This article was downloaded by: [University of Southern Queensland] On: 05 October 2014, At: 07:55 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Sports Sciences Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjsp20

Isometric exercise and cognitive function: an investigation of acute dose–response effects during submaximal fatiguing contractions a

Denver M. Y. Brown & Steven R. Bray

a

a

Department of Kinesiology, McMaster University, Hamilton, Ontario, L8S 4K1 Canada Published online: 26 Sep 2014.

To cite this article: Denver M. Y. Brown & Steven R. Bray (2014): Isometric exercise and cognitive function: an investigation of acute dose–response effects during submaximal fatiguing contractions, Journal of Sports Sciences, DOI: 10.1080/02640414.2014.947524 To link to this article: http://dx.doi.org/10.1080/02640414.2014.947524

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

Journal of Sports Sciences, 2014 http://dx.doi.org/10.1080/02640414.2014.947524

Isometric exercise and cognitive function: an investigation of acute dose–response effects during submaximal fatiguing contractions

DENVER M. Y. BROWN & STEVEN R. BRAY Department of Kinesiology, McMaster University, Hamilton, Ontario, L8S 4K1 Canada

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

(Accepted 19 July 2014)

Abstract The purpose of this study was to explore the dose–response relationship between exercise and cognitive performance using an acute bout of isometric exercise. University students (N = 55) were randomly assigned to control, 30%, 50% and 70% of maximum voluntary handgrip contraction groups. Participants performed a modified Stroop task before and after completion of an isometric handgrip endurance trial at their assigned exercise intensity. Ratings of perceived exertion (RPE) and forearm muscle activation (EMG) showed linear trends of progressively greater RPE and muscle activation at greater exercise intensity levels. Regression analysis showed significant (P < .05) linear degradations in frequency of errors on the Stroop task with increasing exercise intensity. We conclude that performing isometric exercise until exhaustion is associated with reduced cognitive performance and that higher intensity isometric exercise leads to greater performance impairments in a linear dose–response manner. Keywords: isometric exercise, cognitive performance, executive functioning

Introduction Cognitive abilities are critical to most behaviours of daily living and an integral component of health-related quality of life (Williams & Kemper, 2010). As such, understanding factors that preserve, enhance or impair cognitive functioning is a shared goal across domains of psychological, exercise and health sciences. One factor that has captured considerable research attention in relation to cognitive functioning is physical exercise, with major streams of evidence emerging relating to chronic (i.e., long-term training), acute (i.e., short-term training) and lifestyle effects of exercise on cognitive functioning (Hillman, Erickson, & Kramer, 2008). The focus of the present study is on acute effects of a brief session of exercise on cognitive performance. Studies investigating acute effects of exercise on cognitive functioning have typically involved performance of cognitive function tests either during or shortly after a session of exercise. The results of those studies have been mixed; however, narrative reviews (e.g., Brisswalter, Collardeau, & René, 2002; Fox, 1999; McMorris & Graydon, 2000; Tomporowski, 2003) suggest exercise has a facilitative effect on acute cognitive functioning. Recent

meta-analyses support these findings, demonstrating a small positive effect of exercise on cognitive performance (Chang, Labban, Gapin, & Etnier, 2012; Lambourne & Tomporowski, 2010; McMorris & Hale, 2012). While there is some general consensus about the overall size of the effects, the narrative and quantitative reviews also indicate that several factors may be important effect modifiers. Some of the major factors that appear to influence the magnitude of the exercise–cognitive function relationship include the dose (i.e., mode, intensity and duration of the exercise), response (i.e., cognitive functions required by the cognitive tests) and timing of the administration of cognitive testing relative to the performance of the exercise (i.e., during, proximal or distal). For example, one way in which exercise intensity has been found to moderate the exercise– cognitive performance relationship is when performances on executive function tasks are assessed immediately following exercise. According to Chang et al.’s (2012) meta-analysis, small positive effects are evident at very light, light and moderate intensities, whereas effects are null for hard intensity exercise and drift towards small negative effects for very hard and maximal intensity

Correspondence: Denver M. Y. Brown, Department of Kinesiology, McMaster University, 1280 Main St W., Hamilton, Ontario, L8S 4K1 Canada. E-mail: [email protected] © 2014 Taylor & Francis

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

2

D. M. Y. Brown & S. R. Bray

exercise, suggesting that exercising at high intensity levels or to exhaustion or task failure results in impaired cognitive performance. The majority of studies examining the dose– response relationship between acute exercise and cognitive performance have incorporated aerobic exercise tasks involving cycling or running (e.g., Arent & Landers, 2003), with some recent studies also investigating resistance exercise (e.g., Chang & Etnier, 2009a, 2009b). Results of those studies support a positive linear relationship between exercise intensity and cognitive performance of simple stimulus-response tasks requiring little or no central executive processing such as simple reaction time task (e.g., Arent & Landers, 2003). In contrast, evidence supports an inverted-U relationship for tasks of greater cognitive complexity that involve executive functions (Miyake et al., 2000) such as task switching, memory updating and response inhibition (e.g., Chang & Etnier, 2009a, 2009b; Sibley, Etnier, & Le Masurier, 2006). Although aerobic and resistance exercise are common modes of exercise and merit the attention of research on the exercise–cognitive function relationship, one form of exercise that has not yet received research attention is isometric exercise. Isometric exercise involves the application of muscle force without movement of a joint (Powers & Howley, 2012). While dynamic forms of exercise (aerobic or resistance) typically comprise athletic training regimens and public health recommendations for exercise behaviour (e.g., Canadian Society for Exercise Physiology, 2013; U.S. Department of Health and Human Services, 2008), isometric exercise has been shown to increase muscular strength (Folland, Hawker, Leach, Little, & Jones, 2005) and results in physiological responses (e.g., changes in hemodynamic, neuroendocrine and metabolic processes) similar to, or greater than, those activated by aerobic and resistance exercise (Ahlborg et al., 1972; Kozlowski, Brzezinska, Nazar, Kowalski, & Franczyk, 1973; Smolander et al., 1998). Furthermore, isometric exercise training has been shown to have significant therapeutic effects for lowering blood pressure among healthy older adults and people with hypertension (Kelley & Kelley, 2010; Millar, McGowan, Cornelissen, Araujo, & Swaine, 2013) and improving tolerance of pain in healthy participants (Hoeger Bement, Dicapo, Rasiarmos, & Hunter, 2008) and patients with fibromyalgia (Staud, Robinson, & Price, 2005). Thus, given the physiological responses associated with isometric exercise are among those theorised to account for the acute effects of exercise on cognitive function (McMorris, Tomporowski, & Audiffren, 2009) and the potential for isometric exercise to affect other positive health outcomes, the effects of isometric

exercise on cognitive function warrants research attention. The purpose of this study was to investigate the effects of isometric exercise on cognitive performance. Specifically, performance on a test of central executive function (modified Stroop task) prior to a session of isometric exercise was compared to performance following the exercise. We further investigated this general effect in terms of a dose– response relationship using varying intensities of isometric exercise performed to task failure. No prior research has investigated either general or dose–response relationships associated with isometric exercise and cognition. Based on prior research using cardiovascular and resistance exercise manipulations, it was predicted that cognitive performance should improve following moderate intensity exercise but show lesser improvements at lower and higher intensity levels (i.e., a curvilinear, inverted-U, relationship).

Method Participants and design The sample (N = 55; Mage = 20.58, SD = 2.20) consisted of volunteer university students (60.0% women). Volunteers were screened through an email questionnaire for cardiac, neurological, respiratory, orthopaedic, cognitive or vision problems prior to participation in the study to ensure there were no contraindications preventing them from performing maximal isometric handgrip exercise or a colour-word naming task. The study was a single-blind randomised controlled experiment. Participants were randomised to one of four experimental conditions of varying exercise load: low intensity (30% of maximum voluntary contraction: MVC; n = 14), moderate intensity (50% of MVC; n = 13), high intensity (70% of MVC; n = 14) or control (5 Newtons [N]; n = 14) using a 4 (condition) × 2 (pre-post) mixed design. The study protocol was approved by the authors' institutional research ethics board.

Measures Demographics and physical activity history. Participants completed a paper and pencil survey indicating their age, gender and student status. They also completed the Godin Leisure Time Exercise Questionnaire (Godin & Shephard, 1985) to assess their typical weekly engagement in mild, moderate and vigorous intensity exercise as well as a single-item question assessing their typical weekly engagement in resistance exercise.

Isometric exercise & cognitive performance

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Exercise Intensity Manipulation Checks Ratings of perceived exertion (RPE). Participants verbally reported their subjective perceptions of physical exertion using Borg’s RPE scale (Borg, 1982). The scale provides participants with a continuum of exertion ratings ranging from 0 (no exertion at all) to 10 (maximal exertion). Participants provided RPE ratings at 5-second intervals throughout the endurance contractions, which were averaged across the handgrip-squeezing session to provide the measure RPEAVERAGE. The final RPE rating prior to termination of the trial was also recorded as RPEMAX. These manipulation checks were administered in order to assure participants in each of the experimental groups held their endurance contractions to a point of maximal exertion. Proportional EMG amplitude. Surface EMG activity of the hand and wrist flexors was monitored throughout the endurance handgrip squeezing trial as a physiological measure of exercise intensity. Skin was cleaned and abraded on the forearm, and disposable surface electrodes were placed roughly 2 cm apart on the muscle belly of the flexor carpi radialis. A reference electrode was placed over the bony prominence on the medial epicondyle of the humerus at the elbow. The surface EMG signal was amplified, digitised and continuously streamed using a PowerLab ML870 data acquisition system (ADInstruments, Colorado Springs, CO) to a PC at 4000 Hz. To compute the proportional EMG amplitude scores, the EMG signal was then bandpass filtered from 20 to 500 Hz, full wave rectified and smoothed with a 0.5-second moving average and normalised (i.e., as a percentage) to pre-trial MVC values over a series of five, 2-second epochs at the start, 25%, 50%, 75% and end of the endurance trial. All EMG processing was performed using LabView software (National Instruments, Austin, TX). Mood. Participants completed the 16-item Brief Mood Introspection Scale (BMIS) (Mayer & Gaschke, 1988) to measure their state affect and arousal levels. Participants responded to each of 16 adjective items on a 1 (definitely do not feel) to 7 (definitely do feel) Likert-type scale. The items were scored according to separate factors that provide summary scores representing pleasant – unpleasant affect and high – low arousal levels. Modified Stroop task. The main dependent variable of interest was cognitive performance, which was assessed by changes in response rate (speed) and frequency of response errors committed during two 5-minute tests using a modified Stroop task (Wallace

3

& Baumeister, 2002). The modified Stroop task required participants to read aloud from a list of printed words that were mismatched with the ink colour in which they were printed (e.g., the word “black” was printed in “pink” ink). Participants were instructed to say aloud the colour of the ink in which the word was printed and ignore the printed word (e.g., for the word “black” printed in “pink” ink, they would say aloud the word “pink”). This element of the task requires executive function in terms of response inhibition (i.e., inhibiting the dominant response of reading the word and replacing it with the subordinate response of naming the ink colour). A secondary feature of the modified Stroop task was the inclusion of a superordinate rule that required the participant to override the general instruction when they encountered words printed in “red” ink. In these cases, participants were instructed to read aloud the printed word (e.g., for the word “black” printed in red ink, they would say aloud the word “black”). This additional task element requires working memory and shifting between mental sets, thus, furthering the demands on this central executive process (Miyake et al., 2000). The Stroop colour word stimuli were presented in two columns, each consisting of 26 words, on printed sheets of 8.5″ × 14″ paper. Participants were instructed to start with the left column and to work down the column before moving to the right column. After the last word on the page, participants were given another sheet with an additional set of words and instructed to keep reading for a total duration of 5 minutes. When an error was incurred, the experimenter would say “incorrect”, identify the stimulus that resulted in the error and instruct the participant to continue. The total number of words read aloud during the 5-minute trial and the number of errors made was recorded for each of two test trials. The average response speed for each test session was calculated by dividing the number of trials completed by 300 (total seconds). The difference in response speed was calculated by subtracting the average response speed during the first session from the average response speed during the second session. The difference in error frequency was calculated by subtracting the number of errors committed during the first session from the number made during the second session. A further composite measure, the relative error frequency, was computed as the number of errors committed during each session as a function of the number of trials completed. The difference in relative error frequency was then calculated by subtracting the relative error frequency for the first session from the relative error frequency from the second session.

4

D. M. Y. Brown & S. R. Bray

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Manipulations Isometric handgrip exercise. Participants performed one maximum endurance isometric handgrip exercise trial generating and maintaining a contractile force at 30%, 50% or 70% of their MVC. For the control condition, participants performed a nominal isometric handgrip contraction, maintaining a squeezing force of 5 N for a pre-defined interval of 4 minutes. The intention of the control condition was not to elicit fatigue, instead, it served as a sham exercise condition that required participants maintain their focus keeping contractile force at the required target level with minimal energy expenditure due to exercise. All handgrip exercises were performed using an isometric handgrip dynamometer (model MLT003/D; ADInstruments) with graphic computer interface (PowerLab 4/25 T; ADInstruments, CO). In order to determine the target force values required for the isometric handgrip task, each participant performed two 4-second MVCs on the dynamometer to determine their maximum force generation. A maximum force generation value (N) was calculated using the mean force generation value during a 1-second epoch at the peak of the greater MVC. This value served as the criterion upon which the 30%, 50% or 70% submaximal force tasks were calculated. To perform the endurance exercise contractions, participants squeezed the handgrip dynamometer and were provided feedback on a 17″ computer monitor in the form of a force tracing (i.e., a realtime graphed line indicating how much force was being generated). The target force level (e.g., 30% of MVC) was shown as a static line on the screen. Participants were instructed to maintain the handgrip squeeze for as long as possible that kept the force tracing line just above or within a narrow range of the target level (10 N). When the force tracing fell below the target MVC level, participants received a verbal prompt to “squeeze harder so the tracing stays at the target level”; when the tracing fell below the criterion range for longer than 2 second, the experimenter signalled to the participant that the trial was complete. The feedback monitor was set up so that participants had no knowledge of elapsed time or the magnitude of force generation during the endurance trials (other than whether they were maintaining their force at or above the target force line).

Procedure Upon arrival in the laboratory, participants were given a description of the study procedures and provided informed consent. They then completed a demographic survey and were fitted with EMG

recording electrodes. Participants then performed the baseline modified Stroop task and then performed two 100% MVC handgrip squeezes in order to establish maximum grip strength (peak MVC). Each MVC lasted 4 seconds and was separated by 1 minute of rest. Participants were then randomised (stratified by gender), using a random number generator (http://www.random.org/integers/), to one of the control (n = 14), 30% (n = 14), 50% (n = 13) or 70% (n = 14) exercise intensity conditions, rested for 2 minutes during equipment adjustment and calibration, and then performed the endurance handgrip task. During the endurance task, participants were asked to rate their level of perceived exertion using the RPE scale at 5-second intervals until completion of the task. After the endurance handgrip task, participants completed the BMIS. Participants then rested for 1 minute and completed the second modified Stroop task for 5 minutes. Participants were then debriefed, thanked and given a $5 honorarium for participating in the study. Data analysis The effects of the study manipulations (i.e., Mean RPE, Peak RPE, Peak MVC) were assessed using one-way ANOVAs. Proportional EMG amplitude scores were analysed using a 4 (group) × 5 (time) mixed ANOVA. To evaluate the main hypothesis of the effects of isometric exercise on cognitive performance, separate univariate ANOVAs as well as regression analyses were computed to evaluate dose–response relationships for changes in response speed, error frequency and relative error frequency. Following procedures suggested by Cohen, Cohen, West, and Aiken (2003) for testing curvilinear relationships using multiple regression, linear and quadratic regression equations were computed using mean-centred values for exercise intensity. All statistical analyses were performed using IBM SPSS version 20. Results Preliminary analyses were conducted to assess group equivalence and the effectiveness of the randomisation protocol. ANOVA showed no significant differences in mean age across groups, F3,51 = 2.7, P > 0.05. Separate ANOVAs for each of the Godin Leisure Time Exercise Questionnaire exercise intensities showed no differences between groups in exercise history for light, F3,51 = 0.19, P > 0.05, moderate, F3,51 = 0.07, P > 0.05, or vigorous exercise, F3,51 = 0.33, P > 0.05. There were also no between-group differences in frequency of resistance exercise, F3,51 = 1.55, P > 0.05.

