play Angry Birds and Super Mario, while Solitaire was loaded onto a personal computer. If the participant did not have a TV for the Wii U, one was provided to them for the length of the intervention (32-inch flat screen TV). For the participants playing Angry Birds or Super Mario, we created a unique avatar (Nintendo Mii) that recorded the games played, time/date stamps, as well as simple performance metrics such as the number of levels completed and the total score. The Solitaire program recorded similar data including time/date stamps, scores, and win/loss records. We also collected self-reports of video game training time and performance but all analyses were performed on the data logged by the Nintendo Wii U and Solitaire program that was retrieved once the participant had completed the 4 weeks of video game training.

2.6. Statistical Analysis

All statistical analyses were performed using Prism 8 (GraphPad, www.graphpad.com). Pre-planned comparisons were performed using 2-way ANOVAs with repeated measures. Specific statistical tests for multiple comparisons are reported with the results. A significance value of p<0.05 was used for all statistical analyses. A D’Agostino & Pearson test was used for the normality of the distribution.

3. Results

3.1. Training on Super Mario 3D World led to improvements in hippocampal-based memory compared to Solitaire

We had previously observed that playing Super Mario led to improvements in hippocampal-based memory in younger adults (Clemenson & Stark, 2015). Therefore, our primary endpoint in this study was to determine if playing the video game Super Mario 3D World had a similar effect in older adults. We entered the LDI metric of the MST into a repeated-measures 2x4 ANOVA (Geisser-Greenhouse correction) to assess hippocampal-based memory across Super Mario and Solitaire at four time points (Pre, Post1, Post2, Post3). We found a significant interaction (Figure 1B; F(3,93) = 3.46; p < 0.05) and main effect of time (F(2.7, 83.75) = 8.29; p = 0.0001), with performance increasing over the course of the intervention, but no main effect of group (F(1,31) = 0.55; p = 0.46). A post-hoc analysis (Tukey correction for multiple comparisons at p < 0.05) revealed a significant improvement in the Super Mario group from the Pre-test to the 2-week (Post 1), 4-week (Post 2), and 8-week (Post 3) time points. There was no change from the Pre-test to any of the post-tests in the active-control Solitaire group. Importantly, general recognition memory (REC) did not change across the intervention (Figure 1C; F(2.9 89.9) = 0.67; p = 0.56), suggesting that these improvements were specific to hippocampal-based memory.

3.2. Training on Angry Birds leads to an initial improvement in hippocampal-based memory

While we previously did not observe any effects of Angry Birds on hippocampal-based memory in younger adults (Clemenson & Stark, 2015), we hypothesized that the novel experience of playing a video game on a Wii U would provide a somewhat enriching experience for older adults. A repeated-measures 2x4 ANOVA (Geisser-Greenhouse correction) across both Angry Birds and Solitaire and four time points (Pre, Post1, Post2, Post3) revealed a significant main effect of time (Figure 1B; F(2.47, 76.84) = 4.67; p < 0.01) but no significant interaction (Figure; F(3,93) = 0.88, p = 0.45) or main effect of group (F(1,31) = 0.19; p = 0.66). A post-hoc analysis (Tukey correction for multiple comparisons at p < 0.05) revealed a significant improvement in the Angry Birds group from the Pre-test to the 2-week (Post 1) time point but not from the Pre-test to the 4-week (Post 2; p = 0.09) and 8-week (Post 3; p = 0.08) time points. Again, there was no change from the Pre-test to any of the post-tests in the active-control Solitaire group and general recognition memory (REC) did not change across the intervention (Figure 1C; F(2.88, 89.55) = 1.28, p = 0.28).

3.3. The effect size of LDI improvement, across the intervention, was greater in the Super Mario group compared to the Angry Birds group

To better understand the magnitude of these effects, we computed our most robust estimate of the treatment effect for each experimental condition (Super Mario and Angry Birds) compared with the control condition (Solitaire). We found a medium effect in the Super Mario group (ΔLDISM-SOL = 0.097; Cohen’s d = 0.47) and a small effect in the Angry Birds group (ΔLDIAB-SOL = 0.053; Cohen’s d = 0.26) relative to Solitaire (effect sizes vs. 0 were 0.71, 0.52, and 0.27). Furthermore, using a non-linear regression analysis to compare the slopes of LDI performance over time, we found that only the Super Mario group had a slope that was significantly different than zero (either 0-8 or 0-4 weeks; data not shown; p < 0.01).

