Processing of haptic texture information over sequential exploration movements

Abstract

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.

Active Haptic Exploration of Softness: Indentation Force Is Systematically Related to Prediction, Sensation and Motivation

“…In our experiments, we showed that when participants adjusted their peak force more precisely to the object they also generated more sensory signals. In previous work, we additionally showed that perception gets more precise with more generated sensory signals (Lezkan and Drewing, 2018 ; Metzger et al, 2018 ). In sum, accumulating sensory signals seems to improve the precision of movement and perception.…”

“…Consequently, it may be that in our experiment, the reliability of sensory information was not sufficient to warrant a significant effect on movement control. In active touch, sensory information gains reliability with extension of exploration; the more movements performed, the more sensory signals are generated, and the more reliable the sensory information overall will be (Lezkan and Drewing, 2018 ). Therefore, it seems possible that our participants did not explore with the necessary extension to generate sufficient sensory signals.…”

“…Sensory signals are gathered during the exploration. Therefore, later in the exploration process, more sensory signals are available (Lezkan and Drewing, 2018 ). We propose that the sensory signals from initial movements are taken into account as feedback and, thus, that they influence upcoming motor commands, which will generate further sensory signals until a decision on the to-be-judged property is reached (i.e., softness).…”

“…Note also that the acquisition of sensory signals may vary substantially, as people are able to decide how many movements they perform. The more exploratory movements are performed, the more sensory signals are generated, and the more reliable the sensation will be (e.g., Quick, 1974 ; Gescheider et al, 1999 ; Lezkan and Drewing, 2018 ). Although additional exploratory movements can add sensory signals, they are also associated with additional movement costs.…”

Switching Between Objects Improves Precision in Haptic Perception of Softness

“…In haptic perception it was shown that prior information is integrated into the percept of an object's softness [15]. It was also shown that sequentially gathered information from every indentation contributes to the overall perception of an object's softness [16] and information from every stroke over the object's surface contributes to the perception of its roughness [17]. However, the contribution of these single exploratory movements to the overall percept seems to be not equal, as would be predicted if there was no loss of information and integration was statistically optimal.…”