The Acute Effects of Aerobic Exercise on Sensorimotor Adaptation in Chronic Stroke
Phase: NA
Conditions: Stroke
Sponsor: The University of Queensland

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June 1st 2020 
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The acute effects of aerobic exercise on sensorimotor adaptation in chronic stroke. 
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Authors Christopher P Mackay1, Sandra G Brauer1, Suzanne S Kuys2, Mia A 
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Schaumberg3,4,5, Li-Ann Leow5,6. 
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1 The University of Queensland, School of Health and Rehabilitation Sciences, Brisbane, 
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Queensland, Australia. 
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2 Australian Catholic University, School of Allied Health, Brisbane, Queensland, Australia 
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3 University of the Sunshine Coast, School of Health and Sport Sciences, Maroochydore, 
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Queensland, Australia 
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4 Sunshine Coast Health Institute, Birtinya, Queensland, Australia 
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5 The University of Queensland, School of Human Movement and Nutrition Science, 
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Brisbane, Queensland, Australia 
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6 The University of Queensland, School of Psychology, Brisbane, Queensland, Australia 
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Corresponding author: Christopher P Mackay –  
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Address: School of Health and Rehabilitation Sciences, The University of Queensland, 
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Brisbane, Queensland, Australia 
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Business telephone: +61 7 3338 9090 
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 Email: c.mackay@uq.edu.au 
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Abstract: 
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Sensorimotor adaptation, or the capacity to adapt movement to changes in the moving body 
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or environment, is a form of motor learning that is important for functional independence 
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(e.g., regaining stability after slips or trips). Aerobic exercise can acutely improve many 
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forms of motor learning in healthy adults. It is not known, however, whether acute aerobic 
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exercise has similar positive effects on sensorimotor adaptation in stroke survivors as it does 
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in healthy individuals. Purpose: The aim of this study was to determine whether acute 
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aerobic exercise promotes sensorimotor adaptation in people post stroke. Methods: A single-
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blinded crossover study. Participants attended two separate sessions at the university campus, 
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completing an aerobic exercise intervention in one session and a resting control condition in 
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the other session. Sensorimotor adaptation was assessed before and after each session.  
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Participants were twenty people with chronic stroke. Intervention completed was treadmill 
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exercise at mod-high intensity for 30 minutes. Results: Results demonstrated that acute 
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aerobic exercise in chronic stroke survivors significantly increased sensorimotor adaptation 
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from pre to post treadmill intervention. Conclusion: These results indicate a potential role for 
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aerobic exercise to promote the recovery of sensorimotor function in chronic stroke 
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survivors. 
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Keywords: sensorimotor adaptation, aerobic exercise, stroke 
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Introduction: 
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Change in the brain due to neuroplasticity is a foundation principle underpinning the 
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rehabilitation of sensorimotor function following stroke. Plastic effects of acute aerobic 
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exercise on the brain have been previously demonstrated in many domains of cognition [1]. 
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Evidence suggests that the cognitive performance of an individual can be significantly 
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improved due to acute aerobic exercise and that this improvement may be further enhanced 
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when exercising at a moderate to high intensity compared with a lower intensity [2, 3]. Older 
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adults (age 65 years or older) are at an increased risk of cognitive decline, yet there appears to 
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still be benefits of acute aerobic exercise on cognition (executive function), with more 
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demanding cognitive tasks often more sensitive to the effects of physical exercise than less 
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demanding cognitive tasks [4]. As well as improving brain performance from a cognitive 
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function perspective, there is also evidence for specific improvements in sensorimotor 
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function following acute aerobic exercise. This finding corroborates the work of others who 
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have demonstrated that acute exercise improves various forms of motor learning in young 
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healthy adults  [5-9], although not all studies show that exercise improves motor learning [10-
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12].  In a recent study, young healthy participants who first exercised at a moderate intensity 
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on a cycle ergometer for 25 minutes subsequently demonstrated improved movement 
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accuracy and reaction time in a sensorimotor adaptation task [9]. In studies of sensorimotor 
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adaptation, the sensory feedback of a movement is experimentally perturbed, leading to a 
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discrepancy between the predicted sensory outcome and the actual sensory outcome (sensory 
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prediction error) [13]. A perturbation can be created by rotating the visual feedback of a hand 
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movement in a 30˚ clockwise direction during a target reaching task. Perturbations lead to 
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discrepancies between the predicted sensory feedback about the movement and the actual 
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sensory feedback received (i.e., sensory prediction errors) [14]. With repeated reaches, this 
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sensory prediction error triggers an updating of the motor command to reduce the sensory 
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prediction error, and this learning occurs in an implicit, automatic way. Perturbations also 
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often lead to discrepancies between the predicted task outcomes (e.g., hit the target) and the 
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actual task outcomes (e.g., fail to hit the target), termed task errors [15-18]. Such task errors 
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are thought to promote the use of explicit strategies, to obtain desired task outcomes. 
