Exp Brain Res DOI 10.1007/s00221-014-3879-z
Research Article
The influence of a single bout of aerobic exercise on short‑interval intracortical excitability Ashleigh E. Smith · Mitchell R. Goldsworthy · Tessa Garside · Fiona M. Wood · Michael C. Ridding
Received: 11 November 2013 / Accepted: 13 February 2014 © Springer-Verlag Berlin Heidelberg 2014
Abstract Regular physical activity can have positive effects on brain function and plasticity. Indeed, there is some limited evidence that even a single bout of exercise may promote plasticity within the cortex. However, the mechanisms by which exercise acutely promotes plasticity are not clear. To further explore the effects of acute exercise on cortical function, we examined whether a single bout of exercise was associated with changes in cortical excitability and inhibition. Using standard techniques, cortical stimulus–response curves [90 % resting motor threshold (RMT)–150 % RMT] were investigated in nine subjects (four females, 31.1 ± 11.7 years) and short-interval intracortical inhibition (SICI) [interstimulus interval 2 ms and 3 ms, conditioning intensities of 80 % active motor threshold (AMT) and 90 % AMT] in 13 subjects (six females, 28.4 ± 5.1 years) before and at 0 and 15 min following 30 min of ergometer cycling at low–moderate or moderate– high intensity. There were no changes in cortical excitability following exercise but less SICI at both 0 and 15 min post-exercise (F[2, 24] = 7.7, P = 0.003). These findings Ashleigh E. Smith and Mitchell R. Goldsworthy are postdoctoral research fellows. A. E. Smith · M. R. Goldsworthy · M. C. Ridding School of Paediatrics and Reproductive Health, Robinson Institute, The University of Adelaide, Adelaide, Australia A. E. Smith (*) Exercise for Health and Human Performance, School of Health Sciences, Sansom Institute for Health Research, The University of South Australia, GPO Box 2471, Adelaide 5001, Australia e-mail: [email protected] T. Garside · F. M. Wood School of Surgery, University of Western Australia, Perth, Australia
show that a short period of exercise can transiently reduce SICI. Such a change in inhibition after exercise may contribute to the development of a cortical environment that would be more optimal for plasticity and may partially explain previous findings of enhanced neuroplasticity following low-intensity exercise. Keywords Motor cortex · Short-interval intracortical inhibition · GABAA · Transcranial magnetic stimulation · Physical activity
Introduction There is mounting evidence at the behavioural, systems, cellular and molecular levels (Cotman and Berchtold 2002; Bramham and Messaoudi 2005) that engaging in regular aerobic exercise may positively influence brain function in many areas. In particular, regular exercise has positive effects on cognitive behaviours dependent on neuroplastic mechanisms (Cotman and Berchtold 2002). In a recent study, it was observed that, compared with sedentary individuals, highly active individuals had an increased neuroplastic response to paired associative stimulation (PAS) (Cirillo et al. 2009). PAS is a non-invasive brain stimulation protocol that can induce neuroplastic change within the human cortex through long-term potentiation (LTP)-like mechanisms (Stefan et al. 2000, 2002; Hoogendam et al. 2010). These findings provide evidence that high levels of physical activity maintained over an extended period of time can increase the capacity for cortical plasticity. Such an exercise-related increase in neuroplastic capacity may, in part, explain why physical activity has a positive effect on memory and executive function (Cotman and Berchtold 2002).
