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Closed-loop neurostimulation for the treatment of psychiatric disorders

Abstract

Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.

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Fig. 1: Symptoms of psychiatric diseases can be continuous or episodic.
Fig. 2: Considerations of temporal dynamics when designing closed-loop neurostimulation.

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References

  1. Williams LM. Precision psychiatry: a neural circuit taxonomy for depression and anxiety. Lancet Psychiatry. 2016;3:472–80. https://doi.org/10.1016/S2215-0366(15)00579-9.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Spellman T, Liston C. Toward circuit mechanisms of pathophysiology in depression. Am J Psychiatry. 2020;177:381–90. https://doi.org/10.1176/appi.ajp.2020.20030280.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Marek S, Tervo-Clemmens B, Calabro FJ, Montez DF, Kay BP, Hatoum AS, et al. Reproducible brain-wide association studies require thousands of individuals. Nature. 2022;603:654–60. https://doi.org/10.1038/s41586-022-04492-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Essen DCV, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci. 2005;102:9673–8. https://doi.org/10.1073/pnas.0504136102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Raichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. NeuroImage. 2007;37:1083–90. https://doi.org/10.1016/j.neuroimage.2007.02.041.

    Article  PubMed  Google Scholar 

  6. Davey CG, Pujol J, Harrison BJ. Mapping the self in the brain’s default mode network. NeuroImage. 2016;132:390–7. https://doi.org/10.1016/j.neuroimage.2016.02.022.

    Article  PubMed  Google Scholar 

  7. Whitfield-Gabrieli S, Moran JM, Nieto-Castañón A, Triantafyllou C, Saxe R, Gabrieli JDE. Associations and dissociations between default and self-reference networks in the human brain. NeuroImage. 2011;55:225–32. https://doi.org/10.1016/j.neuroimage.2010.11.048.

    Article  PubMed  Google Scholar 

  8. Sestieri C, Corbetta M, Romani GL, Shulman GL. Episodic memory retrieval, parietal cortex, and the default mode network: functional and topographic analyses. J Neurosci. 2011;31:4407–20. https://doi.org/10.1523/jneurosci.3335-10.2011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Sheline YI, Barch DM, Price JL, Rundle MM, Vaishnavi SN, Snyder AZ, et al. The default mode network and self-referential processes in depression. Proc Natl Acad Sci. 2009;106:1942–7. https://doi.org/10.1073/pnas.0812686106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007;62:429–37. https://doi.org/10.1016/j.biopsych.2006.09.020.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Milazzo A-C, Ng B, Jiang H, Shirer W, Varoquaux G, Poline JB, et al. Identification of mood-relevant brain connections using a continuous, subject-driven rumination paradigm. Cereb Cortex. 2016;26:933–42. https://doi.org/10.1093/cercor/bhu255.

    Article  PubMed  Google Scholar 

  12. Posner J, Hellerstein DJ, Gat I, Mechling A, Klahr K, Wang Z, et al. Antidepressants normalize the default mode network in patients with dysthymia. JAMA Psychiatry. 2013;70:373–82. https://doi.org/10.1001/jamapsychiatry.2013.455.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ven V, van de, Wingen M, Kuypers KPC, Ramaekers JG, Formisano E. Escitalopram decreases cross-regional functional connectivity within the default-mode network. PLoS ONE. 2013;8:e68355. https://doi.org/10.1371/journal.pone.0068355.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Liston C, Chen AC, Zebley BD, Drysdale AT, Gordon R, Leuchter B, et al. Default mode network mechanisms of transcranial magnetic stimulation in depression. Biol Psychiatry. 2014;76:517–26. https://doi.org/10.1016/j.biopsych.2014.01.023.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Daws RE, Timmermann C, Giribaldi B, Sexton JD, Wall MB, Erritzoe D, et al. Increased global integration in the brain after psilocybin therapy for depression. Nat Med. 2022:1–8. https://doi.org/10.1038/s41591-022-01744-z.

  16. Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27:2349–56. https://doi.org/10.1523/jneurosci.5587-06.2007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Seeley WW. The salience network: a neural system for perceiving and responding to homeostatic demands. J Neurosci. 2019:1138–17. https://doi.org/10.1523/jneurosci.1138-17.2019.

  18. Rabinak CA, Angstadt M, Welsh RC, Kenndy AE, Lyubkin M, Martis B, et al. Altered amygdala resting-state functional connectivity in post-traumatic stress disorder. Front Psychiatry. 2011;2:62. https://doi.org/10.3389/fpsyt.2011.00062.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sripada RK, King AP, Welsh RC, Garfinkel SN, Wang X, Sripada CS, et al. Neural dysregulation in posttraumatic stress disorder. Psychosom Med. 2012;74:904–11. https://doi.org/10.1097/psy.0b013e318273bf33.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Etkin A, Prater KE, Schatzberg AF, Menon V, Greicius MD. Disrupted amygdalar subregion functional connectivity and evidence of a compensatory network in generalized anxiety disorder. Arch Gen Psychiatry. 2009;66:1361–72. https://doi.org/10.1001/archgenpsychiatry.2009.104.

    Article  PubMed  Google Scholar 

  21. Pannekoek JN, Veer IM, van Tol M-J, van der Werff SJA, Demenescu LR, Aleman A, et al. Resting-state functional connectivity abnormalities in limbic and salience networks in social anxiety disorder without comorbidity. Eur Neuropsychopharmacol. 2013;23:186–95. https://doi.org/10.1016/j.euroneuro.2012.04.018.

    Article  CAS  PubMed  Google Scholar 

  22. Prater KE, Hosanagar A, Klumpp H, Angstadt M, Phan KL. Aberrant amygdala–frontal cortex connectivity during perception of fearful faces and at rest in generalized social anxiety disorder. Depress. Anxiety. 2013;30:234–41. https://doi.org/10.1002/da.22014.

    Article  PubMed  Google Scholar 

  23. Peterson A, Thome J, Frewen P, Lanius RA. Resting-state neuroimaging studies: a new way of identifying differences and similarities among the anxiety disorders. Can J Psychiatry. 2013;59:294–300. https://doi.org/10.1177/070674371405900602.

    Article  Google Scholar 

  24. Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry. 2015;72:603–11. https://doi.org/10.1001/jamapsychiatry.2015.0071.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Menon V, Uddin LQ. Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct. 2010;214:655–67. https://doi.org/10.1007/s00429-010-0262-0.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Nestler EJ, Carlezon WA. The mesolimbic dopamine reward circuit in depression. Biol Psychiatry. 2006;59:1151–9. https://doi.org/10.1016/j.biopsych.2005.09.018.

    Article  CAS  PubMed  Google Scholar 

  27. Cheng W, Rolls ET, Qiu J, Liu W, Tang Y, Huang C-C, et al. Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression. Brain. 2016;139:3296–309. https://doi.org/10.1093/brain/aww255.

    Article  PubMed  Google Scholar 

  28. Satterthwaite TD, Kable JW, Vandekar L, Katchmar N, Bassett DS, Baldassano CF, et al. Common and dissociable dysfunction of the reward system in bipolar and unipolar depression. Neuropsychopharmacology. 2015;40:2258–68. https://doi.org/10.1038/npp.2015.75.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Pizzagalli DA, Holmes AJ, Dillon DG, Goetz EL, Birk JL, Bogdan R, et al. Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. Am J Psychiatry. 2009;166:702–10. https://doi.org/10.1176/appi.ajp.2008.08081201.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Stoy M, Schlagenhauf F, Sterzer P, Bermpohl F, Hägele C, Suchotzki K, et al. Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated depressed patients normalizes after treatment with escitalopram. J Psychopharmacol. 2012;26:677–88. https://doi.org/10.1177/0269881111416686.

    Article  PubMed  Google Scholar 

  31. Kober H, Barrett LF, Joseph J, Bliss-Moreau E, Lindquist K, Wager TD. Functional grouping and cortical–subcortical interactions in emotion: a meta-analysis of neuroimaging studies. NeuroImage. 2008;42:998–1031. https://doi.org/10.1016/j.neuroimage.2008.03.059.

    Article  PubMed  Google Scholar 

  32. Stuhrmann A, Suslow T, Dannlowski U. Facial emotion processing in major depression: a systematic review of neuroimaging findings. Biol Mood Anxiety Disord. 2011;1:10. https://doi.org/10.1186/2045-5380-1-10.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Victor TA, Furey ML, Fromm SJ, Öhman A, Drevets WC. Relationship between amygdala responses to masked faces and mood state and treatment in major depressive disorder. Arch Gen Psychiatry. 2010;67:1128–38. https://doi.org/10.1001/archgenpsychiatry.2010.144.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Robinson OJ, Krimsky M, Lieberman L, Allen P, Vytal K, Grillon C. The dorsal medial prefrontal (anterior cingulate) cortex–amygdala aversive amplification circuit in unmedicated generalised and social anxiety disorders: an observational study. Lancet Psychiatry. 2014;1:294–302. https://doi.org/10.1016/s2215-0366(14)70305-0.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Etkin A, Prater KE, Hoeft F, Menon V, Schatzberg AF. Failure of anterior cingulate activation and connectivity with the amygdala during implicit regulation of emotional processing in generalized anxiety disorder. Am J Psychiatry. 2010;167:545–54. https://doi.org/10.1176/appi.ajp.2009.09070931.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Mannie ZN, Taylor MJ, Harmer CJ, Cowen PJ, Norbury R. Frontolimbic responses to emotional faces in young people at familial risk of depression. J Affect Disord. 2011;130:127–32. https://doi.org/10.1016/j.jad.2010.09.030.

    Article  PubMed  Google Scholar 

  37. Swartz JR, Williamson DE, Hariri AR. Developmental change in amygdala reactivity during adolescence: effects of family history of depression and stressful life events. Am J Psychiatry. 2015;172:276–83. https://doi.org/10.1176/appi.ajp.2014.14020195.

    Article  PubMed  Google Scholar 

  38. Kujawa A, Burkhouse KL. Vulnerability to depression in youth: advances from affective neuroscience. Biol Psychiatry: Cogn Neurosci Neuroimag. 2017;2:28–37. https://doi.org/10.1016/j.bpsc.2016.09.006.

    Article  Google Scholar 

  39. Graybiel AM, Rauch SL. Toward a neurobiology of obsessive-compulsive disorder. Neuron. 2000;28:343–7. https://doi.org/10.1016/S0896-6273(00)00113-6.

    Article  CAS  PubMed  Google Scholar 

  40. Brennan BP, Rauch SL. Functional Neuroimaging Studies in Obsessive-Compulsive Disorder: Overview and Synthesis. In: Pittenger C, Pittenger C (eds) Obsessive-compulsive Disorder: Phenomenology, Pathophysiology, and Treatment. Oxford University Press. 2017.

  41. Cuthbert BN, Insel TR. Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC Med. 2013;11:126. https://doi.org/10.1186/1741-7015-11-126.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Cuthbert BN. Research Domain Criteria: toward future psychiatric nosologies. Dialog Clin Neurosci. 2015;17:89–97. https://doi.org/10.31887/dcns.2015.17.1/bcuthbert.

    Article  Google Scholar 

  43. Diagnostic and statistical manual of mental disorders: fifth edition. American Psychiatric Association. 2013.

  44. Zimmerman M, Ellison W, Young D, Chelminski I, Dalrymple K. How many different ways do patients meet the diagnostic criteria for major depressive disorder? Compr Psychiatry. 2015;56:29–34. https://doi.org/10.1016/j.comppsych.2014.09.007.

    Article  PubMed  Google Scholar 

  45. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, et al. Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. AJP. 2010;167:748–51. https://doi.org/10.1176/appi.ajp.2010.09091379.

    Article  Google Scholar 

  46. Kendler KS, Walters EE, Kessler RC. The prediction of length of major depressive episodes: results from an epidemiological sample of female twins. Psychol Med. 1997;27:107–17. https://doi.org/10.1017/s0033291796003893.

    Article  CAS  PubMed  Google Scholar 

  47. Gilmer WS, Trivedi MH, Rush AJ, Wisniewski SR, Luther J, Howland RH, et al. Factors associated with chronic depressive episodes: a preliminary report from the STAR-D project. Acta Psychiatr Scand. 2005;112:425–33. https://doi.org/10.1111/j.1600-0447.2005.00633.x.

    Article  CAS  PubMed  Google Scholar 

  48. Hall DP, Sing HC, Romanoski AJ. Identification and characterization of greater mood variance in depression. Am J Psychiatry. 1991;148:1341–5. https://doi.org/10.1176/ajp.148.10.1341.

    Article  PubMed  Google Scholar 

  49. Morris DW, Rush AJ, Jain S, Fava M, Wisniewski SR, Balasubramani GK, et al. Diurnal mood variation in outpatients with major depressive disorder: implications for DSM-V from an analysis of the sequenced treatment alternatives to relieve depression study data. J Clin Psychiatry. 2007;68:1339–47.

    Article  PubMed  Google Scholar 

  50. Maldonado G, Kraus JF. Variation in suicide occurrence by time of day, day of the week, month, and lunar phase. Suicide Life Threat Behav. 1991;21:174–87.

    Article  CAS  PubMed  Google Scholar 

  51. Galvão PVM, Silva HRSE, da Silva CMFP. Temporal distribution of suicide mortality: a systematic review. J Affect Disord. 2018;228:132–42. https://doi.org/10.1016/j.jad.2017.12.008.

    Article  PubMed  Google Scholar 

  52. Margraf J, Taylor B, Ehlers A, Roth WT, Agras WS. Panic attacks in the natural environment. J Nerv Ment Dis. 1987;175:558–65. https://doi.org/10.1097/00005053-198709000-00008.

    Article  CAS  PubMed  Google Scholar 

  53. Norton GR, Harrison B, Hauch J, Rhodes L. Characteristics of people with infrequent panic attacks. J Abnorm Psychol. 1985;94:216–21. https://doi.org/10.1037//0021-843x.94.2.216.

    Article  CAS  PubMed  Google Scholar 

  54. American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders (5th edition).

  55. Nota JA, Gibb BE, Coles ME. Obsessions and time of day: a self-monitoring study in individuals with obsessive-compulsive disorder. J Cogn Psychother. 2014;28:134–44. https://doi.org/10.1891/0889-8391.28.2.134.

    Article  PubMed  Google Scholar 

  56. Lam CM, Latif U, Sack A, Govindan S, Sanderson M, Vu DT, et al. Advances in spinal cord stimulation. Bioengineering. 2023;10:185. https://doi.org/10.3390/bioengineering10020185.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Penfield W, Jasper H. Epilepsy and the functional anatomy of the human brain. Little, Brown & Co., Oxford, England. 1954.

  58. Shealy CN, Mortimer JT, Reswick JB. Electrical inhibition of pain by stimulation of the dorsal columns: preliminary clinical report. Anesth Analg. 1967;46:489–91.

    Article  CAS  PubMed  Google Scholar 

  59. Drobisz D, Damborská A. Deep brain stimulation targets for treating depression. Behav Brain Res. 2019;359:266–73. https://doi.org/10.1016/j.bbr.2018.11.004.

    Article  PubMed  Google Scholar 

  60. 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. https://doi.org/10.1016/j.neuron.2005.02.014.

    Article  CAS  PubMed  Google Scholar 

  61. 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. https://doi.org/10.1016/j.biopsych.2008.05.034.

    Article  PubMed  Google Scholar 

  62. Kennedy SH, Giacobbe P, Rizvi SJ, Placenza FM, Nishikawa Y, Mayberg HS, et al. Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years. AJP. 2011;168:502–10. https://doi.org/10.1176/appi.ajp.2010.10081187.

    Article  Google Scholar 

  63. 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. https://doi.org/10.1001/archgenpsychiatry.2011.1456.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Lozano AM, Giacobbe P, Hamani C, Rizvi SJ, Kennedy SH, Kolivakis TT, et al. A multicenter pilot study of subcallosal cingulate area deep brain stimulation for treatment-resistant depression: clinical article. J Neurosurg. 2012;116:315–22. https://doi.org/10.3171/2011.10.JNS102122.

    Article  PubMed  Google Scholar 

  65. 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. https://doi.org/10.1016/S2215-0366(17)30371-1.

    Article  PubMed  Google Scholar 

  66. Riva-Posse P, Choi KS, Holtzheimer PE, McIntyre CC, Gross RE, Chaturvedi A, et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2014;76:963–9. https://doi.org/10.1016/j.biopsych.2014.03.029.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Riva-Posse P, Choi KS, Holtzheimer PE, Crowell AL, Garlow SJ, Rajendra JK, et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol Psychiatry. 2018;23:843–9. https://doi.org/10.1038/mp.2017.59.

    Article  CAS  PubMed  Google Scholar 

  68. Crowell AL, Riva-Posse P, Holtzheimer PE, Garlow SJ, Kelley ME, Gross RE, et al. Long-term outcomes of subcallosal cingulate deep brain stimulation for treatment-resistant depression. AJP. 2019;176:949–56. https://doi.org/10.1176/appi.ajp.2019.18121427.

    Article  Google Scholar 

  69. Malone DA, Dougherty DD, Rezai AR, Carpenter LL, Friehs GM, Eskandar EN, et al. Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biol Psychiatry. 2009;65:267–75. https://doi.org/10.1016/j.biopsych.2008.08.029.

    Article  PubMed  Google Scholar 

  70. Dougherty DD, Rezai AR, Carpenter LL, Howland RH, Bhati MT, O’Reardon 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. https://doi.org/10.1016/j.biopsych.2014.11.023.

    Article  PubMed  Google Scholar 

  71. Bergfeld IO, Mantione M, Hoogendoorn MLC, Ruhé 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. https://doi.org/10.1001/jamapsychiatry.2016.0152.

    Article  PubMed  Google Scholar 

  72. 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. Neuropsychopharmacol. 2008;33:368–77. https://doi.org/10.1038/sj.npp.1301408.

    Article  Google Scholar 

  73. 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. https://doi.org/10.1016/j.biopsych.2009.09.013.

    Article  PubMed  Google Scholar 

  74. 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. Neuropsychopharmacol. 2012;37:1975–85. https://doi.org/10.1038/npp.2012.44.

    Article  CAS  Google Scholar 

  75. 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.

    Article  PubMed  Google Scholar 

  76. Schlaepfer TE, Bewernick BH, Kayser S, Mädler B, Coenen VA. Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73:1204–12. https://doi.org/10.1016/j.biopsych.2013.01.034.

    Article  PubMed  Google Scholar 

  77. 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 Stimulation. 2017;10:664–71. https://doi.org/10.1016/j.brs.2017.01.581.

    Article  PubMed  Google Scholar 

  78. 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. Neuropsychopharmacol. 2019;44:1224–32. https://doi.org/10.1038/s41386-019-0369-9.

    Article  Google Scholar 

  79. Fenoy AJ, Schulz P, Selvaraj S, Burrows C, 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. https://doi.org/10.1016/j.jad.2016.05.064.

    Article  PubMed  Google Scholar 

  80. Nuttin B, Cosyns P, Demeulemeester H, Gybels J, Meyerson B. Electrical stimulation in anterior limbs of internal capsules in patients with obsessive-compulsive disorder. Lancet. 1999;354:1526. https://doi.org/10.1016/S0140-6736(99)02376-4.

    Article  CAS  PubMed  Google Scholar 

  81. Greenberg BD, Gabriels LA, Malone DA, Rezai AR, Friehs GM, Okun MS, et al. Deep brain stimulation of the ventral internal capsule/ventral striatum for obsessive-compulsive disorder: worldwide experience. Mol Psychiatry. 2010;15:64–79. https://doi.org/10.1038/mp.2008.55.

    Article  CAS  PubMed  Google Scholar 

  82. Gadot R, Najera R, Hirani S, Anand A, Storch E, Goodman WK, et al. Efficacy of deep brain stimulation for treatment-resistant obsessive-compulsive disorder: systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2022;93:1166–73. https://doi.org/10.1136/jnnp-2021-328738.

    Article  Google Scholar 

  83. Luyten L, Hendrickx S, Raymaekers S, Gabriëls L, Nuttin B. Electrical stimulation in the bed nucleus of the stria terminalis alleviates severe obsessive-compulsive disorder. Mol Psychiatry. 2016;21:1272–80. https://doi.org/10.1038/mp.2015.124.

    Article  CAS  PubMed  Google Scholar 

  84. Mallet L, Polosan M, Jaafari N, Baup N, Welter M-L, Fontaine D, et al. Subthalamic nucleus stimulation in severe obsessive–compulsive disorder. N. Engl J Med. 2008;359:2121–34. https://doi.org/10.1056/NEJMoa0708514.

    Article  CAS  PubMed  Google Scholar 

  85. Li N, Baldermann JC, Kibleur A, Treu S, Akram H, Elias GJB, et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat Commun. 2020;11:3364. https://doi.org/10.1038/s41467-020-16734-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Baldermann JC, Schüller T, Kohl S, Voon V, Li N, Hollunder B, et al. Connectomic deep brain stimulation for obsessive-compulsive disorder. Biol Psychiatry. 2021;90:678–88. https://doi.org/10.1016/j.biopsych.2021.07.010.

    Article  CAS  PubMed  Google Scholar 

  87. Haber SN, Yendiki A, Jbabdi S. Four deep brain stimulation targets for obsessive-compulsive disorder: are they different? Biol Psychiatry. 2021;90:667–77. https://doi.org/10.1016/j.biopsych.2020.06.031.

    Article  PubMed  Google Scholar 

  88. Wang J, Shang R, He L, Zhou R, Chen Z, Ma Y, et al. Prediction of deep brain stimulation outcome in Parkinson’s disease with connectome based on hemispheric asymmetry. Front Neurosci. 2021;15:620750. https://doi.org/10.3389/fnins.2021.620750.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Mirza KB, Golden CT, Nikolic K, Toumazou C. Closed-loop implantable therapeutic neuromodulation systems based on neurochemical monitoring. Front Neurosci. 2019;13:808.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Fingelkurts AA, Fingelkurts AA, Rytsälä H, Suominen K, Isometsä E, Kähkönen S. Impaired functional connectivity at EEG alpha and theta frequency bands in major depression. Hum Brain Mapp. 2007;28:247–61. https://doi.org/10.1002/hbm.20275.

    Article  PubMed  Google Scholar 

  91. Neumann W-J, Huebl J, Brücke C, Gabriëls L, Bajbouj M, Merkl A, et al. Different patterns of local field potentials from limbic DBS targets in patients with major depressive and obsessive compulsive disorder. Mol Psychiatry. 2014;19:1186–92. https://doi.org/10.1038/mp.2014.2.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Pollock VE, Schneider LS. Quantitative, waking EEG research on depression. Biol Psychiatry. 1990;27:757–80. https://doi.org/10.1016/0006-3223(90)90591-o.

    Article  CAS  PubMed  Google Scholar 

  93. Kemp AH, Griffiths K, Felmingham KL, Shankman SA, Drinkenburg W, Arns M, et al. Disorder specificity despite comorbidity: resting EEG alpha asymmetry in major depressive disorder and post-traumatic stress disorder. Biol Psychol. 2010;85:350–4. https://doi.org/10.1016/j.biopsycho.2010.08.001.

    Article  CAS  PubMed  Google Scholar 

  94. Scangos KW, Khambhati AN, Daly PM, Makhoul GS, Sugrue LP, Zamanian H, et al. Closed-loop neuromodulation in an individual with treatment-resistant depression. Nat Med. 2021;27:1696–1700. https://doi.org/10.1038/s41591-021-01480-w.

    Article  CAS  PubMed  Google Scholar 

  95. Provenza NR, Sheth SA, Dastin-van Rijn EM, Mathura RK, Ding Y, Vogt GS, et al. Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder. Nat Med. 2021;27:2154–64. https://doi.org/10.1038/s41591-021-01550-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Vissani M, Nanda P, Bush A, Neudorfer C, Dougherty D, Richardson RM Toward Closed-Loop Intracranial Neurostimulation in Obsessive-Compulsive Disorder. Biol Psychiatry. 2022. https://doi.org/10.1016/j.biopsych.2022.07.003

  97. Fridgeirsson EA, Bais MN, Eijsker N, Thomas RM, Smit DJA, Bergfeld IO, et al. Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum. J Neural Eng. 2023. https://doi.org/10.1088/1741-2552/acbee1.

  98. Chiken S, Nambu A. Mechanism of deep brain stimulation. Neuroscientist. 2016;22:313–22. https://doi.org/10.1177/1073858415581986.

    Article  PubMed  Google Scholar 

  99. McIntyre CC, Savasta M, Kerkerian-Le Goff L, Vitek JL. Uncovering the mechanism(s) of action of deep brain stimulation: activation, inhibition, or both. Clin Neurophysiol. 2004;115:1239–48. https://doi.org/10.1016/j.clinph.2003.12.024.

    Article  PubMed  Google Scholar 

  100. Ashkan K, Rogers P, Bergman H, Ughratdar I. Insights into the mechanisms of deep brain stimulation. Nat Rev Neurol. 2017;13:548–54. https://doi.org/10.1038/nrneurol.2017.105.

    Article  PubMed  Google Scholar 

  101. Lozano AM, Lipsman N, Bergman H, Brown P, Chabardes S, Chang JW, et al. Deep brain stimulation: current challenges and future directions. Nat Rev Neurol. 2019;15:148–60. https://doi.org/10.1038/s41582-018-0128-2.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Sun FT, Morrell MJ. The RNS system: responsive cortical stimulation for the treatment of refractory partial epilepsy. Expert Rev Med Devices. 2014;11:563–72. https://doi.org/10.1586/17434440.2014.947274.

    Article  CAS  PubMed  Google Scholar 

  103. Stanslaski S, Herron J, Chouinard T, Bourget D, Isaacson B, Kremen V, et al. A chronically implantable neural coprocessor for investigating the treatment of neurological disorders. IEEE Trans Biomed Circuits Syst. 2018;12:1230–45. https://doi.org/10.1109/TBCAS.2018.2880148.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Waltz E. Green light for deep brain stimulator incorporating neurofeedback. Nat Biotechnol. 2020;38:1014–5. https://doi.org/10.1038/s41587-020-0664-3.

    Article  CAS  PubMed  Google Scholar 

  105. Jimenez-Shahed J. Device profile of the percept PC deep brain stimulation system for the treatment of Parkinson’s disease and related disorders. Expert Rev Med Devices. 2021;18:319–32. https://doi.org/10.1080/17434440.2021.1909471.

    Article  CAS  PubMed  Google Scholar 

  106. Arlotti M, Colombo M, Bonfanti A, Mandat T, Lanotte MM, Pirola E, et al. A new implantable closed-loop clinical neural interface: first application in Parkinson’s disease. Front Neurosci. 2021;15:763235.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Ansó J, Benjaber M, Parks B, Parker S, Oehrn CR, Petrucci M, et al. Concurrent stimulation and sensing in bi-directional brain interfaces: a multi-site translational experience. J Neural Eng. 2022;19:026025. https://doi.org/10.1088/1741-2552/ac59a3.

    Article  Google Scholar 

  108. Cameron T, Alo KM. Effects of posture on stimulation parameters in spinal cord stimulation. Neuromodulation: Technol Neural Interface. 1998;1:177–83. https://doi.org/10.1111/j.1525-1403.1998.tb00014.x.

    Article  CAS  Google Scholar 

  109. Schultz DM, Webster L, Kosek P, Dar U, Tan Y, Sun M. Sensor-driven position-adaptive spinal cord stimulation for chronic pain. Pain Physician. 2012;15:1–12.

    Article  PubMed  Google Scholar 

  110. Mekhail N, Levy RM, Deer TR, Kapural L, Li S, Amirdelfan K, et al. Long-term safety and efficacy of closed-loop spinal cord stimulation to treat chronic back and leg pain (Evoke): a double-blind, randomised, controlled trial. Lancet Neurol. 2020;19:123–34. https://doi.org/10.1016/S1474-4422(19)30414-4.

    Article  PubMed  Google Scholar 

  111. Mekhail N, Levy RM, Deer TR, Kapural L, Li S, Amirdelfan K, et al. Durability of clinical and quality-of-life outcomes of closed-loop spinal cord stimulation for chronic back and leg pain: a secondary analysis of the evoke randomized clinical trial. JAMA Neurol. 2022;79:251–60. https://doi.org/10.1001/jamaneurol.2021.4998.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Shirvalkar P, Prosky J, Chin G, Ahmadipour P, Sani OG, Desai M, et al. First-in-human prediction of chronic pain state using intracranial neural biomarkers. Nat Neurosci. 2023:1–10. https://doi.org/10.1038/s41593-023-01338-z

  113. Little S, Pogosyan A, Neal S, Zavala B, Zrinzo L, Hariz M, et al. Adaptive deep brain stimulation in advanced Parkinson disease. Ann Neurol. 2013;74:449–57. https://doi.org/10.1002/ana.23951.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Rosa M, Arlotti M, Ardolino G, Cogiamanian F, Marceglia S, Di Fonzo A, et al. Adaptive deep brain stimulation in a freely moving parkinsonian patient. Mov Disord. 2015;30:1003–5. https://doi.org/10.1002/mds.26241.

    Article  PubMed  PubMed Central  Google Scholar 

  115. Little S, Beudel M, Zrinzo L, Foltynie T, Limousin P, Hariz M, et al. Bilateral adaptive deep brain stimulation is effective in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2016;87:717–21. https://doi.org/10.1136/jnnp-2015-310972.

    Article  PubMed  Google Scholar 

  116. Little S, Tripoliti E, Beudel M, Pogosyan A, Cagnan H, Herz D, et al. Adaptive deep brain stimulation for Parkinson’s disease demonstrates reduced speech side effects compared to conventional stimulation in the acute setting. J Neurol Neurosurg Psychiatry. 2016;87:1388–9. https://doi.org/10.1136/jnnp-2016-313518.

    Article  PubMed  Google Scholar 

  117. Piña-Fuentes D, Little S, Oterdoom M, Neal S, Pogosyan A, Tijssen MAJ, et al. Adaptive DBS in a Parkinson’s patient with chronically implanted DBS: a proof of principle. Mov Disord. 2017;32:1253–4. https://doi.org/10.1002/mds.26959.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Bocci T, Prenassi M, Arlotti M, Cogiamanian FM, Borellini L, Moro E, et al. Eight-hours conventional versus adaptive deep brain stimulation of the subthalamic nucleus in Parkinson’s disease. npj Parkinsons Dis. 2021;7:1–6. https://doi.org/10.1038/s41531-021-00229-z.

    Article  Google Scholar 

  119. Arlotti M, Marceglia S, Foffani G, Volkmann J, Lozano AM, Moro E, et al. Eight-hours adaptive deep brain stimulation in patients with Parkinson disease. Neurology. 2018;90:e971–e976. https://doi.org/10.1212/WNL.0000000000005121.

    Article  PubMed  PubMed Central  Google Scholar 

  120. Velisar A, Syrkin-Nikolau J, Blumenfeld Z, Trager MH, Afzal MF, Prabhakar V, et al. Dual threshold neural closed loop deep brain stimulation in Parkinson disease patients. Brain Stimulation: Basic Transl Clin Res Neuromodulation. 2019;12:868–76. https://doi.org/10.1016/j.brs.2019.02.020.

    Article  CAS  Google Scholar 

  121. Malekmohammadi M, Herron J, Velisar A, Blumenfeld Z, Trager MH, Chizeck HJ, et al. Kinematic adaptive deep brain stimulation for resting tremor in Parkinson’s disease. Mov Disord. 2016;31:426–8. https://doi.org/10.1002/mds.26482.

    Article  PubMed  Google Scholar 

  122. Swann NC, de Hemptinne C, Thompson MC, Miocinovic S, Miller AM, Gilron R, et al. Adaptive deep brain stimulation for Parkinson’s disease using motor cortex sensing. J Neural Eng. 2018;15:046006. https://doi.org/10.1088/1741-2552/aabc9b.

    Article  PubMed  PubMed Central  Google Scholar 

  123. Gilron R, Little S, Perrone R, Wilt R, de Hemptinne C, Yaroshinsky MS, et al. Long-term wireless streaming of neural recordings for circuit discovery and adaptive stimulation in individuals with Parkinson’s disease. Nat Biotechnol. 2021;39:1078–85. https://doi.org/10.1038/s41587-021-00897-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Graupe D, Basu I, Tuninetti D, Vannemreddy P, Slavin KV. Adaptively controlling deep brain stimulation in essential tremor patient via surface electromyography. Neurol Res. 2010;32:899–904. https://doi.org/10.1179/016164110X12767786356354.

    Article  PubMed  Google Scholar 

  125. Yamamoto T, Katayama Y, Ushiba J, Yoshino H, Obuchi T, Kobayashi K, et al. On-demand control system for deep brain stimulation for treatment of intention tremor. Neuromodulation: Technol Neural Interface. 2013;16:230–5. https://doi.org/10.1111/j.1525-1403.2012.00521.x.

    Article  Google Scholar 

  126. Cagnan H, Pedrosa D, Little S, Pogosyan A, Cheeran B, Aziz T, et al. Stimulating at the right time: phase-specific deep brain stimulation. Brain. 2017;140:132–45. https://doi.org/10.1093/brain/aww286.

    Article  PubMed  Google Scholar 

  127. Opri E, Cernera S, Molina R, Eisinger RS, Cagle JN, Almeida L, et al. Chronic embedded cortico-thalamic closed-loop deep brain stimulation for the treatment of essential tremor. Sci Transl Med. 2020;12:eaay7680. https://doi.org/10.1126/scitranslmed.aay7680.

    Article  PubMed  PubMed Central  Google Scholar 

  128. Lesser RP, Kim SH, Beyderman L, Miglioretti DL, Webber WRS, Bare M, et al. Brief bursts of pulse stimulation terminate afterdischarges caused by cortical stimulation. Neurology. 1999;53:2073–2073. https://doi.org/10.1212/WNL.53.9.2073.

    Article  CAS  PubMed  Google Scholar 

  129. Valentin A, Ughratdar I, Venkatachalam G, Williams R, Pina M, Lazaro M, et al. Sustained seizure control in a child with drug resistant epilepsy after subacute cortical electrical stimulation (SCES). Brain Stimul. 2016;9:307–9. https://doi.org/10.1016/j.brs.2015.12.004.

    Article  PubMed  Google Scholar 

  130. Peters TE, Bhavaraju NC, Frei MG, Osorio I. Network system for automated seizure detection and contingent delivery of therapy. J Clin Neurophysiol. 2001;18:545–9. https://doi.org/10.1097/00004691-200111000-00004.

    Article  CAS  PubMed  Google Scholar 

  131. Kossoff EH, Ritzl EK, Politsky JM, Murro AM, Smith JR, Duckrow RB, et al. Effect of an external responsive neurostimulator on seizures and electrographic discharges during subdural electrode monitoring. Epilepsia. 2004;45:1560–7. https://doi.org/10.1111/j.0013-9580.2004.26104.x.

    Article  PubMed  Google Scholar 

  132. Morrell MJ. Responsive cortical stimulation for the treatment of medically intractable partial epilepsy. Neurology. 2011;77:1295–304. https://doi.org/10.1212/WNL.0b013e3182302056.

    Article  PubMed  Google Scholar 

  133. Heck CN, King-Stephens D, Massey AD, Nair DR, Jobst BC, Barkley GL, et al. Two-year seizure reduction in adults with medically intractable partial onset epilepsy treated with responsive neurostimulation: final results of the RNS System Pivotal trial. Epilepsia. 2014;55:432–41. https://doi.org/10.1111/epi.12534.

    Article  PubMed  PubMed Central  Google Scholar 

  134. Bergey GK, Morrell MJ, Mizrahi EM, Goldman A, King-Stephens D, Nair D, et al. Long-term treatment with responsive brain stimulation in adults with refractory partial seizures. Neurology. 2015;84:810–7. https://doi.org/10.1212/WNL.0000000000001280.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Razavi B, Rao VR, Lin C, Bujarski KA, Patra SE, Burdette DE, et al. Real-world experience with direct brain-responsive neurostimulation for focal onset seizures. Epilepsia. 2020;61:1749–57. https://doi.org/10.1111/epi.16593.

    Article  PubMed  PubMed Central  Google Scholar 

  136. Nair DR, Laxer KD, Weber PB, Murro AM, Park YD, Barkley GL, et al. Nine-year prospective efficacy and safety of brain-responsive neurostimulation for focal epilepsy. Neurology. 2020;95:e1244–e1256. https://doi.org/10.1212/WNL.0000000000010154.

