Modulating Brain Excitability with Cardiovascular Exercise in Chronic Stroke: A Randomized Controlled Trial

Abstract

Background:

Corticospinal excitability (CSE) is a surrogate measure of neuroplasticity within the corticospinal tract measured with transcranial magnetic stimulation (TMS). A single bout of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) cardiovascular exercise (CE) have been both demonstrated to transiently augment CSE in people with stroke. However, the effect of multiple sessions of CE and exercise intensity is unknown.

Objectives:

We conducted a randomized controlled trial (NCT03614585) to examine the effect of a HIIT vs. MICT CE program on CSE measures obtained using TMS applied on the ipsilesional (ILH) and contralesional (CLH) hemispheres.

Methods:

Fifty-six individuals with cortical and/or subcortical stroke lesions in the chronic phase of stroke recovery (>6 months) were randomly assigned to a 12-week HIIT (n = 28) or MICT (n = 28) program. CSE measures were obtained at baseline and post-intervention. Linear mixed model analyses were conducted to compare changes in CSE measures and their respective interhemispheric ratios.

Results:

CSE changes were not significantly different between HIIT and MICT but exploratory analyses showed that, when analyzed together, both groups increased resting motor evoked potential (MEP) amplitude (P = .003), decreased resting motor threshold (rMT) (P = .030), and reduced intracortical facilitation (ICF) (P = .049) in the ILH. No CSE changes in the CLH were observed. HIIT and MICT rebalanced interhemispheric rMT (P = .020) and ICF ratios (P = .040), and increased resting MEP amplitude ratio (P = .020).

Conclusions:

Chronic CE increases excitatory ILH CSE measures and reduces interhemispheric imbalances but intensity does not have a moderating effect. More studies are needed to determine the functional relevance of exercise-induced changes in CSE in post-stroke recovery.

Keywords

stroke cardiovascular exercise brain excitability transcranial magnetic stimulation GABA glutamate

Introduction

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that can assess structural and functional changes in the corticospinal tract (CST), a structure whose functional integrity is key for upper limb motor recovery post-stroke.¹ Promoting neuroplasticity to optimize recovery is a primary goal of stroke rehabilitation.² Corticospinal excitability (CSE), assessed with TMS, is a surrogate measure of neuroplasticity in the CST that can be used to investigate whether interventions like cardiovascular exercise (CE) change the brain to potentially impact motor recovery.³

A stroke usually reduces the excitability of the ipsilesional hemisphere (ILH), disrupting interhemispheric CSE balance.⁴ However, during stroke recovery, a dynamic rebalance of CSE driven by excitatory and inhibitory activity regulates processes underlying neuroprotection, neuronal repair and reorganization.⁵ Excitation and inhibition are mediated by glutamate and γ-aminobutyric acid (GABA) receptors, respectively.⁵ The action of these 2 neurotransmitters, which has shown to be important for motor learning^6,7 and recovery^5,8 post-stroke, can be examined with single and paired-pulse TMS protocols.

Single-pulse protocols evaluate excitation and inhibition from motor representational areas of the primary motor cortex (M1), a therapeutic target area for motor recovery post-stroke.⁹ Corollaries of reduced excitability such as the absence of motor-evoked potentials (MEP)¹⁰ and/or higher resting motor thresholds (rMT)¹¹ in the ILH have usually been associated with motor impairment and poor recovery.¹² Single-pulse protocols can also assess intracortical inhibition by examining the cortical silent period (CSP), a marker that has been associated with GABA_B receptors activity.¹³

Paired-pulse TMS protocols can measure intracortical facilitation (ICF) and short-interval intracortical inhibition (SICI). These 2 CSE measures provide, respectively, information on glutamate and GABA_A activity in cortical circuits involved in post-stroke motor learning^6,7 during recovery.^5,8 Symmetry between the ILH and contralesional hemisphere (CLH) in both single and paired-pulse CSE measures has been also been identified as a marker of post-stroke recovery,¹⁴ with interhemispheric CSE balance associated with better motor outcome.¹

Regular cardiovascular exercise (CE) mitigates the risk of stroke recurrence, improves cardiorespiratory, metabolic and functional outcomes,¹⁵ and has shown promise in promoting neuroplasticity.^16,17 In stroke animal models, CE upregulates neurotrophins such as brain-derived neurotrophic factor (BDNF),¹⁸ a protein that affects excitatory and inhibitory mechanisms, and promotes positive adaptations such as reductions in lesion size, synaptogenesis, and dendritic growth.¹⁹ In humans, CE has also shown to stimulate neuroplastic mechanisms leading to adaptations that can be captured with CSE.^3,20

