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An initial 'snapshot' of sensory information biases the likelihood and speed of subsequent changes of mind.
Turner, William; Feuerriegel, Daniel; Hester, Robert; Bode, Stefan.
Afiliación
  • Turner W; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
  • Feuerriegel D; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
  • Hester R; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
  • Bode S; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
PLoS Comput Biol ; 18(1): e1009738, 2022 01.
Article en En | MEDLINE | ID: mdl-35025889
ABSTRACT
We often need to rapidly change our mind about perceptual decisions in order to account for new information and correct mistakes. One fundamental, unresolved question is whether information processed prior to a decision being made ('pre-decisional information') has any influence on the likelihood and speed with which that decision is reversed. We investigated this using a luminance discrimination task in which participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli briefly remained on screen, and participants could change their response. Using psychophysical reverse correlation, we examined how moment-to-moment fluctuations in stimulus luminance affected participants' decisions. This revealed that the strength of even the very earliest (pre-decisional) evidence was associated with the likelihood and speed of later changes of mind. To account for this effect, we propose an extended diffusion model in which an initial 'snapshot' of sensory information biases ongoing evidence accumulation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biología Computacional / Toma de Decisiones / Modelos Neurológicos Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biología Computacional / Toma de Decisiones / Modelos Neurológicos Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Australia