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AJP CME: February 2019 - Connectome-Based Prediction of Cocaine Abstinence

Activity Type:

  • Journal CME

Release Date: 2/1/2019

Expiration Date: 1/31/2021

  • AMA PRA Category 1: 1
  • Participation: 1



Objective: The authors sought to identify a brain-based predictor of cocaine abstinence by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. CPM is a predictive tool and a method of identifying networks that underlie specific behaviors (“neural fingerprints”).

Methods: Fifty-three individuals participated in neuroimaging protocols at the start of treatment for cocaine use disorder, and again at the end of 12 weeks of treatment. CPM with leave-one-out cross-validation was conducted to identify pretreatment networks that predicted abstinence (percent cocaine-negative urine samples during treatment). Networks were applied to posttreatment functional MRI data to assess changes over time and ability to predict abstinence during follow-up. The predictive ability of identified networks was then tested in a separate, heterogeneous sample of individuals who underwent scanning before treatment for cocaine use disorder (N=45).


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Educational Objective

The participant will illustrate how a recently developed machine learning method may be used to identify brain networks that predict treatment outcomes in cocaine use disorder.

Target Audience

This program is designed for all psychiatrists in clinical practice, residents in Graduate Medical Education programs, medical students interested in psychiatry, and other physicians who wish to advance their current knowledge of clinical medicine.

Estimated Time to Complete

Duration: 1 hour
Begin Date: February 1, 2019
End Date: January 31, 2021

How to Earn Credit

In order to earn CME credit, subscribers should read through the material presented in the article. After reading the article, complete the quiz and submit your evaluation and study hours (up to 1 AMA PRA Category 1 Credit™).  A score of 60% or higher is required to receive credit.

Continuing Education Credit

The American Psychiatric Association (APA) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

The APA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Faculty and Planner Disclosures

Title: Connectome-Based Prediction of Cocaine Abstinence

Authors: Sarah W. Yip, Ph.D., M.Sc., Dustin Scheinost, Ph.D., Marc N. Potenza, M.D., Ph.D., Kathleen M. Carroll, Ph.D.

Affiliations: The Department of Psychiatry (S.W.Y., M.N.P., K.M.C.), the Child Study Center (S.W.Y., D.S., M.N.P.), the Department of Radiology and Biomedical Imaging (D.S.), and the Department of Neuroscience (M.N.P.), Yale School of Medicine, New Haven, Conn.; and the Connecticut Mental Health Center, New Haven, Conn. (M.N.P.).

Disclosures: Dr. Potenza has served as consultant or adviser for Ironwood, INSYS, Jazz Pharmaceuticals, Lundbeck, Opiant/Lakelight Therapeutics, RiverMend Health, and Shire and has served as a consultant for legal and gambling entities on issues related to impulse control disorders; he has received unrestricted research support from Mohegan Sun Casino and grant support from the National Center for Responsible Gaming and Pfizer; he has edited journals and journal sections and has given academic lectures in grand rounds, CME events, and other clinical or scientific venues; and he has generated books or book chapters for publishers of mental health texts. Dr. Carroll is a member of CBT4CBT LLC, which makes CBT4CBT available to qualified clinical providers and organizations on a commercial basis; she works with Yale University to manage any potential conflicts of interest. The other authors report no financial relationships with commercial interests.

Discussion of unapproved or investigational use of products*: No.

*APA policy requires disclosure by CME authors of unapproved or investigational use of products discussed in CME programs. Off-label use of medications by individual physicians is permitted and common. Decisions about off-label use can be guided by scientific literature and clinical experience.

Program Planners

Ned H. Kalin, M.D. (Editor-in-Chief, AJP); Michael D. Roy (Editorial Director, AJP); Michael A. Pogachar (Online Content Manager, Journals).

Dr. Kalin has received research support from NIH and NIMH; has served as a consultant for APA, CME Outfitters, the Pritzker Neuropsychiatric Disorders Research Consortium, the Skyland Trail Advisory Board, and TC MSO; owns stock in Celgene and Seattle Genetics; and received honoraria from Elsevier as co-editor of the journal Psychoneuroendocrinology. Mr. Roy and Mr. Pogachar report no financial relationships with commercial interests.

Hardware/Software Requirements

This internet-based CME activity is best experienced using Internet Explorer 8+, Mozilla Firefox 3+, Safari 4+. This Web site requires that JavaScript and session cookies be enabled. Certain activities may require additional software to view multimedia, presentation, or printable versions of the content. These activities will be marked as such and will provide links to the required software. That software may be: Adobe Flash, Adobe Acrobat, Microsoft PowerPoint, and Windows Media Player.
Optimal System Configuration:
  • Flash Player: Adobe Flash Player 10.1+ 
  • Browser: Firefox 3+, Internet Explorer 8.0+, Safari 4.0+, or Google Chrome 7.0+ 
  • Operating System: Windows XP+ or Mac OS X 10.4+ 
  • Internet Connection: 1 Mbps or higher
  • Screen Resolution: 1024 x 768 pixels.

Minimum Requirements:

  • Windows PC:500-MHz Pentium II; Windows XP or higher; 128 MB RAM; Video Card at least 64MB of video memory; Sound Card at least 16-bit; Macromedia Flash Player 10 or higher, audio playback with speakers for programs with video content; Firefox 1.1+, Internet Explorer 7.0+, Safari 1.0+, Google Chrome, or Opera
  • Macintosh: Mac OS X 10.3 or higher with latest updates installed; 1.83MHz Intel Core Duo or faster; RAM: 128MB or more; Video Card: at least 64MB of video memory; Sound Card: at least 16-bit

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