Higher CE intensities promote greater upregulation of neurotrophins^21,22 and changes in excitation and inhibition.^22-24 In neurotypical individuals, a single bout of high-intensity CE elicits greater increases in excitability and reductions in inhibition compared to moderate-intensity exercise.^22,25 In individuals post-stroke, acute high-intensity exercise increases MEP amplitude in the ILH,²⁶ rebalances SICI interhemispheric ratios, and improves motor learning.²⁷ In contrast, acute light and moderate-intensity CE does not change CSE.^28,29 Furthermore, a single bout of high-intensity interval training (HIIT) produces greater increases in CSE in the ILH than a bout of moderate-intensity continuous training (MICT).^20,29

Evaluating the long-term neuromodulation effect of CE on CSE requires multiple bouts of exercise, yet there is not enough evidence supporting the effect of chronic CE on CSE post-stroke.^30,31 Even less is known about the impact of exercise intensity. We conducted a 12-week randomized controlled trial (RCT) comparing HIIT and MICT on CSE in individuals in the chronic stage post-stroke (>6 months post-stroke). We hypothesized that both types of exercise would modulate CSE but that the higher intensities achieved during HIIT would produce greater increases in excitability and reductions in inhibition of the ILH, and that these changes would improve interhemispheric CSE balance.

Methods

Study Design

This RCT study conformed to the standards set by the Declaration of Helsinki and was registered in a clinical trials database (Clinicaltrials.gov, NCT03614585) and was approved by the local research ethics board (CRIR-1310-0218). Informed consent was obtained from all participants of the RCT, which was conducted at the Jewish Rehabilitation Hospital (JRH, Laval, QC, Canada) and McMaster University (Hamilton, ON, Canada) between September 2019 to December 2024. However, due to COVID restrictions, TMS assessments were performed exclusively at the JRH. Assessments were performed at baseline (T0) and post-intervention (T1). A follow-up assessment (T2) took place 8 weeks after T1, but T2 data is reported in a separate manuscript. Age, sex, time since stroke event, stroke location and type, and medication use were collected at baseline. Measures of disability, degree of neurological deficit, upper-limb motor function, physical activity, and global cognitive function were also recorded. Further details on the design of the RCT can be found in the published protocol.³²

Participants

Individuals who were 40-80 years old and 6-60 months after first-ever single ischemic or hemorrhagic stroke confirmed by magnetic resonance imaging or computed tomography were recruited. The chronic phase of stroke recovery (>6 months post-stroke),³³ was chosen to reduce the CSE variability commonly observed in earlier phases of recovery.⁸ Participants were excluded if they presented with contraindications to TMS.³⁴ More details on inclusion/exclusion criteria are provided in the protocol.³²

Only participants with lesions located in cortical or subcortical structures were included in the analyses. Individuals with brainstem or cerebellum lesions were excluded because the spatial resolution of applying TMS on M1 limited targeting to mostly surface cortical structures and interhemispheric ratios cannot be reliably estimated when the lesion is located in brainstem or cerebellum.³⁵ Participants with subcortical lesions were included because subcortical structures may be reached through trans-synaptic cortico-subcortical connections.³⁶

Randomization and Blinding

A computer-generated group assignment (www.randomizer.org) using a 1:1 allocation ratio was used to randomize participants into HIIT or MICT. Investigators not involved in recruitment, consent or data collection (MR and AT) generated the random allocation sequence. Randomization for the JRH site was conducted by the counterpart site, and allocation was concealed until after obtaining participant consent and completing baseline assessments. TMS assessors were not blinded to group allocation due to resource limitations.

Exercise Interventions

HIIT and MICT involved 12 weeks of training performed 3 days/week on recumbent steppers (NuStep T4r; NuStep LLC, Ann Arbor, MI, United States). Sessions were held on alternate days to maximize recovery and adaptations.³⁷ Participants were instructed to not engage in other structured exercise programs during study participation. Prescription of exercise intensity for HIIT or MICT was determined using a cardiopulmonary exercise test³⁸ performed at T0. Details on the test and heart rate reserve (HRR) method³⁹ used for exercise prescription are provided elsewhere.³²

HIIT sessions involved 10 × 1 minute high intensity bouts (80-100% of HRR) interspersed with 9 × 1 minute of active recovery at low intensity (30% HRR). High-intensity bouts targeted 80% HRR and progressively increased 10% every 4 weeks. For MICT, participants initially exercised at 40% HRR for 20 minutes, and progressively increased intensity 10% HRR and duration 5 minutes every 4 weeks. Both protocols included a 3-minute warm-up and 2-minute cool-down periods at 30% HRR. Total session duration of HIIT was 24 minutes and for MICT from 25 to 35 minutes. HR was monitored using sensors (Polar Electro Oy, Kempele, Finland) and rate of perceived exertion (RPE) with the 6-20 Borg scale.⁴⁰

