Laila Craighero

This study explored the temporal dynamics of motor imagery (MI) following the observation of robotic versus human actions using a temporal judgment task. Participants observed goal-directed action videos by a human or a NAO robot, performed MI until an auditory stop signal, then completed a two-alternative forced choice task to identify the frame corresponding to their imagery stop point, choosing between the correct frame and either a preceding (‘Before’) or succeeding (‘After’) frame. Results revealed a systematic temporal bias in MI towards ‘After’ incorrect frames. Crucially, this bias was significantly smaller for imagining robotic actions compared to human actions. This difference was primarily driven by an increased number of ‘Before’ errors for longer robotic actions, suggesting a perceived slowing down of MI (leading to an attenuated forward bias) when simulating less biologically plausible robotic movements, especially over extended durations. For human actions, video duration did not significantly modulate temporal errors. This finding indicates that the temporal distortion in MI is modulated by the observed agent’s movement characteristics and action duration, challenging simplistic embodied simulation accounts.

This study investigated how divergent sensorimotor experiences interact with task intention to influence touchscreen typing performance, kinematics, and strategy in smartphone users. Building on principles of motor learning and embodied cognition, we compared two generational cohorts: individuals whose sensorimotor development was primarily in the physical world, and those whose development occurred concurrently in both physical and digital environments. Participants typed the same sentences in two tasks: WhatsApp Chat (content generation) and Google Search (content consumption). 3D motion capture measured thumb kinematics; video analysis assessed behavioral metrics including typing time, predictive text use, and errors. Behavioral metrics revealed that the group with early digital exposure demonstrated faster overall typing times. The group with later digital adoption showed significantly greater use of predictive text, especially in WhatsApp, while typing errors did not differ. Kinematic analysis showed the early-digital-exposure group exhibited a higher-vigor motor execution profile and later peak deceleration and velocity, indicative of more ballistic, pre-planned movements. Crucially, Movement Time also exhibited a complex interaction, highlighting context-dependent modulation of motor efficiency. Thumb usage patterns did not show major group or task differences. These findings demonstrate that an individual's sensorimotor history contributes to shaping fine-grained sensorimotor skills. Those with early digital exposure display superior motor efficiency and vigor. In contrast, individuals with later digital adoption, though less kinematically efficient, exhibited remarkable strategic flexibility, adapting motor control and leveraging interface features based on task demands. This underscores how divergent sensorimotor histories contribute to distinct expressions of digital fluency and adaptive strategies in the digital age.

The rapid evolution of human–technology interaction necessitates continuous sensorimotor adaptation to new digital interfaces and tasks. Mobile typing, defined as text entry on smartphone touchscreens, offers a compelling example of this process, requiring users to adapt fine motor control and coordination to a constrained virtual environment. Aligned with the embodied cognition framework, understanding these digital sensorimotor experiences is crucial. A key theoretical question is whether these skills primarily involve adaptation of existing motor patterns or necessitate de novo learning, a distinction particularly relevant across generations with differing early sensorimotor experiences. This narrative review synthesizes current understanding of the sensorimotor aspects of smartphone engagement and typing skill evaluation methods. It examines touchscreen competence, skill acquisition, diverse strategies employed, and the influence of interface constraints on motor performance, while also detailing various sophisticated performance metrics and analyzing different data collection methodologies. Research highlights that analyzing typing behaviors and their underlying neural correlates increasingly serves as a potential source of behavioral biomarkers. However, while notable progress has been made, the field is still developing, requiring stronger methodological foundations and crucial standardization of metrics and protocols to fully capture and understand the dynamic sensorimotor processes involved in digital interactions. Nevertheless, mobile typing emerges as a compelling model for advancing our understanding of human sensorimotor learning and cognitive function, offering a rich, ecologically valid platform for investigating human-world interaction.

Every day, we make thousands of finger movements on the touchscreen of our smartphones. The same movements might be directed at various distal goals. We can type “What is the weather in Rome?” in Google to acquire information from a weather site, or we may type it on WhatsApp to decide whether to visit Rome with a friend. In this study, we show that by watching an agent’s typing hands, an observer can infer whether the agent is typing on the smartphone to obtain information or to share it with others. The probability of answering correctly varies with age and typing style. According to embodied cognition, we propose that the recognition process relies on detecting subtle differences in the agent’s movement, a skill that grows with sensorimotor competence. We expect that this preliminary work will serve as a starting point for further research on sensorimotor representations of digital actions.

The discovery of neurons with sensory properties in frontal motor circuits, and the discovery that these circuits send modulatory signals to the sensory parietal areas, strongly challenged the classical idea of a motor system as a mere executor of commands, and suggested that the sensorimotor system may contribute to the cognitive processes necessary for interaction with the world

Neuropsychological, behavioral, and neurophysiological evidence indicates that the coding of space as near and far depends on the involvement of different neuronal circuits. These circuits are recruited on the basis of functional parameters, not of metrical ones, reflecting a general distinction of human behavior, which alternatively attributes to the individual the role of agent or observer. Although much research in cognitive psychology was devoted to demonstrating that language and concepts are rooted in the sensorimotor system, no study has investigated the presence of implicit associations between different adverbs of place (far vs. near) and actions with different functional characteristics. Using a series of Implicit Association Test (IAT) experiments, we tested this possibility for both actions performed in physical space (grasp vs. look at) and those performed when using digital technology (content generation vs. content consumption). For both the physical and digital environments, the results showed an association between the adverb near and actions related to the role of agent, and between the adverb far and actions related to the role of observer. Present findings are the first experimental evidence of an implicit association between different adverbs of place and different actions and of the fact that adverbs of place also apply to the digital environment.

A robot should communicate its intention to collaborate shortly after a human has picked an object to avoid interferences.