[Abstract Title]. - Society for Neuroscience

signal lags, then follows a shifted exponential, reaching asymptote for lags of about 1 second.
The trajectory is consistent with the Leaky, Competing Accumulator Model of Usher and
McClelland (2001). Under these conditions, the optimal policy is to choose the response
associated with the larger reward 100% of the time at the earliest signal lags, where stimulus
identification accuracy is at chance. As evidence accumulates, the reliance on reward relative to
stimulus information should gradually decrease, leveling off as accuracy approaches asymptote.
We examine results from five participants. One showed no reward bias. For the others, the
reward bias is very strong initially and then tapers off to a fixed level, in general agreement with
the optimal policy. However, the initial bias is never as strong as would be optimal. The final
bias is greater than optimal for some participants and less than optimal for others. Quantitative
optimality analysis is carried out based on one dimensional stochastic accumulating models and
signal detection theory. We also found that participants‟ fastest responses at each of the 10
response lags tended to be more extreme than their slower responses (at short lags, faster
responses were more biased toward the higher reward; at long lags, they were more accurate).
We propose a model in which participants may maintain graded evidence and reward values until
the arrival of the response signal, which then drives a race to threshold.
Disclosures: J. Gao, None; R. Tortell, None; J.L. McClelland, None.
Poster
289. Human Decision Making
Time: Sunday, November 16, 2008, 1:00 pm - 5:00 pm
Program#/Poster#: 289.5/RR41
Topic: F.01.g. Decision making and reasoning
Support: EU IST 027198 "Decisions in Motion"
Title: Neural correlates of stimulus independent decisions in motion in depth
Authors: *G. KOVÁCS 1,2 , C. CZIRÁKI 1,2 , M. W. GREENLEE 2 ;
1 Dept Cognitive Sci., Tech. Univ. Budapest, Budapest, Hungary; 2 Inst. of Psychology, Univ. of
Regensburg, Regensburg, Germany
Abstract: Perceptual decision making is a complicated, multi-stage process. Currently human
neuroimaging studies implicated a set of regions, extending from the medial frontal cortex to the
inferior parietal lobule in various steps of perceptual judgments. However, relatively little is
known about the dependence of perceptual decisions on the visual stimulus itself. In the current
study, we used functional magnetic resonance imaging during a demanding 3D heading
estimation task. Subjects (n=13) were presented a constantly expanding optic-flow stimulus,