5

Isometric exercise & cognitive performance

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Manipulation checks Mean RPE (RPEAVERAGE) values from the endurance handgrip trial are presented, by condition, in Table I. Results of a univariate ANOVA showed a significant between-group difference, F3,51 = 72.56, P < 0.001. Post-hoc planned contrasts revealed significant (P < 0.001) differences between the control group and each of the 30%, 50% and 70% contraction conditions. Differences between the 50% group and the 30% or 70% groups and the 30% and 70% groups did not reach significance (all P > 0.05). Peak RPE values are also presented in Table I. With the exception of the control group, all groups reported RPEPEAK of > 9.5/10. A significant univariate ANOVA, F3,51 = 452.80, P < 0.001, with simple contrast follow-up tests showed all training groups differed from the control group, but training groups did not differ from one another (all P > 0.05). Peak MVC values, presented in Table I, were analysed using one-way ANOVA. There were no differences (P > 0.05) between groups in muscle force generation. Time to failure values are also presented in Table I. Between-groups ANOVA showed all groups differed from one another (P < 0.01), with progressively longer time to failure durations across the 70%, 50%, 30% and control groups, respectively. Mean values for the BMIS are presented by condition in Table I. Pleasant-unpleasant and arousal-calm scales were calculated as outlined by Mayer and Gaschke (1988). Results of separate univariate ANOVAs showed no significant between-group differences for the pleasant–unpleasant (P = 0.404) and arousal–calm scales (P = 0.092). The proportional EMG amplitude scores, displayed in Figure 1, were analysed using a 4 (group) × 5 (time) mixed ANOVA. Results showed significant main effects for group, F3,51 = 22.21, P < 0.001, time, F4,50 = 21.67, P < 0.001, and the group × time interaction, F12,50 = 3.71, P < 0.001. Post-hoc contrasts of the group effect showed results consistent with greater muscle motor unit

Figure 1. Proportional muscle activation during isometric handgrip contraction.

recruitment at escalating exercise intensities. Specifically, there were significant (all P < 0.05) differences in mean proportional EMG values between all groups with the exception of the contrast between the 30% and 50% contraction groups (P = 0.181). To summarise, the results of the preliminary analyses and manipulation checks showed no differences between groups for age, exercise history, peak MVC or mood/arousal following the exercise tests, indicating none of these factors should influence the cognitive performance findings. The RPEAVERAGE, time to failure and proportional EMG results corroborated our intended manipulations, showing linear trends of progressively and, in most cases, significantly greater RPE and muscle activation at greater exercise intensity levels and significantly shorter time to failure with higher exercise intensity.

Cognitive performance Mean values for Stroop task performance variables are presented, by condition, in Table II. Raw change scores were computed separately for average response speed, error frequency and relative error frequency. Separate univariate ANOVAs were

Table I. Peak maximum voluntary contraction (MVC), time to task failure (TTF), ratings of perceived exertion (RPE), mood and arousal by condition. Experimental group Variable Peak MVC TTF (seconds) RPEAVERAGE RPEPEAK BMISPLEASANT–UNPLEASANT BMISAROUSAL–CALM

30% MVC (n = 14) 291.98 163.14 6.77 9.96 78.08 40.92

(95.84)a (36.74)a (1.68)a (0.13)a (15.92)a (8.12)a

50% MVC (n = 13) 300.25 74.38 7.04 10.00 78.41 39.77

Note: Values that do not share subscript are different at P < 0.05. P < 0.001.

(88.57)a (24.87)b (1.17)a (0.00)a (16.06)a (8.29)a

70% MVC (n = 14) 297.16 45.45 7.32 9.82 84.36 37.36

(122.93)a (19.03)c (1.21)a (0.37)a (11.13)a (4.27)a

Control (n = 14) 323.61 240.0 1.25 2.14 85.77 44.31

(120.10)a (0)d (0.89)b (1.29)b (14.14)a (6.85)a

F 0.23 186.13* 72.56* 452.80* 0.99 2.27

6

D. M. Y. Brown & S. R. Bray Table II. Change in response speed and total errors across two sessions of modified Stroop task by condition. Experimental group

Variable

30% (n = 14)

50% (n = 13)

70% (n = 14)

Control (n = 14)

F

Change in response speed (seconds) Change errors Change in relative error frequency (%)

−0.11 (0.06)a −1.64 (7.71)b −1.22 (2.98)a,b

−0.13 (0.08)a −3.92 (9.09)a,b −2.57 (4.04)a,b

−0.15 (0.06)a −0.79 (4.14)b −0.55 (1.63)b

−0.14 (0.06)a −7.50 (6.81)a −3.33 (2.47)a

1.14 3.42** 2.66*

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Notes: Values that do not share a common subscript are different at P < 0.05. Negative values represent improvements in performance from Time 1 to Time 2. *P = 0.05, **P < 0.05.

