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Simple speed estimators reproduce MT responses and identify strength of visual illusion
https://uec.repo.nii.ac.jp/records/9202
https://uec.repo.nii.ac.jp/records/920274546ea6-ac88-436f-9696-c00d3cdd9dfc
名前 / ファイル | ライセンス | アクション |
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Nakamura_Satoh_Neural_Comput_and_Applic_rev2 (670.2 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2019-05-23 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Simple speed estimators reproduce MT responses and identify strength of visual illusion | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
言語 | en | |||||
主題 | MT | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Visual illusion | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Lucas–Kanade method | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Computational model | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Nakamura, Daiki
× Nakamura, Daiki× Satoh, Shunji |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Computational models of vision should not only be able to reproduce experimentally obtained results; such models should also be able to predict the input–output properties of vision. Conventional models of MT neurons are based on the concept of velocity filtering, as proposed by Simoncelli and Heeger (Vis Res 38(5):743–761, 1998). As this report describes, we provide another interpretation of the computational function of MT neurons. An MT neuron can be a simple speed estimator with an upper limitation for correct estimation. Subsequently, we assess whether the MT model can account for illusory perception of “rotating drift patterns,” by which humans perceive illusory rotation (clockwise or counterclockwise rotation) depending on the background luminance. Moreover, to predict whether a pattern causes visual illusion, or not, we generate an enormous set of possible visual patterns as inputs to the MT model: 88=16,777,216. Numerical quantities of model outputs obtained through a computer simulation for 88 inputs were used to estimate human illusory perception. Results of psychophysical experiments demonstrate that the model prediction is consistent with human perception. | |||||
書誌情報 |
en : Neural Computing and Applications 巻 31, p. 2523-2535, 発行日 2019-06-01 |
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出版者 | ||||||
出版者 | Springer Nature | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0941-0643 | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1007/s00521-017-3211-5 | |||||
権利 | ||||||
権利情報 | © The Natural Computing Applications Forum 2019 | |||||
関連サイト | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1007/s00521-017-3211-5 | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |