Towards mastery of complex visuo-motor transformations

Abstract

In this paper we review and integrate a set of findings on learning the transformation of a sliding first-order lever, a type of tool with a prominent role in minimal access surgery. Its kinematic transformation is characterized by the so-called fulcrum effect, the inversion of the movement direction of the tip of the lever relative to that of the hand for rotations. A second characteristic is gain anisotropy, which results in curved paths of the tip of the lever for straight paths of the hand and vice versa. An internal model of the kinematic transformation is acquired during practice, the accuracy of which can be assessed in visual open-loop test trials. The accuracy of the acquired internal model is enhanced when visual closed-loop control during practice is impeded, and the accuracy of the internal model is reduced when closed-loop control during practice is facilitated. The internal model consists of a rapidly acquired line-symmetric approximation to the transformation of the sliding lever and a slowly acquired fine tuning. The fine tuning is local, that is, it is specific for the region of the workspace encountered during practice. The internal model is transferred to other regions of the workspace, but not adjusted to the fine tuning appropriate for these regions. Whereas the symmetry approximation is most likely explicit, the fine tuning seems to be represented implicitly. Findings on the straightness of the paths of the tip of the lever and the hand suggest that the internal model of the transformation is confined to initial and final positions of aimed movements, whereas their path is not strictly controlled, but affected by the dynamic transformation of the tool. Only when visual closed-loop control is possible, the path of the effective part of the tool is straightened. These characteristics of the internal model of the sliding first-order lever and its acquisition may be partly specific to sufficiently complex extrinsic transformations that arise from mechanical or electronic extensions of the body.

Driving for Real or on a Fixed-Base Simulator: Is It so Different? An Explorative Study

“…The numerous studies carried out in the context of visuo-motor adaptation support this supposition. Thus, quick adaptation of the sensory-motor system is often observed in highly perturbing environments; for example, video-controlled movements in surgery (for a review see Pennel, Ferrel, Coello, & Orliaguet, 2002;Heuer & Sülzenbrück, 2013). It is also noted in the context of the use by the brain of a new form of sensory feedback to control movement (i.e., pseudo-haptic feedback, Lécuyer, 2009).…”

Beyond Being Real: A Sensorimotor Control Perspective on Interactions in Virtual Reality

“…For example, in a study where the range of motion of the participants' arms and legs were swapped, it took around 10 minutes for participants to learn the remapping and to utilize the range of motion of their avatar's body parts [201]. Motor learning is driven by different processes at multiple timescales and it often involves quick approximations, followed by slow adjustments that enable fine tuning [67]. Beyondreal interactions change how we perceive the affordances of objects and properties of the world around us.…”

“…While the specifics of these learning processes in the brain is not fully understood [88], prior research has proposed different strategies for encouraging exploration. For example, providing lower quality visual feedback may increase uncertainty, promote exploratory risk-taking, and lead to more accurate internal models under the new dynamics [67]. This approach is at odds with the sentiment of effective feedback in interaction design, and more research is needed to unpack this interplay.…”

Why motor imagery is not really motoric: towards a re-conceptualization in terms of effect-based action control

“…For many tools, the effects they produce are clearly dissociable from the motor behaviors that cause them. For example, the Fulcrum effect (Kunde et al, 2007) denotes the fact that in laparoscopic surgery, movements of the hand upwards produce downwards movements of the endoscopic tool, and vice versa (for a review of similar tool transformation findings, see Heuer & Sülzenbrück, 2013). Importantly, when people plan such actions, then bringing to mind the intended motions of the tool suffices to elicit the relevant motor behaviors, even if they are opposite to intended tool motion (Müsseler et al, 2008).…”