Transcranial Magnetic Stimulation Procedures

TMS assessments at T0 and T1 were held at a similar time of day to minimize circadian variations. Positioning of head, hands, and arms including the angles of seat recline and arm placement were recorded at T0 and replicated at T1 to ensure consistency. The maximal voluntary contraction (MVC) of the muscles of the right and left hand was assessed using a custom script (LabView, National Instruments, Austin, Texas, USA).²⁷ Participants were instructed to “squeeze” a response hand-grip force transducer while visual feedback on force level was provided. They performed 2 trials per hand for 3 seconds, separated by a 30-second pause. The highest MVC for each hand was recorded.

TMS was applied by using a 70-mm magnetic coil and Bistim² stimulator (The Magstim Company, Whitland, United Kingdom). Neuronavigation (Brainsight, Rogue Research, Montréal, Canada) was used to co-register participant head dimensions to a MRI template for the purposes of stimulation targeting and recording accurate coil position. The coil was oriented at a 45° angle from the mid-line with the handle pointing posteriorly. Monophasic stimulation pulses were applied bilaterally, in a posterior-anterior direction, on representational areas of the first dorsal interosseous (FDI) muscle of while participants were seated. The FDI is involved in common upper limb actions such as grasping objects and its activation can be elicited with low stimulation intensities.¹³ MEPs amplitude was measured bilaterally by recording electromyographic (EMG) activity using 2 Ag-Cl surface electrodes (Ambu, Copenhagen, Denmark). EMG data were acquired at 2000 Hz with a gain of 300 Hz and filtered using a high- and low-pass cut-off filter of 10 Hz and 500 Hz, respectively.

The optimal location to elicit an MEP (i.e., “hot-spot”) for each hemisphere was localized at T0.²⁷ During hot-spot identification, and rMT, resting MEP amplitude, SICI and ICF measurements, participants were asked to keep their eyes closed but to remain awake. Once the hot-spot was identified, the rMT of the ILH and CLH was determined (see procedures below). The hot-spot was saved and used at T1 to ensure consistency. After determination of the rMT at T0 and T1, single and paired pulse TMS measures were acquired. To minimize the potential effects of repetitive TMS on MEP amplitude, single or paired pulses were applied 5 seconds apart. Twenty-five stimulations per hemisphere were delivered for each CSE measure.

Cortico-spinal Excitability Measures

Resting and Active Motor-evoked Potential Amplitude

The primary outcome of the study was the MEP amplitude,³² a CSE parameter that is an estimation of the net excitability of the CST, including direct excitation of corticospinal neurons and indirect excitation of tangential intra-and trans-cortical neurons.⁶ The average peak-to-peak MEP amplitude of each hemisphere, induced by a pulse at 120% of the rMT,^41,42 was determined during resting and active conditions. Assessing active MEP amplitude required participants to view a user interface (LabView, National Instruments, Austin, Texas, USA) to help maintain a constant muscle contraction of 10% MVC. MEP amplitude was expressed in millivolts (mV), with increases reflecting greater excitability.⁴³

Resting Motor Threshold

The rMT reflects cortico-cortical axonal excitability⁴⁴ and is defined as the lowest stimulation intensity that evokes an MEP of an amplitude of 0.05 mV. ILH and CLH rMTs were determined by identifying the minimum stimulator intensity to elicit 5 MEP amplitudes of a minimum of 0.05 mV from 10 consecutive stimulations.¹³ The rMT was expressed as a percentage of maximum stimulator output (%MSO) intensity, with lower output indicating greater excitability.

Cortical Silent Period

The CSP provides information about the inhibition mediated by GABA_B receptors,¹³ with an increase in CSP duration reflecting greater inhibition. The CSP was obtained from the EMG activity of 25 stimulations elicited at an intensity of 120% rMT during the active MEP amplitude protocol. First, the baseline EMG signal amplitude during the muscle contraction was measured 200 ms before stimulation. The CSP was then determined by recording the duration of time (ms) between the end of the MEP and the recovery of voluntary EMG activity (i.e., increase of 2 standard deviations above the mean baseline signal amplitude).^13,27

Short Intracortical Facilitation and Inhibition

Short Intracortical Facilitation (ICF) and inhibition (SICI) provide information of facilitation mediated by N-methyl-D-aspartate (NMDA) and GABA_A receptors, respectively.¹³ ICF and SICI were measured using a paired pulse TMS protocol, with an unconditioned pulse of 80% rMT, followed by a conditioned pulse of 120% rMT. The ICF and SICI protocols administered unconditioned and conditioned pulses with an interstimulus interval (ISI) of 12 and 2.5 ms, respectively.⁹ The mean conditioned MEP amplitude was normalized to the mean resting MEP amplitude to estimate facilitation (ICF) or inhibition (SICI)⁷ using the following equation:

\frac{c o n d i t i o n e d M E P A m p l i t u d e}{n o n c o n d i t i o n e d M E P A m p l i t u d e} \times 100 = I C F (%) o r S I C I (%)

An increase in ICF and SICI values indicated an increase in intracortical facilitation and reduction in inhibition, respectively.

