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1.
Nature ; 622(7981): 130-138, 2023 Oct.
Article in English | MEDLINE | ID: mdl-37730990

ABSTRACT

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.


Subject(s)
Deep Brain Stimulation , Depression , Depressive Disorder, Major , Humans , Artificial Intelligence , Biomarkers , Deep Brain Stimulation/methods , Depression/physiopathology , Depression/therapy , Depressive Disorder, Major/physiopathology , Depressive Disorder, Major/therapy , Electrophysiology , Treatment Outcome , Local Field Potential Measurement , White Matter , Limbic Lobe/physiology , Limbic Lobe/physiopathology , Facial Expression
2.
bioRxiv ; 2023 Dec 20.
Article in English | MEDLINE | ID: mdl-38187733

ABSTRACT

Background: A critical advance in depression research is to clarify the hypothesized role of interoceptive processing in neural mechanisms of treatment efficacy. This study tests whether cortical interoceptive processing, as indexed by the heartbeat-evoked potential (HEP), is modulated by deep brain stimulation (DBS) to the subcallosal cingulate (SCC) for treatment resistant depression (TRD). Methods: Eight patients with TRD were enrolled in a study of SCC DBS safety and efficacy. Electroencephalography (EEG) and symptom severity measures were sampled in a laboratory setting over the course of a six-month treatment protocol. The primary outcome measure was an EEG-derived HEP, which reflects cortical processing of heartbeat sensation. Cluster-based permutation analyses were used to test the effect of stimulation and time in treatment on the HEP. The change in signal magnitude after treatment was correlated with change in depression severity as measured by the 17-item Hamilton Depression Rating Scale. Results: HEP amplitude was greater after 24 weeks of treatment ( t (7)=-4.40, p =.003, g= -1.38, 95% Cl [-2.3, -0.42]), and this change was inversely correlated with latency of treatment response (rho = -0.75, 95% Cl [-0.95, -0.11], p= .03). An acute effect of DBS was also observed, but as a decrease in HEP amplitude ( t (6) =6.66, p <.001, g= 2.19, 95% Cl [0.81, 3.54]). HEP differences were most pronounced over left posterior sensors from 405-425 ms post-stimulus. Conclusion: Brain-based evidence substantiates a theorized link between interoception and depression, and suggests an interoceptive contribution to the mechanism of treatment efficacy with deep brain stimulation for severe depression.

4.
Curr Opin Neurobiol ; 25: 7-14, 2014 Apr.
Article in English | MEDLINE | ID: mdl-24709594

ABSTRACT

Brain injury profoundly affects global brain dynamics, and these changes are manifest in the electroencephalogram (EEG). Despite the heterogeneity of injury mechanisms and the modularity of brain function, there is a commonality of dynamical features that characterize the EEG along the gamut from coma to recovery. After severest injury, EEG activity is concentrated below 1 Hz. In minimally conscious state during wakefulness, there is a peak of activity in the 3-7 Hz range, often coherent across the brain, and often also activity in the beta (15-30 Hz) range. These spectral changes likely result from varying degrees of functional deafferentation at thalamic and cortical levels. EEG-based indices of brain dynamics that go beyond these simple spectral measures may provide further diagnostic information and physiologic insights.


Subject(s)
Brain Injuries/physiopathology , Brain Waves/physiology , Brain/physiopathology , Consciousness Disorders/physiopathology , Models, Neurological , Humans
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