Physical activity levels determine exercise-induced changes in brain excitability
Identifieur interne : 000A78 ( Pmc/Corpus ); précédent : 000A77; suivant : 000A79Physical activity levels determine exercise-induced changes in brain excitability
Auteurs : Tea Lulic ; Jenin El-Sayes ; Hunter J. Fassett ; Aimee J. NelsonSource :
- PLoS ONE [ 1932-6203 ] ; 2017.
Abstract
Emerging evidence suggests that regular physical activity can impact cortical function and facilitate plasticity. In the present study, we examined how physical activity levels influence corticospinal excitability and intracortical circuitry in motor cortex following a single session of moderate intensity aerobic exercise. We aimed to determine whether exercise-induced short-term plasticity differed between high versus low physically active individuals. Participants included twenty-eight young, healthy adults divided into two equal groups based on physical activity level determined by the International Physical Activity Questionnaire: low-to-moderate (LOW) and high (HIGH) physical activity. Transcranial magnetic stimulation was used to assess motor cortex excitability via motor evoked potential (MEP) recruitment curves for the first dorsal interosseous (FDI) muscle at rest (MEPREST) and during tonic contraction (MEPACTIVE), short-interval intracortical inhibition (SICI) and facilitation (SICF), and intracortical facilitation (ICF). All dependent measures were obtained in the resting FDI muscle, with the exception of AMT and MEPACTIVE recruitment curves that were obtained during tonic FDI contraction. Dependent measures were acquired before and following moderate intensity aerobic exercise (20 mins, ~60% of the age-predicted maximal heart rate) performed on a recumbent cycle ergometer. Results indicate that MEPREST recruitment curve amplitudes and area under the recruitment curve (AURC) were increased following exercise in the HIGH group only (p = 0.002 and p = 0.044, respectively). SICI and ICF were reduced following exercise irrespective of physical activity level (p = 0.007 and p = 0.04, respectively). MEPACTIVE recruitment curves and SICF were unaltered by exercise. These findings indicate that the propensity for exercise-induced plasticity is different in high versus low physically active individuals. Additionally, these data highlight that a single session of aerobic exercise can transiently reduce inhibition in the motor cortex regardless of physical activity level, potentially priming the system for plasticity induction.
Url:
DOI: 10.1371/journal.pone.0173672
PubMed: 28278300
PubMed Central: 5344515
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Physical activity levels determine exercise-induced changes in brain excitability</title><author><name sortKey="Lulic, Tea" sort="Lulic, Tea" uniqKey="Lulic T" first="Tea" last="Lulic">Tea Lulic</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="El Sayes, Jenin" sort="El Sayes, Jenin" uniqKey="El Sayes J" first="Jenin" last="El-Sayes">Jenin El-Sayes</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="Fassett, Hunter J" sort="Fassett, Hunter J" uniqKey="Fassett H" first="Hunter J." last="Fassett">Hunter J. Fassett</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="Nelson, Aimee J" sort="Nelson, Aimee J" uniqKey="Nelson A" first="Aimee J." last="Nelson">Aimee J. Nelson</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">28278300</idno><idno type="pmc">5344515</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5344515</idno><idno type="RBID">PMC:5344515</idno><idno type="doi">10.1371/journal.pone.0173672</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">000A78</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000A78</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Physical activity levels determine exercise-induced changes in brain excitability</title><author><name sortKey="Lulic, Tea" sort="Lulic, Tea" uniqKey="Lulic T" first="Tea" last="Lulic">Tea Lulic</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="El Sayes, Jenin" sort="El Sayes, Jenin" uniqKey="El Sayes J" first="Jenin" last="El-Sayes">Jenin El-Sayes</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="Fassett, Hunter J" sort="Fassett, Hunter J" uniqKey="Fassett H" first="Hunter J." last="Fassett">Hunter J. Fassett</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author><author><name sortKey="Nelson, Aimee J" sort="Nelson, Aimee J" uniqKey="Nelson A" first="Aimee J." last="Nelson">Aimee J. Nelson</name><affiliation><nlm:aff id="aff001"></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Emerging evidence suggests that regular physical activity can impact cortical function and facilitate plasticity. In the present study, we examined how physical activity levels influence corticospinal excitability and intracortical circuitry in motor cortex following a single session of moderate intensity aerobic exercise. We aimed to determine whether exercise-induced short-term plasticity differed between high versus low physically active individuals. Participants included twenty-eight young, healthy adults divided into two equal groups based on physical activity level determined by the International Physical Activity Questionnaire: low-to-moderate (LOW) and high (HIGH) physical activity. Transcranial magnetic stimulation was used to assess motor cortex excitability via motor evoked potential (MEP) recruitment curves for the first dorsal interosseous (FDI) muscle at rest (MEP<sub>REST</sub>) and during tonic contraction (MEP<sub>ACTIVE</sub>), short-interval intracortical inhibition (SICI) and facilitation (SICF), and intracortical facilitation (ICF). All dependent measures were obtained in the resting FDI muscle, with the exception of AMT and MEP<sub>ACTIVE</sub> recruitment curves that were obtained during tonic FDI contraction. Dependent measures were acquired before and following moderate intensity aerobic exercise (20 mins, ~60% of the age-predicted maximal heart rate) performed on a recumbent cycle ergometer. Results indicate that MEP<sub>REST</sub> recruitment curve amplitudes and area under the recruitment curve (AURC) were increased following exercise in the HIGH group only (p = 0.002 and p = 0.044, respectively). SICI and ICF were reduced following exercise irrespective of physical activity level (p = 0.007 and p = 0.04, respectively). MEP<sub>ACTIVE</sub> recruitment curves and SICF were unaltered by exercise. These findings indicate that the propensity for exercise-induced plasticity is different in high versus low physically active individuals. Additionally, these data highlight that a single session of aerobic exercise can transiently reduce inhibition in the motor cortex regardless of physical activity level, potentially priming the system for plasticity induction.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Chaddock, L" uniqKey="Chaddock L">L Chaddock</name></author><author><name sortKey="Erickson, Ki" uniqKey="Erickson K">KI Erickson</name></author><author><name sortKey="Prakash, Rs" uniqKey="Prakash R">RS Prakash</name></author><author><name sortKey="Kim, Js" uniqKey="Kim J">JS Kim</name></author><author><name sortKey="Voss, Mw" uniqKey="Voss M">MW Voss</name></author><author><name sortKey="Vanpatter, M" uniqKey="Vanpatter M">M Vanpatter</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Herting, Mm" uniqKey="Herting M">MM Herting</name></author><author><name sortKey="Nagel, Bj" uniqKey="Nagel B">BJ 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, CA USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28278300</article-id><article-id pub-id-type="pmc">5344515</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0173672</article-id><article-id pub-id-type="publisher-id">PONE-D-16-40437</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Public and Occupational Health</subject><subj-group><subject>Physical Activity</subject><subj-group><subject>Physical Fitness</subject><subj-group><subject>Exercise</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Sports and Exercise Medicine</subject><subj-group><subject>Exercise</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Sports Science</subject><subj-group><subject>Sports and Exercise Medicine</subject><subj-group><subject>Exercise</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Public and Occupational Health</subject><subj-group><subject>Physical Activity</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Public and Occupational Health</subject><subj-group><subject>Physical Activity</subject><subj-group><subject>Physical Fitness</subject><subj-group><subject>Exercise</subject><subj-group><subject>Aerobic Exercise</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Sports and Exercise Medicine</subject><subj-group><subject>Exercise</subject><subj-group><subject>Aerobic Exercise</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Sports