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SUMMARY:Inferring decision rules from evidence\, choice\, and reaction tim
 es - Yul Kang (Columbia University)
DTSTART:20170614T090000Z
DTEND:20170614T094500Z
UID:TALK73062@talks.cam.ac.uk
CONTACT:Daniel McNamee
DESCRIPTION:I will present four related projects about decision-making bas
 ed on one or two evidence streams\, focusing on the quantitative relations
 hip between the choice\, reaction time\, and the contents of evidence.\n\n
 (1) I will show that we can predict choices based on the reported time of 
 covert decisions (decisions without an immediate motor response) in a perc
 eptual decision-making task. We conclude that subjects terminate the decis
 ion when accumulated evidence reaches a threshold even when more evidence 
 is available\, and that the reported time of the mental event (threshold c
 rossing) is reliable enough to enable prediction.\n\n(2) For the decisions
  reported in (1) and for other types of decisions\, it has been suggested 
 that the decision thresholds decrease over time. Here I will present an ef
 ficient technique to estimate time-varying decision thresholds without an 
 assumption on their shape.\n\n(3) As a step toward more complex decisions\
 , I will discuss perceptual decision-making based on two evidence streams\
 , motion and color. I will show that even when the two evidence streams ar
 e available simultaneously at the same location and when only one motor re
 sponse is required to report the decision\, the time to make the combined 
 decision is better explained by the sum of the duration of the two decisio
 n processes than by their maximum\, suggesting interference. I will also d
 iscuss an ongoing project on estimating the degree of interference between
  the two evidence accumulation processes.\n\n(4) Although in (3) we show t
 hat there exists interference between the two decision processes\, it is u
 nclear if the interference is at the evidence acquisition stage (sensory)\
 , or at the evidence accumulation stage (central). I will present a Bayesi
 an reverse-correlation technique to estimate the time-varying probability 
 of simultaneous evidence acquisition from two evidence streams.
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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