3.4. Training on both Angry Birds and Super Mario 3D World led to an improvement in the Rey-Osterrieth complex figure task

Across all neuropsychological assessments, we did not observe any significant changes from pre-test to post-test (all p’s > 0.29) with the exception of the Rey-O. While all three intervention groups performed similarly at pre-test (Table 1), upon completion of the study, we found some evidence that performance on the Rey-0 task improved in both the Angry Birds and Super Mario 3D world groups. Performance on the Rey-0 involves making a copy of a complex figure while it is present (Rey-0 Copy) and then drawing it again later (following a 15-minute delay) from memory (Rey-0 Delay). To account for any variation in drawing and copy performance and to isolate memory, we calculated the ratio between the Rey-0 Delay score and the Rey-0 Copy Score (Figure 2A). Comparing Super Mario and Solitaire across two time points, we found a significant main effect of time (Figure 2A; 2x2 repeated-measures ANOVA: F(1,31) = 14.2, p < 0.001) but no reliable interaction (F(1,31) = 3.32, p = 0.07) or main effect of group (F(1,31) = 0.98, p = 0.32). Comparing Angry Birds and Solitaire across two time points, we found a significant main effect of time (Figure 2A; 2x2 repeated-measures ANOVA: F(1,31) = 23.93, p < 0.0001) and significant interaction (F(1,31) = 7.68, p < 0.01), but no main effect of group (F(1,31) = 0.58, p = 0.45). A post-hoc analysis (Tukey correction for multiple comparisons at p < 0.05) revealed an improvement in both Angry Birds and Super Mario groups from pre-test to post-test (4-week) but not in the Solitaire group. While both Angry Birds and Super Mario groups showed some evidence of better performance than the Solitaire group at post-test, this comparison did not reach significance (AB: p = 0.06 and SM: p = 0.07, uncorrected).

Table 1.

This table presents the demographics information and the means and standard deviations of the neuropsychological tests used in this study at Pre-Test (0-week) and Post-Test (4-week), across all groups.

Demographics Solitaire Angry Birds Super Mario 3D World
Sample size (female/male) 15 (10/5) 18 (14/4) 18 (13/5)
Mean age (SD) 68.73 (5.98) 70.83 (5.98) 67.5 (5.02)
Mean education (SD) 17.33 (1.23) 15.94 (2.65) 16.2 (2.3)
Pre-Test Neuropsychological Assessment (mean, SD)
MMSE 29.44 (0.52) 29.05 (0.93) 28.77 (1.21)
RAVLT Total 50.77 (10.07) 51.72 (11.92) 50.44 (12.01)
RAVLT Immediate 10.22 (3.15) 11.16 (3.14) 10.5 (3.45)
RAVLT Delay 9.66 (2.54) 11.16 (3.16) 11.27 (3.46)
Rey-O Copy 35.11 (1.16) 33.83 (2.53) 33.61 (2.19)
Rey-O Delay 15.5 (5.30) 15.38 (6.46) 16.63 (5.35)
Trails A 35.33 (10.40) 29.71 (12.24) 27.49 (8.71)
Trails B 60.25 (15.71) 70.26 (21.80) 71.30 (14.67)
Digit Span Total 19.44 (4.06) 17.94 (3.55) 17.72 (4.22)
WAISIII LN Sequence 18 (5) 17.76 (5.6) 16.94 (4.31)
Stroop Interference 47 (7.56) 48.94 (8.50) 46.77 (9.73)
Post-Test Neuropsychological Assessment (mean, SD)
MMSE 29.47 (0.64) 28.63 (1.74) 28.78 (1.06)
RAVLT Total 52.27 (7.136) 53 (9.45) 52 (9.12)
RAVLT Immediate 10.53 (3.54) 11.1 (2.85) 11 (2.78)
RAVLT Delay 10.4 (3.81) 11.42 (3.15) 11.22 (2.53)
Rey-O Copy 35.47 (1.12) 33.89 (2.05) 33.25 (4.34)
Rey-O Delay 19.36 (9.81) 22.89 (5.79) 24.55 (11.42)
Trails A 32.06 (11.77) 27.62 (9.92) 27.37 (10.57)
Trails B 63.02 (19.93) 62.51 (24.66) 67.02 (17.4)
Digit Span Total 19.73 (3.45) 18.63 (4.75) 18.22 (3.31)
WAISIII LN Sequence 17.23 (4.51) 14.13 (4.4) 14.67 (4.08)
Stroop Interference 49.46 (5.78) 50.16 (7.14) 49.44 (9.07)
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Figure 2.

