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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
16/02/1998 |
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Data da última atualização: |
12/12/2007 |
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Autoria: |
CARVALHO, L. A. V. de; ROITMAN, V. L. |
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Título: |
A neural model for the visual attention phenomena. |
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Ano de publicação: |
1995 |
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Fonte/Imprenta: |
In: BRAZILIAN SYMPOSIUM ON ARTIFICIAL INTELLIGENCE, 12., 1995, Campinas. Advances in artificial intelligence: proceedings. Berlin: Springer, 1995. |
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Páginas: |
p.191-200 |
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Série: |
(Lecture Notes in Artificial Intelligence, 991; Lecture Notes in Computer Science). |
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ISBN: |
3-540-60436-7 |
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Idioma: |
Inglês |
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Notas: |
SBIA'95. Ed. by Jacques Wainer and Ariadne Carvalho. |
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Conteúdo: |
Two interesting and complex tasks are performed by the brain in the process of perception: the integration of characteristics leading to an easier recognition of a pattern as a whole (binding), and the extraction of properties that need to be detailed and analyzed (attention). Classically, binding is viewed as process whereby sets of properties are gathered in representative entites, which are themselves linked to form higher level structures, in a sequence that culminates in the total integration of the pattern features in a localized construct. The convergent axonal projections from one cortical area to another would be the neurobiological mechanism through which binding is achieved. Attention comprises the selective excitation of neuronal networks or pathways that stand for specific pattern properties. We propose a computational model aiming at bringing together the main (and apparently diverging) ideas about binding and attention. Based on experimental data, a neuronal network representing cortical pyramidal cells is assembled, and its structure and function are related to the binding and attention phenomena. Computer simulation are shown which reproduce the electrophysiology of pyramidal cells and mimie some interesting experimental results in visual attentio. We conclude by conjecturing that attention is a driven interruption in the regular process of binding. |
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Palavras-Chave: |
Artifficial intelligence; Inteligencia artificial. |
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Categoria do assunto: |
-- |
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Marc: |
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001 1005969
005 2007-12-12
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020 $a3-540-60436-7
100 1 $aCARVALHO, L. A. V. de
245 $aA neural model for the visual attention phenomena.
260 $c1995
300 $ap.191-200
490 $a(Lecture Notes in Artificial Intelligence, 991; Lecture Notes in Computer Science).
500 $aSBIA'95. Ed. by Jacques Wainer and Ariadne Carvalho.
520 $aTwo interesting and complex tasks are performed by the brain in the process of perception: the integration of characteristics leading to an easier recognition of a pattern as a whole (binding), and the extraction of properties that need to be detailed and analyzed (attention). Classically, binding is viewed as process whereby sets of properties are gathered in representative entites, which are themselves linked to form higher level structures, in a sequence that culminates in the total integration of the pattern features in a localized construct. The convergent axonal projections from one cortical area to another would be the neurobiological mechanism through which binding is achieved. Attention comprises the selective excitation of neuronal networks or pathways that stand for specific pattern properties. We propose a computational model aiming at bringing together the main (and apparently diverging) ideas about binding and attention. Based on experimental data, a neuronal network representing cortical pyramidal cells is assembled, and its structure and function are related to the binding and attention phenomena. Computer simulation are shown which reproduce the electrophysiology of pyramidal cells and mimie some interesting experimental results in visual attentio. We conclude by conjecturing that attention is a driven interruption in the regular process of binding.
653 $aArtifficial intelligence
653 $aInteligencia artificial
700 1 $aROITMAN, V. L.
773 $tIn: BRAZILIAN SYMPOSIUM ON ARTIFICIAL INTELLIGENCE, 12., 1995, Campinas. Advances in artificial intelligence: proceedings. Berlin: Springer, 1995.
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Embrapa Agricultura Digital (CNPTIA) |
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