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The Influence of Acute Physical Activity on Working Memory

Perceptual and Motor Skills 2016, Vol. 122(2) 365–374 ! The Author(s) 2016 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0031512516631066 pms.sagepub.com

Sima Zach and Eyal Shalom Zinman College of Physical Education and Sport Sciences, Wingate Institute, Netanya, Israel

Abstract The effect of three types of physical activity on two types of working memory were investigated. Participants were 20 adult males who trained twice a week in volleyball two hours per session. Procedures included two pre and post intervention tests of working memory: the Digit span and Visual Memory Span subtests of the Wechsler Memory Scale–Revised. Interventions included tactical volleyball formation, bodyweight resistance exercises, 15 minutes of running, and sub-maximal aerobic activity. Volleyball activity improved memory performance to a greater extent than the other two activities. Results indicate that immediately after acute exercise there is an increase in working memory function, more evident after physical activity in which cognitive functioning is inherent. Keywords ball game activity, resistance exercise, working memory, physical activity type

Introduction A large body of research shows that physical activity improves cognitive functioning (e.g., Chang, Labban, Gapin, & Etnier, 2012; Khan, & Hillman, 2014; Lambourne, & Tomporowski, 2010). These studies have focused mainly on cognitive facilitation by cardiovascular exercise in older adults; fewer studies have investigated younger age groups, or other types of physical activities (VoelckerRehage & Neiman, 2013). In two meta-analyses, it was emphasized that the increase in cognitive functioning is evident following the activity

Corresponding Author: Sima Zach, Zinman College of Physical Education and Sport Sciences, Wingate Institute, Netanya, Israel. Email: [email protected]

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(Chang, Labban, Gapin, & Etnier, 2012; Lambourne, & Tomporowski, 2010). Accordingly, interest has developed regarding changes in cognition functions after participation in physical activity of different types, such as aerobic, coordination exercise, anaerobic, resistance exercise, or a combination of these types (Bossers et al., 2014; Khan & Hillman, 2014; Voelcker-Rehage, Niemann, 2013). In a meta-analytical investigation, McMorris and Hale (2012) showed that, generally, acute exercise has a small but significant mean effect on cognition. However, a comparison between speed and accuracy as dependent variables showed that speed accounted for 98% of the variance. Moderate-intensity exercise improved speed performance, with a moderate effect size. Additionally, they reported that central executive tasks showed a larger effect size than recall and alertness/attention tasks. As for accuracy, a significant mean effect size was found when testing took place post-exercise compared to during exercise, however the effect was very weak. They concluded that increased arousal during moderate-intensity exercise, probably due to increased brain concentrations of the neurotransmitters dopamine and norepinephrine, resulted in faster speed of processing. The authors cautiously posited that the non-existent effect on accuracy might be due to the choice of appropriate tests. Voelcker-Rehage and Neiman (2013) conducted a review on structural and functional brain changes related to different types of physical activity across the life span. Their findings showed that both types of exercise – metabolic (i.e. cardiovascular and resistance) and coordinative (i.e. bimanual coordination) – affect the brain differently. Coordination training includes exercises for fine and gross motor coordination, such as eye-hand coordination, spatial orientation, and reaction to movements (Voelcker-Rehage, Godde, & Staudinger, 2011). These exercises demand higher-level cognitive processes, and generate a smaller change in energy metabolism than cardiovascular and resistance training. Hence, changes generated by coordination exercise are likely to be related to changes in information processing and cognitive tasks that demand attention and managing visual and spatial information (Monno, Temprado, Zanone, & Laurent, 2002). Following Tomporowski (2003) and his colleagues’ (Tomporowski, Davis, Miller, & Naglieri, 2008) recommendations that the effect of physical activity on executive function should be better understood, researchers (e.g., Pesce, Crova, Cereatti, Casella, & Bellucci, 2009; Sibley & Beilock, 2007) have identified the effects of exercise on specific components of cognition that are relevant for the target population. Working memory was one of these important functions. Working memory describes a subset of processes involved in the active storage, maintenance, and manipulation of information to be retrieved within a brief interval (Postle, 2006). It is considered a fundamental facet of cognitive control, because individuals need to transiently hold and manipulate information in order to bring together goal-directed behaviors in an array of cognitive contexts (Diamond, 2006), as necessary for learning and essential for physical and social

