Eccentric cycling enhances primary motor cortex excitability

Eccentric cycling enhances primary motor cortex excitability | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Eccentric cycling enhances primary motor cortex excitability View ORCID Profile Layale Youssef , Amanda O’Farrell , View ORCID Profile Nesrine Harroum , Younes Bakhta , Liora Cohen , View ORCID Profile Benjamin Pageaux , Jason L. Neva doi: https://doi.org/10.1101/2025.07.04.663236 Layale Youssef 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada 2 Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM) , Montréal, Québec, Canada 3 Centre Interdisciplinaire de Recherche sur le Cerveau et l’Apprentissage (CIRCA) , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Layale Youssef For correspondence: layale.youssef{at}umontreal.ca Amanda O’Farrell 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada 2 Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM) , Montréal, Québec, Canada 3 Centre Interdisciplinaire de Recherche sur le Cerveau et l’Apprentissage (CIRCA) , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nesrine Harroum 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada 2 Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM) , Montréal, Québec, Canada 3 Centre Interdisciplinaire de Recherche sur le Cerveau et l’Apprentissage (CIRCA) , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nesrine Harroum Younes Bakhta 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Liora Cohen 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Benjamin Pageaux 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada 2 Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM) , Montréal, Québec, Canada 3 Centre Interdisciplinaire de Recherche sur le Cerveau et l’Apprentissage (CIRCA) , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Benjamin Pageaux Jason L. Neva 1 École de kinésiologie et des sciences de l’activité physique (EKSAP), Faculté de médecine, Université de Montréal , Montréal, Québec, Canada 2 Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM) , Montréal, Québec, Canada 3 Centre Interdisciplinaire de Recherche sur le Cerveau et l’Apprentissage (CIRCA) , Montréal, Québec, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Preview PDF Abstract Acute aerobic exercise (AAE) can modulate primary motor cortex (M1) excitability. To date, studies evaluating the effects of AAE on M1 excitability have focused almost exclusively on concentric cycling. Interestingly, eccentric cycling increases frontal-parietal brain activation more than concentric cycling. Critically, we recently found eccentric AAE enhances motor learning more than concentric AAE. Yet, the M1 excitability mechanisms underlying these effects remain unknown. Thus, the objective of this study was to evaluate the effect of eccentric cycling AAE on M1 excitability using transcranial magnetic stimulation (TMS). Thirty adults performed three 20 min-conditions: i) eccentric cycling AAE, ii) concentric cycling AAE, and iii) rest. Cycling AAE was carried out at a workload corresponding to 70% of peak heart rate (%HR peak ) measured during concentric incremental cycling exercise. TMS assessments were conducted before (Pre), immediately (Post 0 ) and 20 minutes after (Post 20 ) AAE/rest to evaluate changes in corticospinal excitability (CSE) and short interval-intracortical inhibition (SICI). We found CSE increased and SICI decreased at Post 20 following eccentric and concentric cycling AAE compared to rest. Also, %HR peak , muscle pain and perceived effort were lower during eccentric cycling AAE compared to concentric cycling AAE. Our results showed that eccentric cycling impacted M1 excitability change to a comparable degree as concentric cycling, while requiring less cardiovascular response, eliciting less muscle pain and lower perceived effort. Taken together, our results suggest that eccentric cycling AAE may be a valuable intervention to modulate M1 excitability for populations with limited cardiovascular capacity and have potential implications in clinical and sports-related contexts. New and Noteworthy This study demonstrates that both eccentric and concentric cycling exercise enhance corticospinal excitability and reduce short-interval intracortical inhibition. Additionally, eccentric cycling elicited significantly lower cardiovascular and perceptual responses compared to concentric cycling. These findings suggest that eccentric cycling may be a useful intervention for individuals with limited exercise capacity, such as clinical or aging populations. Introduction Acute aerobic exercise (AAE) has been shown to promote neuroplasticity [ 1 – 4 ] and motor learning [ 5 – 8 ]. Investigations employing transcranial magnetic stimulation (TMS) have contributed to our understanding of the influence of AAE on human brain plasticity [ 1 , 9 – 13 ]. A single bout of cycling aerobic exercise has been shown to enhance the brain’s receptiveness to repetitive TMS protocols designed to induce primary motor cortex (M1) neuroplasticity. This suggests that AAE may serve a preparatory or “priming” role in facilitating neural plasticity [ 5 , 12 – 14 ]. Further work has investigated the neurophysiological mechanisms underlying AAE-enhanced neuroplasticity, using methods of single- and paired-pulse TMS to understand the impact of AAE on M1 excitability [ 1 , 3 , 4 , 9 , 10 , 14 – 16 ]. These studies have shown that lower-limb cycling AAE modulates various inhibitory and facilitatory circuitry within the non-exercised upper-limb representation in M1 [ 1 , 9 , 10 , 12 ]. Our recent meta-analysis showed that among the various TMS-based measures of M1 excitability, short-interval intracortical inhibition (SICI) was most consistently decreased and corticospinal excitability (CSE) can be increased [ 1 ]. However, the vast majority of studies assessing M1 excitability changes following lower limb cycling AAE have used the concentric muscle contraction modality, commonly referred to as concentric cycling. As a result, the impact of the eccentric muscle contraction mode during lower limb cycling AAE on M1 excitability remains unclear. Eccentric cycling is a less conventional type of lower limb cycling exercise, which involves contracting the quadriceps with muscle fiber lengthening while resisting a generated force that drives the bike pedals in a backwards cycling motion [ 17 ]. Unlike conventional concentric cycling, which involves muscle shortening to generate movement, eccentric cycling presents the advantage of producing greater power output while eliciting a lower physiological demand on the cardiovascular, respiratory, and metabolic systems [ 18 – 21 ]. Also, eccentric cycling has shown promising applicability for individuals with cardiorespiratory limitations [ 22 ] and older adults [ 23 ]. As a result, there has been growing interest in incorporating eccentric cycling into clinical rehabilitation settings [ 22 , 24 ] as well as in experimental research [ 18 , 20 , 25 ]. Eccentric contraction exercise, such as downhill treadmill walking, have been shown to increase CSE in non-exercised upper limbs M1 representation to a similar extent as concentric contractions during uphill treadmill walking [ 26 ]. Additionally, eccentric contraction exercise of the upper-limbs induced prolonged changes in intracortical inhibition as compared to concentric contraction exercise [ 27 ]. Recent research demonstrated that eccentric cycling AAE leads to greater activation in motor-related brain areas, like prefrontal and parietal cortices, compared to concentric cycling AAE [ 28 ]. Importantly, the