Abstract
Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine whether these circuits converge, we studied depression severity after brain lesions (n = 461, five datasets), transcranial magnetic stimulation (n = 151, four datasets) and deep brain stimulation (n = 101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets (P < 0.001). Circuits derived from lesions, deep brain stimulation and transcranial magnetic stimulation were similar (P < 0.0005), as were circuits derived from patients with major depression versus other diagnoses (P < 0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of transcranial magnetic stimulation and deep brain stimulation sites (P < 0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson’s disease (P < 0.05). We conclude that lesions, transcranial magnetic stimulation and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders.
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Data availability statement
This paper used de-identified data from 14 different datasets collected by 14 different teams of investigators at various institutions across four different countries. Each dataset is available upon reasonable request from each respective team of investigators. Data sharing will be subject to the policies and procedures of the institution where each dataset was collected as well as the laws of the country where each dataset was collected.
Code availability statement
All custom MATLAB code used in this study is available upon reasonable request from the corresponding author.
References
Czéh, B., Fuchs, E., Wiborg, O. & Simon, M. Animal models of major depression and their clinical implications. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 64, 293–310 (2016).
Etkin, A. Mapping causal circuitry in human depression. Biol. Psychiatry 86, 732–733 (2019).
Nestler, E. J. & Hyman, S. E. Animal models of neuropsychiatric disorders. Nat. Neurosci. 13, 1161–1169 (2010).
Monteggia, L. M., Heimer, H. & Nestler, E. J. Meeting report: can we make animal models of human mental illness? Biol. Psychiatry 84, 542–545 (2018).
Fox, M. D. Mapping symptoms to brain networks with the human connectome. N. Engl. J. Med 379, 2237–2245 (2018).
Siddiqi, S. H. et al. Distinct symptom-specific treatment targets for circuit-based neuromodulation. Am. J. Psychiatry 177, 435–446 (2020).
Padmanabhan, J. L. et al. A human depression circuit derived from focal brain lesions. Biol. Psychiatry https://doi.org/10.1016/j.biopsych.2019.07.023 (2019).
Weigand, A. et al. Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites. Biol. Psychiatry 84, 28–37 (2018).
Riva-Posse, P. et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol. Psychiatry 76, 963–969 (2014).
Etkin, A. Addressing the causality gap in human psychiatric neuroscience. JAMA Psychiatry 75, 3–4 (2018).
Ressler, K. J. & Mayberg, H. S. Targeting abnormal neural circuits in mood and anxiety disorders: from the laboratory to the clinic. Nat. Neurosci. 10, 1116–1124 (2007).
Matthews, P. M. & Hampshire, A. Clinical concepts emerging from fMRI functional connectomics. Neuron 91, 511–528 (2016).
Fox, M. D. et al. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proc. Natl Acad. Sci. USA 111, E4367–E4375 (2014).
Drysdale, A. T. et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat. Med. https://doi.org/10.1038/nm.4246 (2016).
Koenigs, M. et al. Focal brain damage protects against post-traumatic stress disorder in combat veterans. Nat. Neurosci. 11, 232–237, https://doi.org/10.1038/nn2032 (2008).
Johnson, K. A. et al. Prefrontal rTMS for treating depression: location and intensity results from the OPT-TMS multi-site clinical trial. Brain Stimul. 6, 108–117 (2013).
Taylor, S. F. et al. Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression. J. Affect Disord. 232, 143–151 (2018).
Cash, R. F. H. et al. Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: independent validation and evaluation of personalization. Biol. Psychiatry 86, e5–e7 (2019).
Horn, A. et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann. Neurol. 82, 67–78 (2017).
Dougherty, D. D. et al. A randomized sham-controlled trial of deep brain stimulation of the ventral capsule/ventral striatum for chronic treatment-resistant depression. Biol. Psychiatry 78, 240–248 (2015).
Irmen, F. et al. Left prefrontal impact links subthalamic stimulation with depressive symptoms. Ann. Neurol. https://doi.org/10.1002/ana.25734 (2020).
Merkl, A. et al. Antidepressant effects after short-term and chronic stimulation of the subgenual cingulate gyrus in treatment-resistant depression. Exp. Neurol. 249, 160–168 (2013).
Schaper, F. L. W. V. J. et al. Deep brain stimulation in epilepsy: a role for modulation of the mammillothalamic tract in seizure control? Neurosurgery 87, 602–610 (2020).
Yeo, B. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).
Bates, E. et al. Voxel-based lesion–symptom mapping. Nat. Neurosci. 6, 448–450 (2003).
Gourisankar, A. et al. Mapping movement, mood, motivation and mentation in the subthalamic nucleus. R. Soc. Open Sci. 5, 171177 (2018).
Choi, K. S., Riva-Posse, P., Gross, R. E. & Mayberg, H. S. Mapping the “depression switch” during intraoperative testing of subcallosal cingulate deep brain stimulation. JAMA Neurol. 72, 1252–1260 (2015).
Joutsa, J., Horn, A., Hsu, J. & Fox, M. D. Localizing parkinsonism based on focal brain lesions. Brain 141, 2445–2456 (2018).
Yang, C. et al. Repetitive transcranial magnetic stimulation therapy for motor recovery in Parkinson’s disease: a meta-analysis. Brain Behav. 8, e01132 (2018).
James, G. A. et al. Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects. NeuroImage 45, 778–787 (2009).
Mayberg, H. S. et al. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am. J. Psychiatry 156, 675–682 (1999).
