Cortical pooling algorithms for judging global motion direction
Physiological studies suggest that decision networks read from the neural representation in the middle temporal area to determine the perceived direction of visual motion, whereas psychophysical studies tend to characterize motion perception in terms of the statistical properties of stimuli. To reco...
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Veröffentlicht in: | Proceedings of the National Academy of Sciences - PNAS 2007-02, Vol.104 (9), p.3532-3537 |
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description | Physiological studies suggest that decision networks read from the neural representation in the middle temporal area to determine the perceived direction of visual motion, whereas psychophysical studies tend to characterize motion perception in terms of the statistical properties of stimuli. To reconcile these different approaches, we examined whether estimating the central tendency of the physical direction of global motion was a better indicator of perceived direction than algorithms (e.g., maximum likelihood) that read from directionally tuned mechanisms near the end of the motion pathway. The task of human observers was to discriminate the global direction of random dot kinematograms composed of asymmetrical distributions of local directions with distinct measures of central tendency. None of the statistical measures of image direction central tendency provided consistently accurate predictions of perceived global motion direction. However, regardless of the local composition of motion directions, a maximum-likelihood decoder produced global motion estimates commensurate with the psychophysical data. Our results suggest that mechanism-based, read-out algorithms offer a more accurate and robust guide to human motion perception than any stimulus-based, statistical estimate of central tendency. |
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To reconcile these different approaches, we examined whether estimating the central tendency of the physical direction of global motion was a better indicator of perceived direction than algorithms (e.g., maximum likelihood) that read from directionally tuned mechanisms near the end of the motion pathway. The task of human observers was to discriminate the global direction of random dot kinematograms composed of asymmetrical distributions of local directions with distinct measures of central tendency. None of the statistical measures of image direction central tendency provided consistently accurate predictions of perceived global motion direction. However, regardless of the local composition of motion directions, a maximum-likelihood decoder produced global motion estimates commensurate with the psychophysical data. 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Our results suggest that mechanism-based, read-out algorithms offer a more accurate and robust guide to human motion perception than any stimulus-based, statistical estimate of central tendency.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Biological Sciences</subject><subject>Central tendencies</subject><subject>Computer Simulation</subject><subject>Estimate reliability</subject><subject>Experimentation</subject><subject>Eye movements</subject><subject>Eyes & eyesight</subject><subject>Humans</subject><subject>Likelihood Functions</subject><subject>Mathematical vectors</subject><subject>Maximum likelihood estimation</subject><subject>Models, Neurological</subject><subject>Motion perception</subject><subject>Motion Perception - physiology</subject><subject>Neuroscience</subject><subject>Photic Stimulation</subject><subject>Population estimates</subject><subject>Psychophysics</subject><subject>Sensory perception</subject><subject>Speed</subject><subject>Studies</subject><subject>Visual Cortex - physiology</subject><issn>0027-8424</issn><issn>1091-6490</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc2PFCEQxYnRuOPo2ZPa8aCn3gUKGrhoNhO_kk086J4JTdO9TJhmhG7j_vfSmcnOakw8QahfPerVQ-g5wecEC7jYjyaf44YQKiXB7AFaEaxI3TCFH6IVxlTUklF2hp7kvMUYKy7xY3RGBDS4EXKF3m9imrw1odrHGPw4VCYMMfnpZperPqZqO3fD8jyE2BZqFycfx6rzydnl9hQ96k3I7tnxXKPrjx--bz7XV18_fdlcXtWWs2aqOyk5YNp2DKhqOyXAALRG8tbxpiXKOsLACcU4Lz5cBz1gZ8EKSW1jW4A1enfQ3c_tznXWjVMyQe-T35l0q6Px-s_K6G_0EH9qIjFvivgavTkKpPhjdnnSO5-tC8GMLs5Zi7IrJSj9L0jKDiUIXsDXf4HbOKexbEFTTBgFxZZvLw6QTTHn5Pq7kQnWS4R6iVCfIiwdL-87PfHHzArw9ggsnSc5ppUGDlT3cwiT-zXdk_o3WYAXB2Cbp5juCMoZbRq5zPLqUO9N1GZIPuvrb8UcYCw4BQHwG-Hywg0</recordid><startdate>20070227</startdate><enddate>20070227</enddate><creator>Webb, Ben S</creator><creator>Ledgeway, Timothy</creator><creator>McGraw, Paul V</creator><general>National Academy of Sciences</general><general>National Acad Sciences</general><scope>FBQ</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7QL</scope><scope>7QP</scope><scope>7QR</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TK</scope><scope>7TM</scope><scope>7TO</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20070227</creationdate><title>Cortical pooling algorithms for judging global motion direction</title><author>Webb, Ben S ; 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To reconcile these different approaches, we examined whether estimating the central tendency of the physical direction of global motion was a better indicator of perceived direction than algorithms (e.g., maximum likelihood) that read from directionally tuned mechanisms near the end of the motion pathway. The task of human observers was to discriminate the global direction of random dot kinematograms composed of asymmetrical distributions of local directions with distinct measures of central tendency. None of the statistical measures of image direction central tendency provided consistently accurate predictions of perceived global motion direction. However, regardless of the local composition of motion directions, a maximum-likelihood decoder produced global motion estimates commensurate with the psychophysical data. 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subjects | Adult Algorithms Biological Sciences Central tendencies Computer Simulation Estimate reliability Experimentation Eye movements Eyes & eyesight Humans Likelihood Functions Mathematical vectors Maximum likelihood estimation Models, Neurological Motion perception Motion Perception - physiology Neuroscience Photic Stimulation Population estimates Psychophysics Sensory perception Speed Studies Visual Cortex - physiology |
title | Cortical pooling algorithms for judging global motion direction |
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