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Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression

  • Robin F.H. Cash
    Correspondence
    Address correspondence to Robin F.H. Cash, Ph.D.
    Affiliations
    Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia

    Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia
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  • Anne Weigand
    Affiliations
    Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts

    Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
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  • Andrew Zalesky
    Affiliations
    Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia

    Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia
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  • Shan H. Siddiqi
    Affiliations
    Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts

    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts

    Division of Neurotherapeutics, McLean Hospital, Belmont, Massachusetts
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  • Jonathan Downar
    Affiliations
    Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

    Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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  • Paul B. Fitzgerald
    Affiliations
    Epworth Centre for Innovation and Mental Health, Epworth Healthcare and Monash University Central Clinical School, Camberwell, Victoria, Australia
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  • Michael D. Fox
    Correspondence
    Michael D. Fox, M.D., Ph.D.
    Affiliations
    Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts

    Departments of Neurology and Radiology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts

    Departments of Neurology, Psychiatry, and Radiology, Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Boston, Massachusetts
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      Abstract

      Transcranial magnetic stimulation (TMS) is an effective treatment for depression but is limited in that the optimal therapeutic target remains unknown. Early TMS trials lacked a focal target and thus positioned the TMS coil over the prefrontal cortex using scalp measurements. Over time, it became clear that this method leads to variation in the stimulation site and that this could contribute to heterogeneity in antidepressant response. Newer methods allow for precise positioning of the TMS coil over a specific brain location, but leveraging these precise methods requires a more precise therapeutic target. We review how neuroimaging is being used to identify a more focal therapeutic target for depression. We highlight recent studies showing that more effective TMS targets in the frontal cortex are functionally connected to deep limbic regions such as the subgenual cingulate cortex. We review how connectivity might be used to identify an optimal TMS target for use in all patients and potentially even a personalized target for each individual patient. We address the clinical implications of this emerging field and highlight critical questions for future research.

      Keywords

      Therapeutic Brain Stimulation for Depression

      Major depressive disorder affects approximately 1 in 5 individuals and 350 million people worldwide and is the leading cause of years lived with disability (
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      The costs of depression.
      ). As few as 30% of patients achieve remission with first-line therapies (
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      • Stewart J.W.
      • Warden D.
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      Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR∗D report.
      ). Individuals who fail multiple treatments are classified as having treatment-resistant depression, and these patients are unlikely to respond to further medication trials (
      • Rush A.J.
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      • Stewart J.W.
      • Warden D.
      • et al.
      Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR∗D report.
      ). Repetitive transcranial magnetic stimulation (rTMS) is an established, safe, and efficacious treatment approved by the U.S. Food and Drug Administration that can alleviate symptoms in patients with treatment-resistant depression (
      • Fitzgerald P.B.
      • Hoy K.E.
      • Anderson R.J.
      • Daskalakis Z.J.
      A study of the pattern of response to rTMS treatment in depression.
      ). It involves focal magnetic stimulation applied externally to the scalp, typically at the dorsolateral prefrontal cortex (DLPFC), which induces electrical stimulation in underlying cortical tissue. The most commonly used clinical TMS coils are figure eight coils, which have a relatively focal stimulation field and will be the focus of this review. However, less focal TMS coils exist, an important topic that is addressed in the Supplement.
      While rTMS is effective for some individuals, many others with similar clinical profiles receive little benefit. Typical response rates, defined as >50% reduction in depression score, and remission rates, defined as a post-TMS depression score below the level that qualifies for depression, are typically between 29% and 46% (response) and 18% and 31% (remission) (
      • Fitzgerald P.B.
      • Hoy K.E.
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      • Daskalakis Z.J.
      A study of the pattern of response to rTMS treatment in depression.
      ,
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      Response, remission and drop-out rates following high-frequency repetitive transcranial magnetic stimulation (rTMS) for treating major depression: A systematic review and meta-analysis of randomized, double-blind and sham-controlled trials.
      ). Although therapeutic response is clinically meaningful, particularly in a treatment-refractory population, remission should be considered the ultimate goal. Research efforts over the past 2 decades have aimed to improve the efficacy and consistency of treatment effects across individuals. While optimal stimulation parameters and dosing are important, one major source of interindividual heterogeneity in treatment outcomes arises from variation in the stimulated site across the spatial extent of the DLPFC (
      • Cash R.F.H.
      • Zalesky A.
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      • Tian Y.
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      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
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      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
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      Comparison of “standard” and “navigated” procedures of TMS coil positioning over motor, premotor and prefrontal targets in patients with chronic pain and depression.
      ).
      Therapeutic targets for the treatment of depression using rTMS have been informed and guided by neuroimaging since its clinical inception in the mid-1990s (Figure 1). Early studies of patients with stroke and tumors suggested that the risk of depression increased with left prefrontal lesions [for further discussion see (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
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      • Cooke D.
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      • Ferguson M.
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      A human depression circuit derived from focal brain lesions.
      ,
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      • Ketter T.A.
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      Prefrontal cortex dysfunction in clinical depression.
      )]. Functional neuroimaging studies in primary depression reported hypometabolism in the left prefrontal cortex that improved with successful antidepressant treatment (
      • George M.S.
      • Ketter T.A.
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      Prefrontal cortex dysfunction in clinical depression.
      ). As such, early rTMS studies targeted the left DLPFC commensurate with our neuroanatomical knowledge of depression (
      • George M.S.
      • Wassermann E.M.
      • Williams W.A.
      • Callahan A.
      • Ketter T.A.
      • Basser P.
      • et al.
      Daily repetitive transcranial magnetic stimulation (rTMS) improves mood in depression.
      ,
      • Pascual-Leone A.
      • Rubio B.
      • Pallardo F.
      • Catala M.D.
      Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression.
      ).
      Figure thumbnail gr1
      Figure 1Evolution of transcranial magnetic stimulation (TMS) targeting approaches for the treatment of depression. This timeline is intended to be conceptual, as research efforts into different targeting approaches have overlapped considerably. Scalp-based measures identified the dorsolateral prefrontal cortex stimulation site as 5–6 cm anterior to the motor cortical hotspot (A) or based on the electroencephalography (EEG) 10-20 system to account for interindividual differences in skull dimensions (B). Neuronavigated approaches were implemented to target an anatomical coordinate in the dorsolateral prefrontal cortex implicated in depression based on prior functional neuroimaging studies (C) or based on positron emission tomography (PET) imaging in individual patients (D). Recent studies suggest that repetitive TMS (rTMS) treatment response is related to resting-state functional connectivity (FC) between the dorsolateral prefrontal cortex stimulation site and subgenual cingulate cortex (SGC), leading to a connectivity-based rTMS target (E). Future research toward precision psychiatry may include connectivity-based rTMS targets that are individualized based on symptoms or patient-specific connectivity (F). BA, Brodmann area; MNI, Montreal Neurological Institute. [Panels (D) and (E) adapted from Weigand et al. (
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ), Paillere Martinot et al. (
      • Paillere Martinot M.L.
      • Galinowski A.
      • Ringuenet D.
      • Gallarda T.
      • Lefaucheur J.P.
      • Bellivier F.
      • et al.
      Influence of prefrontal target region on the efficacy of repetitive transcranial magnetic stimulation in patients with medication-resistant depression: A [(18)F]-fluorodeoxyglucose PET and MRI study.
      ), and Fox et al. (
      • Fox M.D.
      • Halko M.A.
      • Eldaief M.C.
      • Pascual-Leone A.
      Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS).
      ).]
      Over time, it became clear that the left DLPFC is highly heterogeneous, and response rates may depend on exactly where in the DLPFC one administers rTMS (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Herbsman T.
      • Avery D.
      • Ramsey D.
      • Holtzheimer P.
      • Wadjik C.
      • Hardaway F.
      • et al.
      More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response.
      ,
      • Fitzgerald P.B.
      • Hoy K.
      • McQueen S.
      • Maller J.J.
      • Herring S.
      • Segrave R.
      • et al.
      A randomized trial of rTMS targeted with MRI based neuro-navigation in treatment-resistant depression.
      ). Lesion and metabolic neuroimaging studies failed to replicate the simple association between the left DLPFC and depression (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ,
      • Starkstein S.E.
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      • Honig M.A.
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      • Joselyn J.
      • Price T.R.
      Mood changes after right-hemisphere lesions.
      ). More importantly, psychiatric disorders began to be conceptualized as disorders of brain networks, not individual brain regions (
      • Shafi M.M.
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      • Fox M.D.
      • Pascual-Leone A.
      Exploration and modulation of brain network interactions with noninvasive brain stimulation in combination with neuroimaging.
      ,
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      Opportunities and challenges for psychiatry in the connectomic era.
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      ,
      • Liston C.
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      • Zebley B.D.
      • Drysdale A.T.
      • Gordon R.
      • Leuchter B.
      • et al.
      Default mode network mechanisms of transcranial magnetic stimulation in depression.
      ). Similarly, rTMS began to be conceptualized as a network therapy—although stimulation is commonly applied to a single brain region, its effects are mediated via distributed networks (
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Halko M.A.
      • Farzan F.
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      Intermittent theta-burst stimulation of the lateral cerebellum increases functional connectivity of the default network.
      ,
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      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Castrillon G.
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      The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex.
      ). Advances in mapping brain networks and brain connectivity now allow us to identify these networks and potentially refine our therapeutic targets for depression (
      • Berlim M.T.
      • van den Eynde F.
      • Tovar-Perdomo S.
      • Daskalakis Z.J.
      Response, remission and drop-out rates following high-frequency repetitive transcranial magnetic stimulation (rTMS) for treating major depression: A systematic review and meta-analysis of randomized, double-blind and sham-controlled trials.
      ,
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Hawco C.
      • Voineskos A.N.
      • Steeves J.K.E.
      • Dickie E.W.
      • Viviano J.D.
      • Downar J.
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      Spread of activity following TMS is related to intrinsic resting connectivity to the salience network: A concurrent TMS-fMRI study.
      ,
      • Fox M.D.
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      • Pascual-Leone A.
      Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.
      ). This review describes the evolution of therapeutic targeting strategies in depression and new developments in this area.