13
Exp Brain Res
The mechanisms by which regular aerobic exercise has positive effects on brain structure and function are not completely understood. However, studies in animals have shown that physical activity and exposure to enriched environments can elevate the levels of neurotrophic factors such as brain-derived neurotrophic factor (BDNF) (VazquezSanroman et al. 2013). Additionally, exposure to such environments is also associated with a general reduction in gamma-aminobutyric acid (GABA)-mediated inhibition (Sale et al. 2007, 2009; Baroncelli et al. 2010), which in turn can facilitate neuroplasticity. Indeed, using noninvasive techniques, it has been shown that both practisedependent and experimentally induced neuroplasticity are enhanced when GABAA-mediated inhibition is reduced (Ziemann et al. 1998, 2001). Whether a single bout of aerobic exercise can have similar effects on BDNF and inhibition that may promote a cortical environment optimal for plasticity is not clear. However, a recent study reported that a single bout of moderate-level aerobic exercise promoted cortical plasticity induced by a non-invasive brain stimulation protocol (McDonnell et al. 2013). Therefore, this study examined the influence of a single aerobic exercise session on motor cortical (M1) excitability and intracortical inhibition using non-invasive transcranial magnetic stimulation (TMS). In particular, we were interested to investigate whether aerobic exercise had generalised effects on brain excitability and so examined effects of lower limb exercise on excitability within the hand motor representation. Given the relationship between enriched environment training and inhibition in animals, we hypothesised that physical activity would be associated with a reduction in the GABAAmediated short-interval intracortical inhibition (SICI).
Materials and methods Participants Thirteen healthy participants took part in this study. All subjects provided informed written consent, the study was ethically approved by the University of Adelaide Human Research Ethics committee, and experiments were performed in accordance with the Declaration of Helsinki (1998). This included nine participants (four females; 31.1 ± 11.7 years, range 22–54 years) for Experiment 1 investigating the influence of aerobic exercise on corticospinal excitability and 13 participants (six females; 24.8 ± 5.1 years, range 19–36 years) for Experiment 2 investigating the influence of aerobic exercise on SICI. Nine participants took part in both experiments, whereas an extra four only took part in Experiment 2. For each experiment, participants were required to attend two experimental sessions separated by at least a week. Current physical activity levels were determined using the self-report short form of the International Physical Activity Questionnaire (IPAQ) (Table 1). Participants who accumulated more than 3000 metabolic equivalents (METs) over the 7 days prior to participating in the experiments were excluded from the study as they were considered highly physically active. Suitability to participate safely in the exercise protocol was determined by the Sports Medicine Australia (SMA) pre-exercise screening questionnaire (Norton et al. 1998; McHugh et al. 2008; Norton and Norton 2012). All participants had no known history of cognitive impairment, peripheral or neurological impairment, stroke or transient ischaemic attacks, diabetes, epilepsy, regular migraines or other neurodegenerative
Table 1 Participant’s characteristics
SR stimulus–response, IPAQ International Physical Activity Questionnaire, MET metabolic equivalents, RHR resting heart rate, THR target heart rate, RMT resting motor threshold, AMT active motor threshold and TS test stimulus to evoke 1 mV motor evoked potential Participant’s characteristics for each experiment †† Values not collected in a particular experiment
13
Experiment 1: SR curve
Experiment 2: SICI
N (Gender) Age (Years) Physical activity (IPAQ, MET –min/week) RHR (bpm) (low–moderate intensity) THR(bpm) (low–moderate intensity) RHR (bpm) (Moderate–high intensity) THR (bpm) (moderate–high intensity) RMT (%SO) (low–moderate intensity) (pre) RMT (%SO) (low–moderate intensity) (post) RMT (%SO) (moderate–high intensity) (pre) RMT (%SO) (moderate–high intensity) (post) AMT (%SO) (low–moderate intensity) (pre) AMT (%SO) (moderate–high intensity) (pre) TS intensity (%SO) (low–moderate intensity) (pre)
9 (4 females) 31.1 ± 11.7 1,756 ± 483 63.5 ± 12.1 110.3 ± 7.4 64.5 ± 12.8 157.0 ± 2.6 43.3 ± 10.0 43.1 ± 9.4 41.6 ± 8.8 43.6 ± 9.8
