I.MOVE.U – Intention from Movement Understanding
From moving bodies to interactive minds
From observing other people’s movements, humans make inferences that go far beyond the appearance of the observed stimuli: inferences about unobservable mental states such as goals and intentions. For example, by watching everyday actions such as lifting a box, they can tell whether the actor is trying to deceive them about the real weight of the box. Depending on their level of motor skill, they are able to determine whether a basketball player is about to throw a ball or mimic a throw. Moreover, by observing an actor reaching towards an object and grasping it, they are able to discriminate between prehensile movements performed with the intent to cooperate with a partner or compete against an opponent. These findings clearly indicate that human actions visually radiate cues to intention, yet the processes and neural mechanisms that mediate this surprising ability to infer intention from movement remain elusive. How are we able to make such inferences – often fast and reliably? What are the mechanisms that permit us to delve into the mind of the people we interact with?
I.MOVE.U intends to provide the first comprehensive account of how intentions are extracted from body motion during interaction with conspecifics. The project is based on the assumptions that: i) our knowledge of other minds is tightly linked to our interactions with others; ii) isolation paradigms suited at investigating individual minds in isolation fail to capture processes and mechanisms supporting interpersonal understanding (methodological inter-personalism). By combining advanced methods in psychophysics and neuroscience with kinematics and virtual reality technologies, I.MOVE.U develops and tests an integrative and radically new approach to the study of intention understanding. Following topics are the focus of the current research:
Availability of intention information: Covert mental state dispositions such as expectations and intentions can become visually available when they enter into interaction with mechanical and anatomical features to generate the kinematics of a given action. To what extent is kinematic specification of intention effective? In other words, are social intentions a sufficiently strong dynamic contributor to establish kinematic specification as a prominent kind of information? How can we measure intention information?
Sensitivity to intention information: Perception requires not only the availability of potential information, but also the corresponding attunement of the perceptual system. To what extent are observers attuned to intention information conveyed by action kinematics? Is intention information automatically processed from movement observation? Which neural mechanisms mediates the ability to extract intention from movement? Two hypothetical systems have been proposed to contribute to intention understanding: the action observation system and the mentalizing system. Are these systems sensitive to intention information conveyed by action kinematics?
Impact of intention information on social interaction: Predicting what kind of actions others will perform, as well as when and where they will act, is essential for successful social interaction. If we merely reacted to what we saw others doing, we could never achieve the fast and smooth coordination needed to actively and directly interact with them. Do intention-from-motion inferences guide processing of the motion patterns generated by the actions of interacting agents? Can the action of one agent serve as predictor of the action of a second agent? When interacting with another agent, do agents use their own actions to predict the partner’s intention?
By answering these questions, the project is bridging a fundamental gap between observable movements and unobservable mental states, moving bodies and intentional minds, providing knowledge and applications of scientific, technological and clinical impact.