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Colyer, S.

Publications and source records attributed to Colyer, S..

2 recordsLinked to original sources

Walking on the Moon: Hypogravity drives the emergence of a proprioception-dependent locomotor state

Animals must adapt locomotion to changing environmental conditions, but how the nervous system flexibly controls movement remains unclear. Gravity provides a powerful perturbation because it alters body loading, limb dynamics, and proprioceptive feedback. Apollo astronauts often skipped on the Moon, adopting an asymmetric gait rarely used on Earth, yet the sensorimotor basis of this behaviour is unknown. Here, by studying hypogravity locomotion in humans and mice, we show that reduced gravity reveals a conserved proprioception-dependent mechanism for locomotor state expression. In humans, skipping in simulated lunar gravity is generated through flexible temporal reconfiguration of existing motor modules rather than construction of a new motor architecture. In mice, simulated lunar gravity elicited a skipping-like locomotor state, and genetic elimination of muscle proprioceptors abolished this response. Thus, hypogravity reveals how proprioceptive feedback enables flexible expression of locomotor states.

neuroscience↗

Examination of 2D frontal and sagittal markerless motion capture: Implications for 2D and 3D markerless applications

This study examined if occluded joint locations from markerless motion capture produced 2D joint angles with reduced accuracy compared to visible joints, and if 2D frontal plane joint angles were usable for practical applications. Fifteen healthy participants performed over-ground walking whilst recorded by fifteen marker-based cameras and two machine vision cameras (frontal and sagittal plane). Repeated measures Bland-Altman analysis illustrated that markerless standard deviation of bias (random differences) for the occluded-side hip and knee joint angles in the sagittal plane were double that of the camera-side (visible) hip and knee. Camera-side sagittal plane knee and hip angles were near or within marker-based error values previously observed. While frontal plane random differences accounted for 35-46% of total range of motion at the hip and knee, systematic and random differences (-4.6-1.6 {+/-} 3.7-4.2{degrees}) were actually similar to previously reported marker-based error values. This was not true for the ankle, where random difference ({+/-}12{degrees}) was still too high for practical applications. Our results add to previous literature, highlighting shortcomings of current pose estimation algorithms and labelled datasets. As such, this paper finishes by reviewing marker-based methods for creating anatomically accurate markerless training data.

bioengineering↗