Institute for Biomedical Research and Innovation (IRIB), National Research Council, C/Da Burga, Cosenza, Mangone, 87050, Italy.
S. Anna Institute, Crotone, 88900, Italy.
J Autism Dev Disord. 2021 Jul;51(7):2538-2542. doi: 10.1007/s10803-020-04708-9.
A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism and predict treatment response. Social robotics has recently been proposed as an effective tool to strengthen the current treatments in children with autism. However, the high clinical heterogeneity characterizing this disorder might interfere with behavioral effects. Neuroimaging is set to overcome these limitations by capturing the level of heterogeneity. Here, we provide a preliminary evaluation of the neural basis of social robotics and how extracting neural hallmarks useful to design more effective behavioral applications. Despite the endophenotype-oriented neuroimaging research approach is in its relative infancy, this preliminary evidence encourages innovation to address its current limitations.
大量神经影像学研究集中于发现潜在的神经内表型,以帮助理解自闭症的病因和预测治疗反应。社交机器人技术最近被提议作为一种有效的工具,以加强自闭症儿童的现有治疗。然而,这种疾病的高度临床异质性可能会干扰行为效应。神经影像学有望通过捕捉异质性水平来克服这些局限性。在这里,我们提供了对社交机器人的神经基础的初步评估,以及如何提取有用的神经特征来设计更有效的行为应用。尽管以内表型为导向的神经影像学研究方法还处于相对初级的阶段,但这些初步证据鼓励创新以解决其当前的局限性。