prefrontal cortex plays a key role in cognitive, explicit, and executive processes [ 29 ], which support the early stages of motor learning [ 30 ]. Additionally, modulation of corticospinal output excitability [ 31 – 33 ] and SICI circuitry [ 34 – 36 ] have been associated with motor skill acquisition and learning. Our recent work also showed that cycling AAE can preferentially enhance M1 interneuron excitability as assessed by distinct TMS current directions [ 2 , 37 ]. Specifically, M1 excitability assessed with anterior-to-posterior TMS current, which preferentially activates unique interneurons associated with task-related prefrontal cortical engagement [ 38 ] and motor learning [ 39 ], was enhanced to a greater extent than traditional posterior-to-anterior TMS [ 2 , 37 ]. Since eccentric cycling exercise is associated with greater prefrontal cortical activation [ 28 ], it is possible that eccentric AAE may impact M1 interneuron excitability as measured by anterior-to-posterior TMS to a greater extent than concentric AAE. Taken together, these findings suggest that eccentric cycling exercise may engage unique motor-related brain circuits involved in the control of cognitive and motor function, potentially facilitating skill acquisition and motor learning. We recently found that eccentric cycling AAE enhanced motor skill acquisition and learning more than concentric cycling [ 40 ]. While we also found that traditional concentric cycling AAE enhanced motor learning more than rest, in line with previous work [ 5 , 7 , 8 , 41 ], our findings suggest that eccentric cycling AAE may promote greater modulation of M1 excitability than concentric cycling AAE, supporting the enhanced effect of eccentric cycling AAE [ 40 ]. To the best of our knowledge, only one study has examined the effects of eccentric cycling on global corticospinal excitability of a non-exercised upper-limb muscle and reported no significant changes following exercise [ 42 ]. However, the study compared eccentric and concentric cycling conditions without including a rest (a non-exercise control) condition, along with a specific population (i.e., 13 male participants). Critically, we address both of these limitations within the current study design. Thus, the aim of this study was to assess changes in M1 circuit excitability following eccentric cycling AAE as compared to concentric cycling AAE and to rest. We hypothesized that eccentric cycling AAE will result in greater changes in M1 excitability, specifically a greater increase in CSE and a more pronounced reduction in SICI, compared to concentric cycling AAE. We also expected to find a significant decrease in SICI following concentric cycling AAE compared to rest. Methods Participants Thirty healthy adults (28.03 ± 8.88 years, 15 male and 15 female), all right-handed [Edinburgh Handedness Inventory: 93.80 ± 12.36; [ 43 ]], were enrolled in this study. The characteristics of participants are presented in Table 1 . A sensitivity analysis performed in G*Power with an alpha risk of View this table: View inline View popup Download powerpoint Table 1: Participants’ characteristics 0.05 and a sample size of 30 indicated that we had a 90% chance of observing a medium effect size of f(U) = 0.272 (∼ η 2 p = 0.069 ) or higher [ 44 ]. The experimental procedures were approved by the Aging and Neuroimaging Research Ethics Board of the Research Center of the Montreal University Geriatric Institute (CRIUGM), and written informed consent was obtained from all participants prior to their involvement in the study. All participants were assessed for any potential contraindications to TMS through standard screening forms. They indicated no history of neurological disorders, and the Physical Activity Readiness Questionnaire (PAR-Q) indicated they were all in adequate physical condition to complete the exercise protocols. Experimental design Each participant attended three experimental sessions, with at least 4 days between each session. Figure 1 represents an overview of the experimental design. The experimental conditions included: i) seated rest, ii) concentric cycling exercise (CON), and iii) eccentric cycling exercise (ECC) with each lasting approximately 2.5 hours. The first visit involved the resting experimental condition followed by a concentric incremental cycling exercise test to determine the exercise parameters for the subsequent sessions. The incremental exercise test was then followed by eccentric cycling familiarisation. The following two visits consisted of 20 minutes of moderate-intensity exercise, one involving concentric cycling exercise and the other eccentric cycling exercise and were performed in a counterbalanced order (half of the participants underwent concentric cycling exercise before eccentric cycling exercise). Neurophysiological measurements were collected at three time points: before (Pre), immediately after (Post 0 ), and 20 minutes after (Post 20 ) the experimental intervention. To account for potential diurnal variations in corticospinal excitability [ 45 ], all visits were scheduled at the same time of day (± 2 hours) for each participant [ 46 ]. Download figure Open in new tab Figure 1: Overview of the study design Visit 1 consisted of the resting experimental condition followed by an incremental exercise test to determine the exercise parameters for the subsequent sessions. Visits 2 and 3 consisted of the moderate intensity cycling exercise conditions, one involving 20 min of concentric cycling and the other 20 min of eccentric cycling and were performed in a counterbalanced order. Neurophysiological measurements were collected at three time points: Pre (before cycling exercise/rest), Post0 (immediately after cycling exercise/rest) and Post20 (20 min after cycling exercise/rest). At each time timepoint, MEP 110%, MEP 130% and SICI were obtained. TMS = transcranial magnetic stimulation; AAE = acute aerobic exercise; MEP = motor-evoked potential; SICI = short-interval intracortical inhibition. Incremental test A concentric incremental cycling exercise test was conducted on a concentric recumbent cycle ergometer (CY00500, Cyclus 2, Germany) to determine the exercise intensity for the subsequent visits. The starting workload and incremental increases were tailored to each participant’s body weight (e.g., 65W for 65 kg) [ 47 , 48 ]. Participants were instructed to maintain a steady cycling cadence of 60 rpm while seated comfortably on the ergometer. The intensity increased every 2 minutes by 15, 20, 25, or 30 W until exhaustion was reached. Exhaustion was defined as the inability to maintain a cadence at 60 rpm for at least 10 seconds, despite verbal encouragement. Heart rate was continuously monitored (Polar H10, Polar Electro 2024, Finland), and heart rate peak (HR peak ) was recorded at exhaustion. Participants rated their perceived effort and muscle (quadriceps) pain using the CR100 scale [ 49 , 50 ] at the end of each 2-minute increment. Additionally, their affect was assessed using the Feeling scale at the end of each increment [ 51 ]. Cycling exercise and rest The cycling AAE intervention lasted 25 minutes, consisting of a 5-minute warm-up followed by 20 minutes of continuous moderate-intensity cycling exercise. The cycling power for each participant was determined based on their HR peak , measured during the incremental exercise test, to ensure the intensity of the exercise corresponded to a moderate-intensity. During the 5-minute warm-up, participants cycled at a power equivalent to 50% of their HR peak (low intensity), and the subsequent 20-minute continuous cycling exercise