Aerobic exercise improves cognitive and motor function by inducing neural changes detected using molecular, cellular, and systems level neuroscience techniques. This review unifies the knowledge gained across various neuroscience techniques to provide a comprehensive profile of the neural mechanisms that mediate exercise-induced neuroplasticity. Using a model of exercise-induced neuroplasticity, this review emphasizes the sequence of neural events that accompany exercise, and ultimately promote changes in human performance. This is achieved by differentiating between neuroplasticity induced by acute versus chronic aerobic exercise. Furthermore, this review emphasizes experimental considerations that influence the opportunity to observe exercise-induced neuroplasticity in humans. These include modifiable factors associated with the exercise intervention and nonmodifiable factors such as biological sex, ovarian hormones, genetic variations, and fitness level. To maximize the beneficial effects of exercise in health, disease, and following injury, future research should continue to explore the mechanisms that mediate exercise-induced neuroplasticity. This review identifies some fundamental gaps in knowledge that may serve to guide future research in this area.

Transcranial magnetic studies typically rely on measures of active and resting motor threshold (i.e. AMT, RMT). Previous work has demonstrated that adaptive threshold hunting approaches are efficient for estimating RMT. To date, no study has compared motor threshold estimation approaches for measures of AMT, yet this measure is fundamental in transcranial magnetic stimulation (TMS) studies that probe intracortical circuits. The present study compared two methods for acquiring AMT and RMT: the Rossini-Rothwell (R-R) relative-frequency estimation method and an adaptive threshold-hunting method based on maximum-likelihood parameter estimation by sequential testing (ML-PEST). AMT and RMT were quantified via the R-R and ML-PEST methods in 15 healthy right-handed participants in an experimenter-blinded within-subject study design. AMT and RMT estimations obtained with both the R-R and ML-PEST approaches were not different, with strong intraclass correlation and good limits of agreement. However, ML-PEST required 17 and 15 fewer stimuli than the R-R method for the AMT and RMT estimation, respectively. ML-PEST is effective in reducing the number of TMS pulses required to estimate AMT and RMT without compromising the accuracy of these estimates. Using ML-PEST to estimate AMT and RMT increases the efficiency of the TMS experiment as it reduces the number of pulses to acquire these measures without compromising accuracy. The benefits of using the ML-PEST approach are amplified when multiple target muscles are tested within a session.

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_REST) and during tonic contraction (MEP_ACTIVE), 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_ACTIVE 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_REST 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_ACTIVE 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.

Neuroplasticity refers to the brain’s ability to undergo structural and functional adaptations in response to experience, and this process is associated with learning, memory and improvements in cognitive function. The brain’s propensity for neuroplasticity is influenced by lifestyle factors including exercise, diet and sleep. This review gathers evidence from molecular, systems and behavioral neuroscience to explain how these three key lifestyle factors influence neuroplasticity alone and in combination with one another. This review collected results from human studies as well as animal models. This information will have implications for research, educational, fitness and neurorehabilitation settings.