      Targeting TMS Using Scalp Measurements

      The first clinical investigations of rTMS for depression identified the DLPFC target site as being 5 cm anterior to the motor cortical hotspot (
      • George M.S.
      • Wassermann E.M.
      • Williams W.A.
      • Callahan A.
      • Ketter T.A.
      • Basser P.
      • et al.
      Daily repetitive transcranial magnetic stimulation (rTMS) improves mood in depression.
      ,
      • Pascual-Leone A.
      • Rubio B.
      • Pallardo F.
      • Catala M.D.
      Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression.
      ), overlying Brodmann area (BA) 46 and BA 9 in the Talairach atlas (
      • George M.S.
      • Wassermann E.M.
      • Williams W.A.
      • Callahan A.
      • Ketter T.A.
      • Basser P.
      • et al.
      Daily repetitive transcranial magnetic stimulation (rTMS) improves mood in depression.
      ,
      • Pascual-Leone A.
      • Rubio B.
      • Pallardo F.
      • Catala M.D.
      Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression.
      ). This 5-cm method was subsequently used in larger clinical trials that led to Food and Drug Administration approval (
      • George M.S.
      • Wassermann E.M.
      • Kimbrell T.A.
      • Little J.T.
      • Williams W.E.
      • Danielson A.L.
      • et al.
      Mood improvement following daily left prefrontal repetitive transcranial magnetic stimulation in patients with depression: A placebo-controlled crossover trial.
      ,
      • O’Reardon J.P.
      • Solvason H.B.
      • Janicak P.G.
      • Sampson S.
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      • Nahas Z.
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      Efficacy and safety of transcranial magnetic stimulation in the acute treatment of major depression: A multisite randomized controlled trial.
      ,
      • Herwig U.
      • Fallgatter A.J.
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      • Eschweiler G.W.
      • Kron M.
      • Hajak G.
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      Antidepressant effects of augmentative transcranial magnetic stimulation: Randomised multicentre trial.
      ). However, this approach does not account for differences in head dimensions or anatomy, leading to stimulation of the premotor cortex or frontal eye fields in a large percentage of patients (
      • Herbsman T.
      • Avery D.
      • Ramsey D.
      • Holtzheimer P.
      • Wadjik C.
      • Hardaway F.
      • et al.
      More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response.
      ,
      • Herwig U.
      • Padberg F.
      • Unger J.
      • Spitzer M.
      • Schonfeldt-Lecuona C.
      Transcranial magnetic stimulation in therapy studies: Examination of the reliability of “standard” coil positioning by neuronavigation.
      ,
      • Ahdab R.
      • Ayache S.S.
      • Brugieres P.
      • Goujon C.
      • Lefaucheur J.P.
      Comparison of “standard” and “navigated” procedures of TMS coil positioning over motor, premotor and prefrontal targets in patients with chronic pain and depression.
      ,
      • George M.S.
      • Lisanby S.H.
      • Avery D.
      • McDonald W.M.
      • Durkalski V.
      • Pavlicova M.
      • et al.
      Daily left prefrontal transcranial magnetic stimulation therapy for major depressive disorder: A sham-controlled randomized trial.
      ). Many clinical centers therefore adopted 5.5 or 6 cm to move the average stimulation site more anterior and lateral (
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Herbsman T.
      • Avery D.
      • Ramsey D.
      • Holtzheimer P.
      • Wadjik C.
      • Hardaway F.
      • et al.
      More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response.
      ,
      • Fitzgerald P.B.
      • Daskalakis Z.J.
      Repetitive Transcranial Magnetic Stimulation Treatment for Depressive Disorders: A Practical Guide.
      ,
      • Brunoni A.R.
      • Chaimani A.
      • Moffa A.H.
      • Razza L.B.
      • Gattaz W.F.
      • Daskalakis Z.J.
      • et al.
      Repetitive transcranial magnetic stimulation for the acute treatment of major depressive episodes: A systematic review with network meta-analysis.
      ). Recent work estimates that the intersection of BA 9 and BA 46 is actually 6.9 cm anterior to the motor hotspot, but this has not been adopted clinically (
      • Ahdab R.
      • Ayache S.S.
      • Brugieres P.
      • Goujon C.
      • Lefaucheur J.P.
      Comparison of “standard” and “navigated” procedures of TMS coil positioning over motor, premotor and prefrontal targets in patients with chronic pain and depression.
      ). It is also perhaps worth noting that the areal delineation of BA 9 and BA 46 has been redefined several times (
      • Sarkissov S.
      • Filimonoff I.
      • Kononowa E.
      • Preobraschenskaja I.
      • Kukuew L.
      Atlas of the Cytoarchitectonics of the Human Cerebral Cortex.
      ,
      • Rajkowska G.
      • Goldman-Rakic P.S.
      Cytoarchitectonic definition of prefrontal areas in the normal human cortex: I. Remapping of areas 9 and 46 using quantitative criteria.
      ,
      • von Economo C.F.
      • Koskinas G.N.
      Die Cytoarchitektonik der Hirnrinde des Erwachsenen Menschen.
      ) since originally parcellated by Brodmann in 1909 (
      • Brodmann K.
      Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues.
      ) and is highly variable across individuals (
      • Rajkowska G.
      • Goldman-Rakic P.S.
      Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System.
      ). The 5- to 6-cm approach has been the most commonly employed targeting method, accounting for 84% of randomized clinical trials as of 2016 (5 cm: 75%; 6 cm: 9%) [computed from supplemental information in (
      • Brunoni A.R.
      • Chaimani A.
      • Moffa A.H.
      • Razza L.B.
      • Gattaz W.F.
      • Daskalakis Z.J.
      • et al.
      Repetitive transcranial magnetic stimulation for the acute treatment of major depressive episodes: A systematic review with network meta-analysis.
      )].
      A newer targeting approach based on the 10-20 electroencephalography system has been proposed to account for variation in individual skull dimensions. Coregistration of electroencephalography electrode positions with anatomical magnetic resonance imaging (MRI) suggests that the electrode position 1 cm anterolateral to F3 (
      • Herwig U.
      • Satrapi P.
      • Schönfeldt-Lecuona C.
      Using the International 10-20 EEG System for positioning of transcranial magnetic stimulation.
      ), between F3 and F5 (
      • Rusjan P.M.
      • Barr M.S.
      • Farzan F.
      • Arenovich T.
      • Maller J.J.
      • Fitzgerald P.B.
      • et al.
      Optimal transcranial magnetic stimulation coil placement for targeting the dorsolateral prefrontal cortex using novel magnetic resonance image-guided neuronavigation.
      ), or between AF3 and F3 would reliably target the DLPFC (Figure 2) (
      • Fitzgerald P.B.
      • Maller J.J.
      • Hoy K.E.
      • Thomson R.
      • Daskalakis Z.J.
      Exploring the optimal site for the localization of dorsolateral prefrontal cortex in brain stimulation experiments.
      ). Software has since been developed to estimate the F3 electrode position based on only a few scalp measurements (Beam F3) (
      • Beam W.
      • Borckardt J.J.
      • Reeves S.T.
      • George M.S.
      An efficient and accurate new method for locating the F3 position for prefrontal TMS applications.
      ,
      • Mir-Moghtadaei A.
      • Caballero R.
      • Fried P.
      • Fox M.D.
      • Lee K.
      • Giacobbe P.
      • et al.
      Concordance between BeamF3 and MRI-neuronavigated target sites for repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex.
      ). This approach has seen widespread clinical implementation, is located with high reliability (
      • Trapp N.T.
      • Bruss J.
      • Johnson M.K.
      • Uitermarkt B.D.
      • Garrett L.
      • Heinzerling A.
      • et al.
      Reliability of targeting methods in TMS for depression: Beam F3 vs. 5.5 cm.
      ), and is endorsed by the Clinical TMS Society (
      • McClintock S.M.
      • Reti I.M.
      • Carpenter L.L.
      • McDonald W.M.
      • Dubin M.
      • Taylor S.F.
      • et al.
      Consensus recommendations for the clinical application of repetitive transcranial magnetic stimulation (rTMS) in the treatment of depression.
      ). However, this targeting approach has not yet been validated in double-blinded randomized trials as the 5- to 6-cm method has. Further, although this technique ensures that the DLPFC is more consistently targeted (
      • Herwig U.
      • Satrapi P.
      • Schönfeldt-Lecuona C.
      Using the International 10-20 EEG System for positioning of transcranial magnetic stimulation.
      ,
      • Fitzgerald P.B.
      • Maller J.J.
      • Hoy K.E.
      • Thomson R.
      • Daskalakis Z.J.
      Exploring the optimal site for the localization of dorsolateral prefrontal cortex in brain stimulation experiments.
      ,
      • Mir-Moghtadaei A.
      • Caballero R.
      • Fried P.
      • Fox M.D.
      • Lee K.
      • Giacobbe P.
      • et al.
      Concordance between BeamF3 and MRI-neuronavigated target sites for repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex.
      ), and the more anterolateral sites of the DLPFC selected by this approach are understood to be more effective (Figure S2) (
      • Herbsman T.
      • Avery D.
      • Ramsey D.
      • Holtzheimer P.
      • Wadjik C.
      • Hardaway F.
      • et al.
      More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response.
      ), clear gains in antidepressant efficacy remain to be demonstrated [e.g., (
      • Fitzgerald P.B.
      • Hoy K.E.
      • Anderson R.J.
      • Daskalakis Z.J.
      A study of the pattern of response to rTMS treatment in depression.
      ,
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      )]. Another point of interest is the only marginal extent of spatial overlap between targets derived from the 5.5-cm and Beam F3 targeting methods (Figure 2). Given this spatial difference, future work should directly compare these targeting methods to determine if there are differences in antidepressant response or side effects.
      Figure thumbnail gr2
      Figure 2Heterogeneity in transcranial magnetic stimulation (TMS) sites for depression. (A) The distributions of cortical targets derived from the 5.5-cm (Boston cohort; blue) and Beam F3 targeting approaches (Melbourne cohort; red) are depicted. Sites are shown overlaid on a map of resting-state functional connectivity (FC) with the subgenual cingulate cortex. There is relatively little spatial overlap between the sites derived from these 2 targeting methods. Average group coordinates are depicted as larger spheres. The Boston and Melbourne data are derived from open-label studies (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ). (B) Various cortical repetitive TMS targets proposed or used for the treatment of depression are depicted. Note the divergence between the electroencephalography (EEG) F3 coordinates across different studies [compare sites 9–11 (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Herwig U.
      • Satrapi P.
      • Schönfeldt-Lecuona C.
      Using the International 10-20 EEG System for positioning of transcranial magnetic stimulation.
      ,
      • Okamoto M.
      • Dan H.
      • Sakamoto K.
      • Takeo K.
      • Shimizu K.
      • Kohno S.
      • et al.
      Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping.
      )]. Recent studies have proposed coordinates that converge on a more anterolateral site defined by functional connectivity with the subgenual cingulate cortex [sites 12–15 (
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Cash R.
      • Cocchi L.
      • Fitzgerald P.
      • Zalesky A.
      Precision psychiatry: Development of methodology for personalized therapeutic brain stimulation. Program No. 684.09. 2019 Neuroscience Meeting Planner.
      )]. TMS e-fields (detailed in ) are larger than the depicted spheres, which are intended only to indicate the relative spatial positioning of stimulation sites across studies. BA, Brodmann area.