Science</subject><subj-group><subject>Sports and Exercise Medicine</subject><subj-group><subject>Exercise</subject><subj-group><subject>Aerobic Exercise</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Cardiology</subject><subj-group><subject>Heart Rate</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Neuroscience</subject><subj-group><subject>Cellular Neuroscience</subject><subj-group><subject>Neuronal Plasticity</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Anatomy</subject><subj-group><subject>Brain</subject><subj-group><subject>Motor Cortex</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Anatomy</subject><subj-group><subject>Brain</subject><subj-group><subject>Motor Cortex</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Bioassays and Physiological Analysis</subject><subj-group><subject>Electrophysiological Techniques</subject><subj-group><subject>Brain Electrophysiology</subject><subj-group><subject>Transcranial Stimulation</subject><subj-group><subject>Transcranial Magnetic Stimulation</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Physiology</subject><subj-group><subject>Electrophysiology</subject><subj-group><subject>Neurophysiology</subject><subj-group><subject>Brain Electrophysiology</subject><subj-group><subject>Transcranial Stimulation</subject><subj-group><subject>Transcranial Magnetic Stimulation</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Physiology</subject><subj-group><subject>Electrophysiology</subject><subj-group><subject>Neurophysiology</subject><subj-group><subject>Brain Electrophysiology</subject><subj-group><subject>Transcranial Stimulation</subject><subj-group><subject>Transcranial Magnetic Stimulation</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Neuroscience</subject><subj-group><subject>Neurophysiology</subject><subj-group><subject>Brain Electrophysiology</subject><subj-group><subject>Transcranial Stimulation</subject><subj-group><subject>Transcranial Magnetic Stimulation</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Neuroscience</subject><subj-group><subject>Brain Mapping</subject><subj-group><subject>Transcranial Stimulation</subject><subj-group><subject>Transcranial Magnetic Stimulation</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Bioassays and Physiological Analysis</subject><subj-group><subject>Electrophysiological Techniques</subject><subj-group><subject>Muscle Electrophysiology</subject><subj-group><subject>Electromyography</subject></subj-group></subj-group></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Physical activity levels determine exercise-induced changes in brain excitability</article-title><alt-title alt-title-type="running-head">Corticospinal output increases in physically active individuals</alt-title></title-group><contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Lulic</surname><given-names>Tea</given-names></name><xref ref-type="aff" rid="aff001"></xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>El-Sayes</surname><given-names>Jenin</given-names></name><xref ref-type="aff" rid="aff001"></xref></contrib><contrib contrib-type="author"><name><surname>Fassett</surname><given-names>Hunter J.</given-names></name><xref ref-type="aff" rid="aff001"></xref></contrib><contrib contrib-type="author"><name><surname>Nelson</surname><given-names>Aimee J.</given-names></name><xref ref-type="aff" rid="aff001"></xref><xref ref-type="corresp" rid="cor001">*</xref></contrib></contrib-group><aff id="aff001"><addr-line>Department of Kinesiology, McMaster University, Hamilton, Canada</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Antal</surname><given-names>Andrea</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>University Medical Center Goettingen, GERMANY</addr-line></aff><author-notes><fn fn-type="COI-statement" id="coi001"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceptualization:</bold> TL JE AJN.</p></list-item><list-item><p><bold>Data curation:</bold> AJN.</p></list-item><list-item><p><bold>Formal analysis:</bold> TL JE AJN.</p></list-item><list-item><p><bold>Funding acquisition:</bold> AJN.</p></list-item><list-item><p><bold>Investigation:</bold> TL JE HF.</p></list-item><list-item><p><bold>Methodology:</bold> TL JE HF AJN.</p></list-item><list-item><p><bold>Project administration:</bold> TL JE.</p></list-item><list-item><p><bold>Resources:</bold> TL JE AJN.</p></list-item><list-item><p><bold>Software:</bold> TL JE HF AJN.</p></list-item><list-item><p><bold>Supervision:</bold> AJN.</p></list-item><list-item><p><bold>Validation:</bold> TL JE HF AJN.</p></list-item><list-item><p><bold>Visualization:</bold> TL JE HF AJN.</p></list-item><list-item><p><bold>Writing – original draft:</bold> TL JE AJN.</p></list-item><list-item><p><bold>Writing – review & editing:</bold> TL JE HF AJN.</p></list-item></list></p></fn><corresp id="cor001">* E-mail: <email>nelsonaj@mcmaster.ca</email></corresp></author-notes><pub-date pub-type="epub"><day>9</day><month>3</month><year>2017</year></pub-date><pub-date pub-type="collection"><year>2017</year></pub-date><volume>12</volume><issue>3</issue><elocation-id>e0173672</elocation-id><history><date date-type="received"><day>10</day><month>10</month><year>2016</year></date><date date-type="accepted"><day>25</day><month>2</month><year>2017</year></date></history><permissions><copyright-statement>© 2017 Lulic et al</copyright-statement><copyright-year>2017</copyright-year><copyright-holder>Lulic et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="pone.0173672.pdf"></self-uri><abstract><p>Emerging evidence suggests that regular physical activity can impact cortical function and facilitate plasticity. In the present study, we examined how physical activity levels influence corticospinal excitability and intracortical circuitry in motor cortex following a single session of moderate intensity aerobic exercise. We aimed to determine whether exercise-induced short-term plasticity differed between high versus low physically active individuals. Participants included twenty-eight young, healthy adults divided into two equal groups based on physical activity level determined by the International Physical Activity Questionnaire: low-to-moderate (LOW) and high (HIGH) physical activity. Transcranial magnetic stimulation was used to assess motor cortex excitability via motor evoked potential (MEP) recruitment curves for the first dorsal interosseous (FDI) muscle at rest (MEP<sub>REST</sub>) and during tonic contraction (MEP<sub>ACTIVE</sub>), short-interval intracortical inhibition (SICI) and facilitation (SICF), and intracortical facilitation (ICF). All dependent measures were obtained in the resting FDI muscle, with the exception of AMT and MEP<sub>ACTIVE</sub> recruitment curves that were obtained during tonic FDI contraction. Dependent measures were acquired before and following moderate intensity aerobic exercise (20 mins, ~60% of the age-predicted maximal heart rate) performed on a recumbent cycle ergometer. Results indicate that MEP<sub>REST</sub> recruitment curve amplitudes and area under the recruitment curve (AURC) were increased following exercise in the HIGH group only (p = 0.002 and p = 0.044, respectively). SICI and ICF were reduced following exercise irrespective of physical activity level (p = 0.007 and p = 0.04, respectively). MEP<sub>ACTIVE</sub> recruitment curves and SICF were unaltered by exercise. These findings indicate that the propensity for exercise-induced plasticity is different in high versus low physically active individuals. Additionally, these data highlight that a single session of aerobic exercise can transiently reduce inhibition in the motor cortex regardless of physical activity level, potentially priming the system for plasticity induction.</p></abstract><funding-group><award-group id="award001"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000038</institution-id><institution>Natural Sciences and Engineering Research Council of Canada</institution></institution-wrap></funding-source><award-id>RGPIN-2015-06309</award-id><principal-award-recipient><name><surname>Nelson</surname><given-names>Aimee J.</given-names></name></principal-award-recipient></award-group><funding-statement>This study was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC RGPIN -2015-06309).</funding-statement></funding-group><counts><fig-count count="3"></fig-count><table-count count="1"></table-count><page-count count="18"></page-count></counts><custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name><meta-value>All data files are available from the Figshare database at <ext-link ext-link-type="uri" xlink:href="https://figshare.com">https://figshare.com</ext-link> (accession number <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.6084/m9.figshare.4270178">10.6084/m9.figshare.4270178</ext-link>).