Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation
Open accessAbstract
Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is a promising intervention for treatment-resistant depression (TRD). Despite the failure of a clinical trial, multiple case series have described encouraging results, especially with the introduction of improved surgical protocols. Recent evidence further suggests that tractography targeting and intraoperative exposure to stimulation enhances early antidepressant effects that further evolve with ongoing chronic DBS. Accelerating treatment gains is critical to the care of this at-risk population, and identification of intraoperative electrophysiological biomarkers of early antidepressant effects will help guide future treatment protocols. Eight patients underwent intraoperative electrophysiological recording when bilateral DBS leads were implanted in the SCC using a connectomic approach at the site previously shown to optimize 6-month treatment outcomes. A machine learning classification method was used to discriminate between intracranial local field potentials (LFPs) recorded at baseline (stimulation-naïve) and after the first exposure to SCC DBS during surgical procedures. Spectral inputs (theta, 4-8 Hz; alpha, 9-12 Hz; beta, 13-30 Hz) to the model were then evaluated for importance to classifier success and tested as predictors of the antidepressant response. A decline in depression scores by 45.6% was observed after 1 week and this early antidepressant response correlated with a decrease in SCC LFP beta power, which most contributed to classifier success. Intraoperative exposure to therapeutic stimulation may result in an acute decrease in symptoms of depression following SCC DBS surgery. The correlation of symptom improvement with an intraoperative reduction in SCC beta power suggests this electrophysiological finding as a biomarker for treatment optimization.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
For SCC DBS, consistent tractography-based targeting of a site structurally connected to the forceps minor, uncinate fasciculus, cingulum bundle, and frontostriatal fibers was associated with an 88% response rate.
“For SCC DBS, consistent tractographybased targeting of a site in the SCC region structurally connected to the forceps minor, uncinate fasciculus, cingulum bundle, and frontostriatal fibers was associated with an 88% response rate [88]”
From Deep brain stimulation for depression. (2022) · cites this paper as [88]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482 · see citing works
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817 · cited 8× · see citing works
“Intraoperative change in SCC beta power predicts early antidepressant response Figure 1C shows symptom severity scores using the Hamilton Depression Rating Scale (HDRS-17) averaged 4 weeks before and a week after OR stimulation.”
MethodInfluentialRegularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957 · see citing works
Beta-band oscillations—Signalling the status quo?
Engel, A. K., & Fries, P. (2010) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2010.02.015 · Cited by 2,953 · see citing works
Feature selection in machine learning: A new perspective
Cai, J., Luo, J., Wang, S., & Yang, S. (2018) · Neurocomputing · doi:10.1016/j.neucom.2017.11.077 · Cited by 2,107 · see citing works
Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Unipolar and Bipolar Depression
Holtzheimer, P. E. (2012) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.1456 · Cited by 608 · see citing works
Holtzheimer, P. E., Husain, M. M., Lisanby, S. H., Taylor, S. F., Whitworth, L. A., McClintock, S., Slavin, K. V., Berman, J., McKhann, G. M., Patil, P. G., et al. (2017) · The Lancet Psychiatry · doi:10.1016/s2215-0366(17)30371-1 · Cited by 577 · see citing works
Self-citationDeep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years
Kennedy, S. H., Giacobbe, P., Rizvi, S. J., Placenza, F. M., Nishikawa, Y., Mayberg, H. S., & Lozano, A. M. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.10081187 · Cited by 481 · see citing works
Riva-Posse, P., Choi, K. S., Holtzheimer, P. E., Crowell, A. L., Garlow, S. J., Rajendra, J. K., McIntyre, C. C., Gross, R. E., & Mayberg, H. S. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.59 · Cited by 441 · see citing works
Self-citationThe functional role of beta oscillations in Parkinson's disease
Little, S. J., & Brown, P. (2013) · Parkinsonism & Related Disorders · doi:10.1016/s1353-8020(13)70013-0 · Cited by 422 · see citing works
Olbrich, S., & Arns, M. (2013) · International Review of Psychiatry · doi:10.3109/09540261.2013.816269 · Cited by 371 · see citing works
Deep Brain Stimulation for Treatment-Resistant Depression: Follow-Up After 3 to 6Years
Ballenger, J. C. (2012) · Yearbook of Psychiatry and Applied Mental Health · doi:10.1016/j.ypsy.2011.08.041 · Cited by 365 · see citing works
Nested cross-validation when selecting classifiers is overzealous for most practical applications
Wainer, J., & Cawley, G. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115222 · Cited by 309 · see citing works
Puigdemont, D., Pérez‐Egea, R., Portella, M. J., Molet, J., de Diego-Adeliño, J., Gironell, A., Raduà, J., Gómez‐Ansón, B., Rodríguez, R. R., Serra-Blasco, M., et al. (2011) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145711001088 · Cited by 235 · see citing works
Beta oscillations in freely moving Parkinson's subjects are attenuated during deep brain stimulation