computed to assess differences between the means for each variable. As evident in Table II, all groups showed improvements in response speed (i.e., greater number of trials completed in 5 minutes) on the Stroop task from Time 1 to Time 2, with no differences between groups, F3,51 = 1.14, P = 0.340. Results presented in Table II also reveal varying levels of performance across groups in error frequency with larger improvements (i.e., fewer errors) in the control group compared to the exercise groups at Time 2 compared to Time 1. A one-way ANOVA showed this effect was significant, F3,51 = 3.42, P = 0.024. Post-hoc simple contrasts between the condition means (see Table II subscripts) indicated the control group differed significantly from the 70% (P = 0.003) and 30% exercise conditions (P = 0.034), but no other significant differences between conditions. Large effect sizes (Cohen’s d) were observed between the control condition and both the 70% MVC (d = 1.47) and 30% MVC conditions (d = 0.77). Medium effect sizes were seen between the 50% and 70% MVC (d = 0.67) and control vs. 50% MVC conditions (d = 0.45). Small effects were found between the 30% vs. 50% MVC (d = 0.37) and 30% vs. 70% MVC conditions (d = 0.28). Analysis of the change in relative error frequency scores (Table II) revealed a non-significant overall trend, F3,51 = 2.66, P = 0.058. Post-hoc simple contrasts between the condition means (see Table II subscripts) indicated the control group significantly differed from the 70% MVC condition (P = 0.014) and demonstrated a non-significant difference from the 30% MVC condition (P = 0.059), but no other differences between the condition means were significant (all P > 0.05). Large effect sizes between the control and both the 70% MVC (d = 1.33) and 30% MVC conditions (d = 0.80). Medium effect sizes were revealed between the 50% and 70% MVC (d = 0.66) and the 30% and 70% conditions (d = 0.39). Small effect sizes were seen between the 30% and 50% (d = 0.33) and control vs. 50% MVC conditions (d = 0.27). Separate regression analyses (regressing change scores on exercise intensity conditions) were

computed to evaluate dose–response relationships for response speed, frequency of errors and relative error frequency. Following procedures suggested by Cohen et al. (2003) for testing curvilinear relationships using multiple regression, linear and quadratic regression equations were computed using meancentred values for exercise intensity. The regression predicting the change in frequency of errors produced a significant result for the linear (B = 0.11, SEB = 0.04), F1,53 = 7.258, P = 0.009, R2adj = 0.104; however, the quadratic effect was not significant (P = 0.755). These results, showing dose– response trends in error frequency with increasing exercise intensity, are presented graphically in Figure 2. The regression predicting change in relative error frequency produced a significant result for the linear equation (B = 0.03, SEB = 0.02), F1,53 = 4.26, P = 0.044, R2adj = 0.057, with no significant effect for the quadratic equation (P = 0.898). These results, showing dose–response trends in error frequency with increasing exercise intensity, are presented graphically in Figure 3. The regression model predicting response speed produced no significant results for linear, F1,53 = 0.85, P = 0.361, R2adj = ‒0.003, or quadratic trends, F2,52 = 1.41, P = 0.168, R2adj = 0.05. Discussion Prior research on the acute effects of exercise on cognitive performance has primarily utilised aerobic (cardiovascular) or resistance exercise tasks (Chang et al., 2012). The present study was the first to investigate the acute effects of isometric exercise on cognitive performance following the exercise task. Results showed that performing a brief bout of isometric handgrip exercise was associated with reductions in cognitive performance on a modified Stroop task when compared to a nominal exercise control condition. Linear trends further revealed a dose– response relationship with reductions in cognitive performance (relative to controls) following higher intensity doses of isometric handgrip exercise. In this study, we focused on changes in cognitive performance on a modified Stroop task across two

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Isometric exercise & cognitive performance

7

Figure 2. Change in total error frequency.

Figure 3. Change in relative error frequency.

tests separated by isometric handgrip exercise at various intensity loads. In the overall sample there was a significant improvement in response speed for Stroop task performance, with all groups performing more trials in the same amount of time on the second test compared to the first. These findings provide evidence of improvements in cognitive performance speed for this task and are consistent

with a learning or practice effect for the Stroop task that has been observed in other studies (Davidson, Zacks, & Williams, 2003; Edwards, Brice, Craig, & Penri-Jones, 1996). Importantly, analyses showed there were no differences between the groups in response speed changes over time. Thus, these results support an interpretation that increases in response speed that may have been associated with

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

8

D. M. Y. Brown & S. R. Bray

the exercise stimuli did not have an effect over and above what might be expected from a learning effect, which was also seen in the control condition. Although cognitive performance as represented by response speed demonstrated consistent improvement across all conditions, error frequency did not. That is, there was a linear gradient evident in the error response scores with virtually no change in error frequency in the high-intensity group and a large reduction in errors in the nominal exercise control condition. Errors on the modified Stroop task are indicative of inabilities to inhibit either the prepotent response to read the word colour and, in its place, say aloud the colour of the ink or to inhibit the supraordinate response to say aloud the ink colour and say aloud the word colour (i.e., only in the case of words in “red” ink). Our results suggest that rather than improving cognitive performance, engaging in higher levels of isometric exercise intensity may disrupt abilities to inhibit responses and impair executive functioning. As reviewed earlier, narrative and quantitative reviews generally support a small positive effect of exercise on cognitive function; however numerous studies have shown negative effects. For example, in a recent review, McMorris and Hale (2012) presented summary data separating effects for response speed and accuracy. Their results showed an inverted-U pattern of effects with larger positive effects for speed at moderate exercise intensities, but a null relationship between exercise and accuracy. In addition, results from three recent reviews (Chang et al., 2012; Lambourne & Tomporowski, 2010; McMorris & Hale, 2012) revealed consistent findings that illustrate exercising until exhaustion leads to decreases in cognitive performance. In light of these previous findings, the present results are consistent with an interpretation that performing exercise to exhaustion or task failure is associated with impaired cognitive performance and that higher intensity exercise leads to greater impairments in a linear dose–response manner. Although the current findings mesh with other research revealing negative effects of exhaustive or high-intensity exercise on performance of executive function tasks, their interpretation is somewhat ambiguous as theorising has been primarily based on physiological arousal factors associated with large-muscle or whole-body cardiovascular exercise (e.g., McMorris et al., 2009). The handgrip-squeezing task in the present study elicited RPE ratings showing maximum physical effort was invested in the task; however, compared to running or cycling to exhaustion, the energy demands of the task are relatively low. One interpretation that should be considered is that prolonged effort regulation required by the isometric handgrip exercise leads to