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Quantifying how quickly individuals return sensory prediction errors and task errors to pre-
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perturbation levels measures the brain’s ability to learn to adapt to altered sensory feedback 
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via implicit and explicit learning mechanisms, and may indicate the neuroplastic capacity of 
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the individual [19].  
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Although increasing evidence demonstrates beneficial effects of exercise on motor learning 
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in young, healthy individuals, far fewer studies have tested the acute effects of exercise on 
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motor learning in cohorts with neurological deficits. Isolated studies have demonstrated 
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improvements in motor skill learning in people with Parkinson’s disease following a single 
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session of moderate intensity (60-70% V̇O2max) cycling [20], and in people with stroke 
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following high intensity interval training [21]. In contrast, one study in stroke patients 
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showed that acute exercise did not improve split-belt treadmill adaptation, which is a form of 
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sensorimotor adaptation involving adaptation to different treadmill speeds for different legs 
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[22]. To the best of our knowledge, the acute effect of moderate to high intensity aerobic 
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exercise on sensorimotor adaptation with goal-directed reaching of the upper limbs in stroke 
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is not known.  
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Therefore, the aim of this study was to determine if a single bout of moderate to high 
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intensity aerobic exercise performed by people following stroke improved sensorimotor 
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adaptation compared to a control period of rest. We hypothesised that acute aerobic exercise 
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would improve the sensorimotor adaptation of individuals post stroke. 
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Methods 
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Participants  
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Twenty people with chronic stroke participated in the study (aged 61 ± 13 years; 76% male). 
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To be included in the study, participants had to be diagnosed with a stroke at least 3 months 
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prior, be able to walk with or without an aid for at least 10 metres and be able to understand 
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three-stage commands. Individuals were excluded if they were unable to walk independently 
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prior to the current stroke, had co-morbidities that might limit their walking (such as 
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arthritis), had an unstable cardiac status, or were unable to understand instructions or provide 
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informed consent. 
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A sample size of 20 was calculated from data showing changes in BDNF levels after a single 
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bout of exercise in people with MS [23, 24]. Both studies found a change of BDNF levels of 
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5ng/ml from pre to post, with a maximum SD of 5ng/ml. A sample size of 18 is required to 
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detect a difference of 5+/-5ng/ml at a two sided 0.5 significance level with a power of 80%. 
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The primary outcome measure for the current data set was BDNF, but the results for the 
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analysis of BDNF are currently incomplete and not presented here. 
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Information collected to describe the sample participants included date, location and type of 
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stroke, age, sex, medical co-morbidities and current medications. Ethical approval for the 
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study was obtained through the local human research ethics committee. All participants 
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provided written informed consent in accordance with the Declaration of Helsinki.  
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Experimental design 
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In a cross-over design, each participant was pseudo-randomised to complete an intervention 
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condition (Treadmill) or control condition (Rest) first, returning at least one week later 
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(washout period) to complete the alternate condition. A minimum washout period of one 
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week was used to allow for any physiological changes due to exercise to return to resting 
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levels, but to minimise any stroke recovery-associated changes to function. Participants were 
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asked to refrain from exercising in the 24 hours prior to their visit. At each visit, participants 
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completed the sensorimotor adaptation task on two occasions, pre and post intervention, 
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resulting in four assessment timepoints (PreControl, PostControl and PreTreadmill, 
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PostTreadmill). The post intervention assessment aimed to commence within 15 minutes of 
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completing the treadmill or rest condition. 
