Nienke B. Debats

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 (I(1))--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 components 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.

Muscular torque can explain biases in haptic length perception: a model study on the radial-tangential illusion

In haptic length perception biases occur that have previously been shown to depend on stimulus orientation and stimulus length. We propose that these biases arise from the muscular torque needed to counteract the gravitational forces acting on the arm. In a model study, we founded this hypothesis by showing that differences in muscular torque can indeed explain the pattern of biases obtained in several experimental studies.

Kinematic cross-correlation induces sensory integration across separate objects

In a basic cursor‐control task, the perceived positions of the hand and the cursor are biased towards each other. We recently found that this phenomenon conforms to the reliability‐based weighting mechanism of optimal multisensory integration. This indicates that optimal integration is not restricted to sensory signals originating from a single source, as is the prevailing view, but that it also applies to separate objects that are connected by a kinematic relation (i.e. hand and cursor). In the current study, we examined which aspects of the kinematic relation are crucial for eliciting the sensory integration: (i) the cross‐correlation between kinematic variables of the hand and cursor trajectories, and/or (ii) an internal model of the hand‐cursor kinematic transformation. Participants made out‐and‐back movements from the centre of a semicircular workspace to its boundary, after which they judged the position where either their hand or the cursor hit the boundary. We analysed the position biases and found that the integration was strong in a condition with high kinematic correlations (a straight hand trajectory was mapped to a straight cursor trajectory), that it was significantly reduced for reduced kinematic correlations (a straight hand trajectory was transformed into a curved cursor trajectory) and that it was not affected by the inability to acquire an internal model of the kinematic transformation (i.e. by the trial‐to‐trial variability of the cursor curvature). These findings support the idea that correlations play a crucial role in multisensory integration irrespective of the number of sensory sources involved.

Optimal integration of actions and their visual effects is based on both online and prior causality evidence

The brain needs to identify redundant sensory signals in order to integrate them optimally. The identification process, referred to as causal inference, depends on the spatial and temporal correspondence of the incoming sensory signals (‘online sensory causality evidence’) as well as on prior expectations regarding their causal relation. We here examine whether the same causal inference process underlies spatial integration of actions and their visual consequences. We used a basic cursor-control task for which online sensory causality evidence is provided by the correlated hand and cursor movements, and prior expectations are formed by everyday experience of such correlated movements. Participants made out-and-back movements and subsequently judged the hand or cursor movement endpoints. In one condition, we omitted the online sensory causality evidence by showing the cursor only at the movement endpoint. The integration strength was lower than in conditions where the cursor was visible during the outward movement, but a substantial level of integration persisted. These findings support the hypothesis that the binding of actions and their visual consequences is based on the general mechanism of optimal integration, and they specifically show that such binding can occur even if it is previous experience only that identifies the action consequence.

Biases in rhythmic sensorimotor coordination: Effects of modality and intentionality

Sensorimotor biases were examined for intentional (tracking task) and unintentional (distractor task) rhythmic coordination. The tracking task involved unimanual tracking of either an oscillating visual signal or the passive movements of the contralateral hand (proprioceptive signal). In both conditions the required coordination patterns (isodirectional and mirror-symmetric) were defined relative to the body midline and the hands were not visible. For proprioceptive tracking the two patterns did not differ in stability, whereas for visual tracking the isodirectional pattern was performed more stably than the mirror-symmetric pattern. However, when visual feedback about the unimanual hand movements was provided during visual tracking, the isodirectional pattern ceased to be dominant. Together these results indicated that the stability of the coordination patterns did not depend on the modality of the target signal per se, but on the combination of sensory signals that needed to be processed (unimodal vs. cross-modal). The distractor task entailed rhythmic unimanual movements during which a rhythmic visual or proprioceptive distractor signal had to be ignored. The observed biases were similar as for intentional coordination, suggesting that intentionality did not affect the underlying sensorimotor processes qualitatively. Intentional tracking was characterized by active sensory pursuit, through muscle activity in the passively moved arm (proprioceptive tracking task) and rhythmic eye movements (visual tracking task). Presumably this pursuit afforded predictive information serving the coordination process.

Sensory integration of movements and their visual effects is not enhanced by spatial proximity

Spatial proximity enhances the sensory integration of exafferent position information, likely because it indicates whether the information comes from a single physical source. Does spatial proximity also affect the integration of position information regarding an action (here a hand movement) with that of its visual effect (here a cursor motion), that is, when the sensory information comes from physically distinct objects? In this study, participants made out-and-back hand movements whereby the outward movements were accompanied by corresponding cursor motions on a monitor. Their subsequent judgments of hand or cursor movement endpoints are typically biased toward each other, consistent with an underlying optimal integration mechanism. To study the effect of spatial proximity, we presented the hand and cursor either in orthogonal planes (horizontal and frontal, respectively) or we aligned them in the horizontal plane. We did not find the expected enhanced integration strength in the latter spatial condition. As a secondary question we asked whether spatial transformations required for the position judgments (i.e., horizontal to frontal or vice versa) could be the origin of previously observed suboptimal variances of the integrated hand and cursor position judgments. We found, however, that the suboptimality persisted when spatial transformations were omitted (i.e., with the hand and cursor in the same plane). Our findings thus clearly show that the integration of actions with their visual effects is, at least for cursor control, independent of spatial proximity.

The precision of Haptic rod length perception is reduced by lack of visual precision

In studies on haptic rod length perception, participants conventionally report their length estimates by placing a visual landmark at a position equal to the rods perceived endpoint. We hypothesized that this visual aspect substantially increases the variability of the recorded length judgments. To examine this, we developed a virtual reality length judgment apparatus that provides better visual information. Participants performed a rod length perception task in both the conventional apparatus and the virtual reality apparatus. The variability of the length judgments was found to be higher in the conventional apparatus. We determined that between half and two-thirds of the variance in the conventional apparatus is haptic variance. Thus, vision accounts for between one-third and half of the variance that was previously thought to be haptic variance. Our finding implies that the virtual reality apparatus may be more suitable for studying subtle effects in haptic rod length perception.