Document Type

Article

Publication Date

4-15-2021

Identifier

DOI: 10.1016/j.neuroimage.2021.117796

Abstract

BACKGROUND: The Monetary Incentive Delay task (MID) has been used extensively to probe anticipatory reward processes. However, individual differences evident during this task may relate to other constructs such as general arousal or valence processing (i.e., anticipation of negative versus positive outcomes). This investigation used a latent variable approach to parse activation patterns during the MID within a transdiagnostic clinical sample.

METHODS: Participants were drawn from the first 500 individuals recruited for the Tulsa-1000 (T1000), a naturalistic longitudinal study of 1000 participants aged 18-55 (n = 476 with MID data). We employed a multiview latent analysis method, group factor analysis, to characterize factors within and across variable sets consisting of: (1) region of interest (ROI)-based blood oxygenation level-dependent (BOLD) contrasts during reward and loss anticipation; and (2) self-report measures of positive and negative valence and related constructs.

RESULTS: Three factors comprised of ROI indicators emerged to accounted for >43% of variance and loaded on variables representing: (1) general arousal or general activation; (2) valence, with dissociable responses to anticipation of win versus loss; and (3) region-specific activation, with dissociable activation in salience versus perceptual brain networks. Two additional factors were comprised of self-report variables, which appeared to represent arousal and valence.

CONCLUSIONS: Results indicate that multiview techniques to identify latent variables offer a novel approach for differentiating brain activation patterns during task engagement. Such approaches may offer insight into neural processing patterns through dimension reduction, be useful for probing individual differences, and aid in the development of optimal explanatory or predictive frameworks.

Journal Title

NeuroImage

Volume

230

First Page

117796

Last Page

117796

Comments

Grant support

This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.

Publisher's Link: https://www.sciencedirect.com/science/article/pii/S1053811921000732?via%3Dihub

Download

Share

COinS