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Intervention 
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The intervention condition consisted of a single session of moderate-high intensity aerobic 
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exercise (65% of heart rate reserve) for 30 minutes walking on a standard treadmill (Landice 
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L7 treadmill), with arms placed comfortably by participants on the rail (in front) or swinging 
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freely. Information describing the specific features of the training session (e.g. heart rate, 
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blood pressure response, treadmill speed, total distance walked) were recorded to monitor the 
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response to exercise and adherence to the exercise protocol. The single treadmill session 
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included a progressive increase in intensity (usually increased speed, or gradient) to reach the 
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target heart rate (approx. 5 mins) as well as a cooling down period (approx. 5 mins) to allow 
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for participants to return towards resting levels for vital observations. The warm-up and cool-
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down were included as part of the total 30 minutes of walking exercise. Target heart rates 
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were calculated using the Karvonen method [25] with levels adjusted for those taking heart 
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rate lowering medications (i.e. beta blockers), following methods previously published in 
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post stroke populations [26, 27]. Heart rate was measured using a chest strap monitor (polar-
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electro) and monitored by a research assistant who facilitated changes in treadmill parameters 
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to enable participants to reach their target. Participants were asked to self-rate their intensity 
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of exercise every 10 minutes verbally using BORG’s 6-20 scale rating of perceived exertion 
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[28]. Participants were instructed to walk at a pace that resulted in a rating between 11 (fairly 
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light) and 14 (somewhat hard) on the scale. The control condition involved an equivalent 
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time period (30 minutes) of seated resting where participants were provided with an 
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education session about the impact and effects of stroke by the same research assistant. 
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Sensorimotor adaptation task 
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Apparatus and setup. Participants were seated in front of a desk (approximately 50 cm from 
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their coronal plane) and asked to move a digitising pen (15.95 cm long, 1.4 cm wide, 17 g) on 
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a digitizing tablet (WACOM Intuos4 PTK 1240, size: 19.2 x 12 in., resolution = 0.25 mm) 
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from an origin to a target point. The pen’s position on the tablet (XY coordinates) was 
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sampled at 100 Hz and displayed in real time as a circular cursor with a 5-pixel radius (1.25 
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mm) on a horizontally placed computer monitor. Direct vision of the hand was prevented by 
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placing the tablet and the hand directly beneath an opaque stand, with the horizontal monitor 
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placed atop the stand.  
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Task instructions. Participants first received task instructions to move an on-screen cursor 
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from the start to the target, in a straight line, in a single movement, as quickly and as 
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accurately as possible. Further, participants were instructed that the feedback of the 
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movement would be changed from time-to-time, and that participants were to change their 
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movement in response to this change of feedback, whilst keeping movements as straight as 
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possible.  
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In each trial, the participants’ task was to move from the origin location through the target 
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location as quickly and accurately as possible using their dominant upper limb. Targets were 
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presented in one of three locations (210, 225 or 240 degrees from the right horizontal plane) 
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in random order. These target directions were selected such that target-reaching movements 
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involved the horizontal adductors of the shoulder joint.  After moving through the target, or 
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past the target, a high-pitched tone sounded to indicate trial completion. Following 
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completion of a trial the origin location was re-displayed immediately and participant 
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directed to repeat task. If the participant did not complete a successful trial, they were 
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directed to return to the origin location and repeat the trial.  
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First, participants encountered 18 baseline trials under normal (correct) feedback with no 
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rotation. Participants then immediately completed 66 adaptation trials, where the visual 
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feedback on the display monitor was perturbed by rotating it 30 degrees in a clockwise 
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direction (1st testing day) or counter-clockwise direction (2nd testing day). After the 
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adaptation block, to notify participants that the perturbation had been removed, a popup 
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dialog box appeared with the statement “In the next few trials, the disturbance that the 
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computer applied would be removed. Please aim straight to the target.” The instructions on-
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screen were read out by the experimenter to ensure it was understood. This was immediately 
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followed by 6 no-feedback trials. Finally, participants completed 36 washout trials under 
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normal cursor feedback conditions (i.e., no cursor rotation), to return behaviour to an 
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unadapted state. 
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Data Processing and Analysis 
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Custom scripts written in LabVIEW scored reach directions, which were quantified at the 
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15th data point (150 milliseconds into the reach), as online movement corrections typically 
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occur after 150 ms into a reach. Trials with reach direction outside a 120 degree range of the 
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target (60 degrees on either side of the target) were discarded as outliers [29]. Trials were 
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binned into cycles of one visit to each of the three targets. The dependent variable was 
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percent adaptation [30, 31], which quantified reach directions in every cycle relative to the 
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ideal reach direction by calculating reach directions as a percentage of ideal reach directions 
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resulting from perfect adaptation performance. Ideal reach direction was 30 degree clockwise 
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for a 30 degree counter-clockwise rotation, and 30 degrees counter-clockwise for a 30 degree 
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clockwise rotation. 