Interhemispheric Ratios

Interhemispheric balance between ILH and CLH CSE measures was determined by calculating their ratio. Ratio values > 1.0 indicated that interhemispheric asymmetry favored the ILH, and values < 1.0 favored the CLH. A ratio favoring the ILH or CLH for resting and active MEP amplitude and rMT would indicate greater excitability in the favored hemisphere of the ratio. This also applied with respect to facilitation (ICF) and inhibition (CSP and SICI). A ratio approaching 1.0 indicates equilibrium between ILH and CLH.

Transcranial Magnetic Stimulation Data Processing

Frame-by-frame analysis of EMG recordings were conducted using Signal (Cambridge Electronic Design, Cambridge, UK). Recordings with abnormal EMG activity with, respect to amplitude, such as preceding MEPs (>0.05 mV) within 300 ms before stimulation or excessive EMG activity (>0.05 mV) on the opposite hand were removed from analysis. The average peak-to-peak MEP amplitude for single and paired-pulse TMS data from the ILH and CLH was taken at T0 and T1. Data were screened for outlier values > 3 standard deviations of the group mean. Of all the frames collected, 0.027% were determined to be outliers or were removed due to physiological factors and study procedures that led assessors to conclude that removal was justified.

Sample Size Estimation

Using the results of a previous study that found a 5% increase in CSE after a single bout of HIIT in people with chronic stroke,⁴⁵ we estimated that we would require 32 participants per group (n = 64 total) to detect a similar difference between groups at T1 in the resting MEP amplitude. The statistical package G*Power was used to determine the sample size required to obtain a power of 80% (alpha < 0.05).

Statistical Analysis

Data were analyzed using intention-to-treat analyses. The results of the analyses performed as per protocol are presented in supplementary files ( Supplementary Tables 21–38 ). Participant demographics (Table 1) and training characteristics (Table 2) data were presented as means ± standard deviation (SD) and or medians (interquartile range [IQR]) for parametric and non-parametric data, respectively. Categorical data were presented as frequencies (n, %). Group differences in participant demographic and training characteristic data were determined using independent t-tests or Wilcoxon rank-sum tests for parametric and non-parametric data, respectively.

Table 1.

Participant Demographics.

Variable	HIIT	MICT
N	28	28
Sex (% of group)
Female	9 (32)	11 (39)
Male	19 (68)	17 (61)
Age, years (median, [IQR])	67.0 (7.9)	65.8 (8.9)
Time post-stroke, months (median, [IQR])	21.4 (15.8)	19.1 (15.0)
Type of Stroke
Ischemic	23	23
Hemorrhagic	5	5
Location of Stroke
Cortical	7	8
Subcortical	21	20
Medication
SSRI	4	4
TCA	1	1
Atypical antidepressant	5	2
Benzodiazepine	0	2
Muscle relaxant	1	2
Beta blocker	7	3
mRS (median, [IQR])	1.0 [1.8]	1.0 [1.8]
NIHSS (median, [IQR])	0.5 [2]	1.0 [2]
CMSA ILH hand (median, [IQR])	6 [3]	6 [2]
CMSA ILH arm (median, [IQR])	6.0 [2.8]	6.5 [2.8]
MVC, N; ILH hand (mean, [SE])	0.7 (0.5)	0.8 (0.4)
MVC, N; CLH hand (mean, [SE])	0.7 (0.3)	0.9 (0.5)
BMI (kg m²)	28.5 (5.5)	29.6 (9.4)
PASIPD (MET, median [IQR])	10 (15.5)	9.3 (21.9)
V̇O₂ peak (mL kg⁻¹ min⁻¹)	16.9 (5.0)	17.0 (6.2)

Abbreviations: n, number of participants; SSRI, selective serotonin reuptake inhibitor; TCA, tricyclic antidepressant; mRS, modified Rankin Scale; IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale; CMSA, Chedoke McMaster Stroke Assessment; ILH, ipsilesional hemisphere; N, newton; CLH, contralesional hemisphere; MVC, maximum voluntary contraction; BMI, Body mass index V̇O₂peak, peak oxygen uptake; PASIPD, Physical Activity Scale for Individuals with Disabilities; MET, metabolic equivalents.