Figure 2.

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Performance on the Rey-O and change in hippocampal-based memory across age. (A) Performance on the Rey-O task at pre-test (0-week) and post-test (4-week) time points, for all groups. (B) Performance on the lure discrimination index (LDI) at pre-test (0-week) and post-test (4-week) time points for both Super Mario 3D World and Angry Birds groups combined, across age. All data are presented as mean ± SEM, ***p < 0.001, ****p < 0.0001.

3.5. The improvement in LDI was consistent across age but did not correlate with video game performance

Previously, we showed that performance on the MST LDI metric steadily declines across the adult lifespan, from 20-89 years of age (Stark et al., 2013). Here, in our more restricted range of older adults (60-80 years of age) that played Angry Birds and Super Mario 3D World, we again observed a significant decline in LDI with age (Figure 2B) at both pre-test (r2 = 0.09, p < 0.05) and post-test (r2 = 0.09, p < 0.05). These age effects were remarkably consistent in the pre- and post-test scores as the slopes were not reliably different from each other (F = 0.008, p = 0.92). In contrast, the pre- vs post-changes in LDI were reliably different (F = 5.305, p = 0.02). Furthermore, the change in LDI from pre- to post-test for both the Angry Birds and Super Mario groups did not correlate with age (r2 = 0.001, p = 0.84), suggesting that the benefits of the video game intervention on hippocampal-based memory are consistent across age.

Unlike our previous study in young adults (Clemenson & Stark, 2015), where we found that improvements in the LDI metric correlated with how well participants performed in the video game, we did not find any such correlations between change in LDI from pre-test to post-test and video game performance (Solitaire: r2 = 0.05, p = 0.41; Angry Birds: r2 = 0.01, p = 0.64; Super Mario: r2 = 0.01 p = 0.74).

4. Discussion

We tested the hypothesis that playing immersive 3D video games might act as a proxy for environmental enrichment and improve hippocampal-based memory in older adults. We found that older adults who participated in a novel video game intervention (Super Mario 3D World) for 4 weeks showed improved performance on an independent hippocampal-based memory task that persisted for up to four weeks after completion of the intervention. These findings, largely consistent with our previous study in young adults, highlight the potential value of video game play as an effective intervention for older adults.

In the current study, we found that, unlike our prior work in young adults (Clemenson & Stark, 2015), playing Angry Birds had a measurable impact on hippocampal-based memory at the initial two week post-test. While this improvement did not persist throughout the rest of the study, did not appear to be as robust as the Super Mario group, and may have saturated early in the intervention, it did have a positive effect. One potential explanation is that the experience of console-based video game play itself is enriching for older adults. Our initial concern prior to this study was that because our older population had absolutely no experience with video games or video game consoles, showing up to their house with a large flat screen TV and a gaming console and having them play even a simple, novel video game may provide an enriching experience. As noted, the novelty and learning experiences provided by enriched environments are thought to play an important role in its hippocampal influence (Gould et al., 1999; Leuner et al., 2004). Therefore, the benefits we observed here may be due to playing Angry Birds specifically, learning to use the Nintendo Wii U, or simply learning to use a joystick. Critically, actively playing a familiar game (on a familiar computer) did not have appear to have the same benefit. This is, however, merely speculation and future studies are necessary to address the influence of novelty. In addition, it is important to note that like our previous study in young adults, the population of older adults in this study consisted of primarily female participants. We cannot determine any effects of gender with the present data.

Notably, the effects of video game training in our older adults persisted for up to four weeks after completion in the present study, whereas the improvement in our younger adults showed some evidence of regressing back towards baseline within two weeks of completion (Clemenson & Stark, 2015). There are several possible explanations for this difference. First, we should note that our prior work showed that after two weeks without gaming, the LDI scores were no longer reliably above pre-test baseline, but nor were they reliably below the immediately post training scores. That said, we would be remiss to not note that young college students are at a very different point in life than older adults. College is an enriching experience in adulthood. While video game play might be stimulating, there are countless other experiences happening in college (socially and educationally, both positive and negative) that may interfere or even replace the video game experience once it has stopped. Older adults, on the other hand, may-well have a more routine lifestyle and the video game intervention may represent a unique experience in itself. Another major difference between the two studies is the length of the intervention. Since the older adults played twice the amount of time as the younger adults (4 weeks instead of 2 weeks), it is possible that they reached or surpassed some threshold necessary for a longer-lasting change in hippocampal function. Further investigation is required to determine if this is due to the total number of hours played, consistent daily training, or some other aspect of the intervention. Importantly, while the MST has previously been shown to be sensitive to hippocampal function, it is possible that video games may be influencing other structures and cognitive functions that support memory such as attention or visual abilities.