depleted self-control strength (Baumeister, Vohs, & Tice, 2007). According to Baumeister and colleagues’ (2007) strength model of self-control, self-control strength is a limited resource that governs one’s abilities to exert executive control over behaviours, emotions and cognitions. However, performing isometric handgrip exercise to exhaustion is among a collection of tests that have been used to demonstrate that prior utilisation of self-control strength on one task leads to performance impairments on subsequent tasks that also require self control or executive function (e.g., Bray, Martin Ginis, Hicks, & Woodgate, 2008; Muraven, Tice, & Baumeister, 1998). Research has shown the self-control depletion effect is robust, with an average effect size of d = 0.62 across 198 observations and studies involving isometric handgrip exercise showing an average effect of d = 0.64 (Hagger, Wood, Stiff, & Chatzisarantis, 2010). The present findings contribute to research on this perspective, suggesting that greater amounts of one’s limited self-control strength may be consumed by performing higher intensity tasks even if those tasks are performed for brief durations. More specifically, participants in the high-intensity (70%) exercise condition held their maximal endurance contractions for only 46 seconds compared to 79 seconds in the 50% condition and 160 seconds in the 30% condition. Thus, our results suggest that although self-control strength may be needed to sustain isometric handgrip contractions at lower intensities, it may be that greater amounts of self-control strength are needed for higher-intensity exercise, even if those contractions are carried out for much shorter durations. As far as we are aware no studies have investigated dose–response issues relating to self-control depletion and the present study may provide the first indication that such relationships exist. Prior research findings of the effects of cardiovascular exercise on cognitive function may also be accounted for by the limited strength perspective. That is, previous findings by Del Giorno, Hall, O’Leary, Bixby, and Miller (2010) show that performing cardiovascular exercise at very high intensity results in decrements of cognitive performance. What stands out in this research is the cognitive tests utilized in this study were dependent upon executive control (i.e., Wisconsin Card Sorting Task, Continuous Contingent Performance Task), whereas cognitive tests that were not negatively affected by maximal exertion exercise were those that were not dependent upon executive control resources (e.g., Stroop Colour Task, Stroop Word Task). This study provides evidence suggesting exercise that demands extreme effort regulation may deplete executive control resources regardless

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Isometric exercise & cognitive performance of the mode of exercise (i.e., cardiovascular; isometric). Although some research has looked at the crossover or carryover effects of cognitive task performance on effortful exercise performance from the strength model perspective (e.g., Bray et al., 2008; Martin Ginis & Bray, 2010), we believe that no studies in the self-control literature have investigated the aftereffects of exercise-related self-control depletion on cognitive self-control. Self-control depletion manipulations involving physical exercise may allow for more comprehensive evaluation of the self-control strength model. For example, the strength model suggests that self-control is dependent on glucose availability in the brain (Gailliott & Baumeister, 2007; Gailliott et al., 2007). The metabolic demands of exercise increase with greater intensity, thus leading to glycogen or glucose depletion (Gollnick, Piehl, & Saltin, 1974; Vøllestad & Blom, 1985). Consequently, exercising at high intensities, even for shorter durations, could affect brain-glucose availability and account for why cognitive performance may be compromised following exhaustive exercise. Alternatively, expending greater effort or resources performing exercise could lead to a reduction in task engagement on subsequent cognitive tasks, which has also been suggested as a mechanism contributing to reduced self-control (cf. Beedie & Lane, 2012). Future research should apply the strength model of self-control to the effects of exercise on performance of cognitive tasks that involve self-control or executive functions. In summary, the findings of this study indicate that performing isometric exercise until exhaustion is associated with small, but significant reductions in cognitive performance. Furthermore, the findings revealed a dose–response relationship with progressively higher intensity contractions leading to greater reductions in cognitive performance (i.e., greater raw and relative error frequency). Contrary to other studies, our results found that isometric exercise had no effect on cognitive processing speed, as all groups (including controls) experienced a similar improvement in response time. The results of this study are consistent with the broader literature examining multiple intensities to establish a linear dose– response relationship between exercise and cognitive performance (Brisswalter, Arcelin, Audiffren, & Delignieres, 1997; Isaacs & Pohlman, 1991; Travlos & Marisi, 1995); however, this was the first study to assess isometric exercise. The current study provides novel findings demonstrating the effects of an acute bout of isometric exercise on cognitive performance; however, it is not without limitations. Our sample was small and consisted of young, healthy university students and therefore may not generalise to other populations

