Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jan;47(1):395-396.
doi: 10.1038/s41386-021-01124-0. Epub 2021 Aug 5.

Densely sampled neuroimaging for maximizing clinical insight in psychiatric and addiction disorders

Sarah W Yip  1 , Anna B Konova  2
Affiliations

Densely sampled neuroimaging for maximizing clinical insight in psychiatric and addiction disorders

Sarah W Yip et al. Neuropsychopharmacology. 2022 Jan.
No abstract available

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Prognosis-based classification of individuals based on the strength of their “abstinence network” over 6 months of treatment initiation.
Evolution of the strength of an individual’s abstinence network (set of functional brain connections predictive of lowered risk for future substance use [3, 4]) as captured by densely sampled neuroimaging data acquisition (~bi-weekly over 6 months). The example cases represent realistic trajectories: (1) healthy/control, shown to remain at moderate network strength over time; (2) sustained use, also shown to remain stable over time but at a low-abstinence network strength; (3) cycling use, shown to move away from an initial low-abstinence starting point and then start to return to it. Here we also highlight at what time points tailored treatment, such as additional psychosocial support or medication adjustment, might be most efficacious (i.e., when individuals might be most susceptible to intervention strategies) designated by the solid arrows; and (4) remitting use, also shown to change over time but in a single direction approaching health/high-abstinence network strength.
See this image and copyright information in PMC

References

    1. Konova AB, Lopez-Guzman S, Urmanche A, Ross S, Louie K, Rotrosen J, et al. Computational markers of risky decision-making for identification of temporal windows of vulnerability to opioid use in a real-world clinical setting. JAMA Psychiatry. 2020;77:368–77. doi: 10.1001/jamapsychiatry.2019.4013. - DOI - PMC - PubMed
    1. Gueguen CMM, Schweitzer E, Konova AB. Computational theory-driven studies of reinforcement learning and decision-making in addiction: what have we learned? Curr Opin Behav Sci. 2021;38:40–48. doi: 10.1016/j.cobeha.2020.08.007. - DOI - PMC - PubMed
    1. Yip SW, Scheinost D, Potenza MN, Carroll KM. Connectome-based prediction of cocaine abstinence. Am J Psychiatry. 2019;175:156–64. doi: 10.1176/appi.ajp.2018.17101147. - DOI - PMC - PubMed
    1. Lichenstein SD, Scheinost D, Potenza MN, Carroll KM, Yip SW. Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling. Mol Psychiatry. 2019. 10.1038/s41380-019-0586-y - PMC - PubMed
    1. Poldrack RA, Laumann TO, Koyejo O, Gregory B, Hover A, Chen MY, et al. Long-term neural and physiological phenotyping of a single human. Nat Commun. 2015;6:8885. doi: 10.1038/ncomms9885. - DOI - PMC - PubMed

Publication types

MeSH terms