      Targeting TMS Based on Brain Structure, Function, and Metabolism

      Targeting TMS based on scalp-based measures is reasonable if the target is rather broadly defined as the left DLPFC. However, as our knowledge regarding the neuroanatomy of depression increases, more accurate targeting of TMS is warranted. In one of the first examples of this approach, Fitzgerald et al. (
      • Fitzgerald P.B.
      • Laird A.R.
      • Maller J.
      • Daskalakis Z.J.
      A meta-analytic study of changes in brain activation in depression.
      ) conducted a meta-analysis of functional imaging studies of depression to identify a precise coordinate in the left DLPFC that was most consistently abnormal. The authors then used neuronavigated TMS to target this coordinate in patients with depression. Neuronavigation enables the TMS coil to be positioned to target specific anatomical sites based on an individual subject’s structural brain images. Both the neuronavigated and the conventional 5-cm approaches yielded reductions in depression severity; however, there was no significant interaction between targeting approach and clinical trajectory across the two cohorts, nor was there clear decrease in response variability across individuals (
      • Fitzgerald P.B.
      • Hoy K.
      • McQueen S.
      • Maller J.J.
      • Herring S.
      • Segrave R.
      • et al.
      A randomized trial of rTMS targeted with MRI based neuro-navigation in treatment-resistant depression.
      ). Nonetheless, the neuronavigated approach appeared to be more effective at a trend level, resulting in an overall reduction in symptom severity of approximately 49% compared with the 27% observed with the 5-cm approach [recomputed from the absolute values of clinical scores presented in (
      • Fitzgerald P.B.
      • Hoy K.
      • McQueen S.
      • Maller J.J.
      • Herring S.
      • Segrave R.
      • et al.
      A randomized trial of rTMS targeted with MRI based neuro-navigation in treatment-resistant depression.
      )]. Other studies targeting this anatomical location found it to be better than sham conditions (
      • Paillere Martinot M.L.
      • Galinowski A.
      • Ringuenet D.
      • Gallarda T.
      • Lefaucheur J.P.
      • Bellivier F.
      • et al.
      Influence of prefrontal target region on the efficacy of repetitive transcranial magnetic stimulation in patients with medication-resistant depression: A [(18)F]-fluorodeoxyglucose PET and MRI study.
      ) [although see (
      • Duprat R.
      • Desmyter S.
      • Rudi de R.
      • van Heeringen K.
      • Van den Abbeele D.
      • Tandt H.
      • et al.
      Accelerated intermittent theta burst stimulation treatment in medication-resistant major depression: A fast road to remission?.
      )], but likewise failed to demonstrate superiority relative to conventional scalp-based targeting (
      • Li C.T.
      • Cheng C.M.
      • Chen M.H.
      • Juan C.H.
      • Tu P.C.
      • Bai Y.M.
      • et al.
      Antidepressant efficacy of prolonged intermittent theta burst stimulation monotherapy for recurrent depression and comparison of methods for coil positioning: A randomized, double-blind, sham-controlled study.
      ,
      • Blumberger D.M.
      • Maller J.J.
      • Thomson L.
      • Mulsant B.H.
      • Rajji T.K.
      • Maher M.
      • et al.
      Unilateral and bilateral MRI-targeted repetitive transcranial magnetic stimulation for treatment-resistant depression: A randomized controlled study.
      ). Interestingly, adjusting stimulus intensity to account for individual scalp-to-cortex distance did not enhance the effects of anatomical targeting (
      • Blumberger D.M.
      • Maller J.J.
      • Thomson L.
      • Mulsant B.H.
      • Rajji T.K.
      • Maher M.
      • et al.
      Unilateral and bilateral MRI-targeted repetitive transcranial magnetic stimulation for treatment-resistant depression: A randomized controlled study.
      ). This might be because while TMS effects are often dependent on intensity, cortical thresholds or reactivity may differ or even be unrelated across brain regions (
      • Stewart L.
      • Walsh V.
      • Rothwell J.
      Motor and phosphene thresholds: A transcranial magnetic stimulation correlation study.
      ,
      • Gerwig M.
      • Kastrup O.
      • Meyer B.U.
      • Niehaus L.
      Evaluation of cortical excitability by motor and phosphene thresholds in transcranial magnetic stimulation.
      ,
      • Lioumis P.
      • Kicic D.
      • Savolainen P.
      • Makela J.P.
      • Kahkonen S.
      Reproducibility of TMS-evoked EEG responses.
      ), presenting a potential caveat for current clinical practice. In any case, these studies do not provide clear support for the superiority of TMS targeting this anatomical location for depression, possibly because these studies were underpowered, the optimal anatomical target differs from that employed above (
      • Blumberger D.M.
      • Vila-Rodriguez F.
      • Thorpe K.E.
      • Feffer K.
      • Noda Y.
      • Giacobbe P.
      • et al.
      Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): A randomised non-inferiority trial.
      ), or anatomical targeting does not address individual variation in DLPFC functional organization (
      • Rajkowska G.
      • Goldman-Rakic P.S.
      Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System.
      ,
      • Finn E.S.
      • Shen X.
      • Scheinost D.
      • Rosenberg M.D.
      • Huang J.
      • Chun M.M.
      • et al.
      Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity.
      ,
      • Fischl B.
      • Rajendran N.
      • Busa E.
      • Augustinack J.
      • Hinds O.
      • Yeo B.T.
      • et al.
      Cortical folding patterns and predicting cytoarchitecture.
      ,
      • Mueller S.
      • Wang D.
      • Fox M.D.
      • Yeo B.T.
      • Sepulcre J.
      • Sabuncu M.R.
      • et al.
      Individual variability in functional connectivity architecture of the human brain.
      ).
      Other groups have tried to improve TMS for depression by targeting individual differences in metabolism [for review of metabolic abnormalities see (
      • Herwig U.
      • Lampe Y.
      • Juengling F.D.
      • Wunderlich A.
      • Walter H.
      • Spitzer M.
      • et al.
      Add-on rTMS for treatment of depression: A pilot study using stereotaxic coil-navigation according to PET data.
      ,
      • George M.S.
      • Ketter T.A.
      • Post R.M.
      Prefrontal cortex dysfunction in clinical depression.
      ,
      • Kimbrell T.A.
      • Little J.T.
      • Dunn R.T.
      • Frye M.A.
      • Greenberg B.D.
      • Wassermann E.M.
      • et al.
      Frequency dependence of antidepressant response to left prefrontal repetitive transcranial magnetic stimulation (rTMS) as a function of baseline cerebral glucose metabolism.
      )]. In one such study, the site of maximum hypometabolism in the DLPFC was first localized using a positron emission tomography scan for each individual and then targeted using high-frequency rTMS. However, neither this study (
      • Paillere Martinot M.L.
      • Galinowski A.
      • Ringuenet D.
      • Gallarda T.
      • Lefaucheur J.P.
      • Bellivier F.
      • et al.
      Influence of prefrontal target region on the efficacy of repetitive transcranial magnetic stimulation in patients with medication-resistant depression: A [(18)F]-fluorodeoxyglucose PET and MRI study.
      ) nor other similar studies (
      • Herwig U.
      • Lampe Y.
      • Juengling F.D.
      • Wunderlich A.
      • Walter H.
      • Spitzer M.
      • et al.
      Add-on rTMS for treatment of depression: A pilot study using stereotaxic coil-navigation according to PET data.
      ,
      • Garcia-Toro M.
      • Salva J.
      • Daumal J.
      • Andres J.
      • Romera M.
      • Lafau O.
      • et al.
      High (20-Hz) and low (1-Hz) frequency transcranial magnetic stimulation as adjuvant treatment in medication-resistant depression.
      ) were able to demonstrate superiority of this approach relative to conventional targeting approaches. Possible reasons for the failure of this approach include poor spatial resolution of positron emission tomography imaging (
      • Greicius M.D.
      • Flores B.H.
      • Menon V.
      • Glover G.H.
      • Solvason H.B.
      • Kenna H.
      • et al.
      Resting-state functional connectivity in major depression: Abnormally increased contributions from subgenual cingulate cortex and thalamus.
      ), unknown reproducibility of the targets, or the fact that individual foci of prefrontal hypometabolism are not the best antidepressant target. Interestingly, the hypometabolic maximum was located in the right DLPFC in 33% (
      • Paillere Martinot M.L.
      • Galinowski A.
      • Ringuenet D.
      • Gallarda T.
      • Lefaucheur J.P.
      • Bellivier F.
      • et al.
      Influence of prefrontal target region on the efficacy of repetitive transcranial magnetic stimulation in patients with medication-resistant depression: A [(18)F]-fluorodeoxyglucose PET and MRI study.
      ) to 73% (
      • Herwig U.
      • Lampe Y.
      • Juengling F.D.
      • Wunderlich A.
      • Walter H.
      • Spitzer M.
      • et al.
      Add-on rTMS for treatment of depression: A pilot study using stereotaxic coil-navigation according to PET data.
      ) of individuals, which challenges the traditional valence hypotheses of mood lateralization in depression, in line with other recent studies (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Starkstein S.E.
      • Robinson R.G.
      • Honig M.A.
      • Parikh R.M.
      • Joselyn J.
      • Price T.R.
      Mood changes after right-hemisphere lesions.
      ,
      • van der Vinne N.
      • Vollebregt M.A.
      • van Putten M.
      • Arns M.
      Frontal alpha asymmetry as a diagnostic marker in depression: Fact or fiction? A meta-analysis.
      ,
      • Fitzgerald P.B.
      • Brown T.L.
      • Marston N.A.
      • Daskalakis Z.J.
      • de Castella A.
      • Bradshaw J.L.
      • et al.
      Motor cortical excitability and clinical response to rTMS in depression.
      ,
      • Carson A.J.
      • MacHale S.
      • Allen K.
      • Lawrie S.M.
      • Dennis M.
      • House A.
      • et al.
      Depression after stroke and lesion location: A systematic review.
      ,
      • Schiffer F.
      • Teicher M.H.
      • Anderson C.
      • Tomoda A.
      • Polcari A.
      • Navalta C.P.
      • et al.
      Determination of hemispheric emotional valence in individual subjects: A new approach with research and therapeutic implications.
      ).
      Finally, at least 1 trial of TMS for depression has targeted individualized sites of functional MRI (fMRI) activation. This trial used an n-back working memory task to identify individualized TMS targets for each patient, but failed to show a difference in antidepressant response or imaging biomarkers relative to sham (
      • Taylor S.F.
      • Ho S.S.
      • Abagis T.
      • Angstadt M.
      • Maixner D.F.
      • Welsh R.C.
      • et al.
      Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression.
      ).

