Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Brain metabolic changes and clinical response to superolateral medial forebrain bundle deep brain stimulation for treatment-resistant depression

Abstract

Deep brain stimulation (DBS) to the superolateral branch of the medial forebrain bundle is an efficacious therapy for treatment-resistant depression, providing rapid antidepressant effects. In this study, we use 18F-fluorodeoxyglucose-positron emission tomography (PET) to identify brain metabolic changes over 12 months post-DBS implantation in ten of our patients, compared to baseline. The primary outcome measure was a 50% reduction in Montgomery–Åsberg Depression Rating Scale (MADRS) score, which was interpreted as a response. Deterministic fiber tracking was used to individually map the target area; probabilistic tractography was used to identify modulated fiber tracts modeled using the cathodal contacts. Eight of the ten patients included in this study were responders. PET imaging revealed significant decreases in bilateral caudate, mediodorsal thalamus, and dorsal anterior cingulate cortex metabolism that was evident at 6 months and continued to 12 months post surgery. At 12 months post-surgery, significant left ventral prefrontal cortical metabolic decreases were also observed. Right caudate metabolic decrease at 12 months was significantly correlated with mean MADRS reduction. Probabilistic tractography modeling revealed that such metabolic changes lay along cortico-limbic nodes structurally connected to the DBS target site. Such observed metabolic changes following DBS correlated with clinical response provide insights into how future studies can elaborate such data to create biomarkers to predict response, the development of which likely will require multimodal imaging analysis.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Group probabilistic DTI analysis.
Fig. 2: Group PET analysis at 6- and 12-month follow-up.
Fig. 3: Average PET changes in the caudate nuclei and MADRS scores for all subjects.

Similar content being viewed by others

References

  1. Rush AJ, Trivedi MH, Stewart JW, Nierenberg AA, Fava M, Kurian BT, et al. Combining medications to enhance depression outcomes (CO-MED): acute and long-term outcomes of a single-blind randomized study. Am J Psychiatry. 2011;168:689–701.

    PubMed  Google Scholar 

  2. Nemeroff CB. Prevalence and management of treatment-resistant depression. J Clin Psychiatry. 2007;68(Suppl 8):17–25.

    CAS  PubMed  Google Scholar 

  3. Berlim MT, Turecki G. Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Can J Psychiatry. 2007;52:46–54.

    PubMed  Google Scholar 

  4. Lozano AM, Mayberg HS, Giacobbe P, Hamani C, Craddock RC, Kennedy SH. Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2008;64:461–7.

    PubMed  Google Scholar 

  5. Holtzheimer PE, Kelley ME, Gross RE, Filkowski MM, Garlow SJ, Barrocas A, et al. Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression. Arch Gen Psychiatry. 2012;69:150–8.

    PubMed  PubMed Central  Google Scholar 

  6. Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Hamani C, et al. Deep brain stimulation for treatment-resistant depression. Neuron 2005;45:651–60.

    CAS  PubMed  Google Scholar 

  7. Holtzheimer PE, Husain MM, Lisanby SH, Taylor SF, Whitworth LA, McClintock S, et al. Subcallosal cingulate deep brain stimulation for treatment-resistant depression: a multisite, randomised, sham-controlled trial. Lancet Psychiatry. 2017;4:839–49.

    PubMed  Google Scholar 

  8. Maloney DA Jr, Dougherty DD, Rezai AR, Carpenter LL, Friehs GM, Eskander EN, et al. Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biol Psychiatry. 2009;65:267–75.

    Google Scholar 

  9. Dougherty DD, Rezai AR, Carpenter LL, Howland RH, Bhati MT, O’Rearson JP, et al. A randomized sham-controlled trial of deep brain stimulation of the ventral capsule/ventral striatum for chronic treatment-resistant depression. Biol Psychiatry. 2015;78:240–8.

    PubMed  Google Scholar 

  10. Bergfeld IO, Mantione M, Hoogendoorn MLC, Ruhe HG, Notten P, van Laarhoven J, et al. Deep brain stimulation of the ventral anterior limb of the internal capsule for treatment-resistant depression: a randomized clinical trial. JAMA Psychiatry. 2016;73:456–64.

    PubMed  Google Scholar 

  11. Bewernick BH, Kayser S, Sturm V, Schlaepfer TE. Long-term effects of nucleus accumbens deep brain stimulation in treatment-resistant depression: evidence for sustained efficacy. Neuropsychopharmacology. 2012;37:1975–85.

  12. Bewernick BH, Hurlemann R, Matusch A, Kayser S, Grubert C, Hadrysiewicz B, et al. Nucleus accumbens deep brain stimulation decreases ratings of depression and anxiety in treatment-resistant depression. Biol Psychiatry. 2010;67:110–6.

    PubMed  Google Scholar 

  13. Schlaepfer TE, Bewernick BH, Kayser S, Madler B, Coenen VA. Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73:1204–12.

    PubMed  Google Scholar 

  14. Bewernick BH, Kayser S, Gippert SM, Switala C, Coenen VA, Schlaepfer TE. Deep brain stimulation to the medial forebrain bundle for depression- long-term outcomes and a novel data analysis strategy. Brain Stimul. 2017;10:664–71.

    PubMed  Google Scholar 

  15. Coenen VA, Bewernick BH, Kayser S, Kilian H, Boström J, Greschus S, et al. Superolateral medial forebrain bundle deep brain stimulation in major depression: a gateway trial. Neuropsychopharm 2019;44:1224–32.

    Google Scholar 

  16. Fenoy AJ, Schulz PE, Selvaraj S, Burrows CL, Spiker D, Cao B, et al. Deep brain stimulation of the medial forebrain bundle: distinctive responses in resistant depression. J Affect Disord. 2016;203:143–51.

    PubMed  Google Scholar 

  17. Fenoy AJ, Schulz PE, Selvaraj S, Burrows CL, Zunta-Soares G, Durkin K, et al. A longitudinal study on deep brain stimulation of the medial forebrain bundle for treatment-resistant depression. Transl Psychiatry. 2018;8:111–8.

    PubMed  PubMed Central  Google Scholar 

  18. Fenoy AJ, Schulz PE, Sanches M, Selvaraj S, Burrows CL, Asir B, et al. Deep brain stimulation of the ‘medial forebrain bundle’: sustained efficacy of antidepressant effect over years. Mol Psychiatry. 2022;27:2546–53. https://doi.org/10.1038/s41380-022-01504-y.

  19. Gálvez JF, Keser Z, Mwangi B, Ghouse A, Fenoy AJ, Schulz PE, et al. The medial forebrain bundle as a deep brain stimulation target for treatment resistant depression: a review of published data. Prog Neuropsychopharmacol Biol Psychiatry. 2015;58:59–70.

    PubMed  Google Scholar 

  20. Nestler EJ, Carlezon WA Jr. The mesolimbic dopamine reward circuit in depression. Biol Psychiatry. 2006;59:1151–9.

    CAS  PubMed  Google Scholar 

  21. Russo SJ, Nestler EJ. The brain reward circuitry in mood disorders. Nat Rev Neurosci. 2013;14:609–25.

    CAS  PubMed  Google Scholar 

  22. Fenoy AJ, Quevedo J, Soares JC. Deep brain stimulation of the ‘medial forebrain bundle’: a strategy to modulate the reward system and manage treatment-resistant depression. Mol Psychiatry. 2022;27:574–92. https://doi.org/10.1038/s41380-021-01100-6.

  23. Elias GJB, Germann J, Boutet A, Pancholi A, Beyn ME, Bhatia K, et al. Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression. Brain 2022;145:362–77.

    PubMed  Google Scholar 

  24. Brown EC, Clark DL, Forkert ND, Molnar CP, Kiss ZHT, Ramasubbu R. Metabolic activity in subcallosal cingulate predicts response to deep brain stimulation for depression. Neuropsychopharm 2020;45:1681–8.

    CAS  Google Scholar 

  25. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured clinical interview for DSM-IV axis I disorders (SCID I). Washington DC: American Psychiatric Press; 1997.

  26. Fenoy AJ, Simpson RK Jr. Management of device-related wound complications in deep brain stimulation surgery. J Neurosurg. 2012;11:1324–32.

    Google Scholar 

  27. Fenoy AJ, Simpson RK Jr. Risks of common complications in deep brain stimulation surgery: management and avoidance. J Neurosurg. 2014;120:132–9.

    PubMed  Google Scholar 

  28. Coenen VA, Panksepp J, Hurwitz TA, Urbach H, Mädler B. Human medial forebrain bundle (MFB) and anterior thalamic radiation (ATR): imaging of two major subcortical pathways and the dynamic balance of opposite affects in understanding depression. J Neuropsychiatry Clin Neurosci. 2012;24:223–36.

    PubMed  Google Scholar 

  29. Suetens K, Nuttin B, Gabriëls L, Van, Laere K. Differences in metabolic network modulation between capsulotomy and deep-brain stimulation for refractory obsessive-compulsive disorder. J Nucl Med. 2014;55:951–9.

    PubMed  Google Scholar 

  30. Borghammer P, Jonsdottir KY, Cumming P, Ostergaard K, Vang K, Ashkanian M, et al. Normalization of PET group comparison studies – the importance of a valid reference region. NeuroImage 2008;40:529–40.

    PubMed  Google Scholar 

  31. Aihara M, Ida I, Yuuki N, Oshima A, Kumano H, Takahashi K, et al. HPA axis dysfunction in unmedicated major depressive disorder and its normalization by pharmacotherapy correlates with alteration of neural activity in prefrontal cortex and limbic/paralimbic regions. Psychiatry Res. 2007;155:245–56.

    CAS  PubMed  Google Scholar 

  32. Van Laere K, Vanhee A, Verschueren J, De Coster L, Driesen A, Dupont P, et al. Value of 18 Fluorodeoxyglucose-positron emission tomography in amyotrophic lateral sclerosis – a prospective study. JAMA Neurol. 2014;71:553–61.

    PubMed  Google Scholar 

  33. Cox RW. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res. 1996;29:162–73.

    CAS  PubMed  Google Scholar 

  34. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968–80.

    PubMed  Google Scholar 

  35. Behrens TE, Woolrich MW, Jenkinson M, Johansen-Berg H, Nunes RG, Clare S, et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50:1077–88.

    CAS  PubMed  Google Scholar 

  36. Woolrich MW, Jbabdi S, Patenaude B, Chappell M, Makni S, Behrens T, et al. Bayesian analysis of neuroimaging data in FSL. Neuroimage 2009;45(1 Suppl):S173–86.

    PubMed  Google Scholar 

  37. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143–55.

    PubMed  PubMed Central  Google Scholar 

  38. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. FSL. Neuroimage 2012;62:782–90.

    PubMed  Google Scholar 

  39. Behrens TE, Berg HJ, Jbabdi S, Rushworth MF, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? Neuroimage 2007;34:144–55.

    CAS  PubMed  Google Scholar 

  40. Butson CR, Cooper SE, Henderson JM, McIntyre CC. Patient-specific analysis of the volume of tissue activated during deep brain stimulation. Neuroimage 2007;34:661–70.

    PubMed  Google Scholar 

  41. Drevets WC, Price JL, Simpson JR, Todd RD, Reich T, Vannier M, et al. Subgenual prefrontalcortex abnormalities in mood disorders. Nature. 1997;386:824–7.

  42. Mayberg HS, Liotti M, Brannan SK, McGinnis S, Mahurin RK, Jerabek PA, et al. Reciprocal limbic–cortical function and negative mood: Converging PET findings in depression and normal sadness. Am J Psychiatry. 1999;156:675–82.

  43. Rao VR, Sellers KK, Wallace DL, Lee MB, Bijanzadeh M, Sani OG, et al. Direct electrical stimulation of the lateral orbitofronral cortex acutely improves mood in individuals with symptoms of depression. Curr Biol. 2018;28:3893–902.

    CAS  PubMed  Google Scholar 

  44. Fettes P, Peters S, Giacobbe P, Blumberger DM, Downar J. Neural correlates of successful orbitofrontal 1 Hz rTMS following unsuccessful dorsolateral and dorsomedial prefrontal rTMS in major depression: a case report. Brain Stimul. 2017;10:165–7.

    PubMed  Google Scholar 

  45. Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017;23:28–38.

    CAS  PubMed  Google Scholar 

  46. Coenen VA, Schlaepfer TE, Bewernick B, Kilian H, Kaller CP, Urbach H, et al. Frontal white matter architecture predicts efficacy of deep brain stimulation in major depression. Transl Psychiatry. 2019;9:197.

    PubMed  PubMed Central  Google Scholar 

  47. Schlaepfer TE, Cohen MX, Frick C, Kosel M, Brodesser D, Axmacher N, et al. Deep brain stimulation to reward circuitry alleviates anhedonia in refractory major depression. Neuropsychopharmacology 2008;33:368–77.

  48. Zuo C, Ma Y, Sun B, Peng S, Zhang H, Eidelberg D, et al. Metabolic imaging of bilateral anterior capsulotomy in refractory obsessive compulsive disorder: an FDG PET study. J Cereb Blood Flow Metab. 2013;33:880–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, et al. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci USA. 2009;106:2035–40.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA. 2001;98:676–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ. Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev. 2009;33:279–96.

    PubMed  Google Scholar 

Download references

Acknowledgements

The Center of Excellence on Mood Disorders is funded by the Pat Rutherford Jr. Chair in Psychiatry, John S. Dunn Foundation, and Anne and Don Fizer Foundation Endowment for Depression Research. We thank our patients for their participation.

Author information

Authors and Affiliations

Authors

Contributions

AJF and CRC contributed to drafting the manuscript; all authors contributed to the final manuscript. CRC contributed to data collection, mathematical analysis, data processing, and figure development. AJF, JQ, and JCS contributed to clinical management and patient recruitment.

Corresponding authors

Correspondence to Christopher R. Conner or Albert J. Fenoy.

Ethics declarations

Competing interests

AJF serves as a consultant for Medtronic, Inc and receives grant support from the NIH/NINDS (1R01NS113893-01A1). JQ receives research support from the NIH/NIMH (1R21MH117636-01A1), the Faillace Department of Psychiatry and Behavioral Sciences, and LivaNova; has speaker bureau membership with Myriad Neuroscience, Janssen Pharmaceuticals, and Abbvie; is a consultant for Eurofarma; is stockholder at Instituto de Neurociencias Dr. Joao Quevedo; and receives copyrights from Artmed Editora, Artmed Panamericana, and Elsevier/Academic Press. JCS receives grant/research support from Bristol-Meyers Squibb, Forest Laboratories, Merck, and Elan Pharmaceuticals, and serves as a consultant for Pfizer, Abbot, and Astellas Pharma, Inc. CRC reported no biomedical financial interests or potential conflicts of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Conner, C.R., Quevedo, J., Soares, J.C. et al. Brain metabolic changes and clinical response to superolateral medial forebrain bundle deep brain stimulation for treatment-resistant depression. Mol Psychiatry 27, 4561–4567 (2022). https://doi.org/10.1038/s41380-022-01726-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01726-0

This article is cited by

Search

Quick links