Material properties determine how force and position signals combine in haptic shape perception

Processing of haptic texture information over sequential exploration movements

Where textures are defined by repetitive small spatial structures, exploration covering a greater extent will lead to signal repetition. We investigated how sensory estimates derived from these signals are integrated. In Experiment 1, participants stroked with the index finger one to eight times across two virtual gratings. Half of the participants discriminated according to ridge amplitude, the other half according to ridge spatial period. In both tasks, just noticeable differences (JNDs) decreased with an increasing number of strokes. Those gains from additional exploration were more than three times smaller than predicted for optimal observers who have access to equally reliable, and therefore equally weighted, estimates for the entire exploration. We assume that the sequential nature of the exploration leads to memory decay of sensory estimates. Thus, participants compare an overall estimate of the first stimulus, which is affected by memory decay, to stroke-specific estimates during the exploration of the second stimulus. This was tested in Experiments 2 and 3. The spatial period of one stroke across either the first or second of two sequentially presented gratings was slightly discrepant from periods in all other strokes. This allowed calculating weights of stroke-specific estimates in the overall percept. As predicted, weights were approximately equal for all strokes in the first stimulus, while weights decreased during the exploration of the second stimulus. A quantitative Kalman filter model of our assumptions was consistent with the data. Hence, our results support an optimal integration model for sequential information given that memory decay affects comparison processes.

Visual and haptic integration in the estimation of softness of deformable objects

Softness perception intrinsically relies on haptic information. However, through everyday experiences we learn correspondences between felt softness and the visual effects of exploratory movements that are executed to feel softness. Here, we studied how visual and haptic information is integrated to assess the softness of deformable objects. Participants discriminated between the softness of two softer or two harder objects using only-visual, only-haptic or both visual and haptic information. We assessed the reliabilities of the softness judgments using the method of constant stimuli. In visuo-haptic trials, discrepancies between the two senses' information allowed us to measure the contribution of the individual senses to the judgments. Visual information (finger movement and object deformation) was simulated using computer graphics; input in visual trials was taken from previous visuo-haptic trials. Participants were able to infer softness from vision alone, and vision considerably contributed to bisensory judgments (∼35%). The visual contribution was higher than predicted from models of optimal integration (senses are weighted according to their reliabilities). Bisensory judgments were less reliable than predicted from optimal integration. We conclude that the visuo-haptic integration of softness information is biased toward vision, rather than being optimal, and might even be guided by a fixed weighting scheme.

Integration and disruption effects of shape and texture in haptic search

In a search task, where one has to search for the presence of a target among distractors, the target is sometimes easily found, whereas in other searches it is much harder to find. The performance in a search task is influenced by the identity of the target, the identity of the distractors and the differences between the two. In this study, these factors were manipulated by varying the target and distractors in shape (cube or sphere) and roughness (rough or smooth) in a haptic search task. Participants had to grasp a bundle of items and determine as fast as possible whether a predefined target was present or not. It was found that roughness and edges were relatively salient features and the search for the presence of these features was faster than for their absence. If the task was easy, the addition of these features could also disrupt performance, even if they were irrelevant for the search task. Another important finding was that the search for a target that differed in two properties from the distractors was faster than a task with only a single property difference, although this was only found if the two target properties were non-salient. This means that shape and texture can be effectively integrated. Finally, it was found that edges are more beneficial to a search task than disrupting, whereas for roughness this was the other way round.

Learning from vision-to-touch is different than learning from touch-to-vision

We studied whether vision can teach touch to the same extent as touch seems to teach vision. In a 2 × 2 between-participants learning study, we artificially correlated visual gloss cues with haptic compliance cues. In two “natural” tasks, we tested whether visual gloss estimations have an influence on haptic estimations of softness and vice versa. In two “novel” tasks, in which participants were either asked to haptically judge glossiness or to visually judge softness, we investigated how perceptual estimates transfer from one sense to the other. Our results showed that vision does not teach touch as efficient as touch seems to teach vision.