was performed at 70% of their HR peak (moderate intensity). These intensity levels were selected based on the American College of Sports Medicine (ACSM) guidelines [ 47 , 52 ]. For both concentric and eccentric cycling AAE, the power output was set to correspond to 70% of the participant’s HR peak , as determined in the concentric incremental test. During both eccentric (Cyclus 2, Germany; model CY00360) and concentric (Cyclus 2, Germany; model CY00500) cycling, the ergometers operated in isopower mode, with participants instructed to maintain a constant cadence of 60 rpm. The concentric and eccentric ergometers shared identical bike frames; specifically, the motor for concentric cycling (CY00500) was mounted on the same frame model used for the eccentric ergometer. Heart rate was monitored and recorded every 5 minutes during both concentric and eccentric cycling exercise (Polar H10, Polar Electro 2024, Finland). Additionally, participants reported their perceived effort and muscle pain using the CR100 scale [ 49 , 50 ], as well as their affect using the Feeling scale (Hardy & Rejeski, 1989) every 5 minutes. During the cycling exercise, participants were instructed to keep their hands relaxed, resting them gently on top of the handlebars without gripping, to reduce activation of the non-exercised hand muscles. Continuous electromyography (EMG) was recorded from both the right and left abductor pollicis brevis (APB) muscles to confirm that the non-exercised hand muscles remained relaxed. The rest intervention also lasted 25 minutes, during which participants sat comfortably in a chair and watched an emotionally neutral documentary [ 53 ]. They were instructed to keep their upper limbs relaxed throughout the session. Heart rate, perceived effort, muscle pain, and affect were measured every 5 minutes, following the same procedure as the cycling AAE interventions. Muscle pain assessments between exercise sessions After visits 2 and 3, participants were provided with forms to assess at home their muscle pain in three different contexts: “when standing,” “ when walking,” and “ when taking the stairs up and down.” Participants were asked to rate their pain using a visual analog scale, marking a vertical line on a 10-centimeter line ranging from 0 to 10, where 0 represented ’no pain’ and 10 represented ’maximum pain’ [ 54 ]. Pain assessments were completed at 24-, 48-, 72-, and 96-hours post-exercise. Electromyographic recording During all TMS measurements, EMG recordings were obtained from the right abductor APB muscle. In a belly-tendon configuration, 1 cm diameter electrodes (Covidien, Mansfield, MA, USA) were placed over the APB, with the ground electrode positioned on the ulnar styloid. EMG recordings were obtained using LabChart software (LabChart 8.0), with signals sampled through a PowerLab data acquisition system (PL3516 PowerLab, 16/35 16 Channel Recorder, AD Instruments, Colorado Springs, CO, USA) and a bioamplifier (Dual Bio Amp, AD Instruments, Colorado Springs, CO, USA). The data were acquired at a rate of 2 kHz, with a bandpass filter (20-400 Hz) and a notch filter set to a center frequency of 50 Hz. Data were captured in a 500-ms sweep, starting 100 ms before and ending 400 ms after the delivery of TMS. Transcranial magnetic stimulation Participants were comfortably seated on an adjustable chair and remained at rest during TMS measurements. A Magstim BiStim 200 2 stimulator (Magstim Co., UK) was used, connected to a 70 mm figure-of-eight coil (Magstim 70 mm P/N 9790, Magstim Co., UK) to deliver monophasic TMS pulses. The TMS current was adjusted to produce current flow in either a posterior-to-anterior (PA) or anterior-to-posterior (AP) direction. The standard coil delivered TMS pulses in a PA current direction. A custom coil was designed to deliver an AP current, generating a TMS pulse in the opposite direction (i.e., anterior to posterior) to the standard PA TMS coil. The TMS coils were positioned at a 45° angle to the mid-sagittal plane, with the handle facing posteriorly. To generate pulses in the lateral-medial (LM) direction, the standard TMS coil was used by rotating the handle 90° to the mid-sagittal plane [ 39 , 55 – 58 ]. To ensure accurate coil positioning and continuous monitoring, Brainsight neuronavigation software (Rogue Research Inc., Montreal, QC, Canada) was used throughout the study. The standard TMS coil over M1 to identify the “hotspot” associated with the APB representation, was then utilized for all TMS current directions (PA, AP, and LM). Resting motor threshold (RMT) was determined at this site for each of the TMS current directions (PA, AP, and LM). RMT was defined as the minimum intensity required to evoke 5 out of 10 consecutive motor evoked potentials (MEPs) with a peak-to-peak amplitude of at least 50 μV. Throughout the study, TMS pulses were delivered at a random frequency between 0.15 and 0.2 Hz, with approximately 20% variation. MEP amplitudes To investigate potential changes in corticospinal excitability following cycling AAE, MEP amplitudes were measured in both the PA and AP current directions. MEPs were recorded at 110% RMT, as previous research suggests that lower suprathreshold TMS intensities are necessary to preferentially activate distinct interneuron circuits with PA and AP currents [ 39 , 55 , 56 , 59 – 63 ]. Our previous research demonstrated that moderate-intensity AAE increased corticospinal excitability, as measured with the lower intensity (i.e., 110% RMT) in the AP direction but not in the PA direction and had no effect at higher TMS intensities (i.e., 130% RMT and above) [ 2 ]. MEPs were also assessed at 130% RMT to confirm our prior findings following concentric cycling AAE [ 2 ] and to further examine the effect of eccentric cycling AAE on these measures. A total of fifteen stimuli were applied at each TMS intensity and current direction. The intervals between TMS measurements were typically 10-15 seconds, with transitions between the PA and AP coil orientations taking approximately 1 minute. SICI The effect of cycling AAE on intracortical inhibition in the PA and AP current directions was evaluated using short-interval intracortical inhibition (SICI), following methods established in previous research [ 2 ]. A subthreshold conditioning stimulus (CS) was delivered prior to a suprathreshold test stimulus (TS) at the APB hotspot over M1. The CS was set to 80% of the RMT, while the TS intensity was adjusted to elicit an average peak-to-peak MEP amplitude of approximately 1 mV across 15 stimulations. For the PA current direction, an interstimulus interval (ISI) of 2 ms was chosen based on prior studies showing a reduction in inhibition following acute exercise [ 2 – 4 , 10 , 16 , 64 , 65 ]. In contrast, a 3 ms ISI was utilized for SICI measurements in the AP current direction, as this interval has been shown to elicit more stable and robust inhibition compared to the 2 ms ISI [ 2 , 55 , 66 ]. This adjustment accounts for the longer cortical transmission pathways associated with AP TMS [ 67 ], making the 3 ms ISI a more suitable choice for assessing SICI in this direction. At each time point (Pre, Post 0 , and Post 20 ), SICI was measured by delivering 15 paired pulses (CS followed by TS) and 15 single TS for both the PA and AP current directions. MEP onset latencies The earliest onset latency among a set of 15 MEPs was identified to indirectly assess I-wave recruitment and infer the preferential activation of specific interneuron populations. This analysis was performed for both PA and AP TMS current directions, with stimulation set at 110% of the RMT. To