Experimental Effects of Acute Exercise on Prospective Memory and False Memory

Abstract

Research demonstrates that acute exercise can enhance retrospective episodic memory performance. However, limited research has examined the effects of acute exercise on prospective memory, and no studies have examined the effects of exercise on false memory performance. This study examined the potential effects of acute exercise on prospective memory and false memory performance. A between-group randomized controlled trial was employed, with participants (college students; M_age = 20 years) randomized into an exercise group (15-minute acute bout of treadmill walking; N = 25) or a control group (15 minutes of sitting; N = 26). Prospective memory was assessed from two laboratory and two naturalistic assessments outside the lab. False memory was assessed using a word-list trial. There were no statistically significant differences in prospective memory based on group allocation (F_Group×Time = 1.17; P = 0.32; η²= 0.06). However, the control group recalled more false words and had a higher rate of false memory recognition (F_Group×Time = 3.15; P = 0.01; η²= 0.26). These findings indicate that acute moderate-intensity aerobic exercise is not associated with prospective memory performance but provides some suggestive evidence that acute exercise may reduce the rate of false memories.

Keywords

Acquisition confabulation consolidation episodic memory distortion

Introduction

Prospective memory (PM) refers to forming an intention to be carried out after a delay, without external reminders (Einstein & McDaniel, 1990). Specifically, PM may be parsimoniously conceptualized as a three-phase model, including (1) forming an intention, (2) storing the formed intention, and (3) switching from an ongoing task at the appropriate time or event to execute the intended action (Kliegel, Martin, McDaniel, & Einstein, 2002).

Event-based and time-based are two categories often applied to PM. Event-based PM requires the performance of an intended action after recognition of an external cue in the environment (e.g., taking medication at lunch and remembering to stop at the post office after work to pick up stamps), whereas in time-based tasks, action is performed at a specific point in time (e.g., 6:00 a.m.) or after a certain time has elapsed (e.g., calling the doctor in 2 hours). The initial identification of a stimulus as a PM cue (e.g., a sign marking the post office) and a subsequent response with an appropriate PM action (e.g., stopping at the post office) are important components of event-based PM. These components are likely influenced by the individual’s degree of cognitive attention. Time-based PM requires the ability to inhibit an ongoing activity to check the clock, ensuring that the response decision occurs at the correct time. Thus, time-based PM largely depends on time-estimation processes, such as accurate time-monitoring (e.g., number of times an individual checks the clock) (Khan, Sharma, & Dixit, 2008).

Our recent work demonstrates that acute exercise can help to facilitate episodic retrospective memory (Crush & Loprinzi, 2017; Frith, Sng, & Loprinzi, 2017; Loprinzi, Edwards, & Frith, 2017; Loprinzi, Frith, Edwards, Sng, & Ashpole, 2017; Loprinzi & Kane, 2015; Sng, Frith, & Loprinzi, 2018), but to date, few studies have examined the effects of exercise on PM. In theory, regular exercise behavior may help to facilitate PM via shared pathways. For example, PM may be influenced by emotional states and cue valence, and exercise is associated with mood state (Jaffery, Edwards, & Loprinzi, 2017) and emotional memory (Segal, Cotman, & Cahill, 2012). Further, exercise may reduce depression-related rumination (Alderman, Olson, Brush, & Shors, 2016), which theoretically may predispose an individual to be less aware of a PM cue. Additionally, intentions are core constructs influencing both PM and exercise (Vallance, Murray, Johnson, & Elavsky, 2011; Wolff, Warner, Ziegelmann, Wurm, & Kliegel, 2016); similarly, controlled cognitive processes (i.e., executive function-related processes) moderate the relationship between behavioral intention and engagement in exercise (Hall, Fong, Epp, & Elias, 2008) and sedentary behavior (Loprinzi & Nooe, 2016). Further, similar to the critical role that working memory and other executive functions play in subserving PM, research demonstrates that these executive functions also substantively influence and can be influenced by exercise behavior (Loprinzi, Herod, Cardinal, & Noakes, 2013; McAuley et al., 2011). Exercise has also been shown to stimulate neuronal activity in brain areas (e.g., prefrontal cortex, parietal lobe, and cerebellum) known to influence PM (Hayes, Alosco, & Forman, 2014; Thomas, Dennis, Bandettini, & Johansen-Berg, 2012). Taken together, there is plausible evidence to suggest that exercise may favorably influence PM. Very few studies, however, have examined the effects of acute exercise on PM. We examined this in two prior experiments (one using a walking protocol and the either a high-intensity acute bout of exercise), but both studies did not demonstrate a beneficial effect of acute exercise on PM (Frith et al., 2017; Sng et al., 2018). Importantly, these two prior experiments used a relatively crude measure of PM (i.e., whether participants ended up calling the researcher at a specified time in the future). The present experiment builds on these two prior studies by utilizing a more comprehensive assessment of PM (described below).

