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Review
. 2024 Oct 1;13(3):695-701.
doi: 10.1556/2006.2024.00050. Print 2024 Oct 4.

Prediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods

Stephanie Antons  1   2   3 , Sarah W Yip  4   5 , Cheryl M Lacadie  6 , Javid Dadashkarimi  7   8 , Dustin Scheinost  6 , Matthias Brand  1   2   3 , Marc N Potenza  4   5   9   10   11   12
Affiliations
Review

Prediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods

Stephanie Antons et al. J Behav Addict. .

Abstract

Craving is a central feature of substance use disorders and disorders due to addictive behaviors. Considerable research has investigated neural mechanisms involved in the development and processing of craving. Recently, connectome-based predictive modeling, a data-driven method, has been used in four studies aiming to predict craving related to substance use, addictive behaviors, and food. Studies differed in methods, samples, and conceptualizations of craving. Within the commentary we aim to compare, contrast and consolidate findings across studies by considering conceptual and methodological features of the studies. We derive a theoretical model on the functional connectivity-craving relationships across studies.

Keywords: cue-reactivity; fMRI; functional connectivity; machine learning; urge.

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Conflict of interest statement

Conflict of interest: The authors report no conflicts of interest with respect to the content of this manuscript. SA receives funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation); has edited journals and journal sections; has given academic lectures in clinical or scientific venues. MNP has consulted for Opiant Therapeutics, Game Day Data, Baria-Tek, the Addiction Policy Forum, AXA, Boehringer Ingelheim, and Idorsia Pharmaceuticals; been involved in a patent application with Yale University and Novartis; received research support from Mohegan Sun Casino, Children and Screens and the Connecticut Council on Problem Gambling; participated in surveys, mailings, or telephone consultations related to drug addictions, internet use, impulse-control disorders, and other health topics; consulted for or advised gambling, non-profit and legal entities on issues related to internet use, impulse-control and/addictive disorders; and given academic lectures in grand rounds, continuing medical education events, and other clinical or scientific venues. MB receives funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), the EU, and the German Federal Ministry of Education and Research; has performed grant reviews for research-funding agencies; has edited journals and journal sections; has given academic lectures in clinical or scientific venues; and has generated book chapters for publishers of mental health texts. SA, MB, and MNP are associate editors of the Journal of Behavioral Addictions.

Figures

Fig. 1.
Fig. 1.
Integration of the results from Antons, Yip, et al. (2023), Garrison et al. (2023), Yang et al. (2023), and Zhou et al. (2022) regarding networks predicting craving. The red, blue and grey lines were derived from the positive and negative networks observed in Antons, Yip, et al. (2023). Red lines – foremost positive connectivity, blue lines – foremost negative connectivity, grey line – both positive and negative connectivity
See this image and copyright information in PMC

References

    1. Antons, S., Brand, M., & Potenza, M. N. (2020). Neurobiology of cue-reactivity, craving, and inhibitory control in non-substance addictive behaviors. Journal of the Neurological Sciences, 415, 116952. 10.1016/j.jns.2020.116952. - DOI - PubMed
    1. Antons, S., Liebherr, M., Brand, M., & Brandtner, A. (2023). From game engagement to craving responses – The role of gratification and compensation experiences during video-gaming in casual and at-risk gamers. Addictive Behaviors Reports, 18, 100520. 10.1016/j.abrep.2023.100520. - DOI - PMC - PubMed
    1. Antons, S., Yip, S. W., Lacadie, C. M., Dadashkarimi, J., Scheinost, D., Brand, M., & Potenza, M. N. (2023). Connectome-based prediction of craving in gambling disorder and cocaine use disorder. Dialogues in Clinical Neuroscience, 25(1), 33–42. 10.1080/19585969.2023.2208586. - DOI - PMC - PubMed
    1. Brand, M. (2022). Can internet use become addictive? Science, 376(6595), 798–799. 10.1126/science.abn4189. - DOI - PubMed
    1. Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews, 104, 1–10. 10.1016/j.neubiorev.2019.06.032. - DOI - PubMed

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