estimate D-wave activation, the same procedure was applied but using an LM TMS current direction at 150% RMT [ 55 , 56 , 59 – 63 ]. Data processing and statistical analysis Repeated measures analysis of variance (RM-ANOVA) was conducted to assess the effects of concentric AAE, eccentric AAE and rest on heart rate and perceptual responses (perceived effort, muscle pain, and affect) and neurophysiological measures obtained using TMS (MEP amplitude, SICI, and MEP onset latency). Specific analyses are detailed below. When necessary, post hoc comparisons were performed and adjusted for multiple comparisons with the Holm-Bonferroni correction. Significance was set at a p -value of < .05. Effect sizes were calculated following established guidelines [ 68 ] and expressed as partial eta squared (η 2 p ) for ANOVAs (with 0.01, 0.06, and 0.14 indicating small, moderate, and large effects, respectively) and as Cohen’s d for pairwise comparisons (with 0.2, 0.5, and 0.8 indicating small, moderate, and large effects, respectively). All statistical analyses were conducted in R software (4.2.1, foundation for statistical computing, Vienna, Austria). Cycling AAE / rest data To determine whether the AAE or rest conditions (ECC, CON, REST) elicited distinct physiological and psychological responses, we analyzed %HR peak , perceived effort, muscle pain, and affect data during the sessions. Two separate two-way RM-ANOVAs were conducted. The first analysis examined average heart rate peak and affect, with CONDITION (ECC, CON, REST) and TIME (5, 10, 15, and 20 min) as within-subject factors. In the second analysis, REST was excluded for perceived effort and muscle pain, as all participants reported a score of zero throughout the intervention, allowing for a direct comparison between ECC and CON. For the analysis related to the pain assessments after the cycling AAE interventions, a two-way RM-ANOVAS were conducted for each assessment with CONDITION (ECC, CON) and TIME (24h, 48h, 72h and 96h) as within-subject factors. Neurophysiological data RMT, TS % maximum stimulator output (MSO) and TS MEP amplitudes To ensure consistency in RMT (%MSO) at the start of each session (pre-AAE/rest), a two-way RM-ANOVA was performed with CONDITION (ECC, CON, REST) and TMS CURRENT (PA, AP) as within-subject factors. The stability of TS %MSO values during SICI assessment before and after cycling AAE/rest was verified using a three-way RM-ANOVA, incorporating TIME (Pre, Post 0 , Post 20 ), CONDITION (ECC, CON, REST), and TMS CURRENT (PA, AP) as within-subject factors. This confirmed that TMS intensity remained stable throughout SICI assessments across conditions and current directions. Similarly, a three-way RM-ANOVA was conducted to assess the stability of TS MEP amplitudes before and after cycling AAE/rest, considering TIME (Pre, Post 0 , Post 20 ), CONDITION (ECC, CON, REST), and TMS CURRENT (PA, AP). This analysis verified that corticospinal excitability remained consistent across the different AAE conditions and TMS currents during SICI assessment. MEP onset latency A semi-automated system was utilized to calculate MEP onset latency, defined as the moment when the rectified electromyography (EMG) signal exceeded five times the average pre-stimulus EMG level. MEP latencies induced by single-pulse TMS were determined for each current direction (PA, AP, LM). Consistent with prior studies [ 2 , 39 , 55 , 56 , 58 , 61 , 63 , 66 , 67 ], differences in MEP latencies (ΔPA-LM, ΔAP-LM) were employed as indirect markers of I-wave recruitment, providing evidence for the activation of specific interneuron circuits. To analyze the earliest MEP latency responses, we conducted a two-way RM-ANOVA with TMS CURRENT (PA, AP, LM) and CONDITION (ECC, CON, REST) as within-subject factors. In a separate analysis, differences in MEP onset latency between PA-LM and AP-LM were assessed using another two-way RM-ANOVA, with MEP ONSET DIFFERENCE (ΔPA-LM, ΔAP-LM) and CONDITION (ECC, CON, REST) as within-subject factors. EMG and MEP data processing for CSE and SICI For both MEPs (collected at 110% and 130% RMT) and SICI, the electromyography (EMG) data were carefully examined for any voluntary muscle activity. Peak-to-peak MEP amplitudes (in millivolts, mV) were analyzed using custom MATLAB scripts. Trials with any voluntary pre-stimulus EMG activity were excluded from analysis, accounting for 1.2% of the total trials. SICI was quantified as the ratio of CS + TS amplitude to TS MEP amplitude: SICI ratio = (CS + TS) / TS. In this ratio, lower values reflect stronger inhibition, while higher values indicate reduced inhibition (or disinhibition). Corticospinal excitability To evaluate the effect of eccentric and concentric cycling AAE on corticospinal excitability, the mean MEP amplitude was calculated from fifteen responses at each of the two TMS intensities (110% and 130% RMT). Each intensity level was analyzed separately, as lower stimulation intensities (e.g., 110% RMT) increase the likelihood of preferentially engaging distinct interneuron circuits depending on the TMS current direction (PA or AP) [ 38 , 39 , 55 , 58 , 61 , 63 ]. To examine these effects, three-way RM-ANOVAs were conducted for each TMS intensity (110% and 130% RMT), with TIME (Pre, Post 0 , Post 20 ), CONDITION (ECC, CON, REST), and TMS CURRENT (PA, AP) as within-subject factors, using mean MEP amplitude as the dependent variable. Short-interval intracortical inhibition To evaluate the effect of eccentric and concentric cycling AAE on SICI, the mean MEP amplitude was calculated for each of the fifteen TS and CS+TS pulses for both TMS current directions (PA, AP) to determine the SICI ratio. A three-way RM-ANOVA was then performed with TIME (Pre, Post 0 , Post 20 ), CONDITION (ECC, CON, REST), and TMS CURRENT (PA, AP) as within-subject factors, using the SICI ratio as the dependent variable. Results Cycling exercise and rest data Heart rate, perceived effort, muscle pain, and affect were recorded every 5 minutes during the 25-minute experimental interventions. Figure 2 presents the mean values for each intervention, while Figure S1 illustrates their time course. Download figure Open in new tab Figure 2: Parameters obtained during the different experimental interventions. All parameters are averaged over the 20-minute intervention (eccentric cycling, concentric cycling and rest). Panel A: heart rate (% peak value). Panel B: affect (feeling scale from -5 to +5). Panel C: perceived effort (CR100 scale). Panel D: muscle pain (CR100 scale). Dots represent individual data points, while the black diamond represents the mean for each condition. Purple dots refer to the eccentric cycling condition, green dots to the concentric cycling condition, and grey dots to the rest condition. Grey lines connect the data points across the three conditions for the same participants. ***: p -value < .001. For perceived effort and muscle pain, the rest condition was excluded from the analysis as all participants reported a score of 0, allowing for a direct comparison between eccentric and concentric cycling. % HR peak . Figure 2A . There was a main effect of CONDITION [ F 2,58 = 183.924, p <.001, η 2 p = 0.522]. Post hoc analyses revealed that % HR peak was higher for the concentric cycling AAE compared to both eccentric cycling AAE ( p < .001, d = 1.039) and rest ( p < .001, d = 2.306), and eccentric cycling AAE showed a higher % HR peak than rest ( p < .001, d = 1.019). Additionally, there was no main effect of TIME [ F 3,87 = 0.424, p = .736, η 2 p = 0.004], and no CONDITION x TIME interaction [ F 6,174 = 0.185, p = .981, η 2 p = 