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Neural Substrates for Early Data Reduction in Fast Vision: A Psychophysical Investigation.
Castellotti, Serena; Del Viva, Maria Michela.
Afiliação
  • Castellotti S; Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy.
  • Del Viva MM; Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, 50135 Florence, Italy.
Brain Sci ; 14(8)2024 Jul 26.
Article em En | MEDLINE | ID: mdl-39199448
ABSTRACT
To ensure survival, the visual system must rapidly extract the most important elements from a large stream of information. This necessity clashes with the computational limitations of the human brain, so a strong early data reduction is required to efficiently process information in fast vision. A theoretical early vision model, recently developed to preserve maximum information using minimal computational resources, allows efficient image data reduction by extracting simplified sketches containing only optimally informative, salient features. Here, we investigate the neural substrates of this mechanism for optimal encoding of information, possibly located in early visual structures. We adopted a flicker adaptation paradigm, which has been demonstrated to specifically impair the contrast sensitivity of the magnocellular pathway. We compared flicker-induced contrast threshold changes in three different tasks. The results indicate that, after adapting to a uniform flickering field, thresholds for image discrimination using briefly presented sketches increase. Similar threshold elevations occur for motion discrimination, a task typically targeting the magnocellular system. Instead, contrast thresholds for orientation discrimination, a task typically targeting the parvocellular system, do not change with flicker adaptation. The computation performed by this early data reduction mechanism seems thus consistent with magnocellular processing.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália País de publicação: Suíça