Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control

What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode t...改变运动指令所编码的运动具有哪些特征？运动指令是独立编码运动，还是可通过精简的信号集（即运动协同（synergies））进行表征？运动编码面临计算与实践的双重挑战：多数运动由多块肌肉协同驱动，且通常无法获取所有运动指令的同步电生理记录。此外，即便仅靠少量离散信号激活肌肉，单个运动周期（如步幅或振翅周期）内的运动变异仍可能具备高维度特性。本研究基于运动信号与运动数据的互协方差，采用偏最小二乘（partial least squares, PLS）方法提取运动的编码特征。该方法可同时对两类数据集进行分解，仅识别与目标肌肉相关的运动变异。我们运用此方法探究昆虫烟草天蛾（Manduca sexta）的主要下击飞行肌肉如何编码……