9

such as older adults. Future research should expand investigation of the isometric exercise–cognitive function relationship in a larger, more diverse sample to increase statistical power and generalisability as well as with specialised samples including hypertensive patients, people in injury rehabilitation or older adults among whom isometric exercise may be a functional form of therapy. Additionally, the handgrip task was unfamiliar for participants and, therefore, may have involved cognitive or attentional resources in addition to those demanded by controlling physical effort to perform. While the task was novel to all participants, familiarisation or practice with the exercise task prior to task performance should be considered in future research to provide a more precise indication of the effects associated with exercise. Although exercise was performed to exhaustion in the current study, the task involved a small group of muscles in the forearm. The effects of exhaustive isometric exercise may be more pronounced in larger muscles such as the quadriceps that produce greater force and therefore require greater energy demands. Also, while RPE and muscle activation (EMG) were the measures reflecting arousal levels in the current study, we should acknowledge that RPE is a subjective measure and EMG provides an indication of only the local muscle activation. Thus, our study lacks measurement of central indicators (e.g., heart rate) of arousal. Future research should investigate a combination of subjective, peripheral and central indicators of arousal to determine which factors may best account for the exercise–cognition relationship. Balanced against these limitations, the study also has several strengths. Foremost, it is the first empirical study to investigate a dose–response relationship between exercise and cognitive performance using an isometric exercise task. As noted earlier, isometric exercise has been found to offer numerous therapeutic benefits. Accordingly, researchers or practitioners encouraging isometric exercise should be cognizant that people performing these exercises may experience short-term reductions in cognitive performance. Additionally, we might infer from our findings that people whose occupational activities include performing fatiguing isometric contractions (e.g., manufacturing, construction, military service) may be susceptible to short-term cognitive performance decrements that may have implications for health and safety; especially during their initiation to new workplace demands. The present study focused on acute effects of isometric exercise on cognition; however, future research should also investigate the chronic or training effects of isometric exercise on cognitive function. Research on the hypotensive effects of isometric

10

D. M. Y. Brown & S. R. Bray

exercise shows acute blood pressure elevations following the exercise (McGowan et al., 2006). However, over the course of several weeks, resting and reactive blood pressure is shown to decrease below pre-training values (Millar et al., 2013). Future research should be undertaken to investigate whether isometric exercise training may evoke beneficial adaptations that promote cognitive performance over time.

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

References Ahlborg, B., Bergström, J., Ekelund, L. G., Guarnieri, G., Harris, R. C., Hultman, E., & Nordesjö, L. O. (1972). Muscle metabolism during isometric exercise performed at a constant force. Journal of Applied Physiology, 33, 224–228. Arent, S. M., & Landers, D. M. (2003). Arousal, anxiety, and performance: A reexamination of the inverted-U hypothesis. Research Quarterly for Exercise and Sport, 74, 436–444. Baumeister, R. F., Vohs, K. D., & Tice, D. M. (2007). The strength model of self-control. Current Directions in Psychological Science, 16, 351–355. Beedie, C. J., & Lane, A. M. (2012). The role of glucose in selfcontrol: Another look at the evidence and an alternative conceptualization. Journal of Personality and Social Psychology Review, 16, 143–153. Borg, G. A. V. (1982). Psychophysical bases of perceived exertion. Medicine & Science in Sports & Exercise, 14, 377–381. Bray, S. R., Martin Ginis, K. A., Hicks, A. L., & Woodgate, J. (2008). Effects of self-regulatory strength depletion on muscular performance and EMG activation. Psychophysiology, 45, 337–343. Brisswalter, J., Arcelin, R., Audiffren, M., & Delignieres, D. (1997). Influence of physical exercise on simple reaction time: Effect of physical fitness. Perceptual and Motor Skills, 85, 1019– 1027. Brisswalter, J., Collardeau, M., & René, A. (2002). Effects of acute physical exercise characteristics on cognitive performance. Sports Medicine, 32, 555–566. Canadian Society for Exercise Physiology. (2013). Canadian physical activity guidelines. Retrieved December 4, 2013 from http:// www.csep.ca/CMFiles/Guidelines/CSEP_PAGuidelines_adults_ en.pdf Chang, Y. K., & Etnier, J. L. (2009b). Exploring the doseresponse relationship between resistance exercise intensity and cognitive function. Journal of Sport & Exercise Psychology, 31, 640–656. Chang, Y.-K., & Etnier, J. L. (2009a). Effects of an acute bout of localized resistance exercise on cognitive performance in middle-aged adults: A randomized controlled trial study. Psychology of Sport and Exercise, 10, 19–24. Chang, Y. K., Labban, J. D., Gapin, J. I., & Etnier, J. L. (2012). The effects of acute exercise on cognitive performance: A metaanalysis. Brain Research, 1453, 87–101. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates. Davidson, D. J., Zacks, R. T., & Williams, C. C. (2003). Stroop interference, practice, and aging. Aging, Neuropsychology, and Cognition, 10, 85–98. Del Giorno, J. M., Hall, E. E., O’Leary, K. C., Bixby, W. R., & Miller, P. C. (2010). Cognitive function during acute exercise: A test of the transient hypofrontality theory. Journal of Sport & Exercise Psychology, 32, 312–323. Edwards, S., Brice, C., Craig, C., & Penri-Jones, R. (1996). Effects of caffeine, practice, and mode of presentation on