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functioning (see Aronen, Vuontela, Steenari, Salmi, & Carlson, 2005; Passolunghi & Siegel, 2001; Sibley & Beilock, 2007), and for coping with educational and everyday demands (see Potter & Keeling, 2005; Tomporowski & Ganio, 2006). Furthermore, working memory was found to be a predictor of a number of higher-order cognitive tasks, including performance in a number of attention and inhibition tasks (e.g., McVay & Kane, 2012; Unsworth & Spillers, 2010) and a number of secondary or long-term memory tasks (Unsworth, 2010; Unsworth, Brewer, & Spillers, 2009). Working memory tasks have also been shown to predict life-event stress (Klein & Boals, 2001), susceptibility to choking under pressure (Beilock & Carr, 2005), and fluid intelligence (Unsworth, Fukuda, Awh, & Vogel, 2014). As such, it is important to understand the mechanisms and processes that increase working memory. Since much of the reported research was conducted in laboratory settings, the interest here was in examining the short-term effects of exercise on memory performance in adults in a real-world activity context, and therefore a leisure activity environment in a recreational club was chosen. In addition, since the type of exercise that people are involved with may affect the influence of exercise on cognition (Tomporowski, Davis, Miller et al., 2008), and since other researchers recommended that the effects of exercise involving cognitively and socially demanding open skill activities be considered (e.g., Bla¨sing et al., 2012; Kamijo & Yuji, 2013; Pesce, 2012; Pontifex, Hillman, Fernhall, Thompson, & Valentini, 2009), three types of physical activities were chosen for this study. Team ball games was chosen as a type of physical activity that requires complex cognitive processes, such as decision making, planning, coordination of processes, and communication skills, not required in “individualistic” and monotonous activities such as running or strength training (Dietrich, 2006; 2009). The goal was to assess the differences between ball game activity, sub-maximal aerobic exercise, and anaerobic a-lactic resistance exercise, whose relationships with cognition were reviewed above.

Research question Does an activity with high cognitive demands such as playing a ball game have a different effect on working memory than common physical activities done for exercise?

Method Participants Participants were twenty men, ages 18 to 50 years (M ¼ 27.3, SD ¼ 3.2), who trained twice per week in volleyball, two hours per session, as a leisure-time activity at a country club located in the center region of the country.

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Measures Heart Rate. A sports watch with a heart rate monitor, Polar M400 GPS, was used to measure heart rate three minutes before pre-intervention working memory tests, and three to ten minutes after each of the three physical activities, so as to ensure that the participants’ heart rate recovered pre-intervention baseline. Digit span subtest of Wechsler Memory Scale–Revised (Wechsler, 1997), which assesses working memory for an auditory series of digits not logically related. In this study, only the digit span forward test was administered. The participant listens to sets of ascending digit numbers, at a pace of one digit per second. There is a different set of numbers each time. The participant has to listen and then repeat the digits out loud. The test is stopped after two consecutive fails on the same item, meaning two sets with the same items; even if the participant was wrong in the first set, the test continues. Each correct answer gets one point, so the maximal score is 16. Visual memory span subtests of the Wechsler Memory Scale–Revised (Wechsler, 1987) measures visual short-term and working memory abilities. This test includes the repetition of different sequences of three palm-movements: fist, palm on table, and palm vertical to table, in ascending order starting from two movements – fist and palm on table. The test is stopped after two consecutive fails on the same set of movements (that is, two series with the same number of movements). This means that even if the participant was wrong in the first set, the test continues. Each correct repetition gets one point, so the maximal total score is 12. The psychometric properties of these tests have been found to be satisfactory, and have been reported extensively elsewhere (e.g., Millis, Malina, Bowers, & Ricker, 1999; Omura, & Sugishita, 2004).

