| Presentation | 2005/5/19 Neural network model of luminance discrimination based on visual cortex response Akiko IWAIZUMI, Shinichiro KANOH, Ryokou FUTAMI, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Psychophysical experiment of luminance discrimination between two simulteneously presented stimuli was conducted in order to explore the discriminative property that depends on stimulus duration. When the duration is short (150ms), subjects responded more rapidly but mistakingly, keeping nearly 100% of answering rate. We assumed that such phenomenon occurs due to sustained and transient components of stimulus and proposed a winner-take-all typed neural network model that receives sensory input based upon visual cortex responses. Our model reproduced the shape of correct response time distributions and error rates of each condition in experiments. Moreover, the spike sequences of the model closely resembled to neural activity of monkey's parietal and prefrontal area during coherent-motion detection tasks. Finally, we evaluated the ratio of transient/sustained components to reproduce experimental properties, modulating the strength of sensory inputs. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | luminance / discrimination / reaction time distribution / error rate / neural network |
| Paper # | NC2005-2 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2005/5/19(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Neural network model of luminance discrimination based on visual cortex response |
| Sub Title (in English) | |
| Keyword(1) | luminance |
| Keyword(2) | discrimination |
| Keyword(3) | reaction time distribution |
| Keyword(4) | error rate |
| Keyword(5) | neural network |
| 1st Author's Name | Akiko IWAIZUMI |
| 1st Author's Affiliation | Department of Electronic Engineering, Tohoku University() |
| 2nd Author's Name | Shinichiro KANOH |
| 2nd Author's Affiliation | Department of Electronic Engineering, Tohoku University |
| 3rd Author's Name | Ryokou FUTAMI |
| 3rd Author's Affiliation | Faculty of Symbiotic Systems Science, Fukushima University |
| Date | 2005/5/19 |
| Paper # | NC2005-2 |
| Volume (vol) | vol.105 |
| Number (no) | 82 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |