TY - JOUR
T1 - A comparative study of drift diffusion and linear ballistic accumulator models in a reward maximization perceptual choice task
AU - Goldfarb, Stephanie
AU - Leonard, Naomi Ehrich
AU - Simen, Patrick
AU - Caicedo-Núñez, Carlos H.
AU - Holmes, Philip
PY - 2014
Y1 - 2014
N2 - We present new findings that distinguish drift diffusion models (DDMs) from the linear ballistic accumulator (LBA) model as descriptions of human behavior in a two-alternative forcedchoice reward maximization (Rmax) task. Previous comparisons have not considered Rmax tasks, and differences identified between the models' predictions have centered on practice effects. Unlike the parameter-free optimal performance curves of the pure DDM, the extended DDM and LBA predict families of curves depending on their additional parameters, and those of the LBA show significant differences from the DDMs, especially for poorly discriminable stimuli that incur high error rates. Moreover, fits to behavior reveal that the LBA and DDM provide different interpretations of behavior as stimulus discriminability increases. Trends for threshold setting (caution) in the DDMs are consistent between fits, while in the corresponding LBA fits, thresholds interact with distributions of starting points in a complex manner that depends upon parameter constraints. Our results suggest that reinterpretation of LBA parameters may be necessary in modeling the Rmax paradigm.
AB - We present new findings that distinguish drift diffusion models (DDMs) from the linear ballistic accumulator (LBA) model as descriptions of human behavior in a two-alternative forcedchoice reward maximization (Rmax) task. Previous comparisons have not considered Rmax tasks, and differences identified between the models' predictions have centered on practice effects. Unlike the parameter-free optimal performance curves of the pure DDM, the extended DDM and LBA predict families of curves depending on their additional parameters, and those of the LBA show significant differences from the DDMs, especially for poorly discriminable stimuli that incur high error rates. Moreover, fits to behavior reveal that the LBA and DDM provide different interpretations of behavior as stimulus discriminability increases. Trends for threshold setting (caution) in the DDMs are consistent between fits, while in the corresponding LBA fits, thresholds interact with distributions of starting points in a complex manner that depends upon parameter constraints. Our results suggest that reinterpretation of LBA parameters may be necessary in modeling the Rmax paradigm.
KW - Drift diffusion model
KW - Linear ballistic accumulator model
KW - Optimal performance theory
KW - Reward maximization
UR - http://www.scopus.com/inward/record.url?scp=84905053616&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905053616&partnerID=8YFLogxK
U2 - 10.3389/fnins.2014.00148
DO - 10.3389/fnins.2014.00148
M3 - Article
C2 - 25140124
AN - SCOPUS:84905053616
SN - 1662-4548
JO - Frontiers in Neuroscience
JF - Frontiers in Neuroscience
IS - 8 MAY
M1 - 148
ER -