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Dynamic properties of internal noise probed by modulating binocular rivalry.
Baker, Daniel H; Richard, Bruno.
Afiliación
  • Baker DH; Department of Psychology, University of York, Heslington, York, United Kingdom.
  • Richard B; York Biomedical Research Institute, University of York, Heslington, York, United Kingdom.
PLoS Comput Biol ; 15(6): e1007071, 2019 06.
Article en En | MEDLINE | ID: mdl-31170150
ABSTRACT
Neural systems are inherently noisy, and this noise can affect our perception from moment to moment. This is particularly apparent in binocular rivalry, where perception of competing stimuli shown to the left and right eyes alternates over time. We modulated rivalling stimuli using dynamic sequences of external noise of various rates and amplitudes. We repeated each external noise sequence twice, and assessed the consistency of percepts across repetitions. External noise modulations of sufficiently high contrast increased consistency scores above baseline, and were most effective at 1/8Hz. A computational model of rivalry in which internal noise has a 1/f (pink) temporal amplitude spectrum, and a standard deviation of 16% contrast, provided the best account of our data. Our novel technique provides detailed estimates of the dynamic properties of internal noise during binocular rivalry, and by extension the stochastic processes that drive our perception and other types of spontaneous brain activity.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Visión Binocular / Disparidad Visual / Modelos Neurológicos Tipo de estudio: Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Visión Binocular / Disparidad Visual / Modelos Neurológicos Tipo de estudio: Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido