by S. Alagapan, S. Heisig, K Choi, P. Riva-Posse, A. Crowell, V. Tiruvadi, M. Obatusin, A. Veerakumar, A. Waters, R. Gross, S. Quinn, L. Denison, M. O’Shaughnessy, M. Connor, G. Canal, J. Cha, R. Hershenberg, T. Nauvel, F. Isbaine, M. Afzal, M. Figee, B. Kopell, R. Butera, H. Mayberg and C. Rozell
Abstract:
Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD). However, achieving stable recovery is unpredictable, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting. 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 novel 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 (LFP) available from six participants, we deployed an explainable artificial intelligence (xAI) approach to identify SCC LFP 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 behavioral) features of TRD pathology, motivating further research into causes of variability in depression treatment.
Reference:
Cingulate dynamics track depression recovery with deep brain stimulationS. Alagapan, S. Heisig, K Choi, P. Riva-Posse, A. Crowell, V. Tiruvadi, M. Obatusin, A. Veerakumar, A. Waters, R. Gross, S. Quinn, L. Denison, M. O’Shaughnessy, M. Connor, G. Canal, J. Cha, R. Hershenberg, T. Nauvel, F. Isbaine, M. Afzal, M. Figee, B. Kopell, R. Butera, H. Mayberg and C. Rozell. Nature, September 2023. Advanced Online Publication.
Bibtex Entry:
@article{alagapan.21,
author = {Alagapan, S. and Heisig, S. and Choi, K and Riva-Posse, P. and Crowell, A. and Tiruvadi, V. and Obatusin, M. and Veerakumar, A. and Waters, A. and Gross, R. and Quinn, S. and Denison, L. and O’Shaughnessy, M. and Connor, M. and Canal, G. and Cha, J. and Hershenberg, R. and Nauvel, T. and Isbaine, F. and Afzal, M. and Figee, M. and Kopell, B. and Butera, R. and Mayberg, H. and Rozell, C.},
title = {Cingulate dynamics track depression recovery with deep brain stimulation},
year = 2023,
journal = {Nature},
month = sep,
abstract = {Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD). However, achieving stable recovery is unpredictable, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting. 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 novel 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 (LFP) available from six participants, we deployed an explainable artificial intelligence (xAI) approach to identify SCC LFP 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 behavioral) features of TRD pathology, motivating further research into causes of variability in depression treatment.},
note = {Advanced Online Publication.},
url = {https://go.nature.com/48lmlzC}
}