Quinn, E. J., Blumenfeld, Z., Velisar, A., Koop, M. M., Shreve, L., Trager, M. H., Hill, B. C., Kilbane, C., Henderson, J. M., & Bronte-Stewart, H. M. (2015) · Movement Disorders · doi:10.1002/mds.26376 · Cited by 227 · see citing works
Crowell, A. L., Riva‐Posse, P., Holtzheimer, P. E., Garlow, S. J., Kelley, M. E., Gross, R. E., Denison, L., Quinn, S., & Mayberg, H. S. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.18121427 · Cited by 185 · see citing works
Self-citationAdaptive deep brain stimulation in Parkinson's disease
Beudel, M., & Brown, P. (2015) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2015.09.028 · Cited by 165 · see citing works
Choi, K. S., Riva‐Posse, P., Gross, R. E., & Mayberg, H. S. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2015.2564 · Cited by 133 · see citing works
Self-citationNeumann, W., Huebl, J., Brücke, C., Gabriëls, L. A., Bajbouj, M., Merkl, A., Schneider, G.-H., Nuttin, B., Brown, P., & Kühn, A. A. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.2 · Cited by 115 · see citing works
Merkl, A., Schneider, G., Schönecker, T., Aust, S., Kühl, K.-P., Kupsch, A. R., Kühn, A. A., & Bajbouj, M. (2013) · Experimental Neurology · doi:10.1016/j.expneurol.2013.08.017 · Cited by 114 · see citing works
Merkl, A., Aust, S., Schneider, G., Visser-Vandewalle, V. E. R. M., Horn, A., Kühn, A. A., Kuhn, J., & Bajbouj, M. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.11.024 · Cited by 86 · see citing works
Ramasubbu, R., Clark, D. L., Golding, S., Dobson, K. S., Mackie, A., Haffenden, A., & Kiss, Z. H. (2020) · The Lancet Psychiatry · doi:10.1016/s2215-0366(19)30415-8 · Cited by 80 · see citing works
EEG beta and low gamma power correlates with inattention in patients with major depressive disorder
Roh, S.-C., Park, E. J., Shim, M., & Lee, S. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.06.033 · Cited by 76 · see citing works
Adaptive DBS in a Parkinson's patient with chronically implanted DBS: A proof of principle
Piña‐Fuentes, D., Little, S. J., Oterdoom, M., Neal, S., Pogosyan, A. H., Tijssen, M. A. J., van Laar, T., Brown, P., van Dijk, J. M. C., & Beudel, M. (2017) · Movement Disorders · doi:10.1002/mds.26959 · Cited by 76 · see citing works
Merkl, A., Neumann, W., Huebl, J., Aust, S., Horn, A., Krauss, J. K., Dziobek, I., Kuhn, J., Schneider, G., Bajbouj, M., et al. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv100 · Cited by 60 · see citing works
Huebl, J., Brücke, C., Merkl, A., Bajbouj, M., Schneider, G., & Kühn, A. A. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw038 · Cited by 42 · see citing works
Smart, O., Choi, K. S., Riva-Posse, P., Tiruvadi, V., Rajendra, J., Waters, A. C., Crowell, A. L., Edwards, J., Gross, R. E., & Mayberg, H. S. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00043 · Cited by 41 · see citing works
Self-citationClark, D., Brown, E. C., Ramasubbu, R., & Kiss, Z. H. T. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.02.032 · Cited by 40 · see citing works
Effects of Firing Variability on Network Structures with Spike-Timing-Dependent Plasticity
Min, B., Zhou, D., & Cai, D. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00001 · Cited by 38 · see citing works
Rapid Antidepressant Effects of Deep Brain Stimulation and Their Relation to Surgical Protocol
Riva-Posse, P., Crowell, A. L., Wright, K., Waters, A. C., Choi, K., Garlow, S. J., Holtzheimer, P. E., Gross, R. E., & Mayberg, H. S. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.03.017 · Cited by 32 · see citing works
Self-citationWozny, T. A., Wang, D. D., & Starr, P. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116904 · Cited by 16 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Deep brain stimulation for depression.
Figee, M., Riva-Posse, P., Choi, K. S., Bederson, L., Mayberg, H. S., & Kopell, B. H. (2022) · Neurotherapeutics · doi:10.1007/s13311-022-01270-3 · Cited by 175 · see citing works
Self-citation
- Authors
- Sendi, M. S. E., Waters, A. C., Tiruvadi, V., Riva-Posse, P., Crowell, A., Isbaine, F., Gale, J. T., Choi, K. S., Gross, R. E., S. Mayberg, H., & Mahmoudi, B.
- Affiliations
- Georgia Institute of Technology (US)
- Icahn School of Medicine at Mount Sinai (US)
- Emory University (US)
- ORCID
- Venue
- Translational Psychiatry
- Published
- 2021-11-03
- Volume
- 11
- Issue
- 1
- Pages
- 551-551
- ISSN
- 2158-3188 (ISSN-L)
- PMC
- PMC8563808
- OpenAlex
- W3208889148
- Cited by
- 64
- References
- 32
- Citations by year
- 2026: 15 · 2025: 12 · 2024: 14 · 2023: 13 · 2022: 7 · 2021: 3
- FWCI
- 4.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Translational Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (5ug3ns100559-02)
- National Institute of Mental Health (R24MH114796, R01MH106173, R01MH102238)
- National Institute of General Medical Sciences (T32GM008169)
- National Institute of Neurological Disorders and Stroke (UH3NS103550, UG3-NS100559)
- National Institute of Biomedical Imaging and Bioengineering (R01EB028350)
- Topics
- Health Sciences › Medicine › Neurology › Neurological disorders and treatments
- Social Sciences › Psychology › Clinical Psychology › Obsessive-Compulsive Spectrum Disorders
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- deep brain stimulation, subcallosal cingulate, treatment-resistant depression, beta power, electrophysiological markers, antidepressant response prediction, connectomics, machine learning classification
- MeSH terms
- Antidepressive Agents, Gyrus Cinguli, Humans, Treatment Outcome, Deep Brain Stimulation, Depressive Disorder, Treatment-Resistant
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
