Motion integration for optic-flow patterns : the interaction between local and global noise

In the visual system, both the local and global stages of motion processing are susceptible to noise. Given the hierarchical nature of motion processing, do local and global noise interact with each other? If such interaction exists, does it differ across different types of optic-flow patterns? Thes...

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Main Author: Chu, Ann Ning
Other Authors: Gerrit Maus
Format: Final Year Project
Language:English
Published: 2016
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Online Access:http://hdl.handle.net/10356/67255
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-672552019-12-10T14:37:38Z Motion integration for optic-flow patterns : the interaction between local and global noise Chu, Ann Ning Gerrit Maus School of Humanities and Social Sciences DRNTU::Social sciences::Psychology::Experimental psychology In the visual system, both the local and global stages of motion processing are susceptible to noise. Given the hierarchical nature of motion processing, do local and global noise interact with each other? If such interaction exists, does it differ across different types of optic-flow patterns? These questions were addressed using a novel psychophysical technique, in which uncertainty at the local and global stages of motion processing was independently manipulated within the same motion stimulus. We used a multiple-aperture stimulus, which consisted of an array of randomly-oriented, drifting Gabor elements (Amano, Edwards, Badcock, & Nishida, 2009). Global noise was manipulated based on motion coherence and global signal-to-noise ratio (global-SNR) was defined as the ratio between signal and noise element numbers. Local noise, defined as the ratio between the contrasts of Gabor patches and contrast of noise pixels, was introduced by superimposing dynamic-noise pixels on each drifting Gabor patch at every motion frame. Observers performed a two-choice, global-direction-discrimination task on three optic-flow patterns: translational (left or right), circular (clockwise or anticlockwise), and radial (inward or outward). In each block of trials, the local-signal-to-noise-ratio (local-SNR) was fixed and the 75%-accuracy threshold in terms of global-SNR was measured. For all three optic-flow patterns, we found a “trade-off” between local and global noise: global-SNR thresholds decreased log-linearly as local-SNR increased, suggesting an interaction between local and global noise. Beyond a certain local-SNR level, global-SNR thresholds remained constant. This saturation point was lower for circular compared to radial and translational motion, suggesting that global integration mechanisms for circular motion are less susceptible to local noise disturbances. Bachelor of Arts 2016-05-13T04:49:01Z 2016-05-13T04:49:01Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67255 en Nanyang Technological University 44 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Social sciences::Psychology::Experimental psychology
spellingShingle DRNTU::Social sciences::Psychology::Experimental psychology
Chu, Ann Ning
Motion integration for optic-flow patterns : the interaction between local and global noise
description In the visual system, both the local and global stages of motion processing are susceptible to noise. Given the hierarchical nature of motion processing, do local and global noise interact with each other? If such interaction exists, does it differ across different types of optic-flow patterns? These questions were addressed using a novel psychophysical technique, in which uncertainty at the local and global stages of motion processing was independently manipulated within the same motion stimulus. We used a multiple-aperture stimulus, which consisted of an array of randomly-oriented, drifting Gabor elements (Amano, Edwards, Badcock, & Nishida, 2009). Global noise was manipulated based on motion coherence and global signal-to-noise ratio (global-SNR) was defined as the ratio between signal and noise element numbers. Local noise, defined as the ratio between the contrasts of Gabor patches and contrast of noise pixels, was introduced by superimposing dynamic-noise pixels on each drifting Gabor patch at every motion frame. Observers performed a two-choice, global-direction-discrimination task on three optic-flow patterns: translational (left or right), circular (clockwise or anticlockwise), and radial (inward or outward). In each block of trials, the local-signal-to-noise-ratio (local-SNR) was fixed and the 75%-accuracy threshold in terms of global-SNR was measured. For all three optic-flow patterns, we found a “trade-off” between local and global noise: global-SNR thresholds decreased log-linearly as local-SNR increased, suggesting an interaction between local and global noise. Beyond a certain local-SNR level, global-SNR thresholds remained constant. This saturation point was lower for circular compared to radial and translational motion, suggesting that global integration mechanisms for circular motion are less susceptible to local noise disturbances.
author2 Gerrit Maus
author_facet Gerrit Maus
Chu, Ann Ning
format Final Year Project
author Chu, Ann Ning
author_sort Chu, Ann Ning
title Motion integration for optic-flow patterns : the interaction between local and global noise
title_short Motion integration for optic-flow patterns : the interaction between local and global noise
title_full Motion integration for optic-flow patterns : the interaction between local and global noise
title_fullStr Motion integration for optic-flow patterns : the interaction between local and global noise
title_full_unstemmed Motion integration for optic-flow patterns : the interaction between local and global noise
title_sort motion integration for optic-flow patterns : the interaction between local and global noise
publishDate 2016
url http://hdl.handle.net/10356/67255
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