Loes van Dam

Technical University of Darmstadt, Germany

I am currently chairing the Sensorimotor Control and Learning Group at the Technical University of Darmstadt. In the Sensorimotor Control and Learning Group we are interested in human multisensory perception and goal-oriented movement behaviour in virtual reality (VR) as well as the real world. We consider that to be able to move efficiently, several stages of processing are involved. For example, even such simple every-day tasks as picking up a cup of coffee involve sensing the 3D position and orientation of the cup (sensory processing), making an educated guess whether it is currently full or empty to estimate its weight (cognitive processing), and having an idea of our own limb position and where it needs to go next (body perception and movement planning). Thus, being able to move efficiently depends on a mix of sensory and cognitive aspects, besides simply producing the motor commands.

The research in our group takes into account that motor control relies on such a mixture of aspects. We for instance focus on how our sensorimotor system selects and combines relevant pieces of information for the perception of our environment, the perception of our own body, as well as for guiding such goal-oriented movements. To this end we, for instance, investigate the interactions between visual, proprioceptive and tactile feedback for movement control.
The more cognitive aspects included in our work concerns the use of prior knowledge and learned relationships between, for instance, an object’s shape and the appropriate behaviour to interact with it.
Furthermore, our work investigates how our senses, our motor control system and our prior experiences combine to help form a sense of ownership over our own body, an avatar, or a tool and a sense of agency about our actions and their perceptual concequences.
To study these topics we combine experimental work (e.g. psychophysics, game-like sensorimotor control tasks) with modeling approaches such as optimal multisensory integration and optimal control theory.

Understanding these processes informs the development and use of sensory substitution devices in general and is therefore also of relevance for neuroprosthetics. We believe that the naturalness of their use and the acceptance of such devices depends on how the feedforward processes from movement planning and feedback processes linked to these movements can interact and how this information is represented and learned.