    Article  PubMed  PubMed Central  Google Scholar 

  137. van Elmpt WJC, Nijsen TME, Griep PAM, Arends JBAM. A model of heart rate changes to detect seizures in severe epilepsy. Seizure. 2006;15:366–75. https://doi.org/10.1016/j.seizure.2006.03.005.

    Article  PubMed  Google Scholar 

  138. Fisher RS, Afra P, Macken M, Minecan DN, Bagić A, Benbadis SR, et al. Automatic vagus nerve stimulation triggered by ictal tachycardia: clinical outcomes and device performance—The U.S. E-37 trial. Neuromodulation. 2016;19:188–95. https://doi.org/10.1111/ner.12376.

    Article  PubMed  Google Scholar 

  139. Datta P, Galla KM, Sajja K, Wichman C, Wang H, Madhavan D. Vagus nerve stimulation with tachycardia detection provides additional seizure reduction compared to traditional vagus nerve stimulation. Epilepsy Behav. 2020;111:107280. https://doi.org/10.1016/j.yebeh.2020.107280.

    Article  PubMed  Google Scholar 

  140. Hamilton P, Soryal I, Dhahri P, Wimalachandra W, Leat A, Hughes D, et al. Clinical outcomes of VNS therapy with AspireSR® (including cardiac-based seizure detection) at a large complex epilepsy and surgery centre. Seizure. 2018;58:120–6. https://doi.org/10.1016/j.seizure.2018.03.022.

    Article  PubMed  Google Scholar 

  141. Winston GM, Guadix S, Lavieri MT, Uribe-Cardenas R, Kocharian G, Williams N, et al. Closed-loop vagal nerve stimulation for intractable epilepsy: a single-center experience. Seizure - Eur J Epilepsy. 2021;88:95–101. https://doi.org/10.1016/j.seizure.2021.03.030.

    Article  Google Scholar 

  142. Jankovic J, Kurlan R. Tourette syndrome: evolving concepts. Mov Disord. 2011;26:1149–56. https://doi.org/10.1002/mds.23618.

    Article  PubMed  Google Scholar 

  143. Molina R, Okun MS, Shute JB, Opri E, Rossi PJ, Martinez-Ramirez D, et al. Report of a patient undergoing chronic responsive deep brain stimulation for Tourette syndrome: proof of concept. J Neurosurg. 2018;129:308–14. https://doi.org/10.3171/2017.6.JNS17626.

    Article  PubMed  Google Scholar 

  144. Cagle JN, Okun MS, Cernera S, Eisinger RS, Opri E, Bowers D, et al. Embedded human closed-loop deep brain stimulation for tourette syndrome: a nonrandomized controlled trial. JAMA Neurol. 2022;79:1064–8. https://doi.org/10.1001/jamaneurol.2022.2741.

    Article  PubMed  PubMed Central  Google Scholar 

  145. Faller J, Doose J, Sun X, Mclntosh JR, Saber GT, Lin Y, et al. Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults. Brain Stimulation. 2022;15:458–71. https://doi.org/10.1016/j.brs.2022.02.008.

    Article  PubMed  PubMed Central  Google Scholar 

  146. Scangos KW, Makhoul GS, Sugrue LP, Chang EF, Krystal AD. State-dependent responses to intracranial brain stimulation in a patient with depression. Nat Med. 2021;27:229–31. https://doi.org/10.1038/s41591-020-01175-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Allawala A, Bijanki KR, Goodman W, Cohn JF, Viswanathan A, Yoshor D, et al. A novel framework for network-targeted neuropsychiatric deep brain stimulation. Neurosurgery. 2021. https://doi.org/10.1093/neuros/nyab112.

  148. Sheth SA, Bijanki KR, Metzger B, Allawala A, Pirtle V, Adkinson JA, et al. Deep brain stimulation for depression informed by intracranial recordings. Biol Psychiatry. 2022;92:246–51. https://doi.org/10.1016/j.biopsych.2021.11.007.

    Article  PubMed  Google Scholar 

  149. Widge AS, Ellard KK, Paulk AC, Basu I, Yousefi A, Zorowitz S, et al. Treating refractory mental illness with closed-loop brain stimulation: progress towards a patient-specific transdiagnostic approach. Exp Neurol. 2017;287:461–72. https://doi.org/10.1016/j.expneurol.2016.07.021.

    Article  PubMed  Google Scholar 

  150. Basu I, Yousefi A, Crocker B, Zelmann R, Paulk AC, Peled N, et al. Closed-loop enhancement and neural decoding of cognitive control in humans. Nat Biomed Eng. 2023;7:576–88. https://doi.org/10.1038/s41551-021-00804-y.

    Article  PubMed  Google Scholar 

  151. Sani OG, Yang Y, Lee MB, Dawes HE, Chang EF, Shanechi MM. Mood variations decoded from multi-site intracranial human brain activity. Nat Biotechnol. 2018;36:954–61. https://doi.org/10.1038/nbt.4200.

    Article  CAS  PubMed  Google Scholar 

  152. Sani OG, Abbaspourazad H, Wong YT, Pesaran B, Shanechi MM. Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification. Nat Neurosci. 2021;24:140–9. https://doi.org/10.1038/s41593-020-00733-0.

    Article  CAS  PubMed  Google Scholar 

  153. Yuxiao Y, Chang EF, Shanechi MM. Dynamic tracking of non-stationarity in human ECoG activity. Annu Int Conf IEEE Eng Med Biol Soc. 2017;2017:1660–3. https://doi.org/10.1109/EMBC.2017.8037159.

    Article  Google Scholar 

  154. Proix T, Truccolo W, Leguia MG, Tcheng TK, King-Stephens D, Rao VR, et al. Forecasting seizure risk in adults with focal epilepsy: a development and validation study. Lancet Neurol. 2021;20:127–35. https://doi.org/10.1016/S1474-4422(20)30396-3.

    Article  PubMed  Google Scholar 

  155. Baud MO, Kleen JK, Mirro EA, Andrechak JC, King-Stephens D, Chang EF, et al. Multi-day rhythms modulate seizure risk in epilepsy. Nat Commun. 2018;9:88. https://doi.org/10.1038/s41467-017-02577-y.

    Article  PubMed  PubMed Central  Google Scholar 

  156. Beninger RJ, Milner PM. Conditioned reinforcement based on reinforcing electrical stimulation of the brain: chain schedules. Psychobiology. 1977;5:285–9. https://doi.org/10.3758/BF03335332.

    Article  Google Scholar 

  157. Khambhati AN, Shafi A, Rao VR, Chang EF. Long-term brain network reorganization predicts responsive neurostimulation outcomes for focal epilepsy. Sci Transl Med. 2021;13:eabf6588. https://doi.org/10.1126/scitranslmed.abf6588.

    Article  PubMed  Google Scholar 

  158. Huang Y, Hajnal B, Entz L, Fabó D, Herrero JL, Mehta AD, et al. Intracortical dynamics underlying repetitive stimulation predicts changes in network connectivity. J Neurosci. 2019;39:6122–35. https://doi.org/10.1523/JNEUROSCI.0535-19.2019.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Khambhati AN, Kahn AE, Costantini J, Ezzyat Y, Solomon EA, Gross RE, et al. Functional control of electrophysiological network architecture using direct neurostimulation in humans. Netw Neurosci. 2019;3:848–77. https://doi.org/10.1162/netn_a_00089.

    Article  PubMed  PubMed Central  Google Scholar 

  160. Widge AS, Deckersbach T, Eskandar EN, Dougherty DD. Deep brain stimulation for treatment-resistant psychiatric illnesses: what has gone wrong and what should we do next. Biol Psychiatry. 2016;79:e9–e10. https://doi.org/10.1016/j.biopsych.2015.06.005.

    Article  PubMed  Google Scholar 

  161. Bagby RM, Ryder AG, Schuller DR, Marshall MB. The hamilton depression rating scale: has the gold standard become a lead weight? AJP. 2004;161:2163–77. https://doi.org/10.1176/appi.ajp.161.12.2163.

    Article  Google Scholar 

  162. Montgomery SA, Åsberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382–9. https://doi.org/10.1192/bjp.134.4.382.

    Article  CAS  PubMed  Google Scholar 

  163. Davidson J, Turnbull CD, Strickland R, Miller R, Graves K. The Montgomery-Åsberg depression scale: reliability and validity. Acta Psychiatr Scandinavica. 1986;73:544–8. https://doi.org/10.1111/j.1600-0447.1986.tb02723.x.

    Article  CAS  Google Scholar 

  164. Cuijpers P, Li J, Hofmann SG, Andersson G. Self-reported versus clinician-rated symptoms of depression as outcome measures in psychotherapy research on depression: a meta-analysis. Clin Psychol Rev. 2010;30:768–78. https://doi.org/10.1016/j.cpr.2010.06.001.

    Article  PubMed  Google Scholar 

  165. Rush AJ, Carmody TJ, Ibrahim HM, Trivedi MH, Biggs MM, Shores-Wilson K, et al. Comparison of self-report and clinician ratings on two inventories of depressive symptomatology. PS. 2006;57:829–37. https://doi.org/10.1176/ps.2006.57.6.829.

    Article  Google Scholar 

  166. Iannuzzo RW, Jaeger J, Goldberg JF, Kafantaris V, Sublette ME. Development and reliability of the HAM-D/MADRS interview: an integrated depression symptom rating scale. Psychiatry Res. 2006;145:21–37. https://doi.org/10.1016/j.psychres.2005.10.009.

    Article  PubMed  Google Scholar 

  167. van Westen M, Rietveld E, Bergfeld IO, de Koning P, Vullink N, Ooms P, et al. Optimizing deep brain stimulation parameters in obsessive–compulsive disorder. Neuromodulation. 2021;24:307–15. https://doi.org/10.1111/ner.13243.

    Article  PubMed  Google Scholar 

  168. Ramasubbu R, Lang S, Kiss ZHT. Dosing of electrical parameters in deep brain stimulation (DBS) for intractable depression: a review of clinical studies. Front Psychiatry. 2018;9:302. https://doi.org/10.3389/fpsyt.2018.00302.

    Article  PubMed  PubMed Central  Google Scholar 

  169. Boutet A, Madhavan R, Elias GJB, Joel SE, Gramer R, Ranjan M, et al. Predicting optimal deep brain stimulation parameters for Parkinson’s disease using functional MRI and machine learning. Nat Commun. 2021;12:3043. https://doi.org/10.1038/s41467-021-23311-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Malekmohammadi M, Mustakos R, Sheth S, Pouratian N, McIntyre CC, Bijanki KR, et al. Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets. J Neural Eng. 2022;19:046014. https://doi.org/10.1088/1741-2552/ac7e6c.

    Article  Google Scholar 

  171. Butson CR, Noecker AM, Maks CB, McIntyre CC (2007) StimExplorer: deep brain stimulation parameter selection software system. In: Sakas DE, Simpson BA (eds) Operative Neuromodulation: Volume 2: Neural Networks Surgery. Springer, Vienna, pp 569–74.

  172. Widge AS, Bilge MT, Montana R, Chang W, Rodriguez CI, Deckersbach T, et al. Electroencephalographic biomarkers for treatment response prediction in major depressive illness: a meta-analysis. Am J Psychiatry. 2019;176:44–56. https://doi.org/10.1176/appi.ajp.2018.17121358.

    Article  PubMed  Google Scholar 

  173. van der Vinne N, Vollebregt MA, van Putten MJAM, Arns M. Stability of frontal alpha asymmetry in depressed patients during antidepressant treatment. Neuroimage Clin. 2019;24:102056. https://doi.org/10.1016/j.nicl.2019.102056.

    Article  PubMed  PubMed Central  Google Scholar 

  174. Vuga M, Fox NA, Cohn JF, George CJ, Levenstein RM, Kovacs M. Long-term stability of frontal electroencephalographic asymmetry in adults with a history of depression and controls. Int J Psychophysiol. 2006;59:107–15. https://doi.org/10.1016/j.ijpsycho.2005.02.008.

    Article  PubMed  Google Scholar 

  175. Tenke CE, Kayser J, Alvarenga JE, Abraham KS, Warner V, Talati A, et al. Temporal stability of posterior EEG alpha over twelve years. Clin Neurophysiol. 2018;129:1410–7. https://doi.org/10.1016/j.clinph.2018.03.037.

    Article  PubMed  PubMed Central  Google Scholar 

  176. Trotti R, Parker D, McDowell JE, Pearlson G, Keshavan M, Keedy S, et al. Longitudinal stability of psychosis biomarkers: findings from the bipolar-schizophrenia network for intermediate phenotypes (B-SNIP). Biol Psychiatry. 2021;89:S124. https://doi.org/10.1016/j.biopsych.2021.02.321.

    Article  Google Scholar 

  177. Sellers KK, Stapper N, Astudillo Maya DA, Henderson C, Khambhati AN, Fan JM, et al. Changes in intracranial neurophysiology associated with acute COVID-19 infection. Clin Neurophysiol. 2023;148:29–31. https://doi.org/10.1016/j.clinph.2023.01.012.

    Article  PubMed  PubMed Central  Google Scholar 

  178. Katerndahl D, Ferrer R, Best R, Wang C-P. Dynamic patterns in mood among newly diagnosed patients with major depressive episode or panic disorder and normal controls. Prim Care Companion J Clin Psychiatry. 2007;9:183–7.

    Article  PubMed  PubMed Central  Google Scholar 

  179. Bosley HG, Soyster PD, Fisher AJ. Affect dynamics as predictors of symptom severity and treatment response in mood and anxiety disorders: evidence for specificity. J Pers Oriented Res. 2019;5:101–13. https://doi.org/10.17505/jpor.2019.09.

    Article  PubMed  PubMed Central  Google Scholar 

  180. Hosenfeld B, Bos EH, Wardenaar KJ, Conradi HJ, van der Maas HLJ, Visser I, et al. Major depressive disorder as a nonlinear dynamic system: bimodality in the frequency distribution of depressive symptoms over time. BMC Psychiatry. 2015;15:222. https://doi.org/10.1186/s12888-015-0596-5.

    Article  PubMed  PubMed Central  Google Scholar 

  181. Young MA, Fogg LF, Scheftner WA, Fawcett JA. Concordance of symptoms in recurrent depressive episodes. J Affect Disord. 1990;20:79–85. https://doi.org/10.1016/0165-327(90)90120-w.

    Article  CAS  PubMed  Google Scholar 

  182. Roberts RE, Lewinsohn PM, Seeley JR. Symptoms of DSM-III-R major depression in adolescence: evidence from an epidemiological survey. J Am Acad Child Adolesc Psychiatry. 1995;34:1608–17. https://doi.org/10.1097/00004583-199512000-00011.

    Article  CAS  PubMed  Google Scholar 

  183. Chai LR, Khambhati AN, Ciric R, Moore TM, Gur RC, Gur RE, et al. Evolution of brain network dynamics in neurodevelopment. Netw Neurosci. 2017;1:14–30. https://doi.org/10.1162/NETN_a_00001.

    Article  PubMed  PubMed Central  Google Scholar 

  184. Betzel RF, Byrge L, He Y, Goñi J, Zuo X-N, Sporns O. Changes in structural and functional connectivity among resting-state networks across the human lifespan. Neuroimage. 2014;102:345–57. https://doi.org/10.1016/j.neuroimage.2014.07.067.

    Article  PubMed  Google Scholar 

  185. Betzel RF, Satterthwaite TD, Gold JI, Bassett DS. Positive affect, surprise, and fatigue are correlates of network flexibility. Sci Rep. 2017;7:520. https://doi.org/10.1038/s41598-017-00425-z.

    Article  PubMed  PubMed Central  Google Scholar 

  186. Mirchi N, Betzel RF, Bernhardt BC, Dagher A, Mišic B. Tracking mood fluctuations with functional network patterns. Soc Cogn Affect Neurosci. 2019;14:47–57. https://doi.org/10.1093/scan/nsy107.

    Article  PubMed  Google Scholar 

  187. Fan JM, Khambhati AN, Sellers KK, Stapper N, Maya DA, Kunwar E, et al. (2023) Epileptiform discharges triggered with direct electrical stimulation for treatment-resistant depression: Factors that modulate risk and treatment considerations. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation 0: https://doi.org/10.1016/j.brs.2023.02.006.

  188. Rao VR, Sellers KK, Wallace DL, Lee MB, Bijanzadeh M, Sani OG, et al. Direct electrical stimulation of lateral orbitofrontal cortex acutely improves mood in individuals with symptoms of depression. Curr Biol. 2018;28:3893–3902.e4. https://doi.org/10.1016/j.cub.2018.10.026.

    Article  CAS  PubMed  Google Scholar 

  189. Keller CJ, Huang Y, Herrero JL, Fini ME, Du V, Lado FA, et al. Induction and quantification of excitability changes in human cortical networks. J Neurosci. 2018;38:5384–98. https://doi.org/10.1523/JNEUROSCI.1088-17.2018.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  190. Chiang S, Khambhati AN, Wang ET, Vannucci M, Chang EF, Rao VR. Evidence of state-dependence in the effectiveness of responsive neurostimulation for seizure modulation. Brain Stimul. 2021;14:366–75. https://doi.org/10.1016/j.brs.2021.01.023.

    Article  PubMed  PubMed Central  Google Scholar 

  191. Mohan UR, Watrous AJ, Miller JF, Lega BC, Sperling MR, Worrell GA, et al. The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity. Brain Stimul. 2020;13:1183–95. https://doi.org/10.1016/j.brs.2020.05.009.

    Article  PubMed  PubMed Central  Google Scholar 

  192. Patel DM, Walker HC, Brooks R, Omar N, Ditty B, Guthrie BL. Adverse events associated with deep brain stimulation for movement disorders analysis of 510 consecutive cases. Operative Neurosurg. 2015;11:190–9. https://doi.org/10.1227/neu.0000000000000659.

    Article  Google Scholar 

  193. Feldmann LK, Neumann W-J, Faust K, Schneider G-H, Kühn AA. Risk of infection after deep brain stimulation surgery with externalization and local-field potential recordings: twelve-year experience from a single institution. Stereotact Funct Neurosurg. 2021;99:512–20. https://doi.org/10.1159/000516150.

    Article  PubMed  Google Scholar 

  194. Vergani F, Landi A, Pirillo D, Cilia R, Antonini A, Sganzerla EP. Surgical, medical, and hardware adverse events in a series of 141 patients undergoing subthalamic deep brain stimulation for Parkinson Disease. World Neurosurg. 2010;73:338–44. https://doi.org/10.1016/j.wneu.2010.01.017.

    Article  PubMed  Google Scholar 

  195. Buhmann C, Huckhagel T, Engel K, Gulberti A, Hidding U, Poetter-Nerger M, et al. Adverse events in deep brain stimulation: a retrospective long-term analysis of neurological, psychiatric and other occurrences. PLoS ONE. 2017;12:e0178984. https://doi.org/10.1371/journal.pone.0178984.

    Article  PubMed  PubMed Central  Google Scholar 

  196. Dang J, King KM, Inzlicht M. Why are self-report and behavioral measures weakly correlated? Trends Cogn Sci. 2020;24:267–9. https://doi.org/10.1016/j.tics.2020.01.007.

    Article  PubMed  PubMed Central  Google Scholar 

  197. Ertugrul IO, Jeni LA, Ding W, Cohn JF. AFAR: A Deep Learning Based Tool for Automated Facial Affect Recognition. In: 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019). pp 1–1. 2019.

  198. Cohn JF, Okun MS, Jeni LA, Ertugrul IO, Borton D, Malone D, et al. Automated affect detection in deep brain stimulation for obsessive-compulsive disorder: a pilot study. Proc ACM Int Conf Multimodal Interact. 2018;2018:40–44. https://doi.org/10.1145/3242969.3243023.

    Article  PubMed  PubMed Central  Google Scholar 

  199. Hachem LD, Wong SM, Ibrahim GM. The vagus afferent network: emerging role in translational connectomics. Neurosurg Focus. 2018;45:E2. https://doi.org/10.3171/2018.6.FOCUS18216.

    Article  PubMed  Google Scholar 

  200. FDA Premarket Approval (PMA): VNS Therapy System. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P970003. Accessed 11 Feb 2023.

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Acknowledgements

The authors thank members of the Departments of Psychiatry and Behavioral Sciences, Neurology, and Neurological Surgery at the University of California, San Francisco for thoughtful discussion related to the present and future of therapeutic neurostimulation.

Funding

This work was supported by the Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at UCSF. JLC is funded by R25MH060482. JMF is funded by the Doris Duke Charitable Foundation (grant #2021090).

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KKS, JLC, ANK, JMF, AML, EFC, and ADK made substantial contributions to the conception or design of the work. KKS, JLC, ANK, JMF, AML and ADK drafted the work or revised it critically for important intellectual content. KKS, JLC, ANK, JMF, AML, EFC, and ADK approved the final version to be published. EFC and ADK agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Correspondence to Andrew D. Krystal.

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Competing interests

ADK Grant Support: Janssen Pharmaceuticals, Axsome Pharmaceutics, Attune, Harmony, Neurocrine Biosciences, Reveal Biosensors; Consulting; Axsome Therapeutics, Big Health, Eisai, Evecxia, Harmony Biosciences, Idorsia, Janssen Pharmaceuticals, Jazz Pharmaceuticals, Millenium Pharmaceuticals, Merck, Neurocrine Biosciences, Neurawell Therapeutics, Otsuka Pharmaceuticals, Sage, Takeda, Angelini, Genentech. JLC served as a consultant for OptionsMD. The other authors declare no competing interests.

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Sellers, K.K., Cohen, J.L., Khambhati, A.N. et al. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacol. 49, 163–178 (2024). https://doi.org/10.1038/s41386-023-01631-2

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