Work

Distinct neural networks predict cocaine versus cannabis treatment outcomes

Year: 2023

Type: article

Source: Molecular Psychiatry

DOI: 10.1038/s41380-023-02120-0

Authors: Sarah D. Lichenstein, Robert Kohler, Fengdan Ye, Marc N. Potenza, Brian Kiluk, Sarah W. Yip

Institutions: Yale University, Connecticut Mental Health Center

Language: English

Topic: Substance Abuse Treatment and Outcomes

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: U.S. Department of Health and Human Services, Yale University, National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism, National Institute on Drug Abuse, National Center for Advancing Translational Sciences

Awards: G2363323382, G2589109566, Functional networks related to cocaine dependence and its treatment and relapse, G271712309, Connectome-based neuromarkers of problem cannabis use, G32622801, G3349644631, Psychotherapy Development Research Center, G4631260864, Neural mechanisms of CBT in cocaine dependence, Integrating Cognitive Neuroscience Toward Understanding of Mechanisms of CBT for Alcohol Use Disorders, fMRI of Craving in Addictions: Gender Differences, Development of the Opioid Use Disorder Severity Scale, Connectome-based prediction and neurodevelopmental trajectories of alcohol phenotypes across development, G6073970507, G749024168, fMRI of CBT and CM for Cocaine Dependence, Research Training Fellowship in Substance Abuse, Yale Clinical and Translational Science Award

OpenAlex ID: W4380324522

FWCI: 2.248

Cites: 42

Cited by: 12

Related to: 10