Dataset Open Access

Unequal - but fair? Weights in the serial integration of haptic texture information

Lezkan, Alexandra; Drewing, Knut

The sense of touch is characterized by its sequential nature. In texture perception, enhanced spatio-temporal extension of exploration leads to better discrimination performance due to combination of repetitive information. We have previously shown that the gains from additional exploration are smaller than the Maximum Likelihood Estimation (MLE) model of an ideal observer would assume. Here we test if this suboptimal integration can be explained by unequal weighting of information. Participants stroke 2 to 5 times across a virtual grating and judged the ridge period in a 2IFC task. We presented slightly discrepant period information in one of the strokes in the standard grating. Results show linearly decreasing weights of this information with spatio-temporal distance (number of intervening strokes) to the comparison grating. For each exploration extension (number of strokes) the stroke with the highest number of intervening strokes to the comparison was completely disregarded. The results are consistent with the notion that memory limitations are responsible for the unequal weights. This study raises the question if models of optimal integration should include memory decay as an additional source of variance and thus not expect equal weights.

Lezkan, A. & Drewing, K. (2014). Unequal - but fair? Weights in the serial integration of haptic texture information. Haptics: Neuroscience, Devices, Modeling, and Applications (pp. 386-392). Springer: Heidelberg.


The Zip file contains all data relative to the publication. The data of each participant is contained in a separate file.

A description of the variables is contained in the file VARIABLE_CODES.txt

Files (1.6 MB)
Name Size
1.6 MB Download
1.1 kB Download
All versions This version
Views 33
Downloads 00
Data volume 0 Bytes0 Bytes
Unique views 33
Unique downloads 00


Cite as