roger ratcliff, marios g. philiastide, and paul sajda

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Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG Roger Ratcliff, Marios G. Philiastide, and Paul Sajda DDRM 4/19/09

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Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG. DDRM 4/19/09. Roger Ratcliff, Marios G. Philiastide, and Paul Sajda. Face/car discrimination task. early. late. model. EEG. behavior. goal. - PowerPoint PPT Presentation

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Page 1: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

Quality of evidence for perceptual decision making

is indexed by trial-to-trial variability of the EEG

Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

DDRM 4/19/09

Page 2: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

Face/car discrimination task

Page 3: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda
Page 4: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

early late

Page 5: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

goal

Model fit uses % correct in RT quantiles ([0.1:0.2:0.9]), so cannot be fit on a trial-to-trial basis.

=> to look at trial-to-trial relationship between model and behavior, here single-trial EEG data is used.

Is there a relationship

at the single-trial level?

modelEEG

behavior

Page 6: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

logic

• EEG component amplitude was used to divide trials into those with high and low drift rate.

• Then the model was fit separately to the 2 groups of trials.

• The fit uses the behavioral results of the sorted trials to extract drift rate.

• Main result: the drift rate was higher on trials with higher EEG

Page 7: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

Trials of stimulus conditionOne subject

RT, % correct RT, % correct

Fit model Fit model

Drift rate Drift rate?<

Page 8: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

sim

ulat

ion

Page 9: Roger Ratcliff, Marios G. Philiastide, and Paul Sajda