University of Ferrara, Department of Neuroscience and Rehabilitation, Ferrara, Italy; Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy.
Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy.
Cognition. 2021 Aug;213:104652. doi: 10.1016/j.cognition.2021.104652. Epub 2021 Mar 11.
In autism spectrum disorder (ASD), socio-communicative impairments and stereotypical behaviours are paralleled by sensorimotor deficits. Individuals with ASD show an altered selection of motor parameters, resulting in clumsy and fragmented actions. Here, we investigated inter-joint coordination and motor synergies as a potential substrate of motor control problems in ASD. Synergies enable co-controlling redundant motor degrees of freedom (DoF, e.g. joint angles, muscles) by mapping behavioural goals into a flexible and low-dimensional set of variables. This mechanism simplifies motor control and helps to find unambiguous solutions for motor tasks. In a reaching-grasping paradigm, children with ASD showed reduced coupling between DoF, which correlated with socio-communicative symptoms severity. Impaired synergies may help to frame well-established motor problems in ASD, including impaired motor sequencing and abnormal trial-to-trial motor variability. On the other hand, synergies also provide an effective and compact coding system of observed actions. Impaired synergies may thus jeopardize motor interaction by initiating bottom-up cascade effects, leading to pervasive impairments of social behaviour. Finally, we trained an automatic classification algorithm to distinguish between ASD and typically developing (TD) participants based on reaching-grasping kinematics. Classification accuracy reached up to 0.947. This result corroborates and expands previous accounts claiming that motor-based early recognition is feasible and effective in ASD.
在自闭症谱系障碍 (ASD) 中,社交沟通障碍和刻板行为与感觉运动缺陷并存。ASD 患者表现出运动参数选择的改变,导致动作笨拙和不连贯。在这里,我们研究了关节间协调和运动协同作用,作为 ASD 中运动控制问题的潜在基础。协同作用通过将行为目标映射到灵活的低维变量集,实现了对冗余运动自由度 (DoF,例如关节角度、肌肉) 的共同控制。这种机制简化了运动控制,并有助于为运动任务找到明确的解决方案。在伸手抓握范式中,ASD 儿童的 DoF 之间的耦合减少,这与社交沟通症状的严重程度相关。协同作用受损可能有助于构建 ASD 中公认的运动问题,包括运动序列受损和异常的trial-to-trial 运动变异性。另一方面,协同作用也为观察到的动作提供了有效的紧凑编码系统。协同作用受损可能会通过引发自下而上的级联效应来危及运动交互,从而导致社交行为的普遍障碍。最后,我们训练了一个自动分类算法,根据伸手抓握运动学来区分 ASD 和典型发育 (TD) 参与者。分类准确率高达 0.947。这一结果证实并扩展了之前的研究结果,即基于运动的早期识别在 ASD 中是可行和有效的。