0.003]. Affect . Figure 2B . There was a main effect of CONDITION [ F 2,58 = 36.498, p <.001, η 2 p = 0.178]. Post hoc analysis revealed that affects were higher at rest compared to both concentric ( p < .001, d = 1.134) and eccentric ( p < .001, d = 0.602) cycling AAE, and the eccentric cycling AAE showed a higher affect compared to the concentric cycling AAE ( p <.001, d = 0.654). Additionally, there was no main effect of TIME [ F 3,87 = 0.354, p = .787, η 2 p = 0.003] and no CONDITION x TIME interaction [ F 6,174 = .102, p = .996, η 2 p = 0.002]. Perceived effort . Figure 2C . There was a main effect of CONDITION [ F 1,29 = 40.083, p <.001, η 2 p = 0.151] revealing that perceived effort was higher during the concentric cycling AAE compared to the eccentric cycling AAE. Additionally, there was no main effect of TIME [ F 3,87 = 1.811, p = .146, η 2 p = 0.024], and no CONDITION x TIME interaction [ F 3,87 = 1.351, p =.259, η 2 p = 0.017]. Muscle pain . Figure 2D . There was a main effect of CONDITION [ F 1,29 = 16.290, p <.001, η 2 p = 0.067] revealing that muscle pain was higher during the concentric cycling AAE compared to the eccentric cycling AAE. Additionally, there was no main effect of TIME [ F 3,87 = 1.019, p = .385, η 2 p = 0.013], and no CONDITION x TIME interaction [ F 3,87 = 0.135, p = .939, η 2 p = 0.002]. Muscle pain post-AAE Muscle pain i) when standing, ii) when walking and iii) when taking the stairs up and down, were evaluated 24h, 48h, 72h, and 96h post-AAE ( Figure 3 ). Download figure Open in new tab Figure 3: Muscle pain assessments after cycling exercise Purple represents eccentric condition, green represents concentric condition. Time points of 24, 48, 72, and 96 hours indicate when pain was assessed following the exercise intervention. The black diamond shape indicates the mean at each time point. Bars represent the standard error of the mean. Standing test pain: Participants were asked to rate their muscle pain when standing without any movement; Panel A shows the means for each condition, while Panels B and C display individual data points for the eccentric and concentric conditions, respectively. Walking test pain: Participants were asked to rate their muscle pain when walking; Panel D shows the means for each condition, while Panels E and F display individual data points for the eccentric and concentric conditions, respectively. Stairs test pain: Participants were asked to rate their muscle pain when taking the stairs up and down; Panel G shows the means for each condition, while Panels H and I display individual data points for the eccentric and concentric conditions, respectively. * indicates significant difference between both cycling exercise conditions at the specific time point ( p-value < .05). # indicates a significant difference between the two adjacent time points ( p-value < .05). Muscle pain when standing. Figure 3A . There was a CONDITION x TIME interaction (F 3,87 = 26.593, p < .001, η 2 p = 0.478). Post-hoc analyses revealed higher pain following 24h ( p < .001, d = 1.610), 48h ( p < .001, d = 1.808) and 72h ( p = .014, d = 0.876) in the eccentric cycling AAE compared to the concentric cycling AAE. Also, in the eccentric cycling AAE, pain decreased from 48h to 72h ( p < .001, d = 1.368) and from 72h to 96h ( p = .024, d = 0.808). Additionally, there was a main effect of CONDITION (F 1,29 = 42.206, p < .001, η 2 p = 0.593) and a main effect of TIME (F 3,87 = 32.420, p < .001, η 2 p = 0.528). Muscle pain when walking. Figure 3D . There was a CONDITION x TIME interaction (F 3,87 = 31.606, p < .001, η 2 p = 0.522). Post-hoc analyses revealed higher pain following 24h ( p < .001, d = 1.704), 48h ( p < .001, d = 2.234) and 72h ( p = .003, d = 1.010) in the eccentric cycling AAE compared to the concentric cycling AAE. Also, in the eccentric cycling AAE, pain decreased from 48h to 72h ( p < .001, d = 1.778) and from 72h to 96h ( p = .002, d = 1.069). Additionally, there was a main effect of CONDITION (F 1,29 = 62.836, p < .001, η 2 p = 0.684) and a main effect of TIME (F 3,87 = 46.254, p < .001, η 2 p = 0.615). Muscle pain when taking the stairs up and down. Figure 3G . There was a CONDITION x TIME interaction (F = 24.502, p < .001, η 2 p = 0.458). Post-hoc analyses revealed higher pain following 24h ( p < .001, d = 1.608), 48h ( p < .001, d = 1.778) and 72h ( p = .013, d = 0.868) in the eccentric cycling AAE compared to the concentric cycling AAE. Also, in the eccentric cycling AAE, pain decreased from 48h to 72h ( p < .001, d = 1.835) and from 72h to 96h ( p = .008, d = 0.928). Additionally, there was a main effect of CONDITION (F 1,29 = 39.965, p < .001, η 2 p = 0.579) and a main effect of TIME (F 3,87 = 47.362, p < .001, η 2 p = 0.620). Neurophysiological data Baseline neurophysiological data RMT values. Table S1 . There was a main effect of CURRENT (F 2,58 = 69.368, p < .001, η 2 p = 0.705). Post hoc analyses revealed that RMT for PA TMS current was lower than AP TMS current ( p < .001, d = -2.564) and that RMT for LM TMS current was lower than AP TMS current ( p < .001, d = 1.138). Moreover, there was no main effect of CONDITION (F 2,58 = 0.482, p = .620, η 2 p = 0.016) or CURRENT x CONDITION interaction (F 4,116 = 1.434, p = .227, η 2 p = 0.047). TS% MSO. Table S2 . There was a main effect of CURRENT (F 1,29 = 104.537, p < .001, η 2 p = 0.783) revealing higher values for AP TMS current compared to PA TMS current. Additionally, there was no main effect of CONDITION (F 2,58 = 0.622, p = .540, η 2 p = 0.021) or TIME (F 2,58 = 2.812, p =.068, η 2 p = 0.088), nor interactions (all ps < .913). TS MEP amplitudes . Table S2 . TS MEP amplitudes during SICI were constant across time, between exercise conditions and between TMS currents. More specifically, there were no main effects of CONDITION (F 2,58 = 1.038, p = .360, η 2 p = 0.035), TIME (F 2,58 = 2.565 p = .085, η 2 p = 0.081) or CURRENT (F 2,58 = 2.428 p = .130, η 2 p = 0.077), nor interactions (all ps < .774). MEP onset latency. Figure S2B . There was a main effect of CURRENT (F 1,29 = 278.360, p < .001, η 2 p = 0.952) with post hoc analyses showing a shorter MEP onset latency using LM current compared to PA ( p < .001, d = -2.352) and AP ( p < .001, d = -3.413) TMS current. Additionally, MEP onset latency using PA TMS current was shorter compared to AP TMS current ( p < .001, d = -1.881). Moreover, there was no main effect of CONDITION (F 2,58 = 0.208 p = .812, η 2 p = 0.007) or CONDITION x CURRENT interaction (F 4,116 = 1.113 p = .354, η 2 p = 0.277). MEP onset latency difference. Figure S2C . There was a main effect of MEP ONSET DIFFERENCE (F 1,29 = 226.285, p < .001, η 2 p = 0.886) revealing a greater ΔAP-LM compared to ΔPA-LM. Additionally, there was no main effect of CONDITION (F 2,58 = 1.537 p = .224, η 2 p = 0.050) or MEP ONSET DIFFERENCE x CONDITION interaction (F 2,58 = 0.906, p = .411, η 2 p = 0.030). Baseline CSE and SICI measures To ensure that CSE and SICI did not differ between the three experimental conditions prior to the intervention, a two-way repeated-measures ANOVA was conducted. Baseline CSE. For MEP 110%, there were no main effects of CONDITION (F 2,58 = 0.231, p = .794, η 2 p = 0.008), CURRENT (F 1,29 = 0.095, p = .760, η 2 p = 0.003) or CONDITION x CURRENT interaction (F 2,58 = 0.208, p = .813, η 2 p = 0.007). For MEP 130%, there were no main effects of CONDITION (F 2,58 = 0.138, p = .871, η 2 p = 0.005), CURRENT (F 1,29 = 0.642, p = .429, η 2 p = 0.022), or CONDITION x CURRENT interaction (F 2,58 = 0.016, p = .984, η 2 p = 0.001). Baseline SICI. There was a main effect of CURRENT (F 2,58 = 13.508, p <.001, η 