Dynamical Models of Decision Making Optimality, human performance, and principles of neural information processing. Jay McClelland Department of Psychology and Center for Mind Brain and Computation Stanford University. How do we make a decision given a marginal stimulus?.
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Dynamical Models of Decision MakingOptimality, human performance, andprinciples of neural information processing
Department of Psychology and Center for Mind Brain and ComputationStanford University
Hard -> Easy
Activation of neurons responsive to
Selected vs. non-selectedtarget from Chelazzi et al (1993)
dx1/dt = r1-l(x1)+af(x1)–bf(x2)+x1
dx2/dt = r2-l(x2)+af(x2)–bf(x1)+x2
|k-b| = 0
|k-b| = .2
|k-b| = .4
Subjects show both kindsof biases; the less the bias,the higher the accuracy,as predicted.
RT task paradigm of R&T.
Motion coherence anddirection is varied fromtrial to trial.
Data are averaged over many different neurons that areassociated with intended eye movements to the locationof target.
Wong & Wang (2006)
… and the physiological data as well!