13 (6 females) 24.8 ± 5.1 1,812 ± 240 66.3 ± 9.1 111.8 ± 5.6 67.6 ± 10.5 157.6 ± 2.1 47.2 ± 8.0
TS intensity (%SO) (moderate–high intensity) (pre)
††
†† †† ††
††
46.5 ± 8.6 ††
32.5 ± 5.8 31.2 ± 5.7 61.0 ± 10.7 59.3 ± 11.4
Exp Brain Res
disorders according to current guidelines for the safe use of TMS (Rossi et al. 2009). Exercise protocol Participants were seated in a comfortable chair and allowed to rest for 5 min at the beginning of each experimental session before their resting heart rate (RHR) was obtained using an F11 Polar heart rate monitor (Polar, Australia). The exercise intervention was undertaken on a stationary exercise bike (Watt bike, Australia). For both experiments, participants were allowed a 5-min warm-up period followed by 2 × 15 min blocks of cycling either at 40 % of their predicted heart rate reserve (i.e. low–moderate intensity; calculated as (180 − RHR) × 0.4 + RHR) or at 80 % of their predicted heart rate reserve (i.e. moderate– high intensity; calculated as (180 − RHR) × 0.8 + RHR). Target heart rate (THR) refers to the heart rate of participants aimed to reach throughout the exercise intervention. Participants were required to maintain a HR within 5 beats per minute of the THR throughout the cycling bout (Table 1). The exercise intensities used were well tolerated, and there were no adverse outcomes. Heart rate was measured throughout the exercise period. The order in which participants underwent testing was pseudo-randomised between participants. During the intervention, participants were instructed not to grip the handle bars of the bike, but were able to rest their hands on the handle bars for stability. Experimental set‑up Participants were seated comfortably in an armchair with their legs and forearms supported during TMS measurements. Surface electromyographic (EMG) recordings were obtained from the first dorsal interosseous (FDI) muscle of the right hand using bipolar Ag–AgCl electrodes positioned in a belly-tendon montage. The hand muscle was selected as we were interested in examining whether exercise influenced brain excitability in cortical areas (upper limb representation) not primarily involved in the motor performance of the cycling training task (lower limb representation). EMG signals were sampled at 5 kHz with a laboratory interface (Cambridge Electronic Design 1401, Cambridge, UK) and were amplified with a gain of 1,000 and band-pass filtered between 20 Hz and 1,000 Hz (Cambridge Electrical Design 1902, Cambridge, UK) before being stored on a laboratory computer for offline analysis. Transcranial magnetic stimulation (TMS) Single monophasic TMS pulses were applied through a figure of eight coil (outer diameter of the wing, 90 mm)
Fig. 1 Timeline of TMS measurements during experimental sessions. RMT resting motor threshold, AMT active motor threshold, MEP motor evoked potential and SICI short-interval intracortical inhibition
connected to a Magstim 200 magnetic stimulator (Magstim, Whitland, UK). For the SICI measurements, stimuli were applied with the same figure of eight coil connected to a Magstim Bistim 2 programmable interval paired-pulse stimulator (Magstim Co., Dyfed, UK). The coil was held tangentially to the skull, with the handle pointing posteriorly and laterally at an angle of approximately 45° to the sagittal plane over the left M1 hand area. The optimal scalp site for evoking motor evoked potentials (MEPs) from the relaxed right FDI was located and marked with a water-soluble felt marker. Resting motor threshold (RMT) was defined as the lowest stimulator output at which at least five MEPs with minimum peak-to-peak amplitude of 50 μV were evoked from the relaxed FDI in 10 consecutive trials. Active motor threshold (AMT) was determined as the minimum intensity required to evoke an MEP greater than 200 μV in at least five of ten consecutive trials whilst subjects maintained a tonic contraction of their right FDI at approximately 20 % of their maximum force. Visual feedback was provided using an oscilloscope. The protocol used for each experiment is shown in Fig. 1. Experiment 1: Stimulus–response curve protocol Corticospinal stimulus–response curves were constructed to investigate the influence of exercise on cortical excitability. Curves were constructed prior to, immediately following and 15 min following the low–moderate and moderate– high-intensity exercise interventions. TMS was delivered at six different stimulus intensities (seven stimuli per intensity): 90 % RMT, 110 % RMT, 120 % RMT, 130 % RMT, 140 % RMT and 150 % RMT.
13
Experiment 2: Short‑interval intracortical inhibition (SICI) protocol Short-interval intracortical inhibition was measured in the left M1 prior to, immediately following and 15 min following the low–moderate and moderate–high-intensity exercise interventions using a similar method to that described by Kujirai et al. (1993). SICI was investigated using interstimulus intervals (ISIs) of 2 and 3 ms and was recorded in two blocks of 30 consecutive trials (10 trials for each ISI plus 10 trials for the test stimulus alone) at each time point. Two conditioning stimulus (CS) intensities were investigated separately in different blocks: (1) 80 % AMT and (2) 90 % AMT. The test stimulus intensity was set to evoke MEPs with peak-to-peak amplitudes of 1 mV in the right FDI at rest in the absence of a CS. Data analysis and statistics All MEP data were recorded at high gain, and any trials contaminated with EMG activity were discarded. The peakto-peak amplitude of the MEP was calculated for each trial. In Experiment 1, the average amplitude was then calculated for each block of seven MEPs at each of the stimulus intensities (90 % RMT–150 % RMT). The stimulus response MEP data were analysed using a three-way repeated-measures analysis of variance (rANOVA) with TIME (three levels: pre-exercise, 0 min post-exercise and 15 min postexercise), EXERCISE (two levels: low–moderate and moderate–high) and STIMULUS INTENSITY (six levels: 90 % RMT, 110 % RMT, 120 % RMT, 130 % RMT, 140 % RMT and 150 % RMT) as within-subject factors. In Experiment 2, the average peak-to-peak amplitude was calculated for each block of ten MEPs at each of the ISIs, for each of the CS intensities and for the test response alone. Then, the average MEP amplitude at each ISI and for each of the CS intensities was expressed as a percentage of the test response alone. Data for SICI were analysed using a four-way rANOVA with EXERCISE (two levels: low–moderate and moderate–high), TIME (three levels: baseline, 0 min post-exercise and 15 min post-exercise), CS INTENSITY (two levels: 80 % AMT and 90 % AMT) and ISI (two levels: 2 ms and 3 ms) as the within-subject factors. Post hoc analyses were performed using paired t tests or pairwise comparisons using Bonferroni correction. To determine whether the CS evoked significant SICI, MEP data were analysed using a one-way rANOVA with ISI (three levels: test, 2 ms and 3 ms) for both the 80 % CS intensity and 90 % CS intensity conditions. Covariate analyses of age, self-reported physical activity and gender were conducted for all baseline SICI measures. In all rANOVA, where assumptions of sphericity were violated, the critical value of F was adjusted by the
13
Exp Brain Res
Greenhouse–Geisser Epsilon value from the Mauchly test of sphericity. In all tests, a value of P ≤ 0.05 was considered to be statistically significant.
Results Subject characteristics Age, RHR and baseline RMT did not differ between the two experiments (Table 1). No participants reported any side effects to TMS or the exercise. All results are expressed as mean ± SD unless otherwise stated. Experiment 1: Effect of aerobic exercise on stimulus– response curves There was no change in RMT (expressed as a percentage of maximal stimulator output) following exercise at both the low–moderate and moderate–high intensities (low–moderate t[6] = 0.3, P = 0.8 NS and moderate–high t[6] = −1.8, P = 0.1 NS) (Table 1). The group mean stimulus–response curves recorded before and at 0 and 15 min following each of the exercise intensities are shown in Fig. 2. As expected, MEP amplitude increased with increasing stimulus intensity (F[4, 32] = 13.7, P > 0.001). However, there were no other significant main effects for TIME (F[2, 12] = 0.4, P = 0.9 NS) or EXERCISE (F[1, 6] = 0.4, P = 0.6 NS) and no interactions between the two. Experiment 2: SICI is reduced following exercise At baseline, test MEPs were significantly inhibited to approximately 63 % of test amplitude at 2 ms and 67 % at 3 ms when conditioned at 80 % AMT (F[2, 24] = 30.4, P =
Research Article
The influence of a single bout of aerobic exercise on short‑interval intracortical excitability Ashleigh E. Smith · Mitchell R. Goldsworthy · Tessa Garside · Fiona M. Wood · Michael C. Ridding
Received: 11 November 2013 / Accepted: 13 February 2014 © Springer-Verlag Berlin Heidelberg 2014
Abstract Regular physical activity can have positive effects on brain function and plasticity. Indeed, there is some limited evidence that even a single bout of exercise may promote plasticity within the cortex. However, the mechanisms by which exercise acutely promotes plasticity are not clear. To further explore the effects of acute exercise on cortical function, we examined whether a single bout of exercise was associated with changes in cortical excitability and inhibition. Using standard techniques, cortical stimulus–response curves [90 % resting motor threshold (RMT)–150 % RMT] were investigated in nine subjects (four females, 31.1 ± 11.7 years) and short-interval intracortical inhibition (SICI) [interstimulus interval 2 ms and 3 ms, conditioning intensities of 80 % active motor threshold (AMT) and 90 % AMT] in 13 subjects (six females, 28.4 ± 5.1 years) before and at 0 and 15 min following 30 min of ergometer cycling at low–moderate or moderate– high intensity. There were no changes in cortical excitability following exercise but less SICI at both 0 and 15 min post-exercise (F[2, 24] = 7.7, P = 0.003). These findings Ashleigh E. Smith and Mitchell R. Goldsworthy are postdoctoral research fellows. A. E. Smith · M. R. Goldsworthy · M. C. Ridding School of Paediatrics and Reproductive Health, Robinson Institute, The University of Adelaide, Adelaide, Australia A. E. Smith (*) Exercise for Health and Human Performance, School of Health Sciences, Sansom Institute for Health Research, The University of South Australia, GPO Box 2471, Adelaide 5001, Australia e-mail: [email protected] T. Garside · F. M. Wood School of Surgery, University of Western Australia, Perth, Australia
show that a short period of exercise can transiently reduce SICI. Such a change in inhibition after exercise may contribute to the development of a cortical environment that would be more optimal for plasticity and may partially explain previous findings of enhanced neuroplasticity following low-intensity exercise. Keywords Motor cortex · Short-interval intracortical inhibition · GABAA · Transcranial magnetic stimulation · Physical activity
Introduction There is mounting evidence at the behavioural, systems, cellular and molecular levels (Cotman and Berchtold 2002; Bramham and Messaoudi 2005) that engaging in regular aerobic exercise may positively influence brain function in many areas. In particular, regular exercise has positive effects on cognitive behaviours dependent on neuroplastic mechanisms (Cotman and Berchtold 2002). In a recent study, it was observed that, compared with sedentary individuals, highly active individuals had an increased neuroplastic response to paired associative stimulation (PAS) (Cirillo et al. 2009). PAS is a non-invasive brain stimulation protocol that can induce neuroplastic change within the human cortex through long-term potentiation (LTP)-like mechanisms (Stefan et al. 2000, 2002; Hoogendam et al. 2010). These findings provide evidence that high levels of physical activity maintained over an extended period of time can increase the capacity for cortical plasticity. Such an exercise-related increase in neuroplastic capacity may, in part, explain why physical activity has a positive effect on memory and executive function (Cotman and Berchtold 2002).
13
Exp Brain Res
The mechanisms by which regular aerobic exercise has positive effects on brain structure and function are not completely understood. However, studies in animals have shown that physical activity and exposure to enriched environments can elevate the levels of neurotrophic factors such as brain-derived neurotrophic factor (BDNF) (VazquezSanroman et al. 2013). Additionally, exposure to such environments is also associated with a general reduction in gamma-aminobutyric acid (GABA)-mediated inhibition (Sale et al. 2007, 2009; Baroncelli et al. 2010), which in turn can facilitate neuroplasticity. Indeed, using noninvasive techniques, it has been shown that both practisedependent and experimentally induced neuroplasticity are enhanced when GABAA-mediated inhibition is reduced (Ziemann et al. 1998, 2001). Whether a single bout of aerobic exercise can have similar effects on BDNF and inhibition that may promote a cortical environment optimal for plasticity is not clear. However, a recent study reported that a single bout of moderate-level aerobic exercise promoted cortical plasticity induced by a non-invasive brain stimulation protocol (McDonnell et al. 2013). Therefore, this study examined the influence of a single aerobic exercise session on motor cortical (M1) excitability and intracortical inhibition using non-invasive transcranial magnetic stimulation (TMS). In particular, we were interested to investigate whether aerobic exercise had generalised effects on brain excitability and so examined effects of lower limb exercise on excitability within the hand motor representation. Given the relationship between enriched environment training and inhibition in animals, we hypothesised that physical activity would be associated with a reduction in the GABAAmediated short-interval intracortical inhibition (SICI).
Materials and methods Participants Thirteen healthy participants took part in this study. All subjects provided informed written consent, the study was ethically approved by the University of Adelaide Human Research Ethics committee, and experiments were performed in accordance with the Declaration of Helsinki (1998). This included nine participants (four females; 31.1 ± 11.7 years, range 22–54 years) for Experiment 1 investigating the influence of aerobic exercise on corticospinal excitability and 13 participants (six females; 24.8 ± 5.1 years, range 19–36 years) for Experiment 2 investigating the influence of aerobic exercise on SICI. Nine participants took part in both experiments, whereas an extra four only took part in Experiment 2. For each experiment, participants were required to attend two experimental sessions separated by at least a week. Current physical activity levels were determined using the self-report short form of the International Physical Activity Questionnaire (IPAQ) (Table 1). Participants who accumulated more than 3000 metabolic equivalents (METs) over the 7 days prior to participating in the experiments were excluded from the study as they were considered highly physically active. Suitability to participate safely in the exercise protocol was determined by the Sports Medicine Australia (SMA) pre-exercise screening questionnaire (Norton et al. 1998; McHugh et al. 2008; Norton and Norton 2012). All participants had no known history of cognitive impairment, peripheral or neurological impairment, stroke or transient ischaemic attacks, diabetes, epilepsy, regular migraines or other neurodegenerative
Table 1 Participant’s characteristics
SR stimulus–response, IPAQ International Physical Activity Questionnaire, MET metabolic equivalents, RHR resting heart rate, THR target heart rate, RMT resting motor threshold, AMT active motor threshold and TS test stimulus to evoke 1 mV motor evoked potential Participant’s characteristics for each experiment †† Values not collected in a particular experiment
13
Experiment 1: SR curve
Experiment 2: SICI
N (Gender) Age (Years) Physical activity (IPAQ, MET –min/week) RHR (bpm) (low–moderate intensity) THR(bpm) (low–moderate intensity) RHR (bpm) (Moderate–high intensity) THR (bpm) (moderate–high intensity) RMT (%SO) (low–moderate intensity) (pre) RMT (%SO) (low–moderate intensity) (post) RMT (%SO) (moderate–high intensity) (pre) RMT (%SO) (moderate–high intensity) (post) AMT (%SO) (low–moderate intensity) (pre) AMT (%SO) (moderate–high intensity) (pre) TS intensity (%SO) (low–moderate intensity) (pre)
9 (4 females) 31.1 ± 11.7 1,756 ± 483 63.5 ± 12.1 110.3 ± 7.4 64.5 ± 12.8 157.0 ± 2.6 43.3 ± 10.0 43.1 ± 9.4 41.6 ± 8.8 43.6 ± 9.8
