Roger Ratcliff, Marios G. Philiastide, and Paul Sajda

Slides:



Advertisements
Similar presentations
Quasi-Continuous Decision States in the Leaky Competing Accumulator Model Jay McClelland Stanford University With Joel Lachter, Greg Corrado, and Jim Johnston.
Advertisements

HON207 Cognitive Science Sequential Sampling Models.
True/False. False True Subject May Go Here True / False ? Type correct answer here. Type incorrect answer here.
Selection Sort
Rapid Serial Visual Presentation (RSVP) Task (abbreviated sequence) Simulates saccadic vision Used to gauge speed of visual object recognition Thorpe et.
Distinguishing Evidence Accumulation from Response Bias in Categorical Decision-Making Vincent P. Ferrera 1,2, Jack Grinband 1,2, Quan Xiao 1,2, Joy Hirsch.
Theory of Decision Time Dynamics, with Applications to Memory.
An Integrated Model of Decision Making and Visual Attention Philip L. Smith University of Melbourne Collaborators: Roger Ratcliff, Bradley Wolfgang.
Visual Processing in Fingerprint Experts and Novices Tom Busey Indiana University, Bloomington John Vanderkolk Indiana State Police, Fort Wayne Expertise.
Introduction to cognitive modeling Marieke van Vugt University of Groningen The Netherlands.
Seeing motion : From neural circuits to perceptual decisions.
Howto use Eureka ICS 105 Research Team Fall 2000.
Selection Sort
Lexical Decisions -- The Basic Analysis Mean RT as a Function of Trial Type This analysis is based on correct trials only, with practice trials omitted.
Simultaneous integration versus sequential sampling in multiple-choice decision making Nate Smith July 20, 2008.
Next, this study employed SVM to classify the emotion label for each EEG segment. The basic idea is to project input data onto a higher dimensional feature.
Event-Related Potentials Chap2. Ten Simple Rules for Designing ERP Experiments (2/2) 임원진
The Nature of Science To be scientifically literate, science students should have deeper understandings of science that studying the Nature of Science.
Functional Neuroimaging of Perceptual Decision Making
Mechanisms of Simple Perceptual Decision Making Processes
Psychometric Functions
“Perceptual changes induced by Category Learning –an ERP study”
Thomas Andrillon, Sid Kouider, Trevor Agus, Daniel Pressnitzer 
Meditation experience predicts less negative appraisal of pain: Electrophysiological evidence for the involvement of anticipatory neural responses.
The Measurement of Motor Performance
Piercing of Consciousness as a Threshold-Crossing Operation
Contribution of spatial and temporal integration in heading perception
The Evidence-Based Practice Cycle
Dynamical Models of Decision Making Optimality, human performance, and principles of neural information processing Jay McClelland Department of Psychology.
Evoked Response Potential (ERP) and Face Stimuli N170: negative-going potential at 170 ms Largest over the right parietal lobe,
ورشة بعنوان استراتيجيات تعديل السلوك بين النظرية والتطبيق
A Classical Model of Decision Making: The Drift Diffusion Model of Choice Between Two Alternatives At each time step a small sample of noisy information.
Experimental Psychology PSY 433
Comparison of observed switching behavior to ideal switching performance. Comparison of observed switching behavior to ideal switching performance. Conventions.
Rei Akaishi, Kazumasa Umeda, Asako Nagase, Katsuyuki Sakai  Neuron 
Dynamical Models of Decision Making Optimality, human performance, and principles of neural information processing Jay McClelland Department of Psychology.
Volume 26, Issue 4, Pages (February 2016)
Decision Making during the Psychological Refractory Period
Thomas Andrillon, Sid Kouider, Trevor Agus, Daniel Pressnitzer 
Huan Luo, Xing Tian, Kun Song, Ke Zhou, David Poeppel  Current Biology 
Visual Processing in Fingerprint Experts and Novices
Braden A. Purcell, Roozbeh Kiani  Neuron 
Learning to Simulate Others' Decisions
Stimulus Probabilties--The Basic Analysis
Perceptual Learning and Decision-Making in Human Medial Frontal Cortex
Jason Samaha, Bradley R. Postle  Current Biology 
Banburismus and the Brain
C. Shawn Green, Alexandre Pouget, Daphne Bavelier  Current Biology 
Joshua I. Sanders, Balázs Hangya, Adam Kepecs  Neuron 
Nicholas J. Priebe, David Ferster  Neuron 
Ralf M. Haefner, Pietro Berkes, József Fiser  Neuron 
INFO 414 Information Behavior
Franco Pestilli, Marisa Carrasco, David J. Heeger, Justin L. Gardner 
ཡུལ་རྟོགས་ཀྱི་དཔེ་གཟུགས་ངོ་སྤྲོད།
Erie D. Boorman, John P. O’Doherty, Ralph Adolphs, Antonio Rangel 
Redmond G. O’Connell, Michael N. Shadlen, KongFatt Wong-Lin, Simon P
Volume 75, Issue 5, Pages (September 2012)
Rei Akaishi, Kazumasa Umeda, Asako Nagase, Katsuyuki Sakai  Neuron 
Franco Pestilli, Marisa Carrasco, David J. Heeger, Justin L. Gardner 
Jennifer K. Bizley, Ross K. Maddox, Adrian K.C. Lee 
Learning Theory Reza Shadmehr
Learning to Simulate Others' Decisions
Volume 21, Issue 11, Pages (June 2011)
Volume 75, Issue 5, Pages (September 2012)
Orbitofrontal Cortex as a Cognitive Map of Task Space
Volume 78, Issue 2, Pages (April 2013)
Metacognitive Failure as a Feature of Those Holding Radical Beliefs
Divide 9 × by 3 ×
Volume 15, Issue 2, Pages (April 2016)
Volume 23, Issue 11, Pages (June 2013)
Presentation transcript:

Roger Ratcliff, Marios G. Philiastide, and Paul Sajda DDRM 4/19/09 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

Face/car discrimination task

early late

Is there a relationship at the single-trial level? 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? model EEG behavior

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

< Trials of stimulus condition One subject RT, % correct Fit model Fit model ? < Drift rate Drift rate

simulation