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Coupling BCM and neural fields for the emergence of self-organization consensus

Mathieu Lefort 1 Yann Boniface 1 Bernard Girau 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Human beings interact with the environment through different modalities, i.e. perceptions and actions, processed in the cortex by dedicated brain areas. This areas are self-organized, so that spatially close neurons are sensitive to close stimuli, providing generalization from previously learn examples. Although perceptive flows are picked up by different spatially separated sensors, their processing are not isolated. On the contrary, they are constantly interacting, as illustrated by the McGurk effect. When the auditory stimulus /ba/ and the /ga/ lip movement are presented simultaneously, people perceive a /da/, which does not correspond to any of the stimuli. Merging several stimuli into one multimodal perception reduces ambiguities and noises and is essential to interact with the environment. This article proposes a model for modalities association, inspired by the biological properties of the cortex. The model consists on modality maps interacting through an associative map to raise a consistent multimodal perception of the environment. We propose the coupling of BCM learning rule and neural maps to obtain the decentralized and unsupervised self-organization of each modal map influenced by the multisensory context.
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https://hal.inria.fr/inria-00585493
Contributor : Bernard Girau <>
Submitted on : Wednesday, April 13, 2011 - 9:48:02 AM
Last modification on : Friday, February 26, 2021 - 3:28:03 PM

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  • HAL Id : inria-00585493, version 1

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Mathieu Lefort, Yann Boniface, Bernard Girau. Coupling BCM and neural fields for the emergence of self-organization consensus. Hernández, C.; Sanz, R.; Gomez, J.; Smith, L.S.; Hussain, A.; Chella, A.; Aleksander, I. From Brains to Systems - Brain-Inspired Cognitive Systems 2010, 718, Springer, 2011, Advances in Experimental Medicine and Biology, 978-1-4614-0163-6. ⟨inria-00585493⟩

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