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SUMMARY:Modeling feature-integration in human vision with drift diffusion 
 models
DTSTART:20091023T121500
DTSTAMP:20260407T102636Z
UID:504d567bf1a1231fe572e5d9e5d316d5f4c4da48a2282b0b586b7717
CATEGORIES:Conferences - Seminars
DESCRIPTION:Nicolas Marcille\nThe world surrounding us is inherently noisy
  and so is the input into the visual system. Hence\, the visual system is 
 constantly involved in a perceptual decision making process. It has to dec
 ide\, what the most likely event was\, that caused the input. The reaction
  times of such perceptual decisions are generally modeled by drift diffusi
 on models\, in which sensory input is accumulated across time until a thre
 shold is reached and thereby a decision is taken. Most studies in this fie
 ld have used a constant sensory input and a constant drift value of the di
 ffusion process. Using such constant input designs\, the possibilities to 
 investigate the relationship between sensory input and the diffusion's dri
 ft are thus very limited.\n\nHere we use a feature fusion paradigm\, to in
 vestigate how time varying input is accumulated in integration models. In 
 feature fusion\, features of stimuli\, presented in rapid succession\, fus
 e into one percept. E.g. a yellow disk is perceived\, when a red disk is f
 ollowed by a green disk. By using such time varying input we show that the
  integration is not driven by the input directly but by the output of a pr
 eliminary sensory integration process.
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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