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Percent adaptation=100% × (reach direction)/(ideal reach direction) 
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As observed previously [9, 31], there was a rapid error reduction phase of reaching where a 
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majority of learning occurred followed by a slower rate of adaptation. Here, as the targets 
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were spaced close together, rapid error reduction occurred in trials 1-9 (i.e., the first three 
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cycles), similar to recent work [32]. At completion of the fourth cycle, adaptation was greater 
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than 70% both before and after the treadmill and control conditions. We thus selected the first 
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three cycles to quantify rapid error reduction. 
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Individual differences in reach directions at baseline can affect measures of adaptation [33]. 
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Previous methods of accounting for this by subtracting pre-perturbation behaviour from post-
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perturbation behaviour is more sensitive to noisy baselines and risk of Type 2 error (Vickers, 
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2001; Vickers, 2014). To account for pre-perturbation baseline biases, we entered percent 
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adaptation averaged from the final three cycles before rotation onset (i.e., percent adaptation 
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in the last five baseline cycles) as covariates in all of our analysis of covariance analyses.  
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After the adaptation trials, there were two cycles where no feedback was provided to the 
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participant. That is, unlike all previous trials where participants could follow a tracking 
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cursor with their vision, the participants received no real time feedback about where they 
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were reaching. The first no-feedback cycle was taken as a measure of implicit learning, 
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similar to previous work [18]. 
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Our outcome measures of interest were (1) adaptation performance (2) implicit aftereffects, 
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quantified as reaches that remained adapted despite notification of perturbation removal in 
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the no-feedback block and (3) explicit learning, estimated as the volitional disengagement of 
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adapted behaviour after receiving notification of perturbation removal (i.e., the change in 
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percent adaptation from the mean of the last three adaptation cycles to the first no-feedback 
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cycle after receiving notification that the perturbation was gone), and (4) de-adaptation 
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performance. To evaluate these measures, we ran ANCOVAs with the between-subjects 
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factor Intervention Order (Control First, Treadmill First) and the within-subjects factors: 
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Intervention (Control, Treadmill), Time (Pre-Intervention, Post-Intervention) and (where 
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applicable) Cycles (cycles 1..3), with pre-rotation biases as covariates of no interest 
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(estimated from mean percent adaptation in the last three baseline cycles). Where appropriate, 
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Greenhouse-Geisser corrections were applied. Alpha was set at 0.05. SPSS v24.0 was used 
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for statistical analyses.  
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Results 
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Reaching with rotated feedback (adaptation trials) 
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During the rapid error reduction phase of the adaptation trials (cycles 1-3), a significant 
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Intervention x Time interaction was observed [F (1,13) = 6.399, p = 0.027, partial eta squared 
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= 0.346]. Follow-up ANCOVAs were run separately for the Treadmill and Control 
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interventions. Percent adaptation increased pre-to-post in the Treadmill intervention [Figure 
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2B, significant main effect of Time, F(1,15) = 6.241, p = 0.025, partial eta-squared = 0.247, 
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PreTread 52.5  6.2%  [39.1, 66.0] vs. PostTread 65.7  3.8%) [57.4, 74.0], but not for the 
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Control intervention [Figure 2A, non-significant main effect of Time, F(1, 15) = 1.138, p = 
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0.303, partial eta-squared = 0.07, PreControl 62.8  5.9% [49.9%, 75.9%]  vs. PostControl 
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53.9  6.1% [40.5%, 67.5%]].  
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Implicit aftereffects and Explicit learning 
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Implicit learning (Figure 3.A), measured as percent adaptation in the first no-feedback cycle 
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after receiving notification of the perturbation removal [similar to 16], was larger overall in 
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the treadmill intervention conditions than the control intervention conditions, but did not  
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differ significantly from pre- to post- between control and treadmill conditions, as the 
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Intervention x Time interaction was not significant, (p > 0.05). The main effect of treadmill 
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and the main effect of Time was also not significant. 
