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Generalising the drift rate distribution for linear ballistic accumulators

Citation

Terry, A and Marley, AAJ and Barnwal, A and Wagenmakers, E-J and Heathcote, A and Brown, SD, Generalising the drift rate distribution for linear ballistic accumulators, Journal of Mathematical Psychology, 68-69 pp. 49-58. ISSN 0022-2496 (2015) [Refereed Article]

Copyright Statement

© 2015 Elsevier Inc. All rights reserved.

DOI: doi:10.1016/j.jmp.2015.09.002

Abstract

The linear ballistic accumulator model is a theory of decision-making that has been used to analyse data from human and animal experiments. It represents decisions as a race between independent evidence accumulators, and has proven successful in a form assuming a normal distribution for accumulation ("drift") rates. However, this assumption has some limitations, including the corollary that some decision times are negative or undefined. We show that various drift rate distributions with strictly positive support can be substituted for the normal distribution without loss of analytic tractability, provided the candidate distribution has a closed-form expression for its mean when truncated to a closed interval. We illustrate the approach by developing three new linear ballistic accumulation variants, in which the normal distribution for drift rates is replaced by either the lognormal, Fréchet, or gamma distribution. We compare some properties of these new variants to the original normal-rate model.

Item Details

Item Type:Refereed Article
Keywords:response time, evidence accumulation, accumulator model, decision making
Research Division:Psychology and Cognitive Sciences
Research Group:Cognitive Sciences
Research Field:Decision Making
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Psychology and Cognitive Sciences
Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:105724
Year Published:2015
Web of Science® Times Cited:1
Deposited By:Medicine (Discipline)
Deposited On:2016-01-13
Last Modified:2017-10-31
Downloads:0

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