The functional subdivision of the visual brain: Is there a real illusion effect on action? A multi-lab replication study (data for Cortex RR)

Published: 19 March 2016| Version 3 | DOI: 10.17632/4676n2pdrf.3
Karl Kopiske


Data and analyses for the paper 'The functional subdivision of the visual brain: Is there a real illusion effect on action? A multi-lab replication study', published as a Registered Report in Cortex. Authors: Karl K. Kopiske, Nicola Bruno, Constanze Hesse, Thomas Schenk, Volker H. Franz ABSTRACT - It has often been suggested that visual illusions affect perception but not actions such as grasping, as predicted by the "two-visual-systems" hypothesis of Milner & Goodale (1995, The Visual Brain in Action, MIT press). However, at least for the Ebbinghaus illusion, relevant studies seem to reveal a consistent illusion effect on grasping (Franz & Gegenfurtner, 2008. Grasping visual illusions: Consistent data and no dissociation. Cognitive Neuropsychology). Two interpretations are possible: either grasping is not immune to illusions (arguing against dissociable processing mechanisms for vision-for-perception and vision-for-action), or some other factors modulate grasping in ways that mimic a vision-for perception effect in actions. It has been suggested that one such factor may be obstacle avoidance (Haffenden Schiff & Goodale, 2001. The dissociation between perception and action in the Ebbinghaus illusion: Nonillusory effects of pictorial cues on grasp. Current Biology, 11, 177-181). In four different labs (total N=144), we conducted an exact replication of previous studies suggesting obstacle avoidance mechanisms, implementing conditions that tested grasping as well as multiple perceptual tasks. This replication was supplemented by additional conditions to obtain more conclusive results. Our results confirm that grasping is affected by the Ebbinghaus illusion and demonstrate that this effect cannot be explained by obstacle avoidance.


Steps to reproduce

All files should be unzipped to one folder. R is required to run the data analyses. MATLAB is required to run the data processing, but processed data are also already included. All information about running the analyses is contained in README.txt


Natural Sciences