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All conditions showed a clear change in reach directions after receiving instructions that the 
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perturbation had been removed (see Figure 2), indicating a role for explicit learning in this 
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sensorimotor adaptation task. Explicit learning did not differ reliably between before and 
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after the control and treadmill interventions (all main effects of Intervention and Time, and 
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all interactions with Intervention and Time p > 0.05). 
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Reaching with normal feedback (de-adaptation trials) 
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Pre and post-intervention de-adaptation did not differ reliably between Control and Treadmill 
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intervention conditions, [non-significant main effect of Intervention, non-significant x Time 
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interaction, F(1,12) = 0.4, p = 0.538, partial η-squared = 0.03). Participants in both 
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intervention conditions returned to a normal level of baseline reaching, as expected. 
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Discussion 
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This study found that a single bout of moderate to high intensity aerobic exercise was 
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sufficient to increase sensorimotor adaptation performance of chronic stroke survivors. The 
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improvement in reaching performance (observed as a faster rate of adaptation post-
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intervention compared to pre-intervention) was observed during the rapid error reduction 
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phase of the trials after the treadmill exercise had been performed, but not after the rest 
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condition. Thus, the present study showed that a single session of moderate to high intensity 
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aerobic exercise increased capacity to improve sensorimotor adaptation in chronic stroke 
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survivors. 
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Immediate improvement in reaching performance post-exercise was specifically seen in the 
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rapid error reduction phase of adaptation. Participants demonstrated increased ability to adapt 
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to the imposed rotation in the first nine trials following the exercise compared to the control 
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condition. Such an improvement in reaching performance following exercise may represent 
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an acute change in the brain leading to an enhanced internal environment that could facilitate 
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adaptation. We note that the current findings contrast with some recent work by 
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Charalambous et al. (2018, 2019) who found no effects of exercise on consolidation in 
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locomotor adaptation in stroke patients [12] and in healthy controls [10]. Several differences 
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in the design might have led to this pattern of results. First, although locomotor adaptation is 
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also susceptible to effects of explicit learning, people do not appear to actively engage 
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explicit learning in locomotor adaptation [34]. In contrast, behaviour in the type of reach 
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adaptation paradigm used here has a large contribution from explicit learning, particularly in 
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the early phases of learning [35]. Second, Charalambous et al. (2018, 2019) examined the 
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effects of exercise on consolidation of adaptation by testing retention after a >= 24 hour 
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delay, in contrast to the current work which retested participants immediately after the 
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exercise/control interventions. Finally, the duration of exercise (≈5 mins) in Charalambous et 
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al. (2018, 2019) was shorter than that used here (≈25 mins). Future studies explicitly 
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measuring the effects of these factors will be important for designing exercise-based 
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interventions in movement rehabilitation. 
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The current finding that exercise has immediate effects on improving early adaptation in 
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stroke patients is consistent with recent work in young healthy adults. Neva et al. (2019) 
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demonstrated that in young, healthy individuals, performance of a visuomotor upper limb 
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rotation task improved (reflected by a lower peak lateral displacement) following a single 
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bout of aerobic cycling exercise (performed at a similar intensity and duration to the current 
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study, 65-70% of max HR for 25 minutes). This improvement occurred immediately after 
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exercise and was retained at 24 hours post-exercise. Acute benefits of moderate to high 
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intensity exercise have also been shown following treadmill running and high intensity 
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shuttle running with improvements to a motor learning task and a visuomotor adaptation task 
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respectively in healthy young adults [36, 37]. These studies collectively strengthen the 
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argument that completing exercise prior to a movement task (sensorimotor or visuomotor) 
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has a positive impact on performance. A number of mechanisms might contribute to exercise-
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related improvements in learning. This improvement may be related to changes in the brain 
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that accompany intense exercise, such as upregulation of neurotrophic factors such as brain 
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derived neurotrophic factor (BDNF), or proteins such as growth hormone, increased cortisol 
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levels and/or changes to neurotransmitter release [38-40]. Other potential mediators for 
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improved performance include the salience of the task at hand (i.e. how relevant/important is 
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the task to the individual completing it) and the ability of the client to engage with and 
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concentrate on the task. These two mediators (salience and concentration) are of particular 
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importance, highlighted by stroke guideline statements that encourage active task practice 
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outside of scheduled therapy hours to maximise functional return in rehabilitation [41]. 