2 p = .318) revealing greater values for PA TMS current compared to AP TMS current. Additionally, there were no main effects of CONDITION (F 1,29 = 0.235, p = .791, η 2 p = 0.008), or CONDITION x CURRENT interaction (F 2,58 = 0.060, p = .941, η 2 p = 0.002). Corticospinal excitability MEP data are displayed for each TMS intensity (110% RMT and 130% RMT) with TMS currents collapsed and separated into PA and AP ( Figure 4 and Figure S3 in Supplementary material). Download figure Open in new tab Figure 4: Corticospinal excitability results. Panels A and B display mean peak-to-peak amplitudes with TMS currents collapsed et each time point (110% RMT and 130% RMT respectively). Mean peak-to peak amplitudes with PA at 110% RMT (Panel C), AP at 110% RMT (Panel D), PA at 130% RMT (Panel E) and AP at 130% RMT (Panel F) are displayed at each time point. Plots with individual lines represent individual data corresponding to each previously mentioned panel. Bars represent the standard error of the mean. Purple color refers to eccentric condition, green color refers to concentric condition and grey color refers to rest condition. TMS = transcranial magnetic stimulation. AP = anterior-to-posterior; PA = posterior-to-anterior; MEP: motor-evoked potential; mV: millivolt; RMT = resting motor threshold; Pre: before the experimental intervention; Post0: immediately after the experimental intervention; Post20: 20 minutes after the experimental intervention. Horizontal purple and green bars represent the difference between Pre and Post20 for eccentric and concentric cycling respectively. The vertical purple line represents the difference between eccentric cycling and rest at Post20. **: p-value < .01; ***: p-value < .001. MEPs at 110% RMT . Figure 4A . There was a CONDITION x TIME interaction (F 4,116 =3.162, p = .016, η 2 p = 0.098). Post-hoc analyses revealed a greater MEP amplitude for eccentric cycling AAE at Post 20 compared to Pre ( p <.001, d = -1.579). At Post 20 , MEP amplitude was greater for eccentric cycling AAE compared to rest ( p = .002, d = 1.121). Additionally, there were main effects of TIME (F 2,58 = 19.658, p < .001, η 2 p = 0.404), and CONDITION (F 2,58 = 3.398, p = .040, η 2 p = 0.105) with no other effects or interactions (all ps < .975). MEPs at 130% RMT . Figure 4B . There was a CONDITION x TIME interaction (F 4,116 = 3.027, p = .020, η 2 p = 0.095). Post-hoc analyses revealed greater MEP amplitude at Post 20 compared to Pre for both eccentric ( p = .002, d = -1.114) and concentric cycling AAE ( p = .004, d = -1.051). Additionally, there was a main effect of TIME (F 2,58 = 21.208, p < .001, η 2 p = 0.422) and no other effects or interactions (all ps < .981). Short-interval intracortical inhibition SICI data are displayed with TMS currents collapsed and separated into PA and AP currents ( Figure 5 and Figure S3 in Supplementary material). There was a CONDITION x TIME interaction (F 2,58 = 2.542, p = .043, η 2 p = 0.081). Post-hoc analyses revealed lower SICI at Post 20 compared to Pre for both eccentric ( p = .004, d = -1.060) and concentric cycling AAE ( p = .047, d = -0.789). At Post 20 , SICI was lower for eccentric cycling AAE compared to rest ( p = .009, d = 0.959). Additionally, there were main effects of CONDITION (F 2,58 = 6.546, p = .003, η 2 p = 0.184), TIME (F 2,58 = 12.979, p <.001, η 2 p = 0.309) and CURRENT (F 1,29 = 6.507, p = .016, η 2 p = 0.183) with no other interactions (all ps < .793). Download figure Open in new tab Figure 5: Short-interval intracortical inhibition results. Panel A displays mean SICI ratios with TMS currents collapsed et each time point. Mean SICI ratios with PA (Panel B), and AP (Panel C) are displayed at each time point. Plots with individual lines represent individual data corresponding to each previously mentioned panel. Bars represent the standard error of the mean. Higher values represent less GABAergic inhibition. Purple color refers to eccentric condition, green color refers to concentric condition and grey color refers to rest condition. TMS = transcranial magnetic stimulation. AP = anterior-to-posterior; PA = posterior-to-anterior; MEP: motor-evoked potential; SICI = short-interval intracortical inhibition; Pre: before the experimental intervention; Post0: immediately after the experimental intervention; Post20: 20 minutes after the experimental intervention. Horizontal purple and green bars represent the difference between Pre and Post20 for eccentric and concentric cycling respectively. The vertical purple line represents the difference between eccentric cycling and rest at Post20. *: p-value < 0.05; **: p-value < .01. Discussion In this study, we investigated the impact of an acute bout of eccentric and concentric cycling exercise on M1 excitability. We hypothesized that eccentric cycling AAE would enhance CSE and decrease SICI more than concentric cycling AAE. Our findings partially confirmed our hypothesis in that eccentric cycling AAE resulted in significantly greater corticospinal excitability, when assessed at a lower stimulus intensity (110% RMT), when compared to concentric cycling AAE. Contrary to our hypothesis, corticospinal excitability increased similarly following eccentric and concentric cycling AAE when assessed at a higher stimulus intensity (130% RMT). Unexpectedly, SICI decreased similarly following both eccentric and concentric cycling AAE. Finally, eccentric cycling AAE elicited unique psychophysiological responses compared to concentric cycling AAE, with lower %HR peak , perceived effort, muscle pain and better affective response. Given the similar impact on M1 excitability alongside distinct psychophysiological responses, our findings may have important implications in both clinical and sports-related contexts. Acute eccentric and concentric cycling exercise increased corticospinal excitability At low stimulus intensity (110% RMT), only eccentric cycling AAE produced a significant increase in corticospinal excitability. Notably, this increase was sustained at the Post 20 time point, with eccentric cycling AAE showing higher excitability than rest. This consistent increase suggests that eccentric cycling AAE induces longer-lasting neurophysiological changes in M1 excitability compared to concentric cycling AAE and rest. This enhancement could be attributed to the unique neurophysiological demands induced by eccentric contractions. During eccentric contractions, both supraspinal and spinal circuits are engaged, which are critical for modulating output from the motor cortex and in motor control [ 69 ]. In their study, Fang and colleagues demonstrated that eccentric contractions were associated with greater movement-related cortical potential amplitudes compared to concentric contractions, particularly over sensorimotor areas such as M1, supplementary motor area, and primary somatosensory cortex [ 70 ]. This suggests that eccentric contractions engage more extensive cortical resources, which may help explain the increased CSE observed following eccentric activity in the present study. The dynamic modulation of CSE during eccentric contractions could also play a role in this enhancement. Prior to movement execution, CSE tends to decrease, but following the contraction, it increases [ 71 ]. This change in excitability is thought to reflect the unique neural demands of eccentric contractions. The increased CSE observed post-eccentric cycling AAE may be attributed to the priming effect of repeated eccentric contractions on M1. Such priming could have prepared a neural environment for neuroplastic changes, and hence contributed to the enhanced CSE observed following eccentric cycling. However, an increase in CSE was also observed following concentric cycling AAE, although this change did not reach statistical significance. Notably, the magnitude of this effect may be influenced by differences in the PA and AP current directions. Indeed, a closer inspection of individual responses suggests that more participants showed increases in CSE with PA stimulation compared to AP, which may partly explain the overall (combined TMS current directions) non-significant increase in the mean CSE following concentric cycling AAE. These findings highlight the importance of considering TMS current direction and individual variability in interpreting changes in CSE. Future studies with larger sample size could further clarify the consistency and underlying mechanisms of CSE response at 110% RMT following concentric cycling AAE. At higher stimulus intensity (130% RMT), our findings revealed that CSE was enhanced following both concentric and eccentric cycling AAE. Distinct mechanisms likely underlie this modulation, yet both cycling AAE types appear to share common results. While our recent meta-analysis suggested that concentric cycling AAE primarily enhances CSE at high intensity AAE, the current study that used moderate intensity also showed an increase. This result, which was not obtained in our meta-analysis, aligns with certain studies that reported similar effects [ 10 , 15 , 37 ] suggesting that moderate-intensity concentric cycling AAE may also influence CSE. Hence, our study adds to the growing body of evidence supporting the findings presented in our systematic review [ 1 ]. The observed enhancement in CSE might be induced from an increase in blood lactate following moderate-intensity concentric cycling. Although lactate accumulation is usually more pronounced at higher intensities, moderate-intensity exercise is still able to induce a moderate increase in blood lactate levels [ 72 ]. A higher lactate level is associated with increased brain use of lactate as a fuel source [ 72 , 73 ], potentially contributing to enhanced neuronal activity. Lactate is also involved in several signaling mechanisms, including BDNF [ 74 ] and glutamate [ 75 ], which could influence CSE. While low-intensity exercise does not induce significant lactate accumulation [ 76 ], moderate-intensity exercise may still produce sufficient lactate to modulate CSE. Interestingly, CSE at 130% RMT was also enhanced 20 minutes following eccentric cycling AAE. Eccentric muscle contractions are known to elicit greater activation in sensorimotor-related regions of the frontal and parietal lobes during both the planning and execution phases of movement compared to concentric contractions [ 70 ], and they require longer preparation time [ 77 ]. This heightened cortical engagement is further supported by increased activation in the bilateral prefrontal cortex and right parietal lobe during eccentric cycling [ 28 ]. Importantly, CSE shows a distinct temporal modulation associated with eccentric contraction: it tends to decrease before eccentric contraction but increases significantly after execution, displaying a pattern different from that of concentric contraction [ 71 ]. This unique excitability profile likely reflects the complex neural control demands of eccentric contractions, with repeated exposure to these activation patterns during eccentric cycling contributing to increased and distinct modulation of CSE. In contrast to 110% RMT, M1 excitability changes at 130% RMT were not statistically different from rest at Post 20 for both concentric and eccentric cycling AAE, which is likely due to greater inter-individual variability at this higher stimulation intensity. MEPs elicited at 130% RMT are known to be more variable [ 3 , 78 , 79 ] which may have limited the ability to detect differences between cycling AAE and rest despite apparent trends. Notably, visual inspection of the individual data at 130% RMT for both cycling AAE conditions at Post 20 reveals variability in responses, with some individuals showed clear increases in MEP amplitudes while others did not. This inter-individual variability may have contributed to the fact that statistical significance was not reached. Acute eccentric and concentric cycling exercise decreased intracortical inhibition Consistent with previous findings, we observed a decrease in SICI following 20 minutes of concentric cycling AAE, aligning with results from our meta-analysis showing a consistent reduction in SICI up to 30 minutes after moderate to high-intensity concentric cycling AAE. This decrease in SICI has been linked to several mechanisms, including GABAergic disinhibition mediated specifically by GABA A receptors [ 60 , 80 ]. Notably, our study extends this understanding by demonstrating that eccentric cycling AAE similarly decreases SICI, highlighting that both concentric and eccentric cycling modalities can modulate intracortical inhibition in a similar manner. Similarly to CSE, the mechanisms underlying this modulation are likely different but share common pathways for both cycling AAE types. For concentric cycling, the greater cardiorespiratory demand, reflected through a higher heart rate response, likely increases cerebral blood flow [ 81 ]. This increased blood flow may facilitate the delivery and release of neurochemical mediators such as BDNF, dopamine, and other molecules known to influence M1 excitability and intracortical inhibition [ 82 , 83 ]. For example, BDNF has been shown to reduce GABA A receptor activity following exercise, potentially contributing to the observed decrease in SICI [ 82 ]. Dopamine, particularly through D2 receptor activation, is also known to decrease GABAergic inhibition and increase cortical excitability [ 83 ]. In contrast, eccentric cycling AAE induces a lower heart rate response and thus likely does not elicit the same increase in cerebral blood flow as concentric cycling AAE. Therefore, alternative mechanisms may explain the similar magnitude of SICI reduction observed following eccentric cycling AAE. One potential explanation relates to the unique neuromuscular demands of eccentric contractions, which impose high mechanical strain and can induce muscle damage despite lower metabolic costs. Previous research has demonstrated that eccentric contractions lead to a decrease in SICI hours after exercise, possibly reflecting widespread effects of muscle damage on M1 excitability [ 84 , 85 ]. Moreover, eccentric exercise is associated with an inflammatory response characterized by the secretion of cytokines such as interleukin-6 (IL-6) [ 86 , 87 ]. These cytokines are increasingly recognized as modulators of brain plasticity [ 88 ] and may regulate GABA receptor function [ 89 ]. Such neuroimmune interactions could therefore contribute to the decreased SICI observed following eccentric cycling AAE in our study. Supporting this notion, participants reported higher pain levels at 24 and 48 hours post-exercise, indicating muscle damage likely occurred during eccentric cycling AAE. Implications and future directions Our findings showed that both concentric and eccentric cycling enhanced corticospinal excitability and decreased intracortical inhibition, suggesting that both modalities can prime the primary motor cortex for neuroplastic changes. These effects may have meaningful applications in contexts such as motor learning enhancement and functional recovery in rehabilitation programs, particularly given our previous finding that eccentric cycling AAE led to greater improvements in motor learning compared to concentric cycling AAE [ 40 ]. Importantly, and consistent with previous studies [ 40 , 42 ], for the same cycling power output, eccentric cycling was associated with a lower %HR peak and a reduced perceived effort compared to concentric cycling. These characteristics make it suitable for clinical rehabilitation, particularly for individuals with limited cardiovascular capacity, patients recovering from stroke, or older adults who may have reduced tolerance with interventions that place higher cardiovascular demands. Hence, incorporating eccentric cycling into rehabilitation programs may offer a lower metabolically demanding intervention, yet an effective strategy to promote neural plasticity and motor function improvements. Limitations Our study has several limitations. First, although power output was matched between conditions, physiological demands such as oxygen consumption (VO₂) and heart rate were not. This discrepancy may have influenced the observed effects. Future studies could address this by matching physiological demands across conditions to better isolate the specific contribution of eccentric cycling on M1 excitability. Second, exercise intensity was prescribed based on each participant’s measured HR peak . While this is a commonly used method, it may be less precise and more variable than alternative approaches such as oxygen uptake (VO2) or heart rate reserve. Finally, prior research has highlighted the importance of precise timing in detecting transient changes in M1 excitability (Ridding & Ziemann, 2010). In our study, TMS assessments at Pre, Post 0 , and Post 20 spanned approximately 10–20 minutes, which may be considered a relatively long testing window. Given that exercise-induced modulation of M1 excitability is time-sensitive, it is possible that some subtle, short-term effects were missed, potentially explaining the absence of significant differences in certain measures between the eccentric and concentric cycling AAE interventions. To better capture these transient changes, future studies might consider limiting the number of post-exercise TMS measurements or reducing the overall assessment duration. Finally, the findings of this study may have limited generalizability, as the sample did not include diverse age groups, fitness levels, or clinical populations, restricting the broader applicability of the results. Conclusion Our study revealed that both concentric and eccentric cycling AAE induced similar overall changes in M1 excitability, as evidenced by increased corticospinal excitability and reduced intracortical inhibition. Notably, at 110% RMT, only eccentric cycling resulted in a significant increase in corticospinal excitability, suggesting a slightly more robust or consistent effect at lower stimulation thresholds. These findings indicate that, regardless of contraction type, an acute bout of cycling exercise can induce neurophysiological changes in M1, which may support exercise-enhanced neuroplasticity and motor learning. Importantly, eccentric cycling elicited these effects with a lower cardiovascular cost than concentric cycling, positioning it as a promising option for individuals with limited cardiovascular capacity. Therefore, our findings pave the way for further exploration of the effects of eccentric cycling exercise on M1 excitability, which may lead to tailored exercise strategies applicable in both clinical and sports-related contexts. Author contributions Layale Youssef : Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing - Original draft, Visualization. Amanda O’Farrell : Investigation, Writing - Review & Editing. Nesrine Harroum : Investigation, Writing - Review & Editing. Younes Bakhta : Investigation, Data curation. Liora Cohen : Investigation, Data curation. Benjamin Pageaux : Conceptualization, Methodology, Writing - Review & Editing, Visualization, Supervision. Jason L. Neva : Conceptualization, Methodology, Writing - Review & Editing, Visualization, Supervision. Funding This work is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2020-05263 to JLN). Infrastructure was acquired with the support of the Canadian Foundation for Innovation (CFI) John R. Evans Leaders Fund to JLN and BP. LY is supported by both Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM), the Faculté de médecine at Université de Montréal, as well as the Fonds de Recherche du Québec - Nature et Technologies. BP is supported by the Chercheur Boursier Junior 1 award from the Fonds de Recherche du Québec - Santé. JLN is supported by the Chercheur Boursier Junior 1 award from the Fonds de Recherche du Québec - Santé (FRQS #313769). Data availability The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request, and approval of the ethics committee. Individual data are presented in the figures. Supplementary Material View this table: View inline View popup Download powerpoint Table S1: Resting motor threshold across experimental interventions View this table: View inline View popup Download powerpoint Table S2: Test stimulus across experimental interventions and time-points Download figure Open in new tab Figure S1. Parameters obtained across the different experimental interventions Green represents concentric condition, purple represents eccentric condition, and grey represents rest condition. Time points of 5, 10, 15, and 20 minutes indicate when parameters were recorded during the intervention. The black diamond shape indicates the mean at each time point. Heart rate (% peak value): Panel A shows the means for each condition, while Panels B, C, and D display individual data points for the concentric, eccentric, and rest conditions, respectively. Perceived effort: Panel E shows the means for each condition, while Panels F, G, and H display individual data points for the concentric, eccentric, and rest interventions, respectively. Muscle pain: Panel I shows the means for each condition, while Panels J, K, and L display individual data points for the concentric, eccentric, and rest conditions, respectively. Affect: Panel M shows the means for each group, while Panels N, O, and P display individual data points for the concentric, eccentric, and rest conditions, respectively. Download figure Open in new tab Figure S2. Transcranial magnetic stimulation (TMS) current directions and motor evoked potential (MEP) onset latency results. Panel A displays TMS current directions. LM TMS is shown in black, PA TMS in dark grey, and AP TMS in light grey. The figure illustrates the TMS coil current directions, depicted by purple arrows, and their orientations over the left M1 (dominant) abductor pollicis brevis (APB) muscle representation. A standard 8-figure TMS coil was used for both LM and PA stimulations, and a reversed current coil for AP stimulations. The coil was oriented at 90° for LM TMS and at 45° for both PA and AP TMS, relative to the longitudinal fissure. Electromyographic (EMG) traces from a representative participant, recorded from the right (dominant) APB are shown. Vertical dotted lines represent MEP onset latency elicited by the different TMS current directions (LM, PA, AP). Panel B displays boxplots of MEP onset latency for each TMS current (LM, PA, AP), with dots representing individual data. Panel C displays MEP onset latency differences (LM-PA, LM-AP) using boxplots, with connected individual data. AP = anterior-to-posterior; LM = lateral-to-medial; ms: milliseconds; PA = posterior-to-anterior; TMS = transcranial magnetic stimulation; *** p < .001. Download figure Open in new tab Figure S3. Individual data for neurophysiological measures. 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