In addition to improvements on the MST, we found that playing both Angry Birds and Super Mario, but not Solitaire, resulted in a significant improvement on the Rey-O. The Rey-O is a neuropsychological test used both clinically and in research to test several cognitive functions including attention, concentration, fine-motor coordination, visuospatial perception, nonverbal memory, and organizational skills (Shin, Park, Park, Seol, & Kwon, 2006). We examined Delay performance while controlling for the initial Rey-0 Copy performance. The Rey-0 Delay is highly sensitive to hippocampal amnesia (Rempel-Clower, Zola, Squire, & Amaral, 1996) and we have previously observed a positive correlation with LDI and hippocampal volume (Stark & Stark, 2017a). Thus, it is not surprising that similar effects were observed for performance on the Rey-0 and the MST’s LDI, both sensitive measures of hippocampal function. It is promising to see that the benefits from this video game intervention may extend beyond the MST to other tasks and future studies should explore more sensitive measures of other cognitive domains as video games likely influence behaviors outside the hippocampus. We should note that while the Rey-0 has a long history and has its clear merits, repeat testing of it beyond two tests is difficult because alternative versions are not available and results here were not wholly robust. In contrast, the MST has at least 12 possible variants with no evidence of practice effects (Stark et al, 2015).

Lastly, the improvement on the MST (ΔLDI ≈ 0.1, d vs 0 ≈ 0.7) observed here in our older adults is remarkably consistent with what we have observed previously in young adults using Super Mario 3D World (Clemenson & Stark, 2015), young adult competitive gamers specializing in different game genres (Clemenson & Stark, 2015), young adults using Minecraft to explore the world or learn to build complex structures (Clemenson, Henningfield, & Stark, 2019), and older adults in a real-world spatial memory intervention (Kolarik, Stark, & Stark, under review). In combination with our previous work in young adults and the fact that the observed improvement of older adults in this study did not change with age suggests that these interventions are equally effective across age ranges (18-22 and 60-80) and demonstrate the real potential of video games as an effective intervention resulting in improved memory function.

The benefits of using commercially available video games such as Angry Birds or Super Mario is that they are accessible, can be played at home with little instruction, and seem to be engaging and fun. The drawback is that, in many cases, these games lack the control and the ability to measure how people interact with the game. The scores provided by both Super Mario and Angry Birds are relatively crude and do not reflect the effort, number of tries, and other important metrics of training. However, recently we used the video game Minecraft to demonstrate a platform in which we can control and collect quantitative data about how people experience and interact with a video game environment (Clemenson et al., 2019). The work presented here demonstrates the value of a more “hands off’ approach to cognitive training. We are not forcing participants to train in a specific dimension or to meet a training-criteria, we simply provided a video game platform and let their own individual experiences guide, instruct, and motivate them. Amazingly with minimal guidance and effort on the experimenter’s side, we observe improvements in key aspects of memory.

5. Conclusion

We showed that a four-week video game intervention in older adults can improve hippocampal-based memory measured with the MST and may extend to the Rey-O. In conjunction with our previous work, we have shown that these video game interventions are practical, short (4 weeks) with a low daily commitment (~30 minutes/day), can be done remotely at home, and are effective. These studies highlight a real potential of using video games as a therapeutic intervention for age-related cognitive decline.

Highlights.

  • Environmental enrichment can ameliorate age-related cognitive decline

  • Video games are a proxy for environmental enrichment in humans

  • Playing video games can improve key aspects of memory in older adults

  • Playing video games show potential as a therapeutic intervention

Acknowledgments

Funding: This research was supported by a grant from the Dana Foundation. In addition, we would like to acknowledge support for participant recruitment from the UCI ADRC P50AG016573 and for additional salary support from NIA R21AG056145 and NIA R01AG034613. None of the authors have any conflicts of interest to declare.

Footnotes

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