Values are reported as means and standard deviation (SD), unless specified otherwise.

Table 2.

Training Characteristics.

Measure	HIIT	MICT	P
Heart rate zone time (%)
<40% HRR	6.4 (4.8)	15.2 (15.4)	<.01
40-59% HRR	17.2 (8.9)	46.7 (19.8)	<.0001
≥60% HRR	71.7 (12.6)	26.2 (23.3)	<.0001
Median RPE (IQR)	13 (2.0)	9 (3.8)	<.001

Abbreviations: HR, heart rate; HRR, heart rate reserve; RPE, rate of perceived exertion; IQR, interquartile range.

Data presented as mean (SD), unless specified otherwise.

Estimates of the effect of HIIT or MICT at T0 and T1 on CSE measures and respective interhemispheric ratios were determined using linear mixed models (LMMs) for repeated measures, which allowed for the correlation of repeated measures within subjects and missing data, as long as data were missing at random.⁴⁶ Bayesian Information Criterion and log-likelihood ratio tests were used to determine the most appropriate covariance structure.

A LMM for each CSE measure included fixed effects of group, time, and group × time interactions. The LMM for ILH and CLH measures included the MVC of the respective hemisphere as a covariate and the LMM for interhemispheric ratios included the ILH:CLH ratio of MVC as a covariate.⁴⁷ The same LMM structure was used to estimate the effect of HIIT and MICT on upper-limb function using the Chedoke-McMaster Assessment Scale.

LMM estimates and fit parameters, 95% confidence intervals (CI), and P-values for group, time, and group × time interactions are presented in Supplementary Tables 1–18 . Post-hoc student’s t tests were performed to detect statistically significant differences in between and within-group pairwise comparisons. Details of these tests are also reported in Supplementary Tables 19–20 . Statistical significance was set at P < .05. All analyses were conducted using JMP®, Version 17.0. (SAS Institute Inc., Cary, North Carolina, United States).

Results

Fifty-six participants were randomized to HIIT (n = 28) or MICT (n = 28). Participants’ characteristics, including upper-limb impairment, were similar between groups at T0 (Table 1). The trial flow, including dropouts and missing TMS data, is described in Figure 1. HIIT participants spent significantly more time at high exercise intensities (P < .0001, mean percentage [SD]: 71.7% [12.6], Table 2), and reported a significantly higher median RPE (P < .001, median RPE [IQR]: 13 [2], Table 2) compared to the MICT group. Hand (F[1,35.2] = 0.74, P = 0.39) and arm (F[1,31.9] = 1.01, P = 0.32) function did not change significantly in response to training and there were no differences between groups (F[1, 35.2] = 1.96, P = 0.17 and F[1,31.9] = 0.07, P = 0.79). No adverse events were recorded during TMS assessments or during the interventions.

Figure 1.

Flow chart of the randomized controlled trial.

Cortico-spinal Excitability Measures

Estimated means of CSE measures at T0 and T1 are presented in Figure 2. No group × time interactions were observed (F[1,37.1] = 1.14, P = 0.29) but significant time effects for the resting MEP amplitude on the ILH were found (F[1,37.0] = 8.69, P = .003). Exploratory pairwise comparisons revealed significant within-group increases in resting MEP amplitude in the HIIT group only (Figure 2(A), Supplementary Table 19 ). Similarly, the LMM for rMT revealed no group × time interactions (F[1,36.8] = 1.89, P = 0.18) but significant time effects for ILH rMT (F[1,36.8] = 4.49, P = .03). Exploratory pairwise comparisons revealed significant within-group decreases in this CSE measure in the MICT group only (Figure 2(C), Supplementary Table 19 ).

Figure 2.

Change in cortico-spinal excitability T0-T1. (A) Resting MEP amplitude. (B) Active MEP amplitude. (C) Resting Motor Threshold. (D) Cortical Silent Period. (E) Intracortical Facilitation. (F) Short-interval Intracortical Inhibition.

The LMM for ICF of the ILH did not reveal a significant group × time interaction (F[1,43.7] = 0.03, P = 0.86), but a significant time effect (F[1,43.7] = 4.07, P = .049). Exploratory pairwise comparisons, in contrast, did not reveal significant between- or within-group changes in HIIT or MICT ( Supplementary Table 19 ).

No significant group effect was observed in any ILH or CLH CSE measure ( Supplementary Tables 1–12) . Similarly, no group × time interaction or time effect was observed for ILH active MEP amplitude, CSP, and SICI ( Supplementary Tables 2, 4, 6 ) or for any CLH measure (Supplementary Tables 6–12).