13 (6 females) 24.8 ± 5.1 1,812 ± 240 66.3 ± 9.1 111.8 ± 5.6 67.6 ± 10.5 157.6 ± 2.1 47.2 ± 8.0
TS intensity (%SO) (moderate–high intensity) (pre)
††
†† †† ††
††
46.5 ± 8.6 ††
32.5 ± 5.8 31.2 ± 5.7 61.0 ± 10.7 59.3 ± 11.4
Exp Brain Res
disorders according to current guidelines for the safe use of TMS (Rossi et al. 2009). Exercise protocol Participants were seated in a comfortable chair and allowed to rest for 5 min at the beginning of each experimental session before their resting heart rate (RHR) was obtained using an F11 Polar heart rate monitor (Polar, Australia). The exercise intervention was undertaken on a stationary exercise bike (Watt bike, Australia). For both experiments, participants were allowed a 5-min warm-up period followed by 2 × 15 min blocks of cycling either at 40 % of their predicted heart rate reserve (i.e. low–moderate intensity; calculated as (180 − RHR) × 0.4 + RHR) or at 80 % of their predicted heart rate reserve (i.e. moderate– high intensity; calculated as (180 − RHR) × 0.8 + RHR). Target heart rate (THR) refers to the heart rate of participants aimed to reach throughout the exercise intervention. Participants were required to maintain a HR within 5 beats per minute of the THR throughout the cycling bout (Table 1). The exercise intensities used were well tolerated, and there were no adverse outcomes. Heart rate was measured throughout the exercise period. The order in which participants underwent testing was pseudo-randomised between participants. During the intervention, participants were instructed not to grip the handle bars of the bike, but were able to rest their hands on the handle bars for stability. Experimental set‑up Participants were seated comfortably in an armchair with their legs and forearms supported during TMS measurements. Surface electromyographic (EMG) recordings were obtained from the first dorsal interosseous (FDI) muscle of the right hand using bipolar Ag–AgCl electrodes positioned in a belly-tendon montage. The hand muscle was selected as we were interested in examining whether exercise influenced brain excitability in cortical areas (upper limb representation) not primarily involved in the motor performance of the cycling training task (lower limb representation). EMG signals were sampled at 5 kHz with a laboratory interface (Cambridge Electronic Design 1401, Cambridge, UK) and were amplified with a gain of 1,000 and band-pass filtered between 20 Hz and 1,000 Hz (Cambridge Electrical Design 1902, Cambridge, UK) before being stored on a laboratory computer for offline analysis. Transcranial magnetic stimulation (TMS) Single monophasic TMS pulses were applied through a figure of eight coil (outer diameter of the wing, 90 mm)
Fig. 1 Timeline of TMS measurements during experimental sessions. RMT resting motor threshold, AMT active motor threshold, MEP motor evoked potential and SICI short-interval intracortical inhibition
connected to a Magstim 200 magnetic stimulator (Magstim, Whitland, UK). For the SICI measurements, stimuli were applied with the same figure of eight coil connected to a Magstim Bistim 2 programmable interval paired-pulse stimulator (Magstim Co., Dyfed, UK). The coil was held tangentially to the skull, with the handle pointing posteriorly and laterally at an angle of approximately 45° to the sagittal plane over the left M1 hand area. The optimal scalp site for evoking motor evoked potentials (MEPs) from the relaxed right FDI was located and marked with a water-soluble felt marker. Resting motor threshold (RMT) was defined as the lowest stimulator output at which at least five MEPs with minimum peak-to-peak amplitude of 50 μV were evoked from the relaxed FDI in 10 consecutive trials. Active motor threshold (AMT) was determined as the minimum intensity required to evoke an MEP greater than 200 μV in at least five of ten consecutive trials whilst subjects maintained a tonic contraction of their right FDI at approximately 20 % of their maximum force. Visual feedback was provided using an oscilloscope. The protocol used for each experiment is shown in Fig. 1. Experiment 1: Stimulus–response curve protocol Corticospinal stimulus–response curves were constructed to investigate the influence of exercise on cortical excitability. Curves were constructed prior to, immediately following and 15 min following the low–moderate and moderate– high-intensity exercise interventions. TMS was delivered at six different stimulus intensities (seven stimuli per intensity): 90 % RMT, 110 % RMT, 120 % RMT, 130 % RMT, 140 % RMT and 150 % RMT.