Drevets, W. C. et al. Subgenual prefrontal cortex abnormalities in mood disorders. Nature 386, 824–827 (1997).
Müller, V. I. et al. Altered brain activity in unipolar depression revisited: meta-analyses of neuroimaging studies. JAMA Psychiatry 74, 47–55 (2017).
Gray, J. P., Müller, V. I., Eickhoff, S. B. & Fox, P. T. Multimodal abnormalities of brain structure and function in najor depressive disorder: a meta-analysis of neuroimaging studies. Am. J. Psychiatry 177, 422–434 (2020).
Williams, L. M. Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation. Depress. Anxiety 34, 9–24 (2017).
Holtzheimer, P. E. et al. Subcallosal cingulate deep brain stimulation for treatment-resistant depression: a multisite, randomised, sham-controlled trial. Lancet Psychiatry 4, 839–849 (2017).
Yesavage, J. A. et al. Effect of repetitive transcranial magnetic stimulation on treatment-resistant major depression in US veterans: a randomized clinical trial. JAMA Psychiatry 75, 884–893 (2018).
Kozak, M. J. & Cuthbert, B. N. The NIMH Research Domain Criteria initiative: background, issues, and pragmatics. Psychophysiology 53, 286–297 (2016).
Poldrack, R. A. Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding. Neuron 72, 692–697 (2011).
Cole, EleanorJ. et al. Stanford accelerated intelligent neuromodulation therapy for treatment-resistant depression. Am. J. Psychiatry https://doi.org/10.1176/appi.ajp.2019.19070720 (2020).
Blumberger, D. M. et al. Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): a randomised non-inferiority trial. Lancet 391, 1683–1692 (2018).
Cash, R. F. H. et al. Using brain imaging to improve spatial targeting of transcranial magnetic stimulation for depression. Biol. Psychiatry https://doi.org/10.1016/j.biopsych.2020.05.033 (2020).
Cash, R. F. H., Cocchi, L., Lv, J., Fitzgerald, P. B. & Zalesky, A. Functional magnetic resonance imaging-guided personalization of transcranial magnetic stimulation treatment for depression. JAMA Psychiatry, https://doi.org/10.1001/jamapsychiatry.2020.3794 (2020).
Siddiqi, S. H., Weigand, A., Pascual-Leone, A. & Fox, M. D. Identification of personalized TMS targets based on subgenual cingulate connectivity: an independent replication. Biol. Psychiatry https://doi.org/10.1016/j.biopsych.2021.02.015 (2021).
Riva-Posse, P. et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol. Psychiatry 23, 843–849 (2018).
Fox, M. D., Liu, H. & Pascual-Leone, A. Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity. Neuroimage 66, 151–160 (2013).
Opitz, A., Fox, M. D., Craddock, R. C., Colcombe, S. & Milham, M. P. An integrated framework for targeting functional networks via transcranial magnetic stimulation. Neuroimage 127, 86–96 (2016).
Rouder, J. N. & Morey, R. D. Default Bayes factors for model selection in regression. Multivar. Behav. Res. 47, 877–903 (2012).
Wagenmakers, E.-J., Verhagen, J. & Ly, A. How to quantify the evidence for the absence of a correlation. Behav. Res. Methods 48, 413–426 (2016).
Turner, J. A. et al. A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia. Front Neurosci. 7, 137 (2013).
Slotnick, S. D. Cluster success: fMRI inferences for spatial extent have acceptable false-positive rates. Cogn. Neurosci. 8, 150–155 (2017).
Acknowledgements
The authors thank all research participants, funding bodies, allied health staff and other research staff that made this work possible. The present work was supported by the Sidney R. Baer Foundation (S.H.S., J.L.P., M.D.F.), the Brain & Behavior Research Foundation (SHS) and the National Institute of Mental Health (grant no. K23MH121657 to S.H.S.; grant nos. R01MH113929 and R01MH115949 to M.D.F.). The funders were not directly involved in the conceptualization, design, data collection, analysis, decision to publish or preparation of the manuscript.
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Conception and design of study: S.H.S., A.H. and M.D.F. Design of analytical procedures: S.H.S. and M.D.F. Neuroimaging analyses and statistical analyses: S.H.S. Preprocessing and preparation of data for analysis: S.H.S., A.H., J.H., J.L.P. and F.S. Contribution of data: A.H., F.S., R.F.H.C., A.B., K.A.J., N.E., A.M.N., S.G., T.G.P., K.S.C., F.I., A.K., P.B.F., M.S.G., R.P.W.R., S.F.T., A.Z., J.L.V., M.C., D.D.D., A.P.-L., J.H.G., H.S.M. and M.D.F. Writing of manuscript: S.H.S. and M.D.F. with input from all authors.
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S.H.S. serves as a clinical consultant for Kaizen Brain Center. S.H.S. and M.D.F. have jointly received investigator-initiated research support from Neuronetics. None of these organizations were involved in the present work. S.H.S. and M.D.F. each own independent intellectual property on the use of brain network mapping to target neuromodulation. The present work did not utilize any of this intellectual property. The authors report no other conflicts of interest related to the present work.
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Siddiqi, S.H., Schaper, F.L.W.V.J., Horn, A. et al. Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease. Nat Hum Behav 5, 1707–1716 (2021). https://doi.org/10.1038/s41562-021-01161-1
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DOI: https://doi.org/10.1038/s41562-021-01161-1
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