Stroop task performance. Pharmacology Biochemistry and Behavior, 54, 309–315. Folland, J. P., Hawker, K., Leach, B., Little, T., & Jones, D. A. (2005). Strength training: Isometric training at a range of joint angles versus dynamic training. Journal of Sports Sciences, 23, 817–824. Fox, K. R. (1999). The influence of physical activity on mental well-being. Public Health Nutrition, 2, 411–418. Gailliott, M. T., & Baumeister, R. F. (2007). The physiology of willpower: Linking blood glucose to self-control. Personality and Social Psychology Review, 11, 303–327. Gailliott, M. T., Baumeister, R. F., DeWall, C. N., Maner, J. K., Plant, E. A., Tice, D. M., … Schmeichel, B. J. (2007). Selfcontrol relies on glucose as a limited energy source: Willpower is more than a metaphor. Journal of Personality and Social Psychology, 92, 325–336. Godin, G., & Shephard, R. J. (1985). A simple method to assess exercise behavior in the community. Canadian Journal of Applied Sport Sciences, 10, 141–146. Gollnick, P. D., Piehl, K., & Saltin, B. (1974). Selective glycogen depletion pattern in human muscle fibres after exercise of varying intensity and at varying pedaling rates. The Journal of Physiology, 241, 45–57. Hagger, M. S., Wood, C., Stiff, C., & Chatzisarantis, N. L. D. (2010). Ego depletion and the strength model of self-control: A meta-analysis. Psychological Bulletin, 136, 495–525. Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience, 9, 58–65. Hoeger Bement, M. K., Dicapo, J., Rasiarmos, R., & Hunter, S. K. (2008). Dose response of isometric contractions on pain perception in healthy adults. Medicine & Science in Sports & Exercise, 40, 1880–1889. Isaacs, L. D., & Pohlman, R. L. (1991). Effects of exercise intensity on an accompanying timing task. Journal of Human Movement Studies, 20, 123–131. Kelley, G. A., & Kelley, K. S. (2010). Isometric handgrip exercise and resting blood pressure: A meta-analysis of randomized controlled trials. Journal of Hypertension, 28, 411–418. Kozlowski, S., Brzezinska, Z., Nazar, K., Kowalski, W., & Franczyk, M. (1973). Plasma catecholamines during sustained isometric exercise. Clinical Science and Molecular Medicine, 45, 723–731. Lambourne, K., & Tomporowski, P. (2010). The effect of exercise-induced arousal on cognitive task performance: A metaregression analysis. Brain Research, 1341, 12–24. Martin Ginis, K. A., & Bray, S. R. (2010). Application of the limited strength model of self-regulation to understanding exercise effort, planning and adherence. Psychology and Health, 25, 1147–1160. Mayer, J. D., & Gaschke, Y. N. (1988). The experience and metaexperience of mood. Journal of Personality and Social Psychology, 55, 102–111. McGowan, C. L., Levy, A. S., Millar, P. J., Guzman, J. C., Morillo, C. A., McCartney, N., & MacDonald, M. J. (2006). Acute vascular responses to isometric handgrip exercise and effects of training in persons medicated for hypertension. American Journal of Physiology: Heart and Circulatory Physiology, 291, H1797–H1802. McMorris, T., & Graydon, J. (2000). The effect of incremental exercise on cognitive performance. International Journal of Sport Psychology, 31, 66–81. McMorris, T., & Hale, B. J. (2012). Differential effects of differing intensities of acute exercise on speed and accuracy of cognition: A meta-analytical investigation. Brain and Cognition, 80, 338–351. McMorris, T., Tomporowski, P. D., & Audiffren, M. (2009). Exercise and cognitive function: A neuroendocrinological

Downloaded by [University of Southern Queensland] at 07:55 05 October 2014

Isometric exercise & cognitive performance explanation. Exercise and Cognitive Function, 41–68. doi:10.1002/9780470740668.ch2 Millar, P., McGowan, C., Cornelissen, V., Araujo, C., & Swaine, I. (2013). Evidence for the role of isometric exercise training in reducing blood pressure: Potential mechanisms and future directions. Sports Medicine, 44, 1–12. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100. Muraven, M., Tice, D. M., & Baumeister, R. F. (1998). Selfcontrol as a limited resource: Regulatory depletion patterns. Journal of Personality and Social Psychology, 74, 774–789. Powers, S. K., & Howley, E. T. (2012). Exercise physiology (8th ed.). Toronto, ON: McGraw-Hill Ryerson. Sibley, B. A., Etnier, J. L., & Le Masurier, G. C. (2006). Effects of an acute bout of exercise on cognitive aspects of Stroop performance. Journal of Sport and Exercise Psychology, 28, 285–299. Smolander, J., Aminoff, T., Korhonen, I., Tervo, M., Shen, N., Korhonen, O., & Louhevaara, V. (1998). Heart rate and blood pressure responses to isometric exercise in young and older

11

men. European Journal of Applied Physiology and Occupational Physiology, 77, 439–444. Staud, R., Robinson, M. E., & Price, D. D. (2005). Isometric exercise has opposite effects on central pain mechanisms in fibromyalgia patients compared to normal controls. Pain, 118, 176–184. Tomporowski, P. D. (2003). Effects of acute bouts of exercise on cognition. Acta Psychologica, 112, 297–324. Travlos, A. K., & Marisi, D. Q. (1995). Information processing and concentration as a function of fitness level and exercise-induced activation to exhaustion. Perceptual and Motor Skills, 80, 15–26. U.S. Department of Health and Human Services. (2008). Physical activity guidelines for Americans. Retrieved from http://www. health.gov/paguidelines/pdf/paguide.pdf Vøllestad, N. K., & Blom, P. E. R. C. S. (1985). Effect of varying exercise intensity on glycogen depletion in human muscle fibres. Acta Physiologica Scandinavica, 125, 395–405. Wallace, H. M., & Baumeister, R. F. (2002). The effects of success versus failure feedback on further self-control. Self and Identity, 1, 35–41. Williams, K., & Kemper, S. (2010). Exploring interventions to reduce cognitive decline in aging. Journal of Psychosocial Nursing and Mental Health Services, 48, 42–51.