Toward a motor signature in autism: Studies from human-machine interaction.

BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impairments are fundamental aspects of ASD. These impairments are associated with postural and motor control disabilities that we investigated using computational modeling and developmental robotics through human-machine interaction paradigms. METHOD: First, in a set of studies involving a human-robot posture imitation, we explored the impact of 3 different groups of partners (including a group of children with ASD) on robot learning by imitation. Second, using an ecological task, i.e. a real-time motor imitation with a tightrope walker (TW) avatar, we investigated interpersonal synchronization, motor coordination and motor control during the task in children with ASD (n=29), TD children (n=39) and children with developmental coordination disorder (n=17, DCD). RESULTS: From the human-robot experiments, we evidenced that motor signature at both groups' and individuals' levels had a key influence on imitation learning, posture recognition and identity recognition. From the more dynamic motor imitation paradigm with a TW avatar, we found that interpersonal synchronization, motor coordination and motor control were more impaired in children with ASD compared to both TD children and children with DCD. Taken together these results confirm the motor peculiarities of children with ASD despite imitation tasks were adequately performed. DISCUSSION: Studies from human-machine interaction support the idea of a behavioral signature in children with ASD. However, several issues need to be addressed. Is this behavioral signature motoric in essence? Is it possible to ascertain that these peculiarities occur during all motor tasks (e.g. posture, voluntary movement)? Could this motor signature be considered as specific to autism, notably in comparison to DCD that also display poor motor coordination skills? We suggest that more work comparing the two conditions should be implemented, including analysis of kinematics and movement smoothness with sufficient measurement quality to allow spectral analysis.

Setting spatial conservation priorities despite incomplete data for characterizing metapopulations.

Management of spatially structured species poses unique challenges. Despite a strong theoretical foundation, practitioners rarely have sufficient empirical data to evaluate how populations interact. Rather, assumptions about connectivity and source-sink dynamics are often based on incomplete, extrapolated, or modeled data, if such interactions are even considered at all. Therefore, it has been difficult to evaluate whether spatially structured species are meeting conservation goals. We evaluated how estimated metapopulation structure responded to estimates of population sizes and dispersal probabilities and to the set of populations included. We then compared outcomes of alternative management strategies that target conservation of metapopulation processes. We illustrated these concepts for Chinook salmon (Oncorhynchus tshawytscha) in the Snake River, USA. Our description of spatial structure for this metapopulation was consistent with previous characterizations. We found substantial differences in estimated metapopulation structure when we had incomplete information about all populations and when we used different sources of data (three empirical, two modeled) to estimate dispersal, whereas responses to population size estimates were more consistent. Together, these findings suggest that monitoring efforts should target all populations occasionally and populations that play key roles frequently and that multiple types of data should be collected when feasible. When empirical data are incomplete or of uneven quality, analyses using estimates produced from an ensemble of available datasets can help conservation planners and managers weigh near-term options. Doing so, we found trade-offs in connectivity and source dominance in metapopulation-level responses to alternative management strategies that suggest which types of approaches may be inherently less risky.