Interhemispheric Ratios

Estimated means of interhemispheric ratios are presented in Figure 3. No group × time interactions were observed for any CSE ratios ( Supplementary Tables 13–18 ). Time effects were observed for resting MEP amplitude (F[1,40.7] = 5.94, P = .02), with the ratio favoring the ILH. Pairwise comparisons revealed a significant change from T0-T1 in resting MEP amplitude ratio in HIIT participants, favoring the ILH (Figure 3(A), Supplementary Table 20 ). Time effects suggestive of a movement toward ILH:CLH equilibrium were observed for the rMT ratio (F[1,36.1] = 6.44, p = .02). Exploratory pairwise comparisons revealed significant within-group change in the MICT group only (Figure 3(C), Supplementary Table 20 ).

Figure 3.

Interhemispheric ratios T0-T1. (A) Resting MEP amplitude. (B) Active MEP amplitude. (C) Resting Motor Threshold. (D) Cortical Silent Period. (E) Intracortical Facilitation. (F) Short-interval Intracortical Inhibition.

Time effects were also observed for the ICF ratio (F[1,35.8] = 4.35, P = .04), indicating a change towards ILH:CLH equilibrium (Figure 3(E)). However, despite a trend for within-group T0-T1 change in MICT (P = .07), exploratory pairwise comparisons did not reveal significant within-group changes ( Supplementary Tables 20) . LMMs for interhemispheric ratios did not reveal time effects for active MEP amplitude, CSP and SICI ratios ( Supplementary Tables 14, 16, 18) .

Discussion

This is the first study examining the potential neuromodulatory effect of HIIT and MICT on CSE in individuals with chronic stroke. Regardless of the training intensity, 12 weeks of CE modulated excitability by increasing resting MEP amplitudes and reducing rMTs in the ILH. We also observed reductions in facilitation (ICF) in the same hemisphere. Measures of inhibition, CSP and SICI, and active MEP excitability did not change significantly. Notably, changes in excitability and facilitation were exclusive to the ILH, which is usually the most affected hemisphere in terms of CSE.⁴⁸

While group × time interactions revealed no significant differences between groups, time effects for MEP amplitudes, rMTs, and ICF were significant. Exploratory pairwise analyses showed that, compared to baseline values, HIIT produced increases in resting MEP amplitude and MICT reductions in rMT. Analyses of interhemispheric ratios showed that ILH-specific changes in excitability and facilitation promoted a re-balancing of interhemispheric activity in rMT and ICF, in addition to a prioritization of the ILH in resting MEP amplitude ratio. ILH:CLH ratios mirrored group-specific within-group changes of ILH excitability and facilitation measures. Taken together, these findings show that CE has a positive effect on excitatory CSE measures in the ILH and that intensity does not have a clear moderating effect.

The increased resting MEP amplitude in ILH observed in this study aligns well with the CSE responses reported in some, but not all, previous acute-CE stroke studies.³ Acute studies showing significant CSE responses have demonstrated that a single bout of exercise performed at moderate or high exercise intensity tends to transiently increase ILH MEP amplitude.^26,49 For example, Forrester et al,⁴⁹ observed an increase in resting MEP amplitude of the paretic vastus medialis following a submaximal bout of treadmill walking. Similarly, Li et al,²⁶ found a significant increase in ILH MEP amplitude in the extensor-carpi-radialis muscle of the hand after a 5-minute high-intensity bout of treadmill walking. Acute CE may transiently increase cortical concentrations of glutamate,²³ which acts on neuronal and synaptic NMDA receptors⁵⁰ increasing the excitatory activity of the CST,⁵¹ potentially via upregulation of BDNF.^52,53 Our results suggest that chronic CE exposure may trigger long-term adaptations in neural circuitry that lead to changes in MEP amplitude, similar to those reported in acute studies.

The reductions of rMT observed in this study have not been reported in previous acute CE stroke studies.³ However, it should be noted that, because the rMT is usually employed to establish the TMS intensity needed for assessing other CSE measures (e.g., MEP amplitude), post-exercise changes in rMT in acute studies are not always assessed or reported.³ Abraha et al,²⁹ compared an acute bout of HIIT and MICT in 12 individuals with chronic stroke and found that neither protocol produced significant changes in ILH or CLH rMT. In contrast, Boyne et al,²⁰ found significant reductions in the MT of the ILH after a single bout of treadmill HIIT in 16 individuals with chronic stroke. It should be noted, however, that the threshold was assessed during an active contraction and not at rest.

