eCite Digital Repository

A cognitive model-based approach to testing mechanistic explanations for neuropsychological decrements during tobacco abstinence

Citation

Weigard, A and Huang-Pollock, C and Heathcote, A and Hawk, L and Schlienz, NJ, A cognitive model-based approach to testing mechanistic explanations for neuropsychological decrements during tobacco abstinence, Psychopharmacology ISSN 0033-3158 (2018) [Refereed Article]

Copyright Statement

Copyright 2018 Springer-Verlag GmbH Germany, part of Springer Nature

DOI: doi:10.1007/s00213-018-5008-3

Abstract

Rationale: Cigarette smokers often experience cognitive decrements during abstinence from tobacco, and these decrements may have clinical relevance in the context of smoking cessation interventions. However, limitations of the behavioral summary statistics used to measure cognitive effects of abstinence, response times (RT) and accuracy rates, may restrict the field’s ability to identify robust abstinence effects on task performance and test mechanistic hypotheses about the etiology of these cognitive changes.

Objectives: The current study explored whether a measurement approach based on mathematical models of cognition, which make the cognitive mechanisms necessary to perform choice RT tasks explicit, would be able to address these limitations.

Methods: The linear ballistic accumulator model (LBA: Brown and Heathcote, Cogn Psychol 57(3):153-178, 2008) was fit to an existing data set from a study that evaluated the impact of overnight abstinence on flanker task performance. Results: The model-based analysis provided evidence that smokers’ rates of mind wandering increased during abstinence, and was able to index this effect while controlling for participants’ strategy changes that were related to the specific experimental paradigm used.

Conclusion: Mind wandering is a putative explanation for cognitive withdrawal symptoms during smoking cessation and may be indexed using the LBA. More broadly, the use of formal model-based analyses in future research on this topic has the potential to allow for strong and specific tests of mechanistic explanations for these symptoms.

Item Details

Item Type:Refereed Article
Keywords:smoking, tobacco withdrawal, cognitive modeling, bayesian models, response times
Research Division:Psychology and Cognitive Sciences
Research Group:Cognitive Sciences
Research Field:Computer Perception, Memory and Attention
Objective Division:Health
Objective Group:Public Health (excl. Specific Population Health)
Objective Field:Substance Abuse
Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:128268
Year Published:2018
Deposited By:Psychology
Deposited On:2018-09-12
Last Modified:2018-10-15
Downloads:0

Repository Staff Only: item control page