13
Experiment 2: Short‑interval intracortical inhibition (SICI) protocol Short-interval intracortical inhibition was measured in the left M1 prior to, immediately following and 15 min following the low–moderate and moderate–high-intensity exercise interventions using a similar method to that described by Kujirai et al. (1993). SICI was investigated using interstimulus intervals (ISIs) of 2 and 3 ms and was recorded in two blocks of 30 consecutive trials (10 trials for each ISI plus 10 trials for the test stimulus alone) at each time point. Two conditioning stimulus (CS) intensities were investigated separately in different blocks: (1) 80 % AMT and (2) 90 % AMT. The test stimulus intensity was set to evoke MEPs with peak-to-peak amplitudes of 1 mV in the right FDI at rest in the absence of a CS. Data analysis and statistics All MEP data were recorded at high gain, and any trials contaminated with EMG activity were discarded. The peakto-peak amplitude of the MEP was calculated for each trial. In Experiment 1, the average amplitude was then calculated for each block of seven MEPs at each of the stimulus intensities (90 % RMT–150 % RMT). The stimulus response MEP data were analysed using a three-way repeated-measures analysis of variance (rANOVA) with TIME (three levels: pre-exercise, 0 min post-exercise and 15 min postexercise), EXERCISE (two levels: low–moderate and moderate–high) and STIMULUS INTENSITY (six levels: 90 % RMT, 110 % RMT, 120 % RMT, 130 % RMT, 140 % RMT and 150 % RMT) as within-subject factors. In Experiment 2, the average peak-to-peak amplitude was calculated for each block of ten MEPs at each of the ISIs, for each of the CS intensities and for the test response alone. Then, the average MEP amplitude at each ISI and for each of the CS intensities was expressed as a percentage of the test response alone. Data for SICI were analysed using a four-way rANOVA with EXERCISE (two levels: low–moderate and moderate–high), TIME (three levels: baseline, 0 min post-exercise and 15 min post-exercise), CS INTENSITY (two levels: 80 % AMT and 90 % AMT) and ISI (two levels: 2 ms and 3 ms) as the within-subject factors. Post hoc analyses were performed using paired t tests or pairwise comparisons using Bonferroni correction. To determine whether the CS evoked significant SICI, MEP data were analysed using a one-way rANOVA with ISI (three levels: test, 2 ms and 3 ms) for both the 80 % CS intensity and 90 % CS intensity conditions. Covariate analyses of age, self-reported physical activity and gender were conducted for all baseline SICI measures. In all rANOVA, where assumptions of sphericity were violated, the critical value of F was adjusted by the
13
Exp Brain Res
Greenhouse–Geisser Epsilon value from the Mauchly test of sphericity. In all tests, a value of P ≤ 0.05 was considered to be statistically significant.
Results Subject characteristics Age, RHR and baseline RMT did not differ between the two experiments (Table 1). No participants reported any side effects to TMS or the exercise. All results are expressed as mean ± SD unless otherwise stated. Experiment 1: Effect of aerobic exercise on stimulus– response curves There was no change in RMT (expressed as a percentage of maximal stimulator output) following exercise at both the low–moderate and moderate–high intensities (low–moderate t[6] = 0.3, P = 0.8 NS and moderate–high t[6] = −1.8, P = 0.1 NS) (Table 1). The group mean stimulus–response curves recorded before and at 0 and 15 min following each of the exercise intensities are shown in Fig. 2. As expected, MEP amplitude increased with increasing stimulus intensity (F[4, 32] = 13.7, P > 0.001). However, there were no other significant main effects for TIME (F[2, 12] = 0.4, P = 0.9 NS) or EXERCISE (F[1, 6] = 0.4, P = 0.6 NS) and no interactions between the two. Experiment 2: SICI is reduced following exercise At baseline, test MEPs were significantly inhibited to approximately 63 % of test amplitude at 2 ms and 67 % at 3 ms when conditioned at 80 % AMT (F[2, 24] = 30.4, P =
