P131. Moment-To-Moment Brain Signal Variability Reliably Predicts Psychiatric Treatment Outcome

Background: Månsson et al., Biological Psychiatry, In press: Biomarkers of psychiatric treatment response remain elusive. Functional magnetic resonance imaging (fMRI) has shown promise, but low reliability has limited the utility of typical fMRI measures (e.g., average brain signal) as harbingers of treatment success. Notably, although historically considered a source of “noise,” temporal brain signal variability continues to gain momentum as a sensitive and reliable indicator of individual differences in neural efficacy, yet has not been examined in relation to psychiatric treatment outcomes. Methods: Forty-five patients with social anxiety disorder were scanned twice (11 weeks apart) using simple task-based and resting-state fMRI to capture moment-to-moment neural variability. After fMRI test-retest, patients underwent a 9-week cognitive-behavioral therapy. Multivariate modeling and reliability-based cross-validation were utilized to perform brain-based prediction of treatment outcomes. Results: Task-based brain signal variability was the strongest contributor in a treatment outcome prediction model (total r[ACTUAL,PREDICTED]=.77) - outperforming self-reports, resting-state neural variability, and standard mean-based measures of neural activity. Notably, task-based brain signal variability showed excellent test-retest reliability (intraclass correlation coefficient=.80), even with a task length less than 3 minutes long. Conclusions: Rather than a source of undesirable “noise”, moment-to-moment fMRI signal variability may instead serve as a highly reliable and efficient prognostic indicator of clinical outcome.