Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2018 Feb 27;115(9):2222-2227. doi: 10.1073/pnas.1716686115. Epub 2018 Feb 12.

Multivariate resting-state functional connectivity predicts response to cognitive behavioral therapy in obsessive-compulsive disorder.

Author information

1
Department of Psychology, University of California, Los Angeles, CA 90095; nreggente@psych.ucla.edu.
2
Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at University of California, Los Angeles, CA 90095.
3
Department of Psychology, University of California, Los Angeles, CA 90095.
4
Division of Child and Adolescent Psychiatry, David Geffen School of Medicine at University of California, Los Angeles, CA 90095.

Abstract

Cognitive behavioral therapy (CBT) is an effective treatment for many with obsessive-compulsive disorder (OCD). However, response varies considerably among individuals. Attaining a means to predict an individual's potential response would permit clinicians to more prudently allocate resources for this often stressful and time-consuming treatment. We collected resting-state functional magnetic resonance imaging from adults with OCD before and after 4 weeks of intensive daily CBT. We leveraged machine learning with cross-validation to assess the power of functional connectivity (FC) patterns to predict individual posttreatment OCD symptom severity. Pretreatment FC patterns within the default mode network and visual network significantly predicted posttreatment OCD severity, explaining up to 67% of the variance. These networks were stronger predictors than pretreatment clinical scores. Results have clinical implications for developing personalized medicine approaches to identifying individual OCD patients who will maximally benefit from intensive CBT.

TRIAL REGISTRATION:

ClinicalTrials.gov NCT01368510.

KEYWORDS:

CBT; OCD; functional connectivity; machine learning; resting state

PMID:
29440404
PMCID:
PMC5834692
DOI:
10.1073/pnas.1716686115
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center