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Evaluating neuronal algorithms of rapid contour integration.| old_uid | 338 |
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| title | Evaluating neuronal algorithms of rapid contour integration. |
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| start_date | 2005/12/08 |
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| schedule | 16h |
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| online | no |
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| location_info | /, salle des actes |
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| summary | Contour integration is an important step in the decomposition of a visual scene into distinct objects (figure-ground segmentation). During this process oriented, aligned edge elements are bound together to form a coherent contour according to the laws proposed by Gestalt
psychologists.
Psychophysical experiments revealed that contour integration in macaque monkeys and human observers is both very efficient and astonishingly fast. This high performance challenges algorithms of contour integration, and opens the question about the
relevant neurophysiological mechanisms underlying this specific computation in neural information processing.
Several algorithms for contour integration have been proposed, ranging from ideal probabilistic algorithms with multiplicative, directed interactions up to neural networks with long-ranging additive, undirected horizontal couplings. We evaluate this spectrum of different model classes by requiring that a suitable, neurophysiologically plausible
model should not only reproduce the performance of human observers, but also their systematic errors made during the integration of contours.
Our analysis of these errors predicts that contour integration in the brain is mediated by multiplicative and directed interactions, as opposed to current models employing additive and non-directed interactions. |
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| oncancel | Attention : changement de lieu et d’horaire |
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| responsibles | Gutkin |
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