</meta-value></custom-meta></custom-meta-group></article-meta><notes><title>Data Availability</title><p>All data files are available from the Figshare database at <ext-link ext-link-type="uri" xlink:href="https://figshare.com">https://figshare.com</ext-link> (accession number <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.6084/m9.figshare.4270178">10.6084/m9.figshare.4270178</ext-link>).</p></notes></front><body><sec sec-type="intro" id="sec001"><title>Introduction</title><p>Regular aerobic exercise can influence cellular [<xref rid="pone.0173672.ref001" ref-type="bibr">1</xref>–<xref rid="pone.0173672.ref006" ref-type="bibr">6</xref>] and molecular [<xref rid="pone.0173672.ref005" ref-type="bibr">5</xref>, <xref rid="pone.0173672.ref007" ref-type="bibr">7</xref>, <xref rid="pone.0173672.ref008" ref-type="bibr">8</xref>] processes thereby altering hippocampal and sub-cortical loci [<xref rid="pone.0173672.ref001" ref-type="bibr">1</xref>–<xref rid="pone.0173672.ref006" ref-type="bibr">6</xref>] as well as increasing levels of key neurotrophic factors, such as brain derived neurotrophic factor (BDNF) [<xref rid="pone.0173672.ref007" ref-type="bibr">7</xref>], that mediate neuroplasticity [<xref rid="pone.0173672.ref009" ref-type="bibr">9</xref>]. Further, executive function, such as response inhibition and processing speed, is enhanced in physically active individuals [<xref rid="pone.0173672.ref001" ref-type="bibr">1</xref>, <xref rid="pone.0173672.ref002" ref-type="bibr">2</xref>, <xref rid="pone.0173672.ref005" ref-type="bibr">5</xref>, <xref rid="pone.0173672.ref010" ref-type="bibr">10</xref>, <xref rid="pone.0173672.ref011" ref-type="bibr">11</xref>]. Thus, long-term exercise appears to facilitate cognitive function and memory through neuroplasticity and neuroprotective mechanisms. Additionally, regular exercise leads to chronic physiological adaptions that impact the response to a single session of aerobic exercise (see review: [<xref rid="pone.0173672.ref012" ref-type="bibr">12</xref>]). These adaptions include increased metabolic efficiency at a given heart rate [<xref rid="pone.0173672.ref012" ref-type="bibr">12</xref>], increased stroke volume [<xref rid="pone.0173672.ref013" ref-type="bibr">13</xref>], increased brain perfusion [<xref rid="pone.0173672.ref014" ref-type="bibr">14</xref>], and alterations in individual responses to stress, anxiety, and perceived rate of exertion [<xref rid="pone.0173672.ref012" ref-type="bibr">12</xref>]. As such, individuals who regularly exercise may respond differently to a single session of exercise than those who do not.</p><p>A single session of aerobic exercise has the capacity to induce short-term neuroplasticity within the human motor cortex, as assessed via cortical circuits evoked by transcranial magnetic stimulation (TMS). For example, intracortical facilitation (ICF) increases [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>] while short-interval intracortical inhibition (SICI) decreases [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>] or does not change [<xref rid="pone.0173672.ref017" ref-type="bibr">17</xref>] following a single session of exercise. ICF is thought to reflect N-methyl<sub>D</sub>-aspartate (NMDA) receptors [<xref rid="pone.0173672.ref018" ref-type="bibr">18</xref>], while SICI is mediated via GABA<sub>A</sub> receptor activity [<xref rid="pone.0173672.ref019" ref-type="bibr">19</xref>, <xref rid="pone.0173672.ref020" ref-type="bibr">20</xref>]. Both ICF and SICI have been implicated in cortical reorganization and plasticity within the primary motor cortex [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref021" ref-type="bibr">21</xref>]. Further, motor evoked potentials (MEPs), a measure of corticospinal excitability [<xref rid="pone.0173672.ref022" ref-type="bibr">22</xref>, <xref rid="pone.0173672.ref023" ref-type="bibr">23</xref>], are unchanged following a single session of aerobic exercise in individuals who are relatively sedentary [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>]. Aerobic exercise, therefore, provides an opportunity to create short-term changes in specific TMS circuits that may serve as targets for promoting neuroplasticity. Finally, a single session of aerobic exercise can be used to supplement other plasticity inducing approaches to yield greater effects [<xref rid="pone.0173672.ref024" ref-type="bibr">24</xref>–<xref rid="pone.0173672.ref026" ref-type="bibr">26</xref>].</p><p>MEPs can be obtained in the resting or actively contracted muscle to assess distinct mechanisms of corticospinal excitability [<xref rid="pone.0173672.ref022" ref-type="bibr">22</xref>, <xref rid="pone.0173672.ref023" ref-type="bibr">23</xref>]. To date, no studies have investigated whether exercise induces short-term changes in MEPs in actively contracted muscles. Compared to relaxed muscle, voluntarily activation reduces the threshold for TMS activation of motor neurons [<xref rid="pone.0173672.ref023" ref-type="bibr">23</xref>]. Therefore, quantifying MEPs in the active versus resting state assesses corticospinal output with and without the voluntary activation of motor neurons. For example, MEPs are reduced in individuals with spinal cord injury [<xref rid="pone.0173672.ref027" ref-type="bibr">27</xref>] and Parkinson’s disease (PD) [<xref rid="pone.0173672.ref028" ref-type="bibr">28</xref>] compared to controls when they are measured in the active but not resting muscle. Therefore, it is important to determine whether corticospinal excitability can be modulated with aerobic exercise via either of these mechanisms.</p><p>Short interval intracortical facilitation (SICF) is considered to reflect GABA<sub>A</sub> receptor activity [<xref rid="pone.0173672.ref029" ref-type="bibr">29</xref>] and is facilitated in PD [<xref rid="pone.0173672.ref030" ref-type="bibr">30</xref>] and Fabry’s disease [<xref rid="pone.0173672.ref031" ref-type="bibr">31</xref>]. SICF is unchanged following repetitive TMS [<xref rid="pone.0173672.ref032" ref-type="bibr">32</xref>, <xref rid="pone.0173672.ref033" ref-type="bibr">33</xref>]. However, the natural stimulus of aerobic exercise may have the capacity to alter SICF and operate as a method to create neuroplasticity in these populations. To date, no studies have investigated the impact of a single session of aerobic exercise on the SICF circuit, yet this information may benefit clinical neuroscience research.</p><p>The type of exercise and the population tested may influence the opportunity for exercise-induced short-term plasticity. First, aerobic exercise is favored as it increases BDNF more frequently than resistance training (see review [<xref rid="pone.0173672.ref034" ref-type="bibr">34</xref>]). Second, physical activity levels influence the propensity for plasticity. For example, paired associative stimulation (PAS) induces short-term plasticity only in the corticospinal output of physically active individuals [<xref rid="pone.0173672.ref035" ref-type="bibr">35</xref>]. The effects of physical activity levels on exercise-induced plasticity have yet to be investigated.</p><p>In the present study, we aimed to identify the TMS circuits that are modulated following a single session of aerobic exercise and to determine if physical activity levels influence the magnitude of exercise-induced plasticity in these circuits. To assess plasticity, we measured TMS-evoked circuits including MEP recruitment curves in the resting and active states, SICI, ICF, and SICF in a resting hand muscle before and after aerobic exercise. To our knowledge, this is the first study to investigate the influence of physical activity levels on exercise-induced plasticity in these circuits. Our data indicate that a single session of aerobic exercise induces changes in resting MEP recruitment curves, SICI, and ICF, confirming the capability for exercise to induce short-term plasticity. These findings suggest that aerobic exercise, as a plasticity-inducing paradigm, has differential effects on corticospinal excitability depending on physical activity level.</p></sec><sec sec-type="materials|methods" id="sec002"><title>Methods</title><sec id="sec003"><title>Participants</title><p>Twenty-eight young adults who self-identified as physically active (HIGH: N = 14, 22.1 ± 2.8 years, 9 female) or sedentary (LOW: N = 14, 20.6 ± 0.84, 8 female) participated in this study. All participants were right-hand dominant as determined by the modified version of the Edinburgh Handedness Scale [<xref rid="pone.0173672.ref036" ref-type="bibr">36</xref>] and had no known history of neurological disease. Participants were screened for contraindications to TMS [<xref rid="pone.0173672.ref037" ref-type="bibr">37</xref>] and exercise using the Physical Activity Readiness Questionnaire (PAR-Q) [<xref rid="pone.0173672.ref038" ref-type="bibr">38</xref>]. Written informed consent was obtained prior to participation. This study was approved by the McMaster Research Ethics Board and conformed to the Declaration of Helsinki.</p><p>Physical activity levels were determined using the International Physical Activity Questionnaire (IPAQ) that quantifies the physical activity performed in the past week [<xref rid="pone.0173672.ref039" ref-type="bibr">39</xref>]. Participants who accumulated more than 3000 metabolic equivalents (METs) on IPAQ were considered highly physically active (HIGH), while those who accumulated less than 3000 METs were considered low-to-moderately active (LOW) [<xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>, <xref rid="pone.0173672.ref040" ref-type="bibr">40</xref>]. The IPAQ scores were significantly higher for the HIGH (METs 7631 ± 6120; 3231–21162) versus LOW (METs 1305 ± 773; 360–2892) group (p < 0.001). To verify the grouping of participants in the HIGH and LOW categories, the Minnesota Leisure Activity Questionnaire [<xref rid="pone.0173672.ref041" ref-type="bibr">41</xref>] was used to assess long term physical activity levels in each participant. These data confirm the division of HIGH (7441 ± 6157) and LOW (965 ± 1062) activity levels (p < 0.001) in the sample tested.</p></sec><sec id="sec004"><title>Electromyography (EMG) recording</title><p>Electromyography (EMG) was recorded using surface electrodes (9 mm diameter Ag-AgCl) over first dorsal interosseous (FDI) muscle of the right hand in a belly tendon montage. A wet ground electrode was placed around the forearm. EMG measurements were amplified (x1000), and filtered with a band pass (20 Hz—2.5 kHz) (Intronix Technologies Corporation Model 2024F with Signal Conditioning; Intronix Technologies Corporation, Bolton, Canada) and subsequently digitized at 5 kHz (Power1401, Cambridge Electronic Design, Cambridge, UK). EMG data was collected using Signal software version 6.02 (Cambridge Electronic Design, Cambridge, UK).</p></sec><sec id="sec005"><title>Maximum Voluntary Contraction (MVC)</title><p>Participants completed three maximal isometric contractions of the FDI against an immovable structure. Each contraction persisted for 5 s with a 30 s rest interval between trials. The largest maximum EMG activity obtained from the three trials was deemed the maximum voluntary contraction (MVC) of FDI for a given participant. The level of EMG corresponding to the MVC was displayed to the participant on an oscilloscope. The voltage that corresponded to 10% of MVC was calculated and displayed on the oscilloscope with a horizontal target line. The participant then performed a contraction of FDI to move a second horizontal line controlled by their EMG to match the position of the target line. Therefore, participants used their own visual feedback to maintain the 10% MVC during the acquisition of active motor threshold and active MEP recruitment curve (see below).</p></sec><sec id="sec006"><title>Transcranial Magnetic Stimulation (TMS)</title><p>Single and paired monophasic TMS pulses were delivered using a custom-built 50 mm diameter figure-of-eight branding coil connected to a Magstim Bistim stimulator (Magstim, Whitland, UK). The TMS coil was placed over the optimal location to elicit MEPs in the relaxed right FDI. Coil was positioned 45 degrees in relation to the parasagittal plane to induce posterior-to-anterior current in the cortex. The motor hotspot for FDI muscle of the right hand was determined within the left hemisphere motor cortex and defined as the location that consistently elicited MEPs in the relaxed FDI muscle. The motor hotspot was marked by digital registration using a standard MRI template via Brainsight Neuronavigation (Rogue Research, Canada). Resting motor threshold (RMT) and active motor threshold (AMT) were determined for the right FDI. RMT was defined as the lowest intensity required to evoke an MEP ≥ 50 μV in 5 out of 10 consecutive trials in relaxed FDI muscle [<xref rid="pone.0173672.ref037" ref-type="bibr">37</xref>]. AMT was defined as the lowest intensity required to evoke an MEP ≥ 200 μV in 5 out of 10 consecutive trials while participants maintained ~10% of their MVC in right FDI [<xref rid="pone.0173672.ref037" ref-type="bibr">37</xref>]. Visual feedback of the right FDI contraction was provided using an oscilloscope.</p></sec><sec id="sec007"><title>Motor Evoked Potential (MEP) recruitment curves</title><p>MEP recruitment curves were obtained in the resting and active (~10% MVC) right FDI muscle. For each curve, three stimuli were delivered at each of 90%, 100%, 110%, 120%, 130%, 140% and 150% RMT or AMT in a randomized order. The number of pulses delivered at each intensity reflects the results of recent studies examining the consistency of MEPs with few stimuli [<xref rid="pone.0173672.ref042" ref-type="bibr">42</xref>, <xref rid="pone.0173672.ref043" ref-type="bibr">43</xref>].</p></sec><sec id="sec008"><title>Short-interval Intracortical Inhibition (SICI) and Intracortical Facilitation (ICF)</title><p>SICI and ICF were investigated using interstimulus intervals (ISI) of 2 ms and 10 ms between the conditioning stimulus (CS) and test stimulus (TS), respectively. Each circuit was tested with CS intensities of 80% and 90% AMT and with TS set to evoke MEPs with peak-to-peak amplitudes of ~1 mV in the right FDI at rest. For each circuit, 20 trials were acquired whereby equal numbers of unconditioned (i.e. MEP<sub>TS</sub>) and conditioned (MEP<sub>CS-TS</sub>) trials were randomly delivered.</p></sec><sec id="sec009"><title>Short-interval Intracortical Facilitation (SICF)</title><p>SICF was measured using a similar method to that described by Ziemann et al. [<xref rid="pone.0173672.ref044" ref-type="bibr">44</xref>]. SICF was investigated using ISIs of 1.2 ms and 2.5 ms and was recorded in two blocks of 20 trials for each ISI (20 at 1.2 ms, 20 at 2.5 ms; 10 TS and 10 CS/TS each block). CS intensity was set to 90% RMT for both ISIs. The TS intensity was set to evoke MEPs with peak-to-peak amplitudes of ~1 mV in the right FDI at rest.</p></sec><sec id="sec010" sec-type="materials|methods"><title>Experimental design</title><p>The experimental timeline is depicted in <xref ref-type="fig" rid="pone.0173672.g001">Fig 1</xref>. The session was divided into two time blocks: T<sub>0</sub> (pre-exercise) and T<sub>1</sub> (10 minutes post-exercise). All dependent measures were obtained in the resting FDI muscle, with the exception of AMT and MEP<sub>ACTIVE</sub> recruitment curves that were obtained during tonic FDI contraction corresponding to ~10% MVC. The TMS intensity to elicit ~1 mV response in the resting FDI was re-assessed prior to the start of T<sub>1</sub>. The order of dependent measure acquisition was pseudorandomized (William Square Counterbalance).</p><fig id="pone.0173672.g001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0173672.g001</object-id><label>Fig 1</label><caption><title>Experimental timeline.</title><p>Measures of resting motor threshold (RMT), active motor threshold (AMT), motor evoked potential (MEP) recruitment curves obtained at rest (MEP<sub>REST</sub>) and during ~10% MVC (MEP<sub>ACTIVE</sub>), short-interval intracortical inhibition (SICI), intracortical facilitation (ICF) and short-interval intracortical facilitation (SICF) were acquired prior to (T<sub>0</sub>) and ten minutes following the cessation of exercise (T<sub>1</sub>).The order of dependent measure acquisition was pseudo-randomized across participants using a Williams Square design. The exercise intervention began following the assembly of the heart rate (HR) monitor and involved 5 minutes of cycling warm-up, 20 minutes of moderate-intensity exercise (50–70% of age-predicted maximal heart rate (HR)) and 5 minutes of cycling cool-down. During the 20-minute exercise, resistance was adjusted online to maintain HR in the target range. HR was recorded every 2 minutes as shown.</p></caption><graphic xlink:href="pone.0173672.g001"></graphic></fig></sec><sec id="sec011"><title>Exercise procedures</title><p>Participants completed a lower limb exercise on a recumbent cycle ergometer (Exerpeutic Heavy Duty Magnetic Recumbent Bike with Pulse, PARADIGM Health & Wellness, USA). The exercise session included 5 minutes of warm up at a comfortable pace, 20 minutes of moderate intensity exercise at 50–70% age-predicted maximal heart rate (i.e. 220 –age) [<xref rid="pone.0173672.ref045" ref-type="bibr">45</xref>], followed by 5 minutes of cool down at a comfortable pace. All individuals were maintained at ~60% of their age-predicted maximal heart rate, as performed elsewhere [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref040" ref-type="bibr">40</xref>]. Heart rate was monitored using an FT1 Polar heart rate monitor (FT1/FT2 watch and chest strap—Polar, Australia) and recorded by the experimenter every two minutes during the 20-minute exercise period. This information was used to adjust the resistance on the ergometer to maintain the targeted age-predicted heart rate range. Participants were instructed to maintain a cycling speed of 8–12 miles per hour, as indicated on the ergometer display available to them. Throughout the exercise, participants kept their arms comfortably relaxed in their lap to ensure that the FDI muscle, the target muscle for TMS-evoked measures, was not active during the exercise intervention.</p></sec><sec id="sec012"><title>Data analysis and statistics</title><p>For MEP recruitment curves, the mean peak-to-peak amplitude was calculated for each RMT and AMT intensity (90–150%). All slopes were calculated in Microsoft Excel using linear regression of the entire recruitment curve and were subsequently tested for correlation with IPAQ scores. The area under the recruitment curve (AURC) was obtained by taking a trapezoidal integration of the recruitment curves. For paired-pulse TMS measures, the mean peak-to-peak MEP amplitude was calculated for the conditioned and unconditioned stimuli at each CS or ISI intensity separately. The percentage inhibition and facilitation was then calculated as a ratio of conditioned over unconditioned stimulus (CS-TS/TS). For each individual, the depth of the SICI and ICF was examined at T<sub>0</sub> for each of the two CS intensities tested (80%, 90% AMT). The CS intensity at which the greatest depth was observed at T<sub>0</sub> was chosen for further analyses. Since reductions in SICI were hypothesized from previous research [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>], participants were required to demonstrate a minimum of 5% SICI at T<sub>0</sub> to be included in the SICI analysis. Additionally, since increases in facilitation were hypothesized [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>] individuals were required to present with a minimum of 5% ICF or SICF at T<sub>0</sub> to be included in the ICF or SICF analysis.</p><p>Group-level statistics included normality testing via the Shapiro-Wilk analysis. Outlier data were identified via SPSS, as 3 times above or below the interquartile range and were removed from further analyses. Specifically, one participant was removed from the HIGH group for resting and active MEP recruitment curves, and one participant was removed from the LOW group for SICI, ICF, and SICF<sub>1.2ms</sub>. Non-normally distributed data was ranked and a non-parametric Conover’s ANOVA was performed [<xref rid="pone.0173672.ref046" ref-type="bibr">46</xref>]. MEP recruitment curves were analyzed using three-way Conover’s ANOVA using within-subject factors TIME (2 levels: T<sub>0</sub>, T<sub>1</sub>) and factor INTENSITY (7 levels: 90, 100, 110, 120, 130, 140, 150% RMT/AMT) and between-subject factors GROUP (2 levels: LOW, HIGH). RMT, AMT, and SICI were analyzed using two-way ANOVA while AURC, ICF, and SICF were analyzed using a two-way Conover’s ANOVA with within-subject factor TIME (2 levels: T<sub>0</sub>, T<sub>1</sub>) and between-subject factor GROUP (2 levels: LOW, HIGH). For normally distributed dependent measures, post-hoc testing was performed using two-tailed t-tests. Post-hoc tests for non-parametric data included a Wilcoxon Signed-Rank for within group comparisons and Mann-Whitney U test for between group differences. All post-hoc testing was Bonferroni corrected. The significance level was set to p ≤ 0.05.</p></sec></sec><sec sec-type="results" id="sec013"><title>Results</title><p>All participants successfully completed the study and performed the aerobic exercise at ~60% of their age-predicted maximal heart rate (LOW: 60.5 ± 1.9%, HIGH: 58.9 ± 3.3%, p = 0.154). <xref ref-type="table" rid="pone.0173672.t001">Table 1</xref> displays the results of all statistical analyses with associated effect sizes and 95% confidence intervals.</p><table-wrap id="pone.0173672.t001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0173672.t001</object-id><label>Table 1</label><caption><title>Statistical analyses.</title></caption><alternatives><graphic id="pone.0173672.t001g" xlink:href="pone.0173672.t001"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Dependent Measure</th><th align="left" rowspan="1" colspan="1">ANOVA</th></tr></thead><tbody><tr><td align="center" rowspan="5" colspan="1">RMT</td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,26)</sub> = 0.101, p = 0.753</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,26)</sub> = 0.042, p = 0.839</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>TIME x GROUP</bold><sub><bold>(1,26)</bold></sub><bold>= 9.449, p = 0.005</bold><xref ref-type="table-fn" rid="t001fn002"><sup>#</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 14): T<sub>0</sub>: 38.6 ± 1.62%MSO T<sub>1</sub>: 37.5 ± 1.79%MSO, <italic>d</italic> = 0.17</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 14): T<sub>0</sub>: 37.1 ± 1.93%MSO T<sub>1</sub>: 38.0 ± 2.09%MSO, <italic>d</italic> = 0.12</td></tr><tr><td align="center" rowspan="8" colspan="1">MEP<sub>REST</sub> Amplitude<xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,25)</sub> = 0.577, p = 0.455</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,25)</sub> = 1.447, p = 0.240</td></tr><tr><td align="left" rowspan="1" colspan="1">INTENSITY<sub>(6,20)</sub> = 79.32, p = 0.000</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>TIME x GROUP</bold><sub><bold>(1,25)</bold></sub><bold>= 4.788, p = 0.038</bold></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>H: T</bold><sub><bold>0</bold></sub><bold></bold> <sub><bold>1</bold></sub><bold>p = 0.002, <italic>d</italic> = 0.17, 95% CI: -0.93 to 0.61</bold></td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x INTENSITY<sub>(6,20)</sub> = 0.761, p = 0.609</td></tr><tr><td align="left" rowspan="1" colspan="1">INTENSITY x GROUP<sub>(6,20)</sub> = 0.798, p = 0.583</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP x INTENSITY<sub>(6,20)</sub> = 1.594, p = 0.201</td></tr><tr><td align="center" rowspan="4" colspan="1">MEP<sub>REST</sub> AURC<xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,26)</sub> = 0.178, p = 0.676</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,26)</sub> = 3.914, p = 0.059</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>TIME x GROUP</bold><sub><bold>(1,26)</bold></sub><bold>= 6.10, p = 0.02</bold></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>H: T</bold><sub><bold>0</bold></sub><bold></bold> <sub><bold>1</bold></sub><bold>p = 0.044, <italic>d</italic> = 0.54, 95% CI: -1.27 to 0.23 (uncorrected)</bold></td></tr><tr><td align="center" rowspan="5" colspan="1">AMT</td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,26)</sub> = 1.204, p = 0.283</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,26)</sub> = 0.278, p = 0.603</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,26)</sub> = 1.873, p = 0.187</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 14): T<sub>0</sub>: 26.1 ± 0.84%MSO T<sub>1</sub>: 24.7 ± 0.96%MSO, <italic>d</italic> = 0.42</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 14): T<sub>0</sub>: 24.5 ± 1.31%MSO T<sub>1</sub>: 24.6 ± 1.45%MSO, <italic>d</italic> = 0.02</td></tr><tr><td align="center" rowspan="7" colspan="1">MEP<sub>ACTIVE</sub> Amplitude<xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,25)</sub> = 3.554, p = 0.071</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,26)</sub> = 0.365 p = 0.551</td></tr><tr><td align="left" rowspan="1" colspan="1">INTENSITY<sub>(6, 20)</sub> = 55.17, p = 0.000</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,25)</sub> = 0.001, p = 0.981</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x INTENSITY<sub>(6, 20)</sub> = 0.617, p = 0.714</td></tr><tr><td align="left" rowspan="1" colspan="1">INTENSITY x GROUP<sub>(6, 20)</sub> = 1.406, p = 0.261</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP x INTENSITY<sub>(6, 20)</sub> = 1.34, p = 0.286</td></tr><tr><td align="center" rowspan="5" colspan="1">MEP<sub>ACTIVE</sub> AURC<xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,26)</sub> = 0.084, p = 0.775</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,26)</sub> = 0.453, p = 0.507</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,26)</sub> = 0.44, p = 0.513</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 14): T<sub>0</sub>: 6.08 ± 0.67 AURC T<sub>1</sub>: 4.73 ± 0.52 AURC, <italic>d</italic> = 0.60</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 14): T<sub>0</sub>: 5.99 ± 1.01 AURC T<sub>1</sub>: 5.25 ± 0.76 AURC, <italic>d</italic> = 0.22</td></tr><tr><td align="center" rowspan="4" colspan="1">SICI</td><td align="left" rowspan="1" colspan="1"><bold>TIME</bold><sub><bold>(1,22)</bold></sub><bold>= 8.674, p = 0.007</bold></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>T</bold><sub><bold>0</bold></sub><bold></bold> <sub><bold>1</bold></sub><bold>, p = 0.007, <italic>d</italic> = 0.512, 95% CI: -1.08 to 0.07</bold></td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,22)</sub> = 