      Brain Stimulation in the Connectomics Era

      Localization of psychiatric symptoms, including depression, has gradually shifted from a focus on individual brain regions, such as the DLPFC, to a focus on distributed brain networks (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Fornito A.
      • Bullmore E.T.
      • Zalesky A.
      Opportunities and challenges for psychiatry in the connectomic era.
      ,
      • Kaiser R.H.
      • Andrews-Hanna J.R.
      • Wager T.D.
      • Pizzagalli D.A.
      Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity.
      ,
      • Fox M.D.
      Mapping symptoms to brain networks with the human connectome.
      ,
      • Riva-Posse P.
      • Choi K.S.
      • Holtzheimer P.E.
      • Crowell A.L.
      • Garlow S.J.
      • Rajendra J.K.
      • et al.
      A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression.
      ,
      • Anderson R.J.
      • Hoy K.E.
      • Daskalakis Z.J.
      • Fitzgerald P.B.
      Repetitive transcranial magnetic stimulation for treatment resistant depression: Re-establishing connections.
      ). For example, lesion locations associated with depression are not solely located in the left DLPFC, but instead map to a distributed brain network that is centered on the left DLPFC (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ). Similarly, recent network models of depression include a variety of cortical and subcortical brain regions (
      • Kaiser R.H.
      • Andrews-Hanna J.R.
      • Wager T.D.
      • Pizzagalli D.A.
      Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity.
      ). In parallel, it has become clear that the effects of rTMS are not restricted to the stimulated region, but propagate to affect the network of regions connected to the stimulation site (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Liston C.
      • Chen A.C.
      • Zebley B.D.
      • Drysdale A.T.
      • Gordon R.
      • Leuchter B.
      • et al.
      Default mode network mechanisms of transcranial magnetic stimulation in depression.
      ,
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Halko M.A.
      • Farzan F.
      • Eldaief M.C.
      • Schmahmann J.D.
      • Pascual-Leone A.
      Intermittent theta-burst stimulation of the lateral cerebellum increases functional connectivity of the default network.
      ,
      • Rastogi A.
      • Cash R.
      • Dunlop K.
      • Vesia M.
      • Kucyi A.
      • Ghahremani A.
      • et al.
      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Hawco C.
      • Voineskos A.N.
      • Steeves J.K.E.
      • Dickie E.W.
      • Viviano J.D.
      • Downar J.
      • et al.
      Spread of activity following TMS is related to intrinsic resting connectivity to the salience network: A concurrent TMS-fMRI study.
      ,
      • Fox M.D.
      • Buckner R.L.
      • Liu H.
      • Chakravarty M.M.
      • Lozano A.M.
      • Pascual-Leone A.
      Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.
      ).
      One valuable neuroimaging technique for visualizing brain networks is resting-state functional connectivity (FC) MRI (
      • Zalesky A.
      • Fornito A.
      • Cocchi L.
      • Gollo L.L.
      • Breakspear M.
      Time-resolved resting-state brain networks.
      ,
      • Fox M.D.
      • Raichle M.E.
      Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.
      ). Brain regions are interconnected to form intrinsic networks, characterized by shared temporal fluctuations in spontaneous brain activity. These distributed networks can be delineated, even in the absence of external stimuli, and are therefore termed resting-state networks. One advantage of recording these networks at rest is that there is a reduced need for patient compliance and avoidance of confounds related to task performance or instructions (
      • Fox M.D.
      • Greicius M.
      Clinical applications of resting state functional connectivity.
      ). Resting-state networks may also exhibit higher reproducibility compared with conventional task-based imaging (
      • Elliott M.L.
      • Knodt A.R.
      • Ireland D.
      • Morris M.L.
      • Poulton R.
      • Ramrakha S.
      • et al.
      What is the test-retest reliability of common task-fMRI measures? New empirical evidence and a meta-analysis.
      ). The FC within and between these networks is often altered in psychiatric and neurological conditions (
      • Fornito A.
      • Bullmore E.T.
      • Zalesky A.
      Opportunities and challenges for psychiatry in the connectomic era.
      ,
      • Kaiser R.H.
      • Andrews-Hanna J.R.
      • Wager T.D.
      • Pizzagalli D.A.
      Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity.
      ,
      • Fornito A.
      • Zalesky A.
      • Breakspear M.
      The connectomics of brain disorders.
      ), while partial normalization may occur following successful treatment (
      • Kaiser R.H.
      • Andrews-Hanna J.R.
      • Wager T.D.
      • Pizzagalli D.A.
      Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity.
      ,
      • Liston C.
      • Chen A.C.
      • Zebley B.D.
      • Drysdale A.T.
      • Gordon R.
      • Leuchter B.
      • et al.
      Default mode network mechanisms of transcranial magnetic stimulation in depression.
      ), including brain stimulation (
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Halko M.A.
      • Farzan F.
      • Eldaief M.C.
      • Schmahmann J.D.
      • Pascual-Leone A.
      Intermittent theta-burst stimulation of the lateral cerebellum increases functional connectivity of the default network.
      ,
      • Rastogi A.
      • Cash R.
      • Dunlop K.
      • Vesia M.
      • Kucyi A.
      • Ghahremani A.
      • et al.
      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Tik M.
      • Hoffmann A.
      • Sladky R.
      • Tomova L.
      • Hummer A.
      • Navarro de Lara L.
      • et al.
      Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity.
      ). It is now clear that different regions across the spatial extent of the DLPFC map on to different distributed brain networks (
      • Opitz A.
      • Fox M.D.
      • Craddock R.C.
      • Colcombe S.
      • Milham M.P.
      An integrated framework for targeting functional networks via transcranial magnetic stimulation.
      ), potentially explaining a portion of the response variability associated with conventional TMS targeting techniques (Figure S1).
      The shift in focus from brain regions to brain networks has motivated various new approaches to improve TMS for depression. These include the use of TMS to modify connectivity, with the goal of correcting network abnormalities in depression (
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Halko M.A.
      • Farzan F.
      • Eldaief M.C.
      • Schmahmann J.D.
      • Pascual-Leone A.
      Intermittent theta-burst stimulation of the lateral cerebellum increases functional connectivity of the default network.
      ,
      • Rastogi A.
      • Cash R.
      • Dunlop K.
      • Vesia M.
      • Kucyi A.
      • Ghahremani A.
      • et al.
      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Tik M.
      • Hoffmann A.
      • Sladky R.
      • Tomova L.
      • Hummer A.
      • Navarro de Lara L.
      • et al.
      Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity.
      ,
      • Chen A.C.
      • Oathes D.J.
      • Chang C.
      • Bradley T.
      • Zhou Z.W.
      • Williams L.M.
      • et al.
      Causal interactions between fronto-parietal central executive and default-mode networks in humans.
      ,
      • Fox M.D.
      • Halko M.A.
      • Eldaief M.C.
      • Pascual-Leone A.
      Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS).
      ). Another is the use of brain connectivity to predict which patients will respond to TMS treatment (
      • Liston C.
      • Chen A.C.
      • Zebley B.D.
      • Drysdale A.T.
      • Gordon R.
      • Leuchter B.
      • et al.
      Default mode network mechanisms of transcranial magnetic stimulation in depression.
      ,
      • Cash R.F.H.
      • Cocchi L.
      • Anderson R.
      • Rogachov A.
      • Kucyi A.
      • Barnett A.J.
      • et al.
      A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression.
      ,
      • Drysdale A.T.
      • Grosenick L.
      • Downar J.
      • Dunlop K.
      • Mansouri F.
      • Meng Y.
      • et al.
      Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
      ,
      • Salomons T.V.
      • Dunlop K.
      • Kennedy S.H.
      • Flint A.
      • Geraci J.
      • Giacobbe P.
      • et al.
      Resting-state cortico-thalamic-striatal connectivity predicts response to dorsomedial prefrontal rTMS in major depressive disorder.
      ). Finally, brain connectivity has been used to identify rTMS targets for depression based on the connectivity of the stimulated target to other brain regions (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ,
      • Fox M.D.
      • Buckner R.L.
      • Liu H.
      • Chakravarty M.M.
      • Lozano A.M.
      • Pascual-Leone A.
      Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.
      ,
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ).

      Targeting TMS Based on Connectivity to the Subgenual Cingulate Cortex

      An example of the latter approach relates to the observation that antidepressant outcomes were better when stimulation was serendipitously delivered at sites of the DLPFC that displayed stronger negative (anticorrelated) FC with the subgenual cingulate cortex (SGC) (Figure 3) (
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ). The SGC is a region positioned at the anterior-inferior end of the cingulum bundle with extensive connections across prefrontal and limbic structures that have been implicated in depression (
      • Riva-Posse P.
      • Choi K.S.
      • Holtzheimer P.E.
      • Crowell A.L.
      • Garlow S.J.
      • Rajendra J.K.
      • et al.
      A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression.
      ). It is associated with abnormal emotional regulation and processing and has been linked to depression and clinical response across diverse antidepressant treatment modalities (
      • Siegle G.J.
      • Thompson W.K.
      • Collier A.
      • Berman S.R.
      • Feldmiller J.
      • Thase M.E.
      • et al.
      Toward clinically useful neuroimaging in depression treatment: Prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics.
      ,
      • Drevets W.C.
      • Savitz J.
      • Trimble M.
      The subgenual anterior cingulate cortex in mood disorders.
      ,
      • Hamani C.
      • Mayberg H.
      • Stone S.
      • Laxton A.
      • Haber S.
      • Lozano A.M.
      The subcallosal cingulate gyrus in the context of major depression.
      ).
      Figure thumbnail gr3
      Figure 3Antidepressant response to repetitive transcranial magnetic stimulation is associated with functional connectivity (FC) between the stimulation site and the subgenual cingulate cortex (SGC) across different international cohorts. The intrinsic spontaneous activity of the SGC (A) can be compared with that of other regions of the brain to identify regions of strong positively or negatively correlated FC. The dorsolateral prefrontal cortex (DLPFC) (B) includes regions of positive (red) and negative (blue) FC with the SGC. Stronger negative FC with the SGC occurs at more anterolateral sites. (C) Illustration of negative (anticorrelated) time course between the DLPFC (green) and SGC (red). (D, E) Greater treatment outcome (% change in clinical score) was associated with more negative SGC FC at the individual DLPFC stimulation site across the Boston (D) and Melbourne (E) cohorts. For the Boston cohort, the green and red circles in panel (D) highlight individual participants with good and poor clinical outcomes, corresponding to circled cortical sites of negative and positive SGC FC, respectively, displayed in panel (B). BDI, Beck Depression Inventory; BOLD, blood oxygen–level dependent; HCP, Human Connectome Project; MADRS, Montgomery–Åsberg Depression Rating Scale.
      The association between DLPFC-SGC FC at the stimulation site and treatment response has additionally been replicated across 3 geographically distinct clinical cohorts, with findings robust across different populations, methodologies, scanners, stimulators, and DLPFC targeting approaches (5.5-cm, cognitive activation, Beam F3) (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ). More specifically, a 60% to 70% reduction in depressive symptoms occurred when individuals were stimulated near the DLPFC site of maximal FC anticorrelation with SGC, while those stimulated farther away showed no response or worsening of depressive symptoms [c.f. Figure 1C in (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      )]. The association between SGC FC and treatment response is also unique to individuals receiving active and not sham stimulation (
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ).
      Based on these associations, it has been suggested that the DLPFC site most anticorrelated with the SGC could represent an optimal TMS target for depression (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ). The DLPFC coordinates of maximal SGC-FC anticorrelation are at Montreal Neurological Institute coordinates x = −42, y = 44, z = 30 (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ). In line with this reasoning, a recent large randomized trial of TMS used neuronavigation to target this coordinate with the goal of optimizing antidepressant response (
      • Blumberger D.M.
      • Vila-Rodriguez F.
      • Thorpe K.E.
      • Feffer K.
      • Noda Y.
      • Giacobbe P.
      • et al.
      Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): A randomised non-inferiority trial.
      ). However, the goal of this trial was to compare two different forms of active rTMS, not to validate this target. Whether neuronavigated TMS to this target results in stronger or more consistent antidepressant response compared with conventional scalp-based targeting remains to be tested in a dedicated clinical trial. It also remains unclear whether connectivity to the SGC is the only or the most important connection for defining an optimal TMS target. Connectivity of the TMS target to other brain regions implicated in depression may also be important (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Drysdale A.T.
      • Grosenick L.
      • Downar J.
      • Dunlop K.
      • Mansouri F.
      • Meng Y.
      • et al.
      Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
      ,
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ).