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Evidence supports the prescription of moderate to high intensity aerobic exercise to improve 
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sensorimotor performance in healthy individuals. The present study extends these findings to 
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demonstrate that in stroke survivors, utilising moderate to high intensity exercise can improve 
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sensorimotor adaptation. Having a positive change in performance (measured as an increased 
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adaptation) may represent an exercise induced change in the brain. It has been previously 
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stated that BDNF concentrations increase following a single bout of aerobic exercise [39]. 
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BDNF is a neurotrophin that plays a key role in the formation of new neurons, development 
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and strengthening of existing neurons and in the restructure of the neuron pool with use [42-
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44]. It may be possible to harness increased levels of BDNF following exercise to enhance 
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sensorimotor performance, and we have shown that increased levels of BDNF can occur in 
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response to a program of aerobic exercise in neurological populations [45]. This is an 
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important concept for chronic stroke survivors due to the stagnant nature and plateau that 
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often accompanies this phase of recovery. Providing stroke survivors with a way to augment 
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their recovery could lead to enhanced motor re-adaptation, functional gains and ultimately 
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boost community participation of this group. 
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Average time post stroke for participants in this study was four years, representing the 
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chronic phase of recovery. We note that although gains are still made in this phase of 
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recovery, the magnitude of gains may be less than in a more acute recovery phase [46]. The 
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majority of post-stroke recovery is generally observed to occur within the acute (1 - 7 days) 
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and subacute phases of recovery (7 days – 6 months) [47]. Harnessing potential changes in 
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the brain due to exercise is important for all stages of recovery post stroke, but the magnitude 
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and impact of this change may be increased in the earlier phases of recovery. It is therefore 
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important to consider the timing of an aerobic exercise intervention post-stroke to maximise 
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patient benefit in this way. Implementing an aerobic exercise intervention during the subacute 
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phase of recovery may represent a more appropriate temporal window for enhancing 
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neuroplastic benefit. Stroke survivors in the chronic phase of recovery, however should still 
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be encouraged to participate in aerobic exercise for potential benefit. 
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As this study was a within-subject (crossover) design, participants acted as their own control. 
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Participants engaged in the sensorimotor adaptation task four times, on two separate testing 
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days, with a one-week washout period between the two testing days. Compared to the control 
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intervention, the treadmill exercise intervention increased pre-to-post intervention 
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improvement in the rapid error reduction phase. There is the possibility that carryover effects 
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between testing days might have partly contributed to the current pattern of results.  We did, 
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however, attempt to control for this with an equal and opposite rotation on the second testing 
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day in a counter-balanced order (30 degrees clockwise on Day 1 vs 30 degrees 
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counterclockwise on Day 2). We also randomised the number of participants who completed 
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the control condition on their first visit compared to the treadmill condition. Additionally, 
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assessors were blinded to the intervention completed at each session to eliminate bias. There 
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was no follow up testing of the participants to examine whether they retained an 
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improvement due to exercise at a later date. Therefore, we cannot comment on the impact 
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that the exercise may have had on longer-term learning. The assessment item to quantify 
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motor learning in this study was a sensorimotor adaptation task. Although this task has been 
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widely used, it might not fully describe real-life motor skill acquisition [48]. This 
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sensorimotor adaptation task, however, enabled the sensitive detection of exercise-related 
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improvements in motor learning here.  
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This is the first study to our knowledge to demonstrate an improvement in sensorimotor 
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adaptation following moderate-high intensity exercise in a stroke population. Due to the 
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neurological deficit incurred by stroke survivors, being able to improve adaptation of a motor 
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task through aerobic exercise has the potential to significantly improve function in this 
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cohort.   
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Acknowledgements 
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No funding was provided for this study. The authors would like to acknowledge the in kind 
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contributions received from the School of Human Movement and Nutrition Science at The 
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University of Queensland, and the School of Health and Rehabilitation Sciences at The 
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University of Queensland in the form of utilisation of resources, buildings and assistance 
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from staff, including Katrina Kemp. 
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Conflict of Interest 
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All of the authors wish to declare that they have no conflicts of interest in relation to this 
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study. The results of the present study do not constitute endorsement by ACSM. The results 
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of the study are presented clearly, honestly, and without fabrication, falsification, or 
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inappropriate data manipulation. 
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