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1. All the Right Movements? Mediation, Rightist Movements, and Why US Movements Received Extensive Newspaper Coverage

   https://doi.org/10.1093/sf/sox067  

   Amenta, Edwin; Alan Elliott, Thomas (November 2017, Social Forces)
2. Binocular eye movements are adapted to the natural environment

   Gibaldi, Agostino; Banks, Martin S. (January 2019, The journal of neuroscience)
3. Principles and Patterns of Bat Movements: From Aerodynamics to Ecology

   https://doi.org/10.1086/693847  

   Voigt, Christian C.; Frick, Winifred F.; Holderied, Marc W.; Holland, Richard; Kerth, Gerald; Mello, Marco A.; Plowright, Raina K.; Swartz, Sharon; Yovel, Yossi (September 2017, The Quarterly Review of Biology)
4. Reaching movements are automatically redirected to nearby options during target split

   https://doi.org/10.1152/jn.00336.2020  

   Kurtzer, Isaac L.; Muraoka, Tetsuro; Singh, Tarkeshwar; Prasad, Mark; Chauhan, Riddhi; Adhami, Elan (October 2020, Journal of Neurophysiology)

   null (Ed.)

   Motor behavior often occurs in environments with multiple goal options that can vary during the ongoing action. We explored this situation by requiring subjects to select between different target options during an ongoing reach. During split trials the original target was replaced with a left and a right flanking target, and participants had to select between them. This contrasted with the standard jump trials, where the original target would be replaced with a single flanking target, left or right. When participants were instructed to follow their natural tendency, they all tended to select the split target nearest the original. The near-target preference was more prominent with increased spatial disparity between the options and when participants could preview the potential options. Moreover, explicit instruction to obtain the “far” target during split trials resulted many errors compared with a “near” instruction, ~50% vs. ~15%. Online reaction times to target change were delayed in split trials compared with jump trials, ~200 ms vs. ~150 ms, but also highly automatic. Trials in which the instructed far target was correctly obtained were delayed by a further ~50 ms, unlike those in which the near target was incorrectly obtained. We also observed nonspecific responses from arm muscles at the jump trial latency during split trials. Taken together, our results indicate that online selection of reach targets is automatically linked to the spatial distribution of the options, though at greater delays than redirecting to a single target. NEW & NOTEWORTHY This work demonstrates that target selection during an ongoing reach is automatically linked to the option nearest a voided target. Online reaction times for two options are longer than redirection to a single option. Attempts to override the near-target tendency result in a high number of errors at the normal delay and further delays when the attempt is successful. 

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5. Humans Need Augmented Feedback to Physically Track Non-Biological Robot Movements

   https://doi.org/10.1109/ICRA48891.2023.10161075  

   Edraki, Mahdiar; Maurice, Pauline; Sternad, Dagmar (May 2023, IEEE International Conference on Robotics and Automation)

   An important component for the effective collaboration of humans with robots is the compatibility of their movements, especially when humans physically collaborate with a robot partner. Following previous findings that humans interact more seamlessly with a robot that moves with humanlike or biological velocity profiles, this study examined whether humans can adapt to a robot that violates human signatures. The specific focus was on the role of extensive practice and realtime augmented feedback. Six groups of participants physically tracked a robot tracing an ellipse with profiles where velocity scaled with the curvature of the path in biological and nonbiological ways, while instructed to minimize the interaction force with the robot. Three of the 6 groups received real-time visual feedback about their force error. Results showed that with 3 daily practice sessions, when given feedback about their force errors, humans could decrease their interaction forces when the robot’s trajectory violated human-like velocity patterns. Conversely, when augmented feedback was not provided, there were no improvements despite this extensive practice. The biological profile showed no improvements, even with feedback, indicating that the (non-zero) force had already reached a floor level. These findings highlight the importance of biological robot trajectories and augmented feedback to guide humans to adapt to non-biological movements in physical human-robot interaction. These results have implications on various fields of robotics, such as surgical applications and collaborative robots for industry. 

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