Commentary| Volume 8, ISSUE 3, P238-240, March 2023

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Deriving Generalizable and Interpretable Brain-Behavior Phenotypes of Cannabis Use

      With recent changes in drug legislation in the United States, more people than ever are initiating cannabis use. Although the potential health benefits of cannabis are beginning to be recognized, a growing and sizable number of people who use cannabis do so chronically, and a third develop cannabis use disorder. The high prevalence of chronic cannabis use and cannabis use disorder poses a significant burden on personal and public health. The number of people seeking treatment for cannabis use is among the highest of any substance use disorder, as are the rates of co-occurring mental health concerns, including mood and psychotic disorders (
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      ). As the availability and potency of cannabis continue to rise, there is an urgent need to improve our understanding and prediction of the critical transition to chronic and disordered cannabis use.
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      Linked Article

      • An Interpretable and Predictive Connectivity-Based Neural Signature for Chronic Cannabis Use
        Biological Psychiatry: Cognitive Neuroscience and NeuroimagingVol. 8Issue 3
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          Cannabis is one of the most widely used substances in the world, with usage trending upward in recent years. However, although the psychiatric burden associated with maladaptive cannabis use has been well established, reliable and interpretable biomarkers associated with chronic use remain elusive. In this study, we combine large-scale functional magnetic resonance imaging with machine learning and network analysis and develop an interpretable decoding model that offers both accurate prediction and novel insights into chronic cannabis use.
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