0.168, p = 0.686</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,22)</sub> = 0.380, p = 0.544</td></tr><tr><td align="center" rowspan="3" colspan="1">SICI TS</td><td align="left" rowspan="1" colspan="1">TIME<sub>(1,23)</sub> = 0.036, p = 0.851</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 13): T<sub>0</sub>: 1.03 ± 0.04 mV T<sub>1</sub>: 1.13 ± 0.06 mV, <italic>d</italic> = 0.54</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 11): T<sub>0</sub>: 1.16 ± 0.03 mV T<sub>1</sub>: 1.06 ± 0.06 mV, <italic>d</italic> = 0.57</td></tr><tr><td align="center" rowspan="4" colspan="1">ICF<xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1"><bold>TIME</bold><sub><bold>(1,22)</bold></sub><bold>= 5.268, p = 0.032</bold></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>T</bold><sub><bold>0</bold></sub><bold>>T</bold><sub><bold>1</bold></sub><bold>, p = 0.04, <italic>d</italic> = 0.71, 95% CI: -0.14 to 1.51</bold></td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,22)</sub> = 0.000, p = 0.983</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,22)</sub> = 0.222, p = 0.642</td></tr><tr><td align="center" rowspan="3" colspan="1">ICF TS</td><td align="left" rowspan="1" colspan="1">TIME<sub>(1,23)</sub> = 0.060 p = 0.808</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 12): T<sub>0</sub>: 1.05 ± 0.08 mV T<sub>1</sub>: 1.12 ± 0.09 mV, <italic>d</italic> = 0.25</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 12): T<sub>0</sub>: 1.20 ± 0.08 mV T<sub>1</sub>: 1.18 ± 0.06 mV, <italic>d</italic> = 0.07</td></tr><tr><td align="center" rowspan="5" colspan="1">SICF<sub>1.2ms</sub><xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME <sub>(1,24)</sub> = 3.681, p = 0.067</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,24)</sub> = 1.677, p = 0.208</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>TIME x GROUP</bold><sub><bold>(1,24)</bold></sub><bold>= 5.274, p = 0.031</bold><xref ref-type="table-fn" rid="t001fn002"><sup>#</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 13): T<sub>0</sub>: 1.61 ± 0.14 mV T<sub>1</sub>: 1.65 ± 0.13 mV, <italic>d</italic> = 0.08</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 13): T<sub>0</sub>: 2.12 ± 0.22 mV T<sub>1</sub>: 1.76 ± 0.21 mV, <italic>d</italic> = 0.46</td></tr><tr><td align="center" rowspan="3" colspan="1">SICF<sub>1.2ms</sub> TS</td><td align="left" rowspan="1" colspan="1">TIME<sub>(1,25)</sub> = 1.579, p = 0.221</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 13): T<sub>0</sub>: 0.96 ± 0.08 mV T<sub>1</sub>: 0.96 ± 0.07 mV, <italic>d</italic> = 0.00</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 13): T<sub>0</sub>: 0.99 ± 0.06 mV T<sub>1</sub>: 1.16 ± 0.07 mV, <italic>d</italic> = 0.74</td></tr><tr><td align="center" rowspan="5" colspan="1">SICF<sub>2.5ms</sub><xref ref-type="table-fn" rid="t001fn001">*</xref></td><td align="left" rowspan="1" colspan="1">TIME<sub>(1,22)</sub> = 1.247, p = 0.276</td></tr><tr><td align="left" rowspan="1" colspan="1">GROUP<sub>(1,22)</sub> = 0.604, p = 0.445</td></tr><tr><td align="left" rowspan="1" colspan="1">TIME x GROUP<sub>(1,22)</sub> = 0.455, p = 0.507</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 13): T<sub>0</sub>: 1.88 ± 0.21 mV T<sub>1</sub>: 1.91 ± 0.23 mV, <italic>d</italic> = 0.04</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 11): T<sub>0</sub>: 1.68 ± 0.14 mV T<sub>1</sub>: 1.53 ± 0.17 mV, <italic>d</italic> = 0.40</td></tr><tr><td align="center" rowspan="3" colspan="1">SICF<sub>2.5ms</sub> TS</td><td align="left" rowspan="1" colspan="1">TIME<sub>(1,25)</sub> = 0.042, p = 0.840</td></tr><tr><td align="left" rowspan="1" colspan="1">L (N = 13): T<sub>0</sub>: 0.98 ± 0.06 mV T<sub>1</sub>: 1.04 ± 0.06 mV, <italic>d</italic> = 0.28</td></tr><tr><td align="left" rowspan="1" colspan="1">H (N = 11): T<sub>0</sub>: 1.09 ± 0.09 mV T<sub>1</sub>: 1.05 ± 0.09 mV, <italic>d</italic> = 0.14</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="t001fn001"><p>*Conover’s ANOVA (ranked data) and subsequent non-parametric post-hoc analyses.</p></fn><fn id="t001fn002"><p><sup>#</sup>: post-hoc analyses did not pass Bonferroni corrections.</p></fn><fn id="t001fn003"><p>Bolded values indicate significance as shown. Means ± SE displayed. <italic>d</italic>: Cohen’s D, 95% CI: 95% confidence intervalof effect size, T<sub>0</sub> (baseline), T<sub>1</sub> (10 minutes post-exercise), L (LOW group), H (HIGH group).</p></fn></table-wrap-foot></table-wrap><sec id="sec014"><title>Thresholds and MEP recruitment curves</title><p>All participants were included in RMT analysis (N = 14 per group). The group-averaged RMT showed no significant differences among the means (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>). Thirteen and fourteen individuals were included in MEP<sub>REST</sub> analysis for the HIGH and LOW groups, respectively. Group-averaged MEP<sub>REST</sub> recruitment curves (with standard errors) are shown in <xref ref-type="fig" rid="pone.0173672.g002">Fig 2A</xref> and analyses revealed a significant TIME x GROUP interaction (p = 0.038; <xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>) such that amplitudes were significantly increased in the HIGH group following exercise (Wilcoxon: p = 0.002; <xref ref-type="fig" rid="pone.0173672.g002">Fig 2B</xref>). This effect was observed in nine individuals, with little to no change in three individuals and a decrease in MEPs following exercise in one individual. MEP<sub>REST</sub> AURC (N = 14 per group) also revealed a significant TIME x GROUP interaction (p = 0.02; <xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>) such that AURC increased following exercise in the HIGH group only (Wilcoxon: p = 0.04, <xref ref-type="fig" rid="pone.0173672.g002">Fig 2C</xref>). All participants were included in AMT analysis (N = 14 per group). AMT did not statistically differ between groups and was unchanged following exercise (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>). Thirteen and fourteen individuals were included in the MEP<sub>ACTIVE</sub> analysis for the HIGH and LOW groups, respectively. Similarly, the MEP<sub>ACTIVE</sub> recruitment curves (shown in <xref ref-type="fig" rid="pone.0173672.g002">Fig 2D</xref>) and MEP<sub>ACTIVE</sub> AURC were unchanged following exercise (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>). IPAQ scores did not correlate with the percent change in slopes for MEP<sub>REST</sub> or MEP<sub>ACTIVE</sub> recruitment curves (p > 0.05).</p><fig id="pone.0173672.g002" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0173672.g002</object-id><label>Fig 2</label><caption><title>Thresholds and recruitment curves.</title><p><bold>(A)</bold> Group-averaged MEP<sub>REST</sub> recruitment curves (with standard errors) at T<sub>0</sub> and T<sub>1</sub> for the LOW (N = 14) and HIGH (N = 13) groups. TMS intensity is defined as the percentage of RMT. Solid and dashed lines indicate pre (T<sub>0</sub>) and post (T<sub>1</sub>) values, respectively. <bold>(B)</bold> Histograms displaying TIME x GROUP interaction for group-averaged MEP<sub>REST</sub> amplitude (with standard error; LOW: N = 14, HIGH: N = 13). The asterisk indicates a significant increase in MEP<sub>REST</sub> amplitudes. <bold>(C)</bold> Histograms displaying TIME x GROUP interaction for group-averaged MEP<sub>REST</sub> AURC (with standard error; LOW: N = 14, HIGH: N = 14). The asterisk indicates a significant increase in MEP<sub>REST</sub> AURC. <bold>(D)</bold> Group-averaged MEP<sub>ACTIVE</sub> recruitment curves (with standard errors) at T<sub>0</sub> and T<sub>1</sub> for the LOW (N = 14) and HIGH (N = 13) group. TMS intensity is defined as the percentage of the active motor threshold (AMT). Solid and dashed lines indicate pre (T<sub>0</sub>) and post (T<sub>1</sub>) values, respectively.</p></caption><graphic xlink:href="pone.0173672.g002"></graphic></fig></sec><sec id="sec015"><title>Intracortical circuits</title><p>Eleven and thirteen individuals demonstrated SICI at T<sub>0</sub> in the HIGH and LOW groups, respectively, and were included in subsequent analyses. Unconditioned MEPs were maintained at ~1 mV (<xref ref-type="fig" rid="pone.0173672.g003">Fig 3A</xref>). SICI was reduced following exercise regardless of physical activity level (<xref ref-type="fig" rid="pone.0173672.g003">Fig 3B</xref>, showing the main effect of TIME, <xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>, paired t-test: p = 0.007). Fifteen participants (7 HIGH, 8 LOW) demonstrated a reduction in SICI following exercise while three showed little to no change and six revealed increases in SICI. Twelve and twelve individuals demonstrated ICF at T<sub>0</sub> in the HIGH and LOW groups, respectively, and were included in subsequent analyses. Unconditioned MEPs were maintained at ~1 mV (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>, <xref ref-type="fig" rid="pone.0173672.g003">Fig 3C</xref>). ICF was reduced following exercise regardless of physical activity level (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>, Wilcoxon: p = 0.04, <xref ref-type="fig" rid="pone.0173672.g003">Fig 3D</xref>). Fifteen participants (7 HIGH, 8 LOW) demonstrated a reduction in ICF following exercise while three showed little to no change and six revealed increases. SICF<sub>1.2ms</sub> and SICF<sub>2.5ms</sub> were not different between groups and were unchanged by exercise (<xref ref-type="table" rid="pone.0173672.t001">Table 1</xref>).