Procedure The study took place at a country club located in the central region of Israel. The study was implemented along three sessions. In the first session, participants performed two pre-intervention working memory tests: digit span and visual memory span. Then at each session, they performed one of the following physical activities as the intervention phase: (1) a volleyball tactical activity, (2) an aerobic activity, and (3) an anaerobic a-lactic activity. Immediately post-intervention, they conducted the same two working memory tests as they did at pre-intervention. In each of the three physical activity sessions, the working memory tests’ order was changed, in order to circumvent an order effect (Table 1). Intervention included three types of physical activity: (1) an advanced, nonfamiliar 5-1 tactical volleyball formation. In this drill, each player had to perform 3–4 game actions during the game period of 2–3 seconds. In addition, each position exchange was characterized by several actions taken simultaneously,

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Table 1. Study Design. Pre-intervention Working Memory Tests

Session

Intervention Aerobic PA

Rest

Post-intervention Working Memory Tests

1

Visual memory span

Digit span

2

Digit span

Visual memory Anaerobic aspan lactic PA

Digit span

Visual memory span

3

Visual memory span

Digit span

Visual memory span

Digit span

Volleyball Tactical PA

3 minutes Visual memory rest span

Digit span

Note. PA ¼ physical activity.

so that there would be an intermediate cognitive load on working memory at every given moment in the game formation. (2) Body-weight resistance exercises, as follows: three sets10 pushups, three sets 10 sit-ups, and three sets10 squats, with a one-minute rest between each set; (3) 15 minutes of running with a 120–130 heart rate, a sub-maximal aerobic activity. Following each of the three physical activities, the participant rested for three to ten minutes. Data were gathered along two months, with six participants at a time examined at each training session, until all measurements were completed.

Data Analysis Descriptive statistics were calculated for auditory and visual working memory in three types of physical activity, pre- and post-intervention. Two-way ANOVA with repeated measures was conducted to examine the differences between two types of working memory, pre-and post-intervention. To assess the significant differences between the three types of physical activity in two working memory tests, pre- and post-intervention, ANOVA with repeated measures (3 activity type 2 working memory auditory/visual 2 times-pre/post) was employed with a least significant difference (LSD) post hoc test.

Results Table 2 presents descriptive statistics for participants’ auditory and visual working memory at pre- and post-intervention in the three types of physical activity. As appears in Table 2, working memory scores on both tests improved in all three physical activities from pre- to post-intervention. ANOVA with repeated measures revealed no significant differences in either visual and auditory working memory between the three types of activities from pre- to post-intervention (Wilks’ ¼ 0.97; F(2, 18) ¼ 0.33, p ¼ .73; 2 ¼ 0.04). ANOVA with repeated measures revealed that the volleyball tactical activity group demonstrated significantly greater improvement in both working memory tests compared to the

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Table 2. Means and SDs of Working Memory Test Scores (Converted to Percentiles) of Three Physical Activity (PA) Types at Pre- and Post-intervention. Working Memory Test Visual memory span

