Moment-to-moment brain signal variability reliably predicts psychiatric treatment outcome

Abstract

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 as harbingers of treatment success. Strikingly, temporal variability in brain signals has already proven a sensitive and reliable indicator of individual differences, but has not yet been examined in relation to psychiatric treatment outcomes. Here, 45 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. Reliability-based 5-fold cross-validation showed that 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. Rather than a source of undesirable noise , moment-to-moment fMRI variability may instead serve as a highly reliable and efficient prognostic indicator of clinical outcome.