afferent inhibition (SAI) is characterized by the suppression of the transcranial magnetic stimulation motor evoked potential (MEP) by the cortical arrival of a somatosensory afferent volley. It remains unknown whether the magnitude of SAI reflects changes in the sensory afferent volley, similar to that observed for somatosensory evoked potentials (SEPs). The present study investigated stimulus-response relationships between sensory nerve action potentials (SNAPs), SAI, and SEPs and their interrelatedness. Experiment 1 (n ϭ 23, age 23 Ϯ 1.5 yr) investigated the stimulus-response profile for SEPs and SAI in the flexor carpi radialis muscle after stimulation of the mixed median nerve at the wrist using ϳ25%, 50%, 75%, and 100% of the maximum SNAP and at 1.2ϫ and 2.4ϫ motor threshold (the latter equated to 100% of the maximum SNAP). Experiment 2 (n ϭ 20, age 23.1 Ϯ 2 yr) probed SEPs and SAI stimulus-response relationships after stimulation of the cutaneous digital nerve at ϳ25%, 50%, 75%, and 100% of the maximum SNAP recorded at the elbow. Results indicate that, for both nerve types, SAI magnitude is dependent on the volume of the sensory afferent volley and ceases to increase once all afferent fibers within the nerve are recruited. Furthermore, for both nerve types, the magnitudes of SAI and SEPs are related such that an increase in excitation within somatosensory cortex is associated with an increase in the magnitude of afferent-induced MEP inhibition.TMS; short-latency afferent inhibition; somatosensory evoked potentials; sensory nerve action potential; recruitment curve; afferent volley NEW & NOTEWORTHY This is the first investigation of the relationship between short-latency afferent inhibition (SAI) and the sensory afferent volley and the first to examine the relationship between SAI and somatosensory evoked potentials (SEPs).The data indicate that 1) SAI increases with the recruitment of sensory fibers and 2) its stimulus-response profile is correlated with SEPs. These novel data provide practical guidelines and also contribute to our understanding of SAI mechanisms.

When somatosensory input via electrical stimulation of a peripheral nerve precedes a transcranial magnetic stimulation (TMS) pulse over the primary motor cortex (M1) the corticospinal output is substantially reduced, a phenomenon known as short-latency afferent inhibition (SAI). The present study investigated SAI during rest and during pre-movement, phasic and tonic components of movement. Participants were required to perform an index finger flexion reaction time task in response to an auditory cue. In a series of experiments, SAI was evoked from the mixed, median nerve at the wrist or the cutaneous, digital nerve stimulation of the index finger. To assess the spinal versus cortical origin of movement-related modulation of SAI, F-wave amplitudes were measured during rest and the three movement components. Results indicated that SAI was reduced during all movement components compared to rest, an effect that occurred for both nerves stimulated. Pre-movement SAI reduction was primarily attributed to reduced cortical inhibition, while increased spinal excitability additionally contributed to reduced SAI during tonic and phasic components of movement. SAI was differentially modulated across movement components with mixed but not cutaneous nerve stimulation. These findings reveal that SAI is reduced during movement and this reduction begins as early as the preparation to move. Further, these data suggest that the degree of SAI reduction during movement may be specific to the volume and/or composition of afferent input carried by each nerve.

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Purpose Cumulative load has become a popular metric in running biomechanics research to account for potential spatiotemporal changes associated with different locomotion strategies. This study investigated how incorporating mechanical fatigue principles into Achilles tendon cumulative load measurements affected their relationship with running speed. Methods Achilles tendon forces and strains were estimated from a dynamometry/ultrasound session followed by a motion capture session, where participants ran at three speeds. Three cumulative measures of increasing complexity were calculated using Achilles tendon force/strain: 1) cumulative load, defined as the product of the stance phase time integral of Achilles tendon force/strain and the stride count for 1 km of running; 2) cumulative damage, which accounted for the nonlinear relationship between load magnitude and fatigue life by exponentially weighting the time integral of Achilles tendon force/strain before multiplication with stride count; and (3) the probability of fatigue failure, which expanded upon the cumulative damage measure of Achilles tendon strain by fitting a probabilistic Weibull model to existing fatigue life data to account for the inherent variability that exists in the fatigue life of biological samples. Results Cumulative load measures significantly decreased with running speed, whereas the cumulative damage and probabilistic measures either increased or did not change significantly with running speed. Conclusions The choice of cumulative metric has an important influence on the interpretation of overuse injury risk with changes in running speed. Although cumulative load metrics certainly provide meaningful information about the load experienced over a given distance, they do not account for the tissue damage incurred by such load. Cumulative load metrics should therefore be interpreted with caution when making inferences to overuse injury risk.

Background Individual compliances of the foot-shoe interface have been suggested to store and release elastic strain energy via ligamentous and tendinous structures or by increased midsole bending stiffness (MBS), compression stiffness, and resilience of running shoes. It is unknown, however, how these compliances interact with each other when the MBS of a running shoe is increased. The purpose of this study was to investigate how structures of the foot-shoe interface are influenced during running by changes to the MBS of sport shoes. Methods A randomised crossover trial was performed, where 13 male, recreational runners ran on an instrumented treadmill at 3.5 m·s−1 while motion capture was used to estimate foot arch, plantar muscle-tendon unit (pMTU), and shank muscle-tendon unit (sMTU) behaviour in two conditions: (1) control shoe and (2) the same shoe with carbon fibre plates inserted to increase the MBS. Results Running in a shoe with increased MBS resulted in less deformation of the arch (mean ± SD; stiff, 7.26 ± 1.78°; control, 8.84 ± 2.87°; p ≤ 0.05), reduced pMTU shortening (stiff, 4.39 ± 1.59 mm; control, 6.46 ± 1.42 mm; p ≤ 0.01), and lower shortening velocities of the pMTU (stiff, − 0.21 ± 0.03 m·s−1; control, − 0.30 ± 0.05 m·s−1; p ≤ 0.01) and sMTU (stiff, − 0.35 ± 0.08 m·s−1; control, − 0.45 ± 0.11 m·s−1; p ≤ 0.001) compared to a control condition. The positive and net work performed at the arch and pMTU, and the net work at the sMTU were significantly lower in the stiff compared to the control condition. Conclusion The findings of this study showed that if a compliance of the foot-shoe interface is altered during running (e.g. by increasing the MBS of a shoe), the mechanics of other structures change as well. This could potentially affect long-distance running performance.

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