It has been proposed that different forms of rhythmic human limb movement have a common central neural control ('common core hypothesis'), just as in other animals. We compared the modulation patterns of background EMG and cutaneous reflexes during walking, arm and leg cycling, and arm-assisted recumbent stepping. We hypothesized that patterns of EMG and reflex modulation during cycling and stepping (deduced from mathematical principal components analysis) would be comparable to those during walking because they rely on similar neural substrates. Differences between the tasks were assessed by evoking cutaneous reflexes via stimulation of nerves in the foot and hand in separate trials. The EMG was recorded from flexor and extensor muscles of the arms and legs. Angular positions of the hip, knee and elbow joints were also recorded. Factor analysis revealed that across the three tasks, four principal components explained more than 93% of the variance in the background EMG and middle-latency reflex amplitude. Phase modulation of reflex amplitude was observed in most muscles across all tasks, suggesting activity in similar control networks. Significant correlations between EMG level and reflex amplitude were frequently observed only during static voluntary muscle activation and not during rhythmic movement. Results from a control experiment showed that strong correlation between EMG and reflex amplitudes was observed during discrete, voluntary leg extension but not during walking. There were task-dependent differences in reflex modulation between the three tasks which probably arise owing to specific constraints during each task. Overall, the results show strong correlation across tasks and support common neural patterning as the regulator of arm and leg movement during various rhythmic human movements. The innate capacity for generation of rhythmic movement patterns is found across the animal kingdom (Orlovsky et al. 1999). Humans produce a variety of rhythmic motor patterns during all forms of terrestrial and aquatic locomotion by way of walking, running, cycling, crawling, creeping and swimming. Considerable overlap with shared neurons and reorganization of synaptic activity to produce different rhythmic motor patterns with similar neuronal ensembles is well documented in invertebrate preparations such as the crayfish (Hooper & DiCaprio, 2004). A contribution to rhythmic motor outputs by spinal central pattern-generating elements (CPGs) has been suggested in many species, including humans (see for review Rossignol, 1996;Dietz, 2003;Zehr & Duysens, 2004;Yang et al. 2004;Rossignol et al. 2006). Using the research model of the infant walking paradigm, Yang and colleagues have shown that multiple locomotor tasks, including forward and backward walking and side-stepping, are probably controlled by the same reconfigured CPGs (Lamb & Yang, 2000).We previously suggested that an estimate of the probable contributions of CPG activity can be evaluated by the phase-dependent modulation of reflex amplitudes evoked during rhyth...

During rhythmic movement, arm activity contributes to the neural excitation of leg muscles. These observations are consistent with the emergence of human bipedalism and nonhuman primate arboreal quadrupedal walking. These neural and biomechanical linkages could be exploited in rehabilitation after neurotrauma to allow the arms to give the legs a helping hand during gait rehabilitation.

There is extensive modulation of cutaneous and H-reflexes during rhythmic leg movement in humans. Mechanisms controlling reflex modulation (e.g., phase- and task-dependent modulation, and reflex reversal) during leg movements have been ascribed to the activity of spinal central pattern generating (CPG) networks and peripheral feedback. Our working hypothesis has been that neural mechanisms (i.e., CPGs) controlling rhythmic movement are conserved between the human lumbar and cervical spinal cord. Thus reflex modulation during rhythmic arm movement should be similar to that for rhythmic leg movement. This hypothesis has been tested by studying the regulation of reflexes in arm muscles during rhythmic arm cycling and treadmill walking. This paper reviews recent studies that have revealed that reflexes in arm muscles show modulation within the movement cycle (e.g., phase-dependency and reflex reversal) and between static and rhythmic motor tasks (e.g., task-dependency). It is concluded that reflexes are modulated similarly during rhythmic movement of the upper and lower limbs, suggesting similar motor control mechanisms. One notable exception to this pattern is a failure of contralateral arm movement to modulate reflex amplitude, which contrasts directly with observations from the leg. Overall, the data support the hypothesis that CPG activity contributes to the neural control of rhythmic arm movement.

There is a growing interest in the use of Inertial Measurement Unit (IMU)-based systems that employ gyroscopes for gait analysis. We describe an improved IMU-based gait analysis processing method that uses gyroscope angular rate reversal to identify the start of each gait cycle during walking. In validation tests with six subjects with Parkinson disease (PD), including those with severe shuffling gait patterns, and seven controls, the probability of True-Positive event detection and False-Positive event detection was 100% and 0%, respectively. Stride time validation tests using high-speed cameras yielded a standard deviation of 6.6 ms for controls and 11.8 ms for those with PD. These data demonstrate that the use of our angular rate reversal algorithm leads to improvements over previous gyroscope-based gait analysis systems. Highly accurate and reliable stride time measurements enabled us to detect subtle changes in stride time variability following a Parkinson's exercise class. We found unacceptable measurement accuracy for stride length when using the Aminian et al gyro-based biomechanical algorithm, with errors as high as 30% in PD subjects. An alternative method, using synchronized infrared timing gates to measure velocity, combined with accurate mean stride time from our angular rate reversal algorithm, more accurately calculates mean stride length.

During bipedal locomotor activities, humans use elements of quadrupedal neuronal limb control. Evolutionary constraints can help inform the historical ancestry for preservation of these core control elements support transfer of the huge body of quadrupedal non-human animal literature to human rehabilitation. In particular, this has translational applications for neurological rehabilitation after neurotrauma where interlimb coordination is lost or compromised. The present state of the field supports including arm activity in addition to leg activity as a component of gait retraining after neurotrauma.