Haptic distal spatial perception mediated by strings: size at a distance and egocentric localization based on ellipse geometry

Participants explored ellipse perimeters defined by fixed-length strings, held taut by their moving finger, with ends attached to two fixed hooks (foci). Participants haptically judged ellipse interfocal distance (IFD; in effect, exocentric separation, or size at a distance) or location of ellipse major axes (i.e., egocentric localization relative to the moving finger). In Experiment 1A, perceivers made reliable and accurate multialternative forced choice IFD judgments. Experiment 1B showed similar reliability for direct estimations but showed greater scaling error. In Experiment 2, perceivers reliably localized ellipse major axes. Both experiments derived from a priori geometrical analysis, consistent with the Gibsonian perceptual research program and previous string-mediated haptic distal spatial studies. Results are discussed with respect to haptic perception as a telemodality and to dynamic touch.

Exploratory Movements Determine Cue Weighting in Haptic Length Perception of Handheld Rods

In the present study, we sought to unravel how exploratory movements affect length perception of rods that are held in and wielded by hand. We manipulated the mechanical rod properties—mass ( m), first moment of mass distribution (M), major principal moment of inertia ( I1)—individually, allowing us to assess the relative contribution of each of these mechanical variables to the perceptual judgment. Furthermore we developed a method to quantify the force components of the mechanical variables in the total of forces acting at the hand-rod interface, and we calculated each component's relative contribution. The laws of mechanics dictate that these relative force contributions depend on the characteristics of the exploratory movements performed. We found a clear relationship between the relative force contribution of the mechanical variables and their contribution to perceived rod length. This finding is the first quantitative demonstration that exploration style determines how much each mechanical variable influences length perception. Moreover, this finding suggested a cue weighting mechanism in which exploratory movements determine cue reliability (and thus cue weighting). We developed a cue combination model for which we first identified three length cues in the form of ratios between the mechanical variables. Second, we calculated the weights of these cues from the recorded rod movements. The model provided a remarkably good prediction of the experimental data. This strongly suggests that rod length perception by wielding is achieved through a weighted combination of three specific length cues, whereby the weighting depends on the characteristics of the exploratory movements.

Haptic shape perception from force and position signals varies with exploratory movement direction and the exploring finger

We investigated how exploratory movement influences signal integration in active touch. Participants judged the amplitude of a bump specified by redundant signals: When a finger slides across a bump, the finger's position follows the bump's geometry (position signal); simultaneously, it is exposed to patterns of forces depending on the gradient of the bump (force signal). We varied amplitudes specified by force signals independently of amplitudes specified by position signals. Amplitude judgment was a weighted linear function of the amplitudes specified by both signals, under different exploratory conditions. The force signal's contribution to the judgment was higher when the participants explored with the index finger, as opposed to the thumb, and when they explored along a tangential axis, as opposed to a radial one (pivot congruent with shoulder joint). Furthermore, for tangential, as compared with radial, axis exploration, amplitude judgments were larger (and more accurate), and amplitude discrimination was better. We attribute these exploration-induced differences to biases in estimating bump amplitude from force signals. Given the choice, the participants preferred tangential explorations with the index finger-a behavior that resulted in good discrimination performance. A role for an active explorer, as well as biases that depend on exploration, should be taken into account when signal integration models are extended to active touch.

Transfer of the curvature aftereffect in dynamic touch

A haptic curvature aftereffect is a phenomenon in which the perception of a curved shape is systematically altered by previous contact to curvature. In the present study, the existence and intermanual transfer of curvature aftereffects for dynamic touch were investigated. Dynamic touch is characterized by motion contact between a finger and a stimulus. A distinction was made between active and passive contact of the finger on the stimulus surface. We demonstrated the occurrence of a dynamic curvature aftereffect and found a complete intermanual transfer of this aftereffect, which suggests that dynamically obtained curvature information is represented at a high level. In contrast, statically perceived curvature information is mainly processed at a level that is connected to a single hand, as previous studies indicated. Similar transfer effects were found for active and passive dynamic touch, but a stronger aftereffect was obtained when the test surface was actively touched. We conclude that the representation of object information depends on the exploration mode that is used to acquire information.