To date, 2 smaller CE studies involving people in the chronic post-stroke period (n = 14³¹ and n = 18,³⁰ respectively) have found similar reductions in ILH rMT after 4 weeks of body-weight support treadmill training. Reductions in rMT and augmentation of MEP amplitude have also been observed in neurotypical individuals after 12 weeks of moderate-intensity CE.⁵⁴ Our study corroborates these findings and also shows that 12 weeks of CE reduces ILH rMT regardless of the training intensity.

We hypothesized that CE would induce increases in facilitation and reductions in inhibition in the ILH. Instead, we found a reduction in facilitation (ICF) and no significant changes in inhibition measures (CSP and SICI). The reduction of facilitation is a novel finding that has not yet been reported in acute or chronic CE stroke studies,³ and that is consistent with some, but not all, acute CE studies in neurotypical individuals.⁵⁵ It should be noted, however, that similar ICF reductions and null changes in SICI have been described in a study with neurotypical sedentary males who underwent 6 weeks of HIIT.⁵⁶

ICF represents the net facilitation of cortical circuits comprising excitatory neurons, mediated by NMDA receptors, and to a lesser extent, inhibitory interneurons mediated by GABA.⁴⁴ Our sample showed a relatively high level of facilitation in the ILH at T0 (Figure 2(E)), a finding which is uncommon post-stroke.⁴⁸ It should be noted, however, that when compared directly, differences between hemispheres in ICF at T0 were not statistically significant (P = 0.2384) and that the higher ICF observed in the ILH was driven by a small set of observations with disproportionally higher values. Regardless, it is possible that rather than a net facilitatory effect, chronic CE could have had a homeostatic normalization effect, reducing the abnormally high levels of facilitation in the ILH, thus maintaining CSE within a physiological range.⁵⁶ The unexpected increases in intracortical inhibition at T1 (Figure 2(D) and (F)),^20,27 albeit non-significant, could have also contributed to suppress the high levels of facilitation observed in this hemisphere. Future research is required to investigate the effect of chronic CE-induced reductions in facilitation and underlying mechanisms, as well as the role of inhibition post-stroke.³

HIIT and MICT-mediated change in ILH excitability and facilitation measures led to changes in interhemispheric ratios. Specifically, we found that exercise had a rebalancing effect in the ILH:CLH ratio of rMT and ICF and that the ratio of resting MEP amplitude further prioritized ILH. Our results contrast with a previous acute-CE study by Nepveu et al,²⁷ that found that a graded maximal exercise test elicited a rebalancing of ILH:CLH SICI ratio and no significant changes in the same CSE measures. However, an important limitation of this study was the lack of standardization of the exercise bout in terms of duration and intensity,²⁷ both of which may have been insufficient to induce change in CSE.

When also considering the lack of change observed in the study by Abraha et al,²⁹ who compared a similar battery of CSE measures after 25 minutes of HIIT and MICT, we conclude that the chronic CE paradigm used was probably the most important factor mediating our results. Since asymmetry of interhemispheric CSE is a hallmark of post-stroke motor impairment,⁵⁷ these results are promising. Chronic exposure to CE, regardless of the intensity of exercise used, may have a re-balancing effect on interhemispheric CSE in people in the chronic phase of stroke recovery.

Limitations

Due to COVID-related barriers to in-person clinical research and resource limitations, the present study did not attain the estimated study sample initially proposed.³² It is unknown if with a larger sample size, we could have detected significant differences between HIIT and MICT. The sample size, however, was enough to detect novel and significant change in CSE measures in response to CE. This study also recruited a sample size that is considerably larger than any TMS chronic CSE study published not only in patients post-stroke but also in neurotypical individuals.³

Blinding of assessors to group allocation was not possible after baseline assessments due to restrictions in available staffing resources. However, we implemented procedures to limit confounding effects from training and data collection.³² These included randomized group allocation to control for intergroup differences at baseline and application of strict standardized protocols to ensure consistency in TMS data collection and analysis.

Methodology pertaining to the application of TMS may have also influenced our findings and should be taken into consideration. First, for SICI we employed an ISI (2.5 ms) that has shown to suppress the MEP response⁵⁸ and that we have used in previous stroke studies.²⁷ The results of some studies, however, suggest that ISIs of 2 ms are more appropriate for SICI because longer ISIs may be influenced by facilitatory mechanisms, especially when the intensity of the conditioned stimulus is relatively high.⁵⁹ While we cannot rule out completely the potential influence of facilitatory mechanisms in SICI, clearly both the ISI and stimulation intensity used in our study were effective at reducing the conditioned MEP and produced inhibition. It is also important to note that SICI is a complex measure and that, compared to healthy individuals,⁵⁹ people with stroke may respond differently to different ISIs ranges (see for discussion⁶⁰).

