Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient’s current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Negative emotion differentiation (NED) refers to the ability to identify and label discrete negative emotions. Low NED has been previously linked to depression and other indices of low psychological well-being. However, this construct has rarely been explored during adolescence, a time of escalating depression risk, or examined in the context of naturalistic stressors. Further, the association between NED and depression has never been tested longitudinally. We propose a diathesisstress model wherein low NED amplifies the association between stressful life events (SLEs) and depression. A sample of 233 community-recruited midadolescents (Mage = 15.90 years, 54% female) completed diagnostic interviews and reported on mood and daily stressors 4 times per day for 7 days. SLEs were assessed using a semistructured interview with diagnosis-blind team coding based on the contextual threat method. Follow-up interviews were conducted 1.5 years after baseline. Low NED was correlated with depression but did not predict prospective changes in depression as a main effect. Confirming predictions and supporting a diathesis-stress model, low NED predicted (a) within-subjects associations between daily hassles and momentary depressed mood, (b) betweensubjects associations between SLE severity and depression, and (c) prospective associations between SLE severity and increases in depression at follow-up. Results were specific to negative (vs. positive) emotion differentiation. Results suggest that low NED is primarily depressogenic in the context of high stress exposure.

Background: Calls to implement measurement-based care (MBC) in psychiatry are increasing. A recent Cochrane meta-analysis concluded that there is insufficient evidence that routine application of patient reported outcomes (PROs) improves treatment outcomes for common psychiatric disorders. There is a particular paucity of this information in patients with treatment resistant depression (TRD). Methods: A TRD sample (n = 302) and a treatment-naïve sample with major depression (n = 344) were assessed for the level of agreement in depression severity between two PROs (the Beck Depression Inventory, BDI, and the Quick Inventory of Depressive Symptomatology Self-report, QIDS-SR) and two Clinician Rated (CRs) measures (Hamilton Depression Rating Scale, HDRS, and the Montgomery-Asberg Depression Rating Scale, MADRS). Results: Correlations between CR and PRO total scores in the TRD sample ranged from 0.57 (HDRS-QIDS-SR) to 0.68 (MADRS-BDI), reflecting a moderate-to-strong relationship between assessment tools. Correlations in the treatment naïve sample were non-significantly lower for most comparisons, ranging from 0.51 (HDRS-QIDS-SR) to 0.64 (MADRS-BDI). Few predictors of discordance between CRs and PROs were identified, though chronicity of the current episode in treatment-naïve patients was associated with greater agreement. Limitations: Inter-rater reliability of the clinician interviews was conducted separately within the two studies so we could not determine the reliability between the two groups of raters used in the studies. Conclusion: Findings generally supported acceptably high levels of agreement between patient and clinician ratings of baseline depression severity. More work is needed to determine the extent to which PROs can improve outcomes in MBC for depression and, more specifically, TRD.

The American Psychological Association’s Society of Clinical Psychology recently adopted the “Tolin Criteria” to evaluate empirically supported treatments. These criteria better account for strength and quality of rapidly accumulating evidence bases for various treatments. Here we apply this framework to cognitive behavioral therapy for insomnia (CBT-I). Following procedures outlined by Tolin, McKay, et al. (2015), Step 1 included an examination of quantitative systematic reviews; nine met inclusion criteria. Step 2 evaluated review quality and effect size data. We found high-quality evidence that CBT-I produces clinically and statistically significant effects on insomnia and other sleep-related outcomes. Based on the Tolin Criteria, the literature merits a “strong” recommendation for CBT-I. This report is a working model for subsequent applications of the Tolin Criteria.