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A simple vector-like law for perceptual information combination is also followed by a class of cortical multisensory bimodal neurons.
Billock, Vincent A; Kinney, Micah J; Schnupp, Jan W H; Meredith, M Alex.
Afiliación
  • Billock VA; Naval Aerospace Medical Research Laboratory, NAMRU-D, Wright-Patterson Air Force Base, OH 45433, USA.
  • Kinney MJ; Naval Aerospace Medical Research Laboratory, NAMRU-D, Wright-Patterson Air Force Base, OH 45433, USA.
  • Schnupp JWH; Naval Air Warfare Center, NAWCAD, Patuxent River, MD 20670, USA.
  • Meredith MA; Department of Neuroscience, City University of Hong Kong, Kowloon Tong, Hong Kong, China.
iScience ; 24(6): 102527, 2021 Jun 25.
Article en En | MEDLINE | ID: mdl-34142039
An interdisciplinary approach to sensory information combination shows a correspondence between perceptual and neural measures of nonlinear multisensory integration. In psychophysics, sensory information combinations are often characterized by the Minkowski formula, but the neural substrates of many psychophysical multisensory interactions are unknown. We show that audiovisual interactions - for both psychophysical detection threshold data and cortical bimodal neurons - obey similar vector-like Minkowski models, suggesting that cortical bimodal neurons could underlie multisensory perceptual sensitivity. An alternative Bayesian model is not a good predictor of cortical bimodal response. In contrast to cortex, audiovisual data from superior colliculus resembles the 'City-Block' combination rule used in perceptual similarity metrics. Previous work found a simple power law amplification rule is followed for perceptual appearance measures and by cortical subthreshold multisensory neurons. The two most studied neural cell classes in cortical multisensory interactions may provide neural substrates for two important perceptual modes: appearance-based and performance-based perception.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: IScience Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: IScience Año: 2021 Tipo del documento: Article