In addition to extending this gap in the literature, this study also examines the potential effects of acute exercise on false memory function. Such an investigation has yet to be examined in the literature. Previous work has discussed potential mechanisms of false memory (Johnson & Raye, 2000; Plancher, Guyard, Nicolas, & Piolino, 2009; Schnider, von Daniken, & Gutbrod, 1996; Shapiro, Alexander, Gardner, & Mercer, 1981). In brief, false memories, or memory distortions, may arise from culturally determined expectations, labeling of the memory/event, and imperfect reality monitoring processes, such as source monitoring, which includes attributions about the origin of activation information. The source monitoring framework (Johnson, 1997) is perhaps one of the more extensive theoretical accounts of false memories, which highlights several key aspects of false memories. These key aspects indicate that memory attributions arise from (1) various qualitative characteristics of the mental experience (e.g., perceptual, spatial, temporal, or emotional details), (2) the embeddedness of the mental experience (e.g., availability of supporting memories), and (3) goals, beliefs, motivation, and social factors. Per this model, false memories occur because mental experiences arising from different events have overlapping characteristics that are imperfectly differentiated. Additional work also indicates that episodic memory and executive function performance predicts false memory function (Plancher et al., 2009). Both of these cognitive functions have been shown to be influenced by acute exercise (Chang et al., 2011; Loprinzi, Edwards, et al., 2017), providing plausibility for a potential relationship between acute exercise and reducing false memory performance. To address these two gaps in the literature, the purpose of this experiment was to evaluate if acute moderate-intensity exercise is beneficial in improving PM and reducing false memory performance.

Methods

Study design

This study was approved by the authors’ institutional review board. The present study was a two-arm, parallel, between-group randomized controlled trial, consisting of an exercise experimental group and a control group. The exercise group engaged in an acute 15-minute bout of moderate-intensity exercise. The control group sat quietly for 15 minutes. Both groups completed one laboratory visit.

At the start of the laboratory visit, informed consent was obtained. After this, participants completed a 15-minute bout of exercise or sat for 15 minutes, depending on the group they were randomized into. After this, detailed instructions on the PM assessment occurred (described below). Following this, participants completed a false memory task (described below). After the false memory task, they completed the PM task assuming they remembered to complete this task (described below). This then concluded the laboratory visit.

Participants

Participants (college students) were randomly assigned to the exercise (N = 25) or control group (N = 26). This sample size aligns with our previous experimental work on this topic (Crush & Loprinzi, 2017; Frith et al., 2017; Jaffery, Edwards, & Loprinzi, 2018; Loprinzi & Kane, 2015; Sng et al., 2018). Participants were recruited via classroom announcements and word-of-mouth. Participants were excluded if they:

Self-reported as a daily smoker (Jubelt et al., 2008; Klaming, Annese, Veltman, & Comijs, 2017)

Self-reported being pregnant (Henry & Rendell, 2007)

Exercised within 5 hours of testing (Labban & Etnier, 2011)

Consumed caffeine within 3 hours of testing (Sherman, Buckley, Baena, & Ryan, 2016)

Had a concussion or head trauma within the past 30 days (Wammes, Good, & Fernandes, 2017)

Took marijuana or other illegal drugs within the past 30 days (Hindocha, Freeman, Xia, Shaban, & Curran, 2017)

Were considered a “heavy” alcohol user (>30/month for women; >60/month for men) (Le Berre, Fama, & Sullivan, 2017)

Were left-hand dominant or mixed-handed (Alipour, Aerab-sheybani, & Akhondy, 2012)

Exercise protocol

Those randomized to the exercise group walked on a treadmill for 15 minutes at a self-selected “brisk walk” pace. Specifically, they were asked to “self-select a brisk walking pace, a pace as if you were late for class; please ensure that the speed is at least 3.0 mph and please attempt to maintain this speed throughout the treadmill walk.” We confirmed that the pace was maintained throughout the exercise bout.

Memory assessment

Prospective memory

To assess PM, the RPA-ProMem test (Royal Price Alfred Prospective Memory Test) was used (Aronov et al., 2015; Radford, Lah, Say, & Miller, 2011). Specifically, we used Form 2 of the RPA-ProMem. In brief, participants completed two laboratory and two naturalistic PM tasks, including both time-based and event-based tasks. The first laboratory PM task (short-term time-based) included having the participant inform the researcher what their last meal was at a particular point in time during the lab visit (i.e., approximately 20 minutes after they finished exercising). The researcher gives these instructions approximately 5 minutes after the bout of exercise and it was up to the participant to remember to complete this task. For the second laboratory PM task (short-term event-based), the researcher indicated that they would like to borrow something from the participant (e.g., phone or wallet), and when the alarm (the researcher’s phone alarm) goes off in the lab, the participant is to remind the researcher to give back the personal object. One of the naturalistic PM tasks (long-term event-based) included the participant calling the researcher on the phone when they got home and leaving a message on the researcher’s voice machine. The second naturalistic PM task (long-term time-based) included the participant returning an envelope to the researcher’s mailbox one week after the laboratory visit, in which the contents inside the envelope were to include the weather of that day. For each of the four components (short-term time-based; short-term event-based; long-term time-based; and long-term event-based), participants were given a score between 0 and 3 (based on whether the task was completed correctly and on-time). For example, for the long-term time-based task, they received 3 points if they returned the envelope on the correct day with the correct information; 2 points if they returned the envelope on the incorrect day with the correct information; 2 points for the correct day but incorrect information; 1 point for the incorrect day and incorrect information; and 0 points if the envelope was not returned. Thus, the total points possible for the PM task was 12, with a higher score indicating a better PM performance.

False memory task

The false memory task (Deese-Roediger-McDermott Paradigm) served as a distraction between the instructions of the PM task and the execution of the PM task.

The procedures of this false memory task were modeled after Roediger and McDermott (Roediger & McDermott, 1995). Participants listened (via headphones) to a recording of a list of 15 words; each word was read at a rate of 1 word per 1.5 seconds. They listened to six separate lists (see Table 1). After each list, they were asked to write down (on paper) all the words they could remember from the list. As an example, each list was composed of associates (e.g., bed, rest, awake) of one non-presented word/lure (e.g., sleep). If, for example, they wrote down the word “sleep,” then this was evidence of constructing a false memory.

Table 1.

Six separate word lists for the false memory task.

Mountain	Needle	Chair	Rough	Sleep	Sweet
Hill	Thread	Table	Smooth	Bed	Sour
Valley	Pin	Sit	Bumpy	Rest	Candy
Climb	Eye	Legs	Road	Awake	Sugar
Summit	Sewing	Seat	Tough	Tired	Bitter
Top	Sharp	Couch	Sandpaper	Dream	Good
Molehill	Point	Desk	Jagged	Wake	Taste
Peak	Prick	Recliner	Ready	Snooze	Tooth
Plain	Thimble	Sofa	Coarse	Blanket	Nice
Glacier	Haystack	Wood	Uneven	Doze	Honey
Goat	Thorn	Cushion	Riders	Slumber	Soda
Bike	Hurt	Swivel	Rugged	Snore	Chocolate
Climber	Injection	Stool	Sand	Nap	Heart
Range	Syringe	Sitting	Boards	Peace	Cake
Steep	Cloth	Rocking	Ground	Yawn	Tart
Ski	Knitting	Bench	Gravel	Drowsy	Pie

After their recall of the sixth list, we assessed their false memory “recognition” by giving them a piece of paper that has 42 words on it. Of these 42 words, 12 words were words that they studied from one of the previous six lists. However, 30 were non-studied words. Among the 30 non-studied words, 6 were critical words/lures from which the lists were generated (e.g., sleep), 12 were unrelated to any of the items on the list, and 12 were related to the words on the lists (2 per list). The 42 items were subdivided into 6 blocks, with each block consisting of 7 items. Each block included 2 studied words, 2 related words, 2 unrelated words, and the critical non-studied word/lure. For each of the 42 items, they were asked to rate the item on a 4-point scale, including the following response options: 4 for sure that they item was old (studied); 3 for probably old, 2 for probably new, and 1 for sure it was new.

Other assessments

A few brief surveys were completed by each participant at the beginning of the visit, which included a self-reported moderate-to-vigorous physical activity (MVPA) assessment (MVPA min/week) (Greenwood, Joy, & Stanford, 2010) and a mood state survey (Positive and Negative Affect Schedule (PANAS)) (Watson, Clark, & Tellegen, 1988). Regarding the PANAS (Watson et al., 1988), participants rated 20 items (e.g., excited, upset, irritable, attentive) on a Likert scale (1, very slightly or not at all; to 5, extremely), with half of the items constituting a “positive” mood state, with the other half being a “negative” mood state. In this sample, for the positive and negative mood states, respectively, Cronbach’s alpha was 0.85 and 0.82. For potential confounding purposes, we assessed these variables to determine the similarities of these parameters across the experimental and control groups.

Statistical analysis

All statistical analyses were computed in Stata (v. 12). A 2 (group) × 4 (time) repeated measures ANOVA was computed for the PM assessment. A 2 (group) × 6 (time) repeated measures ANOVA was computed for the number of correctly recalled words from the false memory task. An independent t-test was computed comparing the number of recalled false words across the two groups. Finally, a 2 (group) × 6 (time) repeated measures ANOVA was computed for the recognition of the false memory of the six critical words. Statistical significance will be set at a nominal alpha of 0.05.

Results

Table 1 displays the words used for the false memory task. Table 2 displays the characteristics of the sample across the experimental (exercise) and control groups. These two groups were similar regarding demographic (e.g., age, gender, race-ethnicity), behavioral (e.g., habitual physical activity behavior), physiological (i.e., similar resting heart rate), and psychological (i.e., mood state) parameters.

Table 2.

Characteristics of the sample.

Variable	Exercise	Control
N	25	26
Age, mean years	20.4 (0.2)	20.5 (0.1)
Female, %	72.0	73.1
White, %	72.0	80.7
Waist circumference, mean cm	86.8 (2.4)	80.4 (2.2)
Resting HR, bpm	81.7 (2.4)	76.8 (2.5)
End of Exercise HR, bpm	115.1 (2.6)	–
Treadmill Speed, mean MPH	3.5 (0.1)	–
MVPA, mean min/week	294.4 (46.0)	313.6 (43.0)
Mood, Mean Positive	29.3 (1.3)	30.5 (1.3)
Mood, Mean Negative	12.8 (0.7)	13.0 (0.9)

Note: BPM: beats per minute; HR: heart rate; MPH: miles per hour; MVPA: moderate-to-vigorous physical activity.

Table 3 displays the performance scores on the PM tasks. There were no statistically significant differences in PM performance based on group allocation (F_Group×Time = 1.17; P = 0.32; η²= 0.06). Table 4 displays the number of words correctly recalled from each list of the false memory task, as well as the number of recalled false words. There were no group differences in the number of words correctly recalled from the six lists (F_Group×Time = 1.10; P = 0.35). Although the exercise group (2.4) recalled fewer number of false words than the control group (2.9), this was not statistically significant (t = 1.3; P = 0.17). Finally, Table 5 displays the recognition of false memory for the six critical words. The 2 (group) × 6 (time) repeated measures ANOVA was statistically significant (F_Group×Time = 3.15; P = 0.01; η²= 0.26). Post-hoc tests indicated that the exercise group, compared with the control group, were less likely to rate the “needle,” “rough,” and “sleep” lure/critical words as a studied word. That is, the control group was more likely to have a false memory for these words.

Table 3.

Performance on prospective memory.

	Short-term		Long-term		F_Group×Time	P_Group×Time	η²
	Time	Event	Time	Event	1.17	0.32	0.06
Exercise	1.7 (0.2)	2.3 (0.2)	1.2 (0.3)	1.8 (0.3)
Control	2.6 (0.2)	2.8 (0.1)	1.3 (0.3)	2.0 (0.3)

Note: A 2 (group) × 4 (time) ANOVA was computed. F_Group×Time = F-value for the Group × Time interaction; P_Group×Time = P-value for the Group × Time interaction; η²= Effect size estimate (partial eta-squared).

Table 4.

Recall number of correct and false items.

	Number of words correctly recalled from each list						F_Group×Time P_Group×Time	No. of recalled false words	T-value P-value
Group	List 1	List 2	List 3	List 4	List 5	List 6	F_Group×Time = 1.10 P_{Group×Time =}0.35	No. of recalled false words	T = 1.3 P = 0.17
Exercise	6.9 (0.3)	5.9 (0.3)	7.1 (0.3)	6.2 (0.4)	6.7 (0.3)	7.2 (0.4)		2.4 (0.2)
Control	6.9 (0.3)	6.5 (0.3)	7.5 (0.4)	6.5 (0.3)	6.8 (0.3)	6.6 (0.3)		2.9 (0.2)

Note: A 2 (group) × 6 (time) ANOVA was computed. F_Group×Time = F-value for the Group x Time interaction; P_Group×Time = P-value for the Group x Time interaction; T-Value is the calculated t-value for an independent t-test comparing the # of recalled false words across the two groups.

Table 5.

Recognition of false memory for the six critical words.

Group	Mountain	Needle	Chair	Rough	Sleep	Sweet	F_Group×Time	P_Group×Time	η²
Exercise	3.2 (0.1)	3.4 (0.2)	4.0 (0.0)	3.8 (0.1)	3.4 (0.2)	3.7 (0.1)	3.15	0.01	0.26
Control	3.2 (0.2)	3.7 (0.1)	3.7 (0.2)	4.0 (0.0)	3.6 (0.2)	3.7 (0.1)

Note: A 2 (group) × 6 (time) ANOVA was computed. F_Group×Time = F-value for the Group _× Time interaction; P_{Group × Time} = P-value for the Group × Time interaction; η²= Effect size estimate (partial eta-squared). For each of the critical items, participants rated the item on a 4-point scale, including the following response options: 4 for sure that they item was old (studied); 3 for probably old, 2 for probably new, and 1 for sure it was new.

Discussion

Previous work indicates that, for example, acute exercise is associated with explicit- (Crush & Loprinzi, 2017; Frith et al., 2017; Loprinzi, Edwards, et al., 2017; Loprinzi, Frith, et al., 2017; Loprinzi & Kane, 2015; Sng et al., 2018) and implicit-related (Loprinzi & Edwards, 2018) episodic memory function. However, limited research has examined the effects of acute exercise on PM function (Frith et al., 2017; Sng et al., 2018), with no studies examining the effects of acute exercise on false memory. The present study addresses these gaps in the literature. The findings of this study confirm the null effects of exercise on PM, but provide some suggestive evidence that acute exercise may help to reduce false memories.

Given the null effects of acute exercise on PM in the present experiment as well as in our two previous experiments, we limit this discussion to addressing the potential effects of acute exercise in reducing false memories. However, before abandoning the possibility that acute exercise may subserve PM, future work may wish to consider, for example, utilizing more objective measures of PM (computerized tests) and examining this topic in other populations (e.g., older adults).

Regarding our observed association between acute exercise and false memory, this effect should be interpreted cautiously. In both groups (exercise and control), there was a high rate of false memories (similar to other work; Payne, Nadel, Allen, Thomas, & Jacobs, 2002), demonstrating credence of the measure we used. Such a high rate of false memories is not unexpected, as the exposure of the semantically related words may cause the activation of the related lure word, which may leave the participant thinking that the lure word was previously presented during the encoding task. This “source monitoring” problem aligns with our results shown in Table 5; the mean estimate across the entire sample ranged from 3.2 to 4 (possible range is 0–4), with a “4” indicating that the participant was sure that the item/word was old (i.e., that they heard that specific word).

Given that the present study is the only study, to our knowledge, to examine the effects of acute exercise on false memories, future confirmatory work is needed. If such work confirms a beneficial effect of acute exercise on reducing false memories, then investigation into the underlying mechanisms would be warranted. It is not clear as to how acute exercise may, potentially, reduce false memories. This stems from the fact that the etiology of false memories is multi-fold and may vary based on the population studied (e.g., age-group (Devitt & Schacter, 2016) or whether a neurological disorder is present (Fairfield et al., 2016; Fairfield, Colangelo, Mammarella, Di Domenico, & Cornoldi, 2017)). Further, human studies using behavioral and functional magnetic resonance imaging techniques have not been able to identify the brain regions and circuits responsible for generating false memories. Two potential candidates that may help to reduce the generation of false memories is the prefrontal cortex and hippocampus. The hippocampus plays an important role in binding together elements of a contextual situation that make up an episodic memory (Nadel, 1991; Nadel & WIllner, 1980). The prefrontal cortex also plays a role binding elements, possibly as a result of modulating hippocampal processing or directly influencing source monitoring (Rugg, Fletcher, Chua, & Dolan, 1999). Through its impact on the hippocampus and prefrontal cortex (Chang et al., 2011; Loprinzi, Edwards, et al., 2017; Tsujii, Komatsu, & Sakatani, 2013), acute exercise may enhance an individual’s ability to encode contextually specific information (reactivate verbatim memory traces and minimize the reactivation/overreliance of gist traces (Brainerd & Reyna, 2002)), and thus, potentially help to minimize false recognition of words.

In conclusion, in this study, we examined the potential effects of acute exercise on PM and false memory. We did not observe an association between exercise and PM, but provide some evidence to suggest that acute exercise may help to reduce false memories from a word-list task. Future work examining these underinvestigated lines of inquiry are warranted.

Footnotes

Article Notes

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