Physical Activity Aerobic Anaerobic a-lactic Volleyball tactical PA

Digit span

Aerobic Anaerobic a-lactic Volleyball tactical PA

Time

M

SD

Pre Post Pre Post Pre Post

71.87 74.37 69.06 70.93 70.62 85.31

9.82 5.70 9.17 5.47 5.40 6.50

Pre Post Pre Post Pre Post

78.33 83.75 77.91 82.50 80.83 95.00

9.13 8.75 8.67 6.57 9.40 5.67

sub-maximal aerobic and anaerobic a-lactic activity groups (p < .05). No significant interaction appeared between working memory tests and type of physical activity (Wilks’ ¼ 0.92; F(2, 18) ¼ 0.74, p ¼ .49, 2 ¼ 0.08). In addition, there was a significant interaction between pre- and post-intervention working memory scores and type of activity (Wilks’ ¼ 0.36; F(2, 18) ¼ 16.27, p < .001, 2 ¼ 0.64). This means that for the two memory tests, a similar trend was observed, so that for the sub-maximal aerobic and anaerobic a-lactic activities there was no improvement, whereas for the volleyball tactical activity a significant improvement was noted. ANOVA showed no differences between auditory working memory and visual memory; both improved from pre- to post-intervention regardless of which activity was implemented. As expected, ANOVA showed different working memory improvement between the three activities that were examined. The LSD post hoc test showed that game activity had the greatest effect on working memory, compared to the aerobic and resistance exercises.

Discussion The current study examined whether playing a ball game has a different effect on working memory than other types of physical activity. The findings strengthen earlier studies’ results, which claim that acute activity has a beneficial effect on working memory (e.g., Coles, & Tomporowski, 2008; Pontifex, Hillman, Fernhall, Thompson, & Valentini, 2009). Working memory increased after all three types of activity that were included in the intervention phase of this study.

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As expected, the extent of working memory improvement differed between the three activities that were examined. Game activity had the greatest effect on working memory compared to the aerobic and resistance exercises. This result is congruent with earlier studies’ results showing that different types of physical activity improve working memory (e.g., Best, 2010; Colcombe & Kramer, 2003; Kramer et al., 1999). However, while some studies included only aerobic (e.g., Colcombe & Kramer, 2003; Masley, Roetzheim, & Gualtieri, 2009) or resistance (e.g., Lachman, Neupert, Bertrand, & Jette, 2006) exercise, or a combination of these types of exercise (e.g., Kramer et al., 1999; Pontifex, Hillman, Fernhall, Thompson, & Valentini, 2009), this study added a tactical ball game activity. A few limitations should be mentioned regarding this study: (1) no intermediate variables were taken into consideration that may have had an effect on working memory, in addition to the type of the activity itself, such as mood, motivation, level of fitness, or well-being; (2) the range of the participants’ age was quite wide, and working memory is affected differently at different ages; (3) it might be that an improvement in memory was related to the participant’s initial fitness or mood, which was not monitored in this study, and (4) intensities and duration of exercise in each condition differed, and this may have affected the results. Nonetheless, the uniqueness of the current study is manifested in several aspects. First, the design included a ball game activity, in which cognitive requirements are higher. Second, the design was naturalistic, examining individuals during their regular exercise, while other studies have examined participants mainly in a laboratory setting (e.g., Ellemberg, & St. Louis-Descheˆnes, 2010; Quelhas, Kavussanu, Willoughby, & Ring, 2013). Third, the use of a withinsubject design, in which all participants experienced the three physical activity manipulations, is a strength. This study demonstrated that a physical activity requiring tactical thinking improved working memory to a greater extent than sub-maximal aerobic activity or resistance activity.

Conclusions Leisure-time acute physical activity can improve working memory among adults. However, each type of activity, specifically sub-maximal aerobic/anaerobic a-lactic/ball game-volleyball, had a different influence on the level of improvement. It should be noted that this study examined working memory immediately after physical activity, and therefore the long-term effect of the activity still has to be examined. It is recommended that future research examine longer intervention programs, over a wide range of ages of participants, taking into account a leisure time physical activity as well as physical activity in other settings, in order to determine the longitudinal effect of an active lifestyle on people’s cognitive functioning.

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Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Author Biographies Sima Zach is the Head of the School of Education at the Zinman College of Physical Education and Sport Sciences, Wingate Institute, Israel. She is also the Director of the Teacher Education Program. Her research interests are in sport psychology, physical education psychology, and psychology of leisure-time physical activity. Eyal Shalom, MEd, is a physical education teacher in high school, and a basketball and a volleyball certified coach.