</p><fig id="pone.0173672.g003" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0173672.g003</object-id><label>Fig 3</label><caption><p>SICI: (A) Group-averaged unconditioned MEPs (i.e. MEP<sub>TS</sub>) (with standard errors) for both groups (LOW: N = 13; HIGH: N = 11) at both time points. (B) Group-averaged SICI (with standard errors) for each group (LOW: N = 13; HIGH: N = 11) displaying the main effect of TIME. The asterisk indicates a significant decrease in SICI. ICF: (C) Group-averaged unconditioned MEPs (i.e. MEP<sub>TS</sub>) (with standard errors) for both groups (LOW: N = 12; HIGH: N = 12) at both time points. (B) Group-averaged ICF (with standard errors) for each group (LOW: N = 12; HIGH: N = 12) displaying main effect of TIME. The asterisk indicates a significant decrease in ICF.</p></caption><graphic xlink:href="pone.0173672.g003"></graphic></fig></sec></sec><sec sec-type="conclusions" id="sec016"><title>Discussion</title><p>This study revealed that exercise-induced short-term plasticity depends on the physical activity level of the individual. Exercise increased the amplitude of corticospinal output in the HIGH group, and in contrast, did not alter corticospinal output in the LOW group. This finding indicates that physical activity levels influence the propensity and direction of exercise-induced short-term plasticity. Our data also indicated that exercise reduces SICI, in support of previous literature [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>]. We extend this finding to indicate that SICI reduction occurs in both fit and relatively sedentary individuals. We discuss these findings and the implications for rehabilitation.</p><sec id="sec017"><title>Exercise induces short-term plasticity in corticospinal output</title><p>A key finding in this study is that exercise alters corticospinal excitability depending on the level of physical activity. Corticospinal excitability in the HIGH group increased by ~28% following exercise while no changes were observed for the LOW group. Our findings are similar to the effects of PAS that increases MEPs in physically active but not sedentary groups [<xref rid="pone.0173672.ref035" ref-type="bibr">35</xref>]. While spike-timing dependent mechanisms mediate PAS effects [<xref rid="pone.0173672.ref047" ref-type="bibr">47</xref>], less is known about the neural mechanisms that mediate exercise-induced plasticity. Modulation of neurotransmitter concentration may participate in increasing corticospinal excitability. A single session of aerobic exercise upregulates the release of serotonin [<xref rid="pone.0173672.ref048" ref-type="bibr">48</xref>, <xref rid="pone.0173672.ref049" ref-type="bibr">49</xref>], norepinephrine [<xref rid="pone.0173672.ref050" ref-type="bibr">50</xref>, <xref rid="pone.0173672.ref051" ref-type="bibr">51</xref>], and upregulates [<xref rid="pone.0173672.ref048" ref-type="bibr">48</xref>, <xref rid="pone.0173672.ref050" ref-type="bibr">50</xref>, <xref rid="pone.0173672.ref052" ref-type="bibr">52</xref>–<xref rid="pone.0173672.ref055" ref-type="bibr">55</xref>] or does not change [<xref rid="pone.0173672.ref056" ref-type="bibr">56</xref>] dopamine. These neurotransmitters have been shown to modulate the excitability of motor neurons [<xref rid="pone.0173672.ref057" ref-type="bibr">57</xref>–<xref rid="pone.0173672.ref060" ref-type="bibr">60</xref>]. Exercise-induced increases in corticospinal output may also be due to an increase in glutamate. A single session of exercise increases glutamate [<xref rid="pone.0173672.ref057" ref-type="bibr">57</xref>, <xref rid="pone.0173672.ref058" ref-type="bibr">58</xref>], as measured via <sup>1</sup>H-MRS and a positive correlation exists such that greater cortical glutamate is associated with steeper MEP recruitment curves [<xref rid="pone.0173672.ref059" ref-type="bibr">59</xref>].</p><p>It has been shown that long-term physical activity is linked to improved cognitive function and memory [<xref rid="pone.0173672.ref001" ref-type="bibr">1</xref>, <xref rid="pone.0173672.ref002" ref-type="bibr">2</xref>, <xref rid="pone.0173672.ref005" ref-type="bibr">5</xref>, <xref rid="pone.0173672.ref060" ref-type="bibr">60</xref>]. Although the mechanisms that underpin such improvements remain unclear, there is strong evidence to implicate BDNF as a mediator of neural plasticity. Higher fitness levels are associated with a lower concentration of peripheral BDNF [<xref rid="pone.0173672.ref061" ref-type="bibr">61</xref>, <xref rid="pone.0173672.ref062" ref-type="bibr">62</xref>], suggesting that gains in fitness may yield more efficient uptake and utilization of BDNF in the central nervous system [<xref rid="pone.0173672.ref063" ref-type="bibr">63</xref>]. The exercise-induced facilitation of MEPs we observed in the HIGH group may relate to an increased uptake of BDNF within the central nervous system. Future studies may consider measuring BDNF and corticospinal excitability, simultaneously.</p><p>Increases in MEPs may also be associated with the physiological differences between the two groups. The HIGH group may have increased stroke volume [<xref rid="pone.0173672.ref012" ref-type="bibr">12</xref>], increased brain perfusion [<xref rid="pone.0173672.ref014" ref-type="bibr">14</xref>], and muscle adaptions that may reduce fatigue [<xref rid="pone.0173672.ref012" ref-type="bibr">12</xref>]. Comparatively, the LOW group lacks these chronic adaptions to exercise, which may reduce neuroplasticity induction. This is supported by the trend towards decreases in excitability seen in the LOW group. Since we opted to control heart rate only, differences in the resting MEPs between the groups may be contributed by variances in the workload performed, stress or anxiety associated with the exercise regime and/or the rate of perceived exertion associated with the exercise intervention. Future studies will need to address whether MEPs differ between HIGH and LOW groups when the exercise intervention controls for one or more of these variables. From the present results, we can conclude that exercise controlled by heart rate revealed differences in resting MEPs only and did not create changes in intracortical circuits. However, we note again, that we cannot exclude the contribution of workload, cortisol levels, anxiety and perceived exertion, which were not controlled and may also contribute to these differences.</p></sec><sec id="sec018"><title>Exercise induces short-term plasticity in intracortical inhibition and facilitation</title><p>We observed a reduction in SICI following exercise in support of previous literature [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>], but extend these findings to show that SICI is reduced irrespective of the physical activity level. Previous studies report reductions in SICI following moderate intensity exercise (~20% in [<xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>] and ~35% in [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>]). In our study, we observed an overall decrease of ~18%. The difference may reflect our less intense exercise (~60% age-predicted maximal heart rate vs. 65–70% in [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>]) or the muscle studied (FDI vs. flexor carpi radialis). The mechanisms by which exercise reduces SICI may involve changes in GABA<sub>A</sub> receptor activity that are considered to mediate the circuit [<xref rid="pone.0173672.ref019" ref-type="bibr">19</xref>, <xref rid="pone.0173672.ref020" ref-type="bibr">20</xref>]. Aerobic exercise increases serum BDNF [<xref rid="pone.0173672.ref025" ref-type="bibr">25</xref>, <xref rid="pone.0173672.ref061" ref-type="bibr">61</xref>, <xref rid="pone.0173672.ref063" ref-type="bibr">63</xref>–<xref rid="pone.0173672.ref074" ref-type="bibr">74</xref>] that in turn reduces GABA<sub>A</sub> receptor activity [<xref rid="pone.0173672.ref075" ref-type="bibr">75</xref>]. Additionally, in rat models, BDNF reduces GABA<sub>A</sub> receptor function [<xref rid="pone.0173672.ref076" ref-type="bibr">76</xref>]. Thus, as suggested elsewhere [<xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>] and above, aerobic exercise may increase serum BDNF that acts to decrease SICI.