Second, for assessing active MEP we used an stimulation intensity of 120% of the rMT. In principle, this intensity may increase the possibility of ceiling effects in the active MEP.⁶¹ It is important to note, however, that the risks of MEP saturation effects are usually seen at 30-40% of the MVC.⁶¹ Our study, in contrast, used very low levels of force (10% MVC), which reduced the risk of reaching ceiling effects in MEP amplitude during the active condition.

Some previous studies of acute and chronic CE for people in the chronic post-stroke period describe benefits to post-stroke motor learning and function.^27,31,62 Similarly, the same changes in CSE observed after CE have been associated with improvements in motor function in people post-stroke.⁶³ The present study was not designed to measure changes in motor function. We used the Chedoke-McMaster Assessment Scale to assess impairment for the hand and arm of the affected side (Table 1). However, the minimal changes in CMSA pre-post were not associated with changes in any CSE measure. The Fugl-Meyer assessment could have provided greater sensitivity for detecting change in response to exercise and associations with TMS measures but given the relatively high functional level of our sample and the fact that our intervention did not target specifically upper limb function, it is unlikely that CSE changes would have directly translated to changes in motor function.⁶³ We encourage future studies to examine associations between CSE change and measures of motor function to determine the clinical relevance of these findings.³

This RCT did not include a non-exercise control group, which could restrict comparisons on the extent of exercise-mediated effects. However, the selection of participants in the chronic stages of post-stroke recovery and the requirement that participants were not engaged in an ongoing exercise regimen or clinical services meant that participants were unlikely to experience spontaneous changes in CSE. Hence, it is unlikely that the changes in CSE observed in this study could be explained by factors unrelated to the CE interventions.

Conclusions

Relative to subacute stages of stroke recovery, the capacity to induce changes in neuroplasticity and the potential for further recovery in the chronic phase of stroke are diminished.² This RCT demonstrates that chronic exposure to CE has the potential to promote CSE changes in the ILH. Independently of exercise intensity, CE increased resting MEP amplitude and reduced rMT and ICF in this hemisphere. Importantly, these changes resulted in optimized interhemispheric equilibrium in rMT and ICF, as well as a prioritization of the ILH in resting MEP amplitude ratio. These findings provide support for the use of CE as a neuromodulation strategy in people with chronic stroke. Whether similar changes in CSE can be observed in more impaired individuals or in patients at earlier stages of stroke recovery, and the functional implications of these changes is yet to be elucidated.

Supplemental Material

sj-docx-1-nnr-10.1177_15459683251351883 – Supplemental material for Modulating Brain Excitability with Cardiovascular Exercise in Chronic Stroke: A Randomized Controlled Trial

Supplemental material, sj-docx-1-nnr-10.1177_15459683251351883 for Modulating Brain Excitability with Cardiovascular Exercise in Chronic Stroke: A Randomized Controlled Trial by Lynden Rodrigues, Kevin Moncion, Bernat De Las Heras, Jacopo Cristini, Roya Khalili, Janice J. Eng, Joyce Fung, Marilyn MacKay-Lyons, Alexander Thiel, Ada Tang and Marc Roig in Neurorehabilitation and Neural Repair

Footnotes

Author Contributions

Lynden Rodrigues: Formal analysis; Investigation; Methodology; Project administration; Validation; Writing - original draft.

Kevin Moncion: Methodology; Writing - review & editing.

Bernat De las Heras: Investigation; Writing - review & editing

Jacopo Cristini: Investigation; Writing - review & editing.

Roya Khalili: Investigation; Writing - review & editing.

Janice Eng: Conceptualization; Writing - review & editing.

Joyce Fung: Conceptualization; Writing - review & editing.

Marilyn MacKay-Lyons: Conceptualization; Writing - review & editing.

Alexander Thiel: Conceptualization; Writing - review & editing.

Ada Tang: Conceptualization; Funding acquisition; Methodology; Project administration; Supervision; Writing - review & editing.

Marc Roig: Conceptualization; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Supervision; Writing - review & editing.

Data Availability

Data from this manuscript is available upon request from the corresponding author.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Lynden Rodrigues is supported by a postdoctoral Scholarship from StrokeCog. Kevin Moncion is supported by a postdoctoral scholarship from the Canadian Institutes of Health Research (CIHR). Janice Eng is supported by the Canada Research Chairs program. Marc Roig is supported by a Salary Award (Junior II) from Fonds de Recherche Santé Québec (FRQS). This project was funded by a project grant from CIHR (388320).

ORCID iDs

Kevin Moncion

Bernat De Las Heras

Jacopo Cristini

Janice J. Eng

Marilyn MacKay-Lyons

Ada Tang

Marc Roig

Supplementary material for this article is available on the Neurorehabilitation & Neural Repair website along with the online version of this article.

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