Visual and Somatosensory Information about Object Shape Control Manipulative Fingertip Forces

Abstract

We investigated the importance of visual versus somatosensory information for the adaptation of the fingertip forces to object shape when humans used the tips of the right index finger and thumb to lift a test object. The angle of the two flat grip surfaces in relation to the vertical plane was changed between trials from −40 to 30°. At 0° the two surfaces were parallel, and at positive and negative angles the object tapered upward and downward, respectively. Subjects automatically adapted the balance between the horizontal grip force and the vertical lift force to the object shape and thereby maintained a rather constant safety margin against frictional slips, despite the huge variation in finger force requirements. Subjects used visual cues to adapt force to object shape parametrically in anticipation of the force requirements imposed once the object was contacted. In the absence of somatosensory information from the digits, sighted subjects still adapted the force coordination to object shape, but without vision and somatosensory inputs the performance was severely impaired. With normal digital sensibility, subjects adapted the force coordination to object shape even without vision. Shape cues obtained by somatosensory mechanisms were expressed in the motor output about 0.1 sec after contact. Before this point in time, memory of force coordination used in the previous trial controlled the force output. We conclude that both visual and somatosensory inputs can be used in conjunction with sensorimotor memories to adapt the force output to object shape automatically for grasp stability.

Lighter or Heavier Than Predicted: Neural Correlates of Corrective Mechanisms during Erroneously Programmed Lifts

“…Because a block design was used in the previous study, the present results obtained by an event-related design provide more compelling evidence that the supramarginal cortex is activated at the time point when the weight is actually changed. The updating of the sensorimotor memory representations of objects typically takes place on a single-trial basis during precision grip lifts (Gordon et al, 1993;Jenmalm and Johansson, 1997;Johansson and Westling, 1988). The activity in the supramarginal gyrus may signal the discrepancy between the predicted and actual sensory information (Blakemore and Sirigu, 2003), or the updating of the sensorimotor memories of the object's physical proprieties.…”

Internal models for bi-manual tasks

“…Although learning of the predictive control of grip force has been examined, its generalization properties have previously not been examined. Previous studies of grip force learning have shown that grip force levels can be set without somatosensory feedback, anticipating the physical properties of the object, which include the object's weight, shape, and friction at its surface (Jenmalm and Johansson 1997;Westling 1984, 1988;Johansson and Cole 1994). Such object properties are learned through development, indicated by increasing ability to correctly parameterize grip force to the object being manipulated Forssberg et al 1991Forssberg et al , 1992Forssberg et al , 1995.…”

“…However, if the load force is self-generated, for example, by pushing on the object using the other hand, then grip force anticipates the load force with near zero delay, suggesting a predictive process (Johansson and Cole 1992). Anticipatory grip force modulation has been shown to be scaled to object weight (Johansson and Westling 1988), texture (Johansson and Westling 1984), shape (Jenmalm and Johansson 1997), center of mass (Wing and Lederman 1998), and previous experience (Gordon et al 1993). Such prediction is not hard-wired but learned through development (Forssberg et al 1991).…”

Grasping and Manipulation of Unknown Objects Based on Visual and Tactile Feedback

“…Without the sense of touch, subjects have severe difficulties maintaining a stable grasp or performing a complex action such as lightning matches [1,2]. Also in robot applications, lacking tactile feedback results in loosing an initially grasped object or failing to robustly carry out manipulation tasks [3].…”