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Applications of open-source software ROAST in clinical studies: A review

  • Mohigul Nasimova
    Affiliations
    Department of Biomedical Engineering, City College of the City University of New York, New York, NY, 10031, USA
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  • Yu Huang
    Correspondence
    Corresponding author. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
    Affiliations
    Department of Biomedical Engineering, City College of the City University of New York, New York, NY, 10031, USA

    Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
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Open AccessPublished:July 14, 2022DOI:https://doi.org/10.1016/j.brs.2022.07.003

      Highlights

      • 225 articles that cited ROAST were reviewed.
      • 94 clinical TES studies were identified that used ROAST for modeling.
      • Over 1800 individual heads have been modeled by ROAST for more than 30 different clinical applications.
      • Similar electric field intensities were found across studies at the same brain area under same or similar stimulation montages.

      Abstract

      Background

      Transcranial electrical stimulation (TES) is broadly investigated as a therapeutic technique for a wide range of neurological disorders. The electric fields induced by TES in the brain can be estimated by computational models. A realistic and volumetric approach to simulate TES (ROAST) has been recently released as an open-source software package and has been widely used in TES research and its clinical applications. Rigor and reproducibility of TES studies have recently become a concern, especially in the context of computational modeling.

      Methods

      Here we reviewed 94 clinical TES studies that leveraged ROAST for computational modeling. When reviewing each study, we pay attention to details related to the rigor and reproducibility as defined by the locations of stimulation electrodes and the dose of stimulating current. Specifically, we compared across studies the electrode montages, stimulated brain areas, achieved electric field strength, and the relations between modeled electric field and clinical outcomes.

      Results

      We found that over 1800 individual heads have been modeled by ROAST for more than 30 different clinical applications. Similar electric field intensities were found to be reproducible by ROAST across different studies at the same brain area under same or similar stimulation montages.

      Conclusion

      This article reviews the use cases of ROAST and provides an overview of how ROAST has been leveraged to enhance the rigor and reproducibility of TES research and its applications.

      1. Introduction

      Transcranial electrical stimulation (TES) has been broadly investigated as a therapeutic technique for a wide range of neurological disorders such as major depression [
      • Bikson M.
      • Bulow P.
      • Stiller J.
      • Datta A.
      • Battaglia F.
      • Karnup S.
      • Postolache T.
      Transcranial direct current stimulation for major depression: a general system for quantifying transcranial electrotherapy dosage.
      ], epilepsy [
      • Auvichayapat N.
      • Rotenberg A.
      • Gersner R.
      • Ngodklang S.
      • Tiamkao S.
      • Tassaneeyakul W.
      • Auvichayapat P.
      Transcranial direct current stimulation for treatment of refractory childhood focal epilepsy.
      ,
      • Fregni F.
      • Thome-Souza S.
      • Nitsche M.A.
      • Freedman S.D.
      • Valente K.D.
      • Pascual-Leone A.
      A controlled clinical trial of cathodal DC polarization in patients with refractory epilepsy.
      ,
      • Regner G.G.
      • Pereira P.
      • Leffa D.T.
      • de Oliveira C.
      • Vercelino R.
      • Fregni F.
      • Torres I.L.S.
      Preclinical to clinical translation of studies of transcranial direct-current stimulation in the treatment of epilepsy: a systematic review.
      ,
      • San-Juan D.
      • Morales-Quezada L.
      • Orozco Garduño A.J.
      • Alonso-Vanegas M.
      • González-Aragón M.F.
      • Espinoza López D.A.
      • Vázquez Gregorio R.
      • Anschel D.J.
      • Fregni F.
      Transcranial direct current stimulation in epilepsy.
      ], Parkinson's disease [
      • Fregni F.
      • Boggio P.S.
      • Santos M.C.
      • Lima M.
      • Vieira A.L.
      • Rigonatti S.P.
      • Silva M.T.A.
      • Barbosa E.R.
      • Nitsche M.A.
      • Pascual-Leone A.
      Noninvasive cortical stimulation with transcranial direct current stimulation in Parkinson's disease.
      ], chronic pain [
      • Fregni F.
      • Freedman S.
      • Pascual-Leone A.
      Recent advances in the treatment of chronic pain with non-invasive brain stimulation techniques.
      ,
      • Lefaucheur J.-P.
      Cortical neurostimulation for neuropathic pain: state of the art and perspectives