      Targeting TMS Based on Individualized Connectivity

      The above TMS target based on SGC connectivity may not be optimal for all patients owing to individual differences in brain connectivity. The above target was based on group connectivity, averaged across 1000 healthy individuals. This averaging allows for robust maps that help counteract the low signal-to-noise ratio of the SGC region (
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ); however, it ignores potentially important individual differences in connectivity.
      Many have suggested that rTMS might be improved by personalizing the stimulation site based on individual differences in connectivity (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Buckner R.L.
      • White M.P.
      • Greicius M.D.
      • Pascual-Leone A.
      Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.
      ,
      • Barbour T.
      • Lee E.
      • Ellard K.
      • Camprodon J.
      Individualized TMS target selection for MDD: Clinical outcomes, mechanisms of action and predictors of response.
      ,
      • Siddiqi S.H.
      • Trapp N.T.
      • Hacker C.D.
      • Laumann T.O.
      • Kandala S.
      • Hong X.
      • et al.
      Repetitive transcranial magnetic stimulation with resting-state network targeting for treatment-resistant depression in traumatic brain injury: a randomized, controlled, double-blinded pilot study.
      ,
      • Siddiqi S.H.
      • Trapp N.T.
      • Shahim P.
      • Hacker C.D.
      • Laumann T.O.
      • Kandala S.
      • et al.
      Individualized connectome-targeted transcranial magnetic stimulation for neuropsychiatric sequelae of repetitive traumatic brain injury in a retired NFL player.
      ,
      • Singh A.
      • Erwin-Grabner T.
      • Sutcliffe G.
      • Antal A.
      • Paulus W.
      • Goya-Maldonado R.
      Personalized repetitive transcranial magnetic stimulation temporarily alters default mode network in healthy subjects.
      ,
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ,
      • Cocchi L.
      • Zalesky A.
      Personalized transcranial magnetic stimulation in psychiatry.
      ,
      • Sack A.T.
      • Cohen Kadosh R.
      • Schuhmann T.
      • Moerel M.
      • Walsh V.
      • Goebel R.
      Optimizing functional accuracy of TMS in cognitive studies: A comparison of methods.
      ,
      • Ning L.
      • Makris N.
      • Camprodon J.A.
      • Rathi Y.
      Limits and reproducibility of resting-state functional MRI definition of DLPFC targets for neuromodulation.
      ,
      • Cash R.
      • Cocchi L.
      • Fitzgerald P.
      • Zalesky A.
      Precision psychiatry: Development of methodology for personalized therapeutic brain stimulation. Program No. 684.09. 2019 Neuroscience Meeting Planner.
      ). Recent work demonstrates that SGC FC shows considerable interindividual variation across the spatial extent of the DLPFC (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ,
      • Cash R.
      • Cocchi L.
      • Fitzgerald P.
      • Zalesky A.
      Precision psychiatry: Development of methodology for personalized therapeutic brain stimulation. Program No. 684.09. 2019 Neuroscience Meeting Planner.
      ). Indeed, prefrontal regions show some of the highest levels of interindividual variation in terms of cytoarchitecture, structural morphology, neural function, and connectivity (
      • Rajkowska G.
      • Goldman-Rakic P.S.
      Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System.
      ,
      • Finn E.S.
      • Shen X.
      • Scheinost D.
      • Rosenberg M.D.
      • Huang J.
      • Chun M.M.
      • et al.
      Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity.
      ,
      • Fischl B.
      • Rajendran N.
      • Busa E.
      • Augustinack J.
      • Hinds O.
      • Yeo B.T.
      • et al.
      Cortical folding patterns and predicting cytoarchitecture.
      ,
      • Mueller S.
      • Wang D.
      • Fox M.D.
      • Yeo B.T.
      • Sepulcre J.
      • Sabuncu M.R.
      • et al.
      Individual variability in functional connectivity architecture of the human brain.
      ,
      • Miranda-Dominguez O.
      • Mills B.D.
      • Carpenter S.D.
      • Grant K.A.
      • Kroenke C.D.
      • Nigg J.T.
      • et al.
      Connectotyping: Model based fingerprinting of the functional connectome.
      ,
      • Doucet G.E.
      • Lee W.H.
      • Frangou S.
      Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases.
      ,
      • Gordon E.M.
      • Laumann T.O.
      • Adeyemo B.
      • Petersen S.E.
      Individual variability of the system-level organization of the human brain.
      ). However, these individual differences are likely to prove useful as TMS targets only if one can overcome signal-to-noise limitations of single-subject fMRI data (
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ).
      The past decade has seen substantial advances in fMRI acquisition, preprocessing, and noise-reduction strategies (
      • Parkes L.
      • Fulcher B.
      • Yucel M.
      • Fornito A.
      An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI.
      ) as well as in our capacity to model the relationship between stimulation site, network engagement, and treatment response (described further in the Supplement). With sufficient data, clear individual differences in functional network architecture are evident (Figure S1) (
      • Finn E.S.
      • Shen X.
      • Scheinost D.
      • Rosenberg M.D.
      • Huang J.
      • Chun M.M.
      • et al.
      Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity.
      ,
      • Fischl B.
      • Rajendran N.
      • Busa E.
      • Augustinack J.
      • Hinds O.
      • Yeo B.T.
      • et al.
      Cortical folding patterns and predicting cytoarchitecture.
      ,
      • Gratton C.
      • Laumann T.O.
      • Nielsen A.N.
      • Greene D.J.
      • Gordon E.M.
      • Gilmore A.W.
      • et al.
      Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation.
      ,
      • Braga R.M.
      • Buckner R.L.
      Parallel interdigitated distributed networks within the individual estimated by intrinsic functional connectivity.
      ,
      • Horien C.
      • Shen X.
      • Scheinost D.
      • Constable R.T.
      The individual functional connectome is unique and stable over months to years.
      ); however, several of these studies used many hours of MRI scanning, which is not practical for clinical patients. Further, limbic areas such as the SGC are particularly prone to signal-to-noise problems, limiting our ability to identify robust TMS targets (
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ). In fact, recent work indicated that single-subject TMS targets derived from individual connectivity to a small region of interest in the SGC are not reproducible enough to provide an advantage over group-based connectivity (
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ,
      • Ning L.
      • Makris N.
      • Camprodon J.A.
      • Rathi Y.
      Limits and reproducibility of resting-state functional MRI definition of DLPFC targets for neuromodulation.
      ). This signal-to-noise hurdle may be overcome through creative strategies to obtain reproducible individualized targets. In one such strategy, connectivity to a network of limbic regions, rather than just the subgenual alone, resulted in robust individualized targets (
      • Fox M.D.
      • Liu H.
      • Pascual-Leone A.
      Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.
      ), findings that have since been replicated and extended (
      • Cash R.
      • Cocchi L.
      • Fitzgerald P.
      • Zalesky A.
      Precision psychiatry: Development of methodology for personalized therapeutic brain stimulation. Program No. 684.09. 2019 Neuroscience Meeting Planner.
      ,
      • Cash R.
      • Cocchi L.
      • Lv J.
      • Fitzgerald P.
      • Zalesky A.
      Toward state-of-the-art connectivity-guided TMS: Personalization, precision & clinical response. Program No. 0047.
      ).
      A number of small clinical trials have begun using SGC-FC TMS targets derived from individualized connectivity (Table 1). Some of these trials have reported very high response and remission rates (
      • Williams N.R.
      • Sudheimer K.D.
      • Bentzley B.S.
      • Pannu J.
      • Stimpson K.H.
      • Duvio D.
      • et al.
      High-dose spaced theta-burst TMS as a rapid-acting antidepressant in highly refractory depression.
      ,
      • Barbour T.
      • Lee E.
      • Ellard K.
      • Camprodon J.
      Individualized TMS target selection for MDD: Clinical outcomes, mechanisms of action and predictors of response.
      ,
      • Siddiqi S.H.
      • Trapp N.T.
      • Hacker C.D.
      • Laumann T.O.
      • Kandala S.
      • Hong X.
      • et al.
      Repetitive transcranial magnetic stimulation with resting-state network targeting for treatment-resistant depression in traumatic brain injury: a randomized, controlled, double-blinded pilot study.
      ,
      • Cole E.J.
      • Stimpson K.H.
      • Bentzley B.S.
      • Gulser M.
      • Cherian K.
      • Tischler C.
      • et al.
      Stanford accelerated intelligent neuromodulation therapy for treatment-resistant depression.
      ), but whether personalization exceeds the efficacy of conventional targeting methods remains to be established in a dedicated clinical trial. It is important to note that these studies have been performed in small cohorts and typically without a comparison target or sham group. It is also possible that the placebo effect of rTMS is greater when additional technologies such as MRI scanning and neuronavigation are used. Future research with larger trials and comparator groups is warranted. These trials would further benefit from validation of the accuracy and reproducibility of the individualized targeting method [e.g., as per (
      • Cash R.
      • Cocchi L.
      • Lv J.
      • Fitzgerald P.
      • Zalesky A.
      Toward state-of-the-art connectivity-guided TMS: Personalization, precision & clinical response. Program No. 0047.
      )].
      Table 1Clinical Outcomes of rTMS for Depression Using Conventional or Connectivity-Based Targeting
      StudySample and SizeControl ConditionTreatment ParadigmResponse Rate (%)Remission Rate (%)
      Conventional Targeting
      Berlim et al., 2014 (
      • Berlim M.T.
      • van den Eynde F.
      • Tovar-Perdomo S.
      • Daskalakis Z.J.
      Response, remission and drop-out rates following high-frequency repetitive transcranial magnetic stimulation (rTMS) for treating major depression: A systematic review and meta-analysis of randomized, double-blind and sham-controlled trials.
      )
      Meta-analysis of 29 RCTs, double-blinded sham-controlled (N = 1371)Various sham control conditionsHF rTMS (≥10 sessions)Active: 29%

      Sham: 10%
      Active: 19%

      Sham: 5%
      Fitzgerald et al., 2016 (
      • Fitzgerald P.B.
      • Hoy K.E.
      • Anderson R.J.
      • Daskalakis Z.J.
      A study of the pattern of response to rTMS treatment in depression.
      )
      Internal review of 11 RCTs, mostly open-label with active-comparator (N = 1132)VariousActive: 46%Active: 31%
      Group SGC FC Target
      Blumberger et al., 2018 (
      • Blumberger D.M.
      • Vila-Rodriguez F.
      • Thorpe K.E.
      • Feffer K.
      • Noda Y.
      • Giacobbe P.
      • et al.
      Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): A randomised non-inferiority trial.
      )
      MDD (N = 414)All conditions active; rTMS (n = 205) vs. TBS (n = 209)Target was SGC FC group coordinate [MNI x = −38, y = 44, z = 26]. rTMS (10 Hz, 120% RMT, 3000 pulses/session); iTBS (120% RMT, 600 pulses/session). Once-daily, Monday–Friday, 4 weeksrTMS: 47%

      iTBS: 49%
      rTMS: 27%

      iTBS: 32%
      Personalized SGC FC Target
      Cole et al., 2020 (
      • Cole E.J.
      • Stimpson K.H.
      • Bentzley B.S.
      • Gulser M.
      • Cherian K.
      • Tischler C.
      • et al.
      Stanford accelerated intelligent neuromodulation therapy for treatment-resistant depression.
      )
      MDD (n = 31)Active condition onlyAccelerated TBS. 10 sessions of iTBS per day for 5 consecutive days (90,000 total pulses). 90% RMT90%90% (all responders were remitters)
      Siddiqi et al., 2019 (
      • Siddiqi S.H.
      • Trapp N.T.
      • Hacker C.D.
      • Laumann T.O.
      • Kandala S.
      • Hong X.
      • et al.
      Repetitive transcranial magnetic stimulation with resting-state network targeting for treatment-resistant depression in traumatic brain injury: a randomized, controlled, double-blinded pilot study.
      )
      TBI with treatment-resistant depression (N = 14)Active (n = 9) and sham (n = 5)Bilateral standard rTMS. 20 daily sessions of bilateral rTMS (10-Hz left DLPFC, 4000 pulses followed by 1 train of 1-Hz rTMS, 1000 pulses; 120% RMT)Active: 77%

      Sham: 0%
      Active: 44%

      Sham: 0%
      Williams et al., 2018 (
      • Williams N.R.
      • Sudheimer K.D.
      • Bentzley B.S.
      • Pannu J.
      • Stimpson K.H.
      • Duvio D.
      • et al.
      High-dose spaced theta-burst TMS as a rapid-acting antidepressant in highly refractory depression.
      )
      Highly refractive TRD that previously failed standard or deep rTMS (N = 6)Active condition onlyAccelerated TBS with personalized target. As for Cole et al., 2018 (above)83%66%
      DLPFC, dorsolateral prefrontal cortex; FC, functional connectivity; HF, high-frequency; iTBS, intermittent theta burst stimulation; MDD, major depressive disorder; MNI, Montreal Neurological Institute; RCT, randomized controlled trial; RMT, resting motor threshold; rTMS, repetitive transcranial magnetic stimulation; SGC, subgenual cingulate cortex; TBI, traumatic brain injury; TRD, treatment-resistant depression.

      Targeting TMS Based on Symptom-Specific Brain Networks

      The TMS target based on SGC connectivity may not be the best target for all depression symptoms (Figure 4A). Emerging evidence suggests that separate symptom clusters might respond to stimulation of different brain circuits (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Drysdale A.T.
      • Grosenick L.
      • Downar J.
      • Dunlop K.
      • Mansouri F.
      • Meng Y.
      • et al.
      Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
      ,
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ,
      • Downar J.
      Orbitofrontal cortex: A “non-rewarding” new treatment target in depression?.
      ). Anterolateral DLPFC sites with anticorrelated FC to the SGC may be more effective in moderating dysphoric symptoms such as sadness, decreased interest, and suicidality, whereas posterior DLPFC and medial prefrontal targets appear more effective for ameliorating anxiosomatic symptoms such as insomnia, decreased libido, and irritability (Figure 4B) (
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ). Different depression symptoms may therefore benefit from different TMS targets.
      Figure thumbnail gr4
      Figure 4Symptom specificity. (A) Many, but not all, symptoms improve as the transcranial magnetic stimulation (TMS) target site approaches the site of most negative subgenual cingulate cortex (SGC) functional connectivity (FC). The relationship between SGC FC at the stimulation site and symptom improvement appears to be relatively consistent across the Boston and Melbourne cohorts. The symptoms that appeared less consistently related to SGC FC were agitation, sleeping pattern, irritability, appetite, fatigue, and interest in sex. These might be better treated at an alternative stimulation site. The Boston and Melbourne data are derived from open-label studies (
      • Cash R.F.H.
      • Zalesky A.
      • Thomson R.H.
      • Tian Y.
      • Cocchi L.
      • Fitzgerald P.B.
      Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: Independent validation and evaluation of personalization.
      ,
      • Weigand A.
      • Horn A.
      • Caballero R.
      • Cooke D.
      • Stern A.P.
      • Taylor S.F.
      • et al.
      Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites.
      ). (B) Therapeutic response to anatomically targeted TMS (5- to 5.5-cm approach) was used to identify symptom-specific spatial TMS targets (
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ). Together these maps were found to delineate 2 distinct spatial profiles corresponding to amelioration of a cluster of either dysphoric symptoms (sadness, decreased interest, and suicidal thoughts) or anxiosomatic symptoms (changes in sleep, decreased libido, and worry/irritability) following TMS therapy (
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ). Accordingly, it might be possible to spatially target TMS to ameliorate specific symptom clusters on a personalized basis. The color bar represents the spatial correlation between symptom improvement and FC to the stimulation site. These therapeutic response profiles were delineated retrospectively following treatment and as such remain preliminary until they can be confirmed prospectively.

      TMS Sites Outside the Left DLPFC

      Thus far, our review has focused on high-frequency rTMS to the left DLPFC; however, other TMS sites and parameters have been selected for depression. The most common alternative is low-frequency TMS to the right DLPFC, which has produced comparable clinical outcomes to high-frequency left DLPFC TMS in randomized trials (
      • Berlim M.T.
      • van den Eynde F.
      • Tovar-Perdomo S.
      • Daskalakis Z.J.
      Response, remission and drop-out rates following high-frequency repetitive transcranial magnetic stimulation (rTMS) for treating major depression: A systematic review and meta-analysis of randomized, double-blind and sham-controlled trials.
      ,
      • Fitzgerald P.B.
      • Hoy K.
      • Daskalakis Z.J.
      • Kulkarni J.
      A randomized trial of the anti-depressant effects of low- and high-frequency transcranial magnetic stimulation in treatment-resistant depression.
      ,
      • Isenberg K.
      • Downs D.
      • Pierce K.
      • Svarakic D.
      • Garcia K.
      • Jarvis M.
      • et al.
      Low frequency rTMS stimulation of the right frontal cortex is as effective as high frequency rTMS stimulation of the left frontal cortex for antidepressant-free, treatment-resistant depressed patients.
      ,
      • Stern W.M.
      • Tormos J.M.
      • Press D.Z.
      • Pearlman C.
      • Pascual-Leone A.
      Antidepressant effects of high and low frequency repetitive transcranial magnetic stimulation to the dorsolateral prefrontal cortex: A double-blind, randomized, placebo-controlled trial.
      ). Traditionally, high- and low-frequency rTMS paradigms have been delivered with the aim of increasing or decreasing cortical activity and potentially normalizing metabolic abnormalities in depression. However, whether 1-Hz rTMS reduces cortical activity (when measured in terms of regional cerebral blood flow, etc.) remains uncertain (
      • Kimbrell T.A.
      • Little J.T.
      • Dunn R.T.
      • Frye M.A.
      • Greenberg B.D.
      • Wassermann E.M.
      • et al.
      Frequency dependence of antidepressant response to left prefrontal repetitive transcranial magnetic stimulation (rTMS) as a function of baseline cerebral glucose metabolism.
      ,
      • Li X.
      • Nahas Z.
      • Kozel F.A.
      • Anderson B.
      • Bohning D.E.
      • George M.S.
      Acute left prefrontal transcranial magnetic stimulation in depressed patients is associated with immediately increased activity in prefrontal cortical as well as subcortical regions.
      ,
      • Loo C.K.
      • Sachdev P.S.
      • Haindl W.
      • Wen W.
      • Mitchell P.B.
      • Croker V.M.
      • et al.
      High (15 Hz) and low (1 Hz) frequency transcranial magnetic stimulation have different acute effects on regional cerebral blood flow in depressed patients.
      ,
      • Speer A.M.
      • Benson B.E.
      • Kimbrell T.K.
      • Wassermann E.M.
      • Willis M.W.
      • Herscovitch P.
      • et al.
      Opposite effects of high and low frequency rTMS on mood in depressed patients: relationship to baseline cerebral activity on PET.
      ,
      • Speer A.M.
      • Kimbrell T.A.
      • Wassermann E.M.
      • D Repella J.
      • Willis M.W.
      • Herscovitch P.
      • et al.
      Opposite effects of high and low frequency rTMS on regional brain activity in depressed patients.
      ,
      • Nahas Z.
      • Teneback C.C.
      • Kozel A.
      • Speer A.M.
      • DeBrux C.
      • Molloy M.
      • et al.
      Brain effects of TMS delivered over prefrontal cortex in depressed adults: Role of stimulation frequency and coil-cortex distance.
      ,
      • Fitzgerald P.B.
      • Sritharan A.
      • Daskalakis Z.J.
      • de Castella A.R.
      • Kulkarni J.
      • Egan G.
      A functional magnetic resonance imaging study of the effects of low frequency right prefrontal transcranial magnetic stimulation in depression.
      ) and may depend on stimulation intensity, flipping from inhibitory to excitatory at higher intensities (
      • Berlim M.T.
      • van den Eynde F.
      • Tovar-Perdomo S.
      • Daskalakis Z.J.
      Response, remission and drop-out rates following high-frequency repetitive transcranial magnetic stimulation (rTMS) for treating major depression: A systematic review and meta-analysis of randomized, double-blind and sham-controlled trials.
      ,
      • Maeda F.
      • Keenan J.P.
      • Tormos J.M.
      • Topka H.
      • Pascual-Leone A.
      Interindividual variability of the modulatory effects of repetitive transcranial magnetic stimulation on cortical excitability.
      ,
      • Maeda F.
      • Keenan J.P.
      • Tormos J.M.
      • Topka H.
      • Pascual-Leone A.
      Modulation of corticospinal excitability by repetitive transcranial magnetic stimulation.
      ,
      • Chen R.
      • Classen J.
      • Gerloff C.
      • Celnik P.
      • Wassermann E.M.
      • Hallett M.
      • et al.
      Depression of motor cortex excitability by low-frequency transcranial magnetic stimulation.
      ,
      • Berger U.
      • Korngreen A.
      • Bar-Gad I.
      • Friedman A.
      • Wolfus S.
      • Yeshurun Y.
      • et al.
      Magnetic stimulation intensity modulates motor inhibition.
      ) [for a discussion of the physiological mechanisms mediating this phenomenon see (
      • Cash R.F.
      • Jegatheeswaran G.
      • Ni Z.
      • Chen R.
      Modulation of the direction and magnitude of hebbian plasticity in human motor cortex by stimulus intensity and concurrent inhibition.
      )]. A similar phenomenon has been described with continuous theta burst stimulation, which elicits excitatory, rather than inhibitory, effects at higher stimulus intensities (
      • Doeltgen S.H.
      • Ridding M.C.
      Low-intensity, short-interval theta burst stimulation modulates excitatory but not inhibitory motor networks.
      ), as typically employed clinically (
      • Brunoni A.R.
      • Chaimani A.
      • Moffa A.H.
      • Razza L.B.
      • Gattaz W.F.
      • Daskalakis Z.J.
      • et al.
      Repetitive transcranial magnetic stimulation for the acute treatment of major depressive episodes: A systematic review with network meta-analysis.
      ). Consistent with this observation, studies comparing the effects of low- and high-frequency rTMS to the left DLPFC have often reported similar antidepressant efficacy (
      • Rosenberg P.B.
      • Mehndiratta R.B.
      • Mehndiratta Y.P.
      • Wamer A.
      • Rosse R.B.
      • Balish M.
      Repetitive transcranial magnetic stimulation treatment of comorbid posttraumatic stress disorder and major depression.
      ,
      • Padberg F.
      • Zwanzger P.
      • Thoma H.
      • Kathmann N.
      • Haag C.
      • Greenberg B.D.
      • et al.
      Repetitive transcranial magnetic stimulation (rTMS) in pharmacotherapy-refractory major depression: Comparative study of fast, slow and sham rTMS.
      ,
      • Miniussi C.
      • Bonato C.
      • Bignotti S.
      • Gazzoli A.
      • Gennarelli M.
      • Pasqualetti P.
      • et al.
      Repetitive transcranial magnetic stimulation (rTMS) at high and low frequency: An efficacious therapy for major drug-resistant depression?.
      ,
      • Speer A.M.
      • Wassermann E.M.
      • Benson B.E.
      • Herscovitch P.
      • Post R.M.
      Antidepressant efficacy of high and low frequency rTMS at 110% of motor threshold versus sham stimulation over left prefrontal cortex.
      ,
      • Dell’Osso B.
      • Oldani L.
      • Camuri G.
      • Dobrea C.
      • Cremaschi L.
      • Benatti B.
      • et al.
      Augmentative repetitive transcranial magnetic stimulation (rTMS) in the acute treatment of poor responder depressed patients: A comparison study between high and low frequency stimulation.
      ,
      • Liu Q.
      • Shen Y.
      • Cao X.
      • Li Y.
      • Chen Y.
      • Yang W.
      • et al.
      Either at left or right, both high and low frequency rTMS of dorsolateral prefrontal cortex decreases cue induced craving for methamphetamine.
      ), with high-frequency stimulation generally delivering more robust effects (
      • Brunoni A.R.
      • Chaimani A.
      • Moffa A.H.
      • Razza L.B.
      • Gattaz W.F.
      • Daskalakis Z.J.
      • et al.
      Repetitive transcranial magnetic stimulation for the acute treatment of major depressive episodes: A systematic review with network meta-analysis.
      ,
      • Miniussi C.
      • Bonato C.
      • Bignotti S.
      • Gazzoli A.
      • Gennarelli M.
      • Pasqualetti P.
      • et al.
      Repetitive transcranial magnetic stimulation (rTMS) at high and low frequency: An efficacious therapy for major drug-resistant depression?.
      ). In sum, the assumption that rTMS normalizes an imbalance in cortical activity between the left and right DLPFC may be too simplistic. Connectivity-based studies of TMS sites in the right DLPFC, similar to those reported here for the left DLPFC, may shed light on whether the same connections mediate rTMS response in the two hemispheres. It is worth noting that high- and low-frequency rTMS do not implicitly evoke opposite changes in FC; indeed, the effects on connectivity explicitly depend on stimulation site and frequency and are difficult to anticipate prior to experimentation (
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Halko M.A.
      • Farzan F.
      • Eldaief M.C.
      • Schmahmann J.D.
      • Pascual-Leone A.
      Intermittent theta-burst stimulation of the lateral cerebellum increases functional connectivity of the default network.
      ,
      • Rastogi A.
      • Cash R.
      • Dunlop K.
      • Vesia M.
      • Kucyi A.
      • Ghahremani A.
      • et al.
      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Castrillon G.
      • Sollmann N.
      • Kurcyus K.
      • Razi A.
      • Krieg S.M.
      • Riedl V.
      The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex.
      ,
      • Hawco C.
      • Voineskos A.N.
      • Steeves J.K.E.
      • Dickie E.W.
      • Viviano J.D.
      • Downar J.
      • et al.
      Spread of activity following TMS is related to intrinsic resting connectivity to the salience network: A concurrent TMS-fMRI study.
      ,
      • Cocchi L.
      • Sale M.V.
      • L Gollo L.
      • Bell P.T.
      • Nguyen V.T.
      • Zalesky A.
      • et al.
      A hierarchy of timescales explains distinct effects of local in wdb 390 ihibition of primary visual cortex and frontal eye fields.
      ,
      • Beynel L.
      • Powers J.P.
      • Appelbaum L.G.
      Effects of repetitive transcranial magnetic stimulation on resting-state connectivity: A systematic review.
      ).
      Other targets include dorsomedial PFC (DMPFC) and orbitofrontal cortex (OFC) (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ,
      • Downar J.
      Orbitofrontal cortex: A “non-rewarding” new treatment target in depression?.
      ,
      • Feffer K.
      • Fettes P.
      • Giacobbe P.
      • Daskalakis Z.J.
      • Blumberger D.M.
      • Downar J.
      1Hz rTMS of the right orbitofrontal cortex for major depression: Safety, tolerability and clinical outcomes.
      ). The DMPFC target was identified from convergent evidence of lesion, stimulation, and connectivity studies in depression (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.
      ), and TMS to this target was found to impact impulsivity in healthy control subjects (
      • Cho S.S.
      • Koshimori Y.
      • Aminian K.
      • Obeso I.
      • Rusjan P.
      • Lang A.E.
      • et al.
      Investing in the future: Stimulation of the medial prefrontal cortex reduces discounting of delayed rewards.
      ,
      • Cho S.S.
      • Ko J.H.
      • Pellecchia G.
      • Van Eimeren T.
      • Cilia R.
      • Strafella A.P.
      Continuous theta burst stimulation of right dorsolateral prefrontal cortex induces changes in impulsivity level.
      ). In depression, case series suggest comparable remission rates to DLPFC rTMS (
      • Bakker N.
      • Shahab S.
      • Giacobbe P.
      • Blumberger D.M.
      • Daskalakis Z.J.
      • Kennedy S.H.
      • et al.
      rTMS of the dorsomedial prefrontal cortex for major depression: Safety, tolerability, effectiveness, and outcome predictors for 10 Hz versus intermittent theta-burst stimulation.
      ) and a bimodal outcome distribution (
      • Cash R.F.H.
      • Cocchi L.
      • Anderson R.
      • Rogachov A.
      • Kucyi A.
      • Barnett A.J.
      • et al.
      A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression.
      ,
      • Downar J.
      • Geraci J.
      • Salomons T.V.
      • Dunlop K.
      • Wheeler S.
      • McAndrews M.P.
      • et al.
      Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal repetitive transcranial magnetic stimulation in major depression.
      ). Congruently, more recent work identified 4 biotypes of patients with major depressive disorder based on whole-brain FC (
      • Drysdale A.T.
      • Grosenick L.
      • Downar J.
      • Dunlop K.
      • Mansouri F.
      • Meng Y.
      • et al.
      Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
      ), with markedly higher DMPFC rTMS response rates in certain biotypes.
      The lateral OFC is proposed as a nonreward pathway complementary to classic medial reward projections from ventral striatum; the nonreward attractor theory of depression proposes that lateral OFC-striatal nonreward circuits may enter a feedback loop in major depressive disorder (
      • Rolls E.T.
      A non-reward attractor theory of depression.
      ). A recent study using implanted cortical electrodes in patients with depression and epilepsy found that 100-Hz lateral OFC stimulation specifically attenuated negative thought content (
      • Rao V.R.
      • Sellers K.K.
      • Wallace D.L.
      • Lee M.B.
      • Bijanzadeh M.
      • Sani O.G.
      • et al.
      Direct electrical stimulation of lateral orbitofrontal cortex acutely improves mood in individuals with symptoms of depression.
      ). Case series of 1-Hz right OFC rTMS suggest antidepressant effects (24% remission) in a subset of patients failing previous DMPFC rTMS (
      • Feffer K.
      • Fettes P.
      • Giacobbe P.
      • Daskalakis Z.J.
      • Blumberger D.M.
      • Downar J.
      1Hz rTMS of the right orbitofrontal cortex for major depression: Safety, tolerability and clinical outcomes.
      ). Notably, in one study (
      • Drysdale A.T.
      • Grosenick L.
      • Downar J.
      • Dunlop K.
      • Mansouri F.
      • Meng Y.
      • et al.
      Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
      ), one of the biotypes featured a large nexus of abnormal connectivity in the right OFC. Prospective studies of biotype-targeted rTMS of OFC, DMFPC, and DLPFC are under way. It will also be important to test whether TMS to these different targets impacts different symptoms of depression as predicted by recent work (
      • Siddiqi S.H.
      • Taylor S.
      • Cooke D.
      • Pascual-Leone A.
      • George M.S.
      • Fox M.D.
      Distinct symptom-specific treatment targets for circuit-based neuromodulation.
      ).

      Relationship to Other Disorders and Stimulation Modalities in This Field

      Although TMS and deep brain stimulation have traditionally been considered separate therapies with distinct neuroanatomical treatment targets, they may target different nodes of the same brain network (
      • Fox M.D.
      • Buckner R.L.
      • Liu H.
      • Chakravarty M.M.
      • Lozano A.M.
      • Pascual-Leone A.
      Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.
      ). Indeed, connectomics is lending major insight into deep brain stimulation just as it has lent insight into TMS (
      • Riva-Posse P.
      • Choi K.S.
      • Holtzheimer P.E.
      • Crowell A.L.
      • Garlow S.J.
      • Rajendra J.K.
      • et al.
      A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression.
      ,
      • Horn A.
      The impact of modern-day neuroimaging on the field of deep brain stimulation.
      ). For example, while early trials of SGC deep brain stimulation failed to exceed antidepressant efficacy relative to sham stimulation (sham: electrodes inserted but not active), more refined targeting strategies have demonstrated stepwise gains in efficacy by selecting a single anatomical site defined based on treatment response in a previous cohort (41% response at 6 months) (
      • Holtzheimer P.E.
      • Kelley M.E.
      • Gross R.E.
      • Filkowski M.M.
      • Garlow S.J.
      • Barrocas A.
      • et al.
      Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression.
      ) and, more recently, individualized connectomics-based targeting (73% response rate at 6 months) (
      • Riva-Posse P.
      • Choi K.S.
      • Holtzheimer P.E.
      • Crowell A.L.
      • Garlow S.J.
      • Rajendra J.K.
      • et al.
      A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression.
      ). Connectomics is also increasingly being used to inform rTMS targeting for cognitive applications (
      • Rastogi A.
      • Cash R.
      • Dunlop K.
      • Vesia M.
      • Kucyi A.
      • Ghahremani A.
      • et al.
      Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation.
      ,
      • Wang J.X.
      • Rogers L.M.
      • Gross E.Z.
      • Ryals A.J.
      • Dokucu M.E.
      • Brandstatt K.L.
      • et al.
      Targeted enhancement of cortical-hippocampal brain networks and associative memory.
      ,
      • Koch G.
      • Bonni S.
      • Pellicciari M.C.
      • Casula E.P.
      • Mancini M.
      • Esposito R.
      • et al.
      Transcranial magnetic stimulation of the precuneus enhances memory and neural activity in prodromal Alzheimer’s disease.
      ) and to guide the modulation of corticostriatothalamic loops in obsessive-compulsive disorder (
      • Cocchi L.
      • Zalesky A.
      • Nott Z.
      • Whybird G.
      • Fitzgerald P.B.
      • Breakspear M.
      Transcranial magnetic stimulation in obsessive-compulsive disorder: A focus on network mechanisms and state dependence.
      ,
      • Dunlop K.
      • Woodside B.
      • Olmsted M.
      • Colton P.
      • Giacobbe P.
      • Downar J.
      Reductions in cortico-striatal hyperconnectivity accompany successful treatment of obsessive-compulsive disorder with dorsomedial prefrontal rTMS.
      ). Connectivity-guided targeted brain stimulation therefore offers a manifold of opportunities for improving clinical outcomes across treatment-resistant psychiatric disorders (
      • Fox M.D.
      • Buckner R.L.
      • Liu H.
      • Chakravarty M.M.
      • Lozano A.M.
      • Pascual-Leone A.
      Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.
      ).

      Moving Beyond “Where” to “How” to Administer TMS

      Answering the question of where to administer TMS may be easy compared with questions of how to administer TMS. Trials directly comparing different forms of TMS, such as 10-Hz versus intermittent theta burst stimulation, are starting to emerge (
      • Blumberger D.M.
      • Vila-Rodriguez F.
      • Thorpe K.E.
      • Feffer K.
      • Noda Y.
      • Giacobbe P.
      • et al.
      Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): A randomised non-inferiority trial.
      ), but there are an almost endless number of ways in which TMS might be administered. For example, 20-Hz rTMS is rarely employed in the clinic but may elicit more reliable changes in brain activity (
      • Eldaief M.C.
      • Halko M.A.
      • Buckner R.L.
      • Pascual-Leone A.
      Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner.
      ,
      • Maeda F.
      • Keenan J.P.
      • Tormos J.M.
      • Topka H.
      • Pascual-Leone A.
      Interindividual variability of the modulatory effects of repetitive transcranial magnetic stimulation on cortical excitability.
      ,
      • Maeda F.
      • Keenan J.P.
      • Tormos J.M.
      • Topka H.
      • Pascual-Leone A.
      Modulation of corticospinal excitability by repetitive transcranial magnetic stimulation.
      ,
      • Cash R.F.H.
      • Dar A.
      • Hui J.
      • De Ruiter L.
      • Baarbé J.
      • Fettes P.
      • et al.
      Influence of inter-train interval on the plastic effects of rTMS.
      ) compared with 10-Hz or theta burst stimulation (
      • Hamada M.
      • Murase N.
      • Hasan A.
      • Balaratnam M.
      • Rothwell J.C.
      The role of interneuron networks in driving human motor cortical plasticity.
      ,
      • Jannati A.
      • Block G.
      • Oberman L.M.
      • Rotenberg A.
      • Pascual-Leone A.
      Interindividual variability in response to continuous theta-burst stimulation in healthy adults.
      ). Standard protocols could potentially be substantially shortened, with recent work indicating that rTMS is equally effective when the intertrain interval is reduced from 32 to 4 seconds, enabling a course of 20-Hz rTMS to be delivered in as little as 3 minutes (
      • Cash R.F.H.
      • Dar A.
      • Hui J.
      • De Ruiter L.
      • Baarbé J.
      • Fettes P.
      • et al.
      Influence of inter-train interval on the plastic effects of rTMS.
      ,
      • Miron J.P.
      • Feffer K.
      • Cash R.F.H.
      • Derakhshan D.
      • Kim J.M.S.
      • Fettes P.
      • et al.
      Safety, tolerability and effectiveness of a novel 20 Hz rTMS protocol targeting dorsomedial prefrontal cortex in major depression: An open-label case series.
      ) with equivalent clinical effects (
      • Miron J.P.
      • Feffer K.
      • Cash R.F.H.
      • Derakhshan D.
      • Kim J.M.S.
      • Fettes P.
      • et al.
      Safety, tolerability and effectiveness of a novel 20 Hz rTMS protocol targeting dorsomedial prefrontal cortex in major depression: An open-label case series.
      ,
      • Xie J.
      • Chen J.
      • Wei Q.
      Repetitive transcranial magnetic stimulation versus electroconvulsive therapy for major depression: A meta-analysis of stimulus parameter effects.
      ,
      • Ke J.
      • Zou X.
      • Huang M.
      • Huang Q.
      • Li H.
      • Zhou X.
      High-frequency rTMS with two different inter-train intervals improves upper limb motor function at the early stage of stroke.
      ). Personalized temporal tuning according to individual patterns of cortical inhibition (
      • Cash R.F.
      • Murakami T.
      • Chen R.
      • Thickbroom G.W.
      • Ziemann U.
      Augmenting plasticity induction in human motor cortex by disinhibition stimulation.
      ) or endogenous brain rhythms (
      • Chung S.W.
      • Sullivan C.M.
      • Rogasch N.C.
      • Hoy K.E.
      • Bailey N.W.
      • Cash R.F.
      • et al.
      The effects of individualised intermittent theta burst stimulation in the prefrontal cortex: A TMS-EEG study.
      ) also appears promising. Similarly, TMS may be more effective when delivered during specific phases of oscillatory brain activity, a phenomenon we first described as phase-dependent plasticity (
      • Cash R.F.
      • Mastaglia F.L.
      • Thickbroom G.W.
      Evidence for high-fidelity timing-dependent synaptic plasticity of human motor cortex.
      ). Innovative closed-loop systems have now been developed that enable this phenomenon to be harnessed and personalized by triggering stimulus bursts during specific phases of brain activity determined using electroencephalography (
      • Stefanou M.I.
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      • Bergmann T.O.
      • Blum C.
      • Gordon P.C.
      • et al.
      Brain state-dependent brain stimulation with real-time electroencephalography-triggered transcranial magnetic stimulation.
      ,
      • Bergmann T.O.
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      • Lindner C.
      • Marshall L.
      • Born J.
      • et al.
      EEG-guided transcranial magnetic stimulation reveals rapid shifts in motor cortical excitability during the human sleep slow oscillation.
      ,
      • Bergmann T.O.
      • Karabanov A.
      • Hartwigsen G.
      • Thielscher A.
      • Siebner H.R.
      Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: Current approaches and future perspectives.
      ,
      • Zrenner B.
      • Zrenner C.
      • Gordon P.C.
      • Belardinelli P.
      • McDermott E.J.
      • Soekadar S.R.
      • et al.
      Brain oscillation-synchronized stimulation of the left dorsolateral prefrontal cortex in depression using real-time EEG-triggered TMS.
      ). This approach is now being trialed in individuals with depression (
      • Zrenner B.
      • Zrenner C.
      • Gordon P.C.
      • Belardinelli P.
      • McDermott E.J.
      • Soekadar S.R.
      • et al.
      Brain oscillation-synchronized stimulation of the left dorsolateral prefrontal cortex in depression using real-time EEG-triggered TMS.
      ). Finally, rTMS might be improved if administered during a behavioral task designed to activate affective or emotional regulatory pathways (
      • Donse L.
      • Padberg F.
      • Sack A.T.
      • Rush A.J.
      • Arns M.
      Simultaneous rTMS and psychotherapy in major depressive disorder: Clinical outcomes and predictors from a large naturalistic study.
      ,
      • Neacsiu A.D.
      • Luber B.M.
      • Davis S.W.
      • Bernhardt E.
      • Strauman T.J.
      • Lisanby S.H.
      On the concurrent use of self-system therapy and functional magnetic resonance imaging–guided transcranial magnetic stimulation as treatment for depression.
      ). The parameter space for how to administer TMS is much larger than the parameter space for where to administer TMS. We hope that advances in where to target TMS for depression will help guide or complement ongoing research into how to administer TMS, and together these advances will improve antidepressant outcomes.

      Future Directions

      Mounting evidence suggests that connectivity-based TMS targets may lead to clinical improvements, but much of this evidence is based on retrospective analyses or observational trials. A central focus for future work will be to prospectively test connectivity-based TMS targeting in large, blinded, comparator-controlled clinical trials to evaluate and quantify their superiority relative to conventional scalp-based targeting methodologies. Control conditions will also help to disambiguate TMS-specific effects relative to behavioral activation associated with regular attendance for daily treatment. This line of research may also yield new targets for different symptoms (
      • Downar J.
      • Daskalakis Z.J.
      New targets for rTMS in depression: A review of convergent evidence.