Non-linear integration of crowded orientation signals

Vision Research
Carolina Gheri, S Baldassi

Abstract

Crowding of oriented signals has been explained as linear, compulsory averaging of the signals from target and flankers [Parkes, L., Lund, J., Angelucci, A., Solomon, J. A., & Morgan, M. (2001). Compulsory averaging of crowded orientation signals in human vision. Nature Neuroscience, 4(7), 739-744]. On the other hand, a comparable search task with sparse stimuli is well modeled by a 'Signed-Max' rule that integrates non-linearly local tilt estimates [Baldassi, S., & Verghese, P. (2002). Comparing integration rules in visual search. Journal of Vision, 2(8), 559-570], as reflected by the bimodality of the distributions of reported tilts in a magnitude matching task [Baldassi, S., Megna, N., & Burr, D. C. (2006). Visual clutter causes high-magnitude errors. PLoS Biology, 4(3), e56]. This study compares the two models in the context of crowding by using a magnitude matching task, to measure distributions of perceived target angles and a localization task, to probe the degree of access to local information. Response distributions were bimodal, implying uncertainty, only in the presence of abutting flankers. Localization of the target is relatively preserved but it quantitatively falls in between the predictions of the two models, po...Continue Reading

References

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Citations

Apr 18, 2014·Journal of Cognitive Neuroscience·David E AndersonEdward Awh
Jul 21, 2009·Proceedings of the National Academy of Sciences of the United States of America·John A GreenwoodSteven C Dakin
May 15, 2012·Vision Research·Katrin HerrmannMarisa Carrasco
Jun 16, 2009·Vision Research·Stefano BaldassiGiovanni Cioni
Aug 3, 2011·Trends in Cognitive Sciences·Michael A Cohen, Daniel C Dennett
Nov 13, 2012·I-Perception·Endel Põder
Jan 27, 2019·Attention, Perception & Psychophysics·Miranda Scolari, Edward Awh

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