</p><p>We also observed ~15% reduction in ICF following exercise irrespective of the physical activity level. Previous study reports increase in ICF following moderate intensity exercise [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>]. The disparity between previous work and our study may be attributed to differences in exercise or TMS protocols (% AMT vs. % RMT). However, our findings are similar to the effects of continuous theta burst stimulation (cTBS) over M1 which reduced both ICF and SICI [<xref rid="pone.0173672.ref077" ref-type="bibr">77</xref>]. ICF is thought to be mediated via glutamatergic facilitation coupled with persisting GABAergic inhibition [<xref rid="pone.0173672.ref029" ref-type="bibr">29</xref>]. Previous research on drugs has demonstrated that administration of GABA<sub>A</sub> agonists and NMDA antagonists reduces ICF [<xref rid="pone.0173672.ref078" ref-type="bibr">78</xref>–<xref rid="pone.0173672.ref080" ref-type="bibr">80</xref>]. Further, some dopamine agonists, such as cabergoline, also reduce ICF [<xref rid="pone.0173672.ref081" ref-type="bibr">81</xref>] and hence, changes in ICF may be dependent on more than one neuronal circuit [<xref rid="pone.0173672.ref082" ref-type="bibr">82</xref>], as suggested previously [<xref rid="pone.0173672.ref083" ref-type="bibr">83</xref>].</p></sec><sec id="sec019"><title>Circuitry unaltered by exercise</title><p>Several measures of cortical activity were unchanged following exercise. RMT and AMT were unaltered by physical activity levels or exercise, in support of previous literature [<xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>, <xref rid="pone.0173672.ref035" ref-type="bibr">35</xref>, <xref rid="pone.0173672.ref084" ref-type="bibr">84</xref>]. Therefore, a single session of aerobic exercise does not alter the membrane thresholds. Additionally, MEP recruitment curves obtained in the actively contracted FDI were unchanged by exercise, indicating that exercise only alters corticospinal output without the voluntary activation of motor neurons. Lastly, we did not observe significant changes in the SICF circuits following exercise, suggesting that moderate intensity aerobic exercise does not modulate early and late indirect waves (i.e. I-waves), similar to other plasticity inducing paradigms [<xref rid="pone.0173672.ref032" ref-type="bibr">32</xref>, <xref rid="pone.0173672.ref033" ref-type="bibr">33</xref>].</p></sec><sec id="sec020"><title>Implications</title><p>One of the main implications of this work is that pre-existing physical activity levels determine the propensity for plasticity. In our sedentary group, exercise did not alter excitability, while in the active group the neuronal output to a hand muscle was enhanced, which is a major goal of rehabilitative approaches. Collectively our data suggest that physically active individuals demonstrate a propensity for increasing neuronal output to the hand muscle following a single session of exercise. We speculate that this may have ramifications for the success of rehabilitation protocols aiming to promote neural plasticity, such that individuals with greater physical activity levels may demonstrate increased propensity for plasticity. Indeed, evidence in the animal literature suggests that physically active animals show better recovery of behavioural performance than their sedentary counterparts [<xref rid="pone.0173672.ref008" ref-type="bibr">8</xref>]. It is important to note that exercise also protects from further neurodegeneration after injury and promotes better recovery. In humans, rehabilitation protocols involving exercise regimes have shown improvements in physical function [<xref rid="pone.0173672.ref085" ref-type="bibr">85</xref>], movement initiation [<xref rid="pone.0173672.ref086" ref-type="bibr">86</xref>], and activities of daily living [<xref rid="pone.0173672.ref087" ref-type="bibr">87</xref>]. Our results support the PAS results [<xref rid="pone.0173672.ref035" ref-type="bibr">35</xref>], indicating that short-term plasticity is observed only in the corticospinal output of physically active individuals. Therefore, regular physical activity may be a determinant for the success of rehabilitation approaches that aim to increase corticospinal output to impaired muscles. Further, our data suggests that exercise can be used to prime the motor cortex for plasticity via a reduction in inhibition, regardless of physical activity level. Recent studies have shown improvements in motor learning [<xref rid="pone.0173672.ref088" ref-type="bibr">88</xref>] and increased response to brain stimulation in healthy adults [<xref rid="pone.0173672.ref024" ref-type="bibr">24</xref>, <xref rid="pone.0173672.ref025" ref-type="bibr">25</xref>, <xref rid="pone.0173672.ref040" ref-type="bibr">40</xref>, <xref rid="pone.0173672.ref089" ref-type="bibr">89</xref>] when exercise is used as a prime.</p></sec><sec id="sec021"><title>Limitations and future directions</title><p>Direct assessment of aerobic capacity may be achieved using maximal volume oxygen uptake (VO<sub>2</sub> max). We use the IPAQ that provides a reliable self-report of physical activity in the past 7 days [<xref rid="pone.0173672.ref039" ref-type="bibr">39</xref>] as used elsewhere [<xref rid="pone.0173672.ref016" ref-type="bibr">16</xref>, <xref rid="pone.0173672.ref035" ref-type="bibr">35</xref>, <xref rid="pone.0173672.ref040" ref-type="bibr">40</xref>]. Future studies may confirm our findings using VO<sub>2</sub> max. Additionally, the recumbent cycle ergometer used in our study did not provide wattage as a function of resistance level. Therefore, we cannot provide the workload achieved by the exercising lower limb muscles. However, we chose to control the aerobic intensity via heart rate as performed elsewhere [<xref rid="pone.0173672.ref015" ref-type="bibr">15</xref>, <xref rid="pone.0173672.ref040" ref-type="bibr">40</xref>], as changes in heart rate yield modification in serum BDNF [<xref rid="pone.0173672.ref090" ref-type="bibr">90</xref>]. An alternative approach is to control for both workload and heart rate by altering the duration of the exercise. Future studies should examine how controlling for workload or altering exercise duration affects exercise-induced neuroplasticity. We collected MEP recruitment curves using 3 pulses per intensity to reduce the intrusion of TMS-induced plasticity. This is a small number of pulses to obtain an estimate of MEP amplitudes, that while used elsewhere [<xref rid="pone.0173672.ref091" ref-type="bibr">91</xref>] may benefit from a greater number of stimuli delivered [<xref rid="pone.0173672.ref092" ref-type="bibr">92</xref>–<xref rid="pone.0173672.ref094" ref-type="bibr">94</xref>]. Thus, future studies should consider using more pulses per intensity to reduce variability in this dependent measure. Further, we emphasize that these findings are achieved following a single session of exercise. Multiple sessions of exercise may increase the opportunity for plasticity to be observed in sedentary individuals [<xref rid="pone.0173672.ref011" ref-type="bibr">11</xref>]. Finally, we have tested young adults, and it remains unknown whether these findings will also be revealed across the lifespan.</p></sec><sec id="sec022"><title>Conclusions</title><p>The present study demonstrated that physical activity levels influence motor cortex excitability and the propensity for exercise-induced plasticity. First, corticospinal excitability is increased following exercise in highly active individuals only. Second, exercise reduces cortical inhibition regardless of physical activity level. A reduction of inhibitory input in the motor cortex creates a more favorable environment for plasticity induction. Therefore, we conclude that physical activity levels should be taken into consideration when investigating corticospinal excitability and plasticity induction within the motor cortex in healthy and clinical populations.</p></sec></sec></body><back><ack><p>The authors thank the Natural Sciences and Engineering Research Council for funding to AJN.</p></ack><ref-list><title>References</title><ref id="pone.0173672.ref001"><label>1</label><mixed-citation publication-type="journal"><name><surname>Chaddock</surname><given-names>L</given-names></name>, <name><surname>Erickson</surname><given-names>KI</given-names></name>, <name><surname>Prakash</surname><given-names>RS</given-names></name>, <name><surname>Kim</surname><given-names>JS</given-names></name>, <name><surname>Voss</surname><given-names>MW</given-names></name>, <name><surname>Vanpatter</surname><given-names>M</given-names></name>, <etal>et al</etal><article-title>A neuroimaging investigation of the association between aerobic fitness, hippocampal volume, and memory performance in preadolescent children</article-title>. <source>Brain Res</source>. <year>2010</year>;<volume>1358</volume>:<fpage>172</fpage>–<lpage>83</lpage>. 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