A Kalman filter model for predicting discrimination performance in free and restricted haptic explorations

Haptic exploration of objects usually consists of repeated exploratory movements and our perception of their properties is the result of the integration of information gained during each of these single movements. The serial nature of information integration in haptic perception requires that sensory estimates from single exploratory movements are retained in memory. Here we propose an optimal model for serial integration of information in haptic explorations which considers memory limitations. We tested the model by predicting discrimination performance in free and restricted (fixed number of indentations and varied number of switches between the stimuli) explorations of softness. Our model overall well predicts performance given different exploratory patterns in both free and restricted explorations. The model slightly overestimates performance in the restricted exploration and predictions are accurate in free explorations. These results suggest that integration of information can be well approximated by our model, in particular in free haptic exploration. We further tested whether participants prefer explorations which maximize performance. The model predicts that with constant number of indentations switching between the stimuli increases performance. Our results show that participants increase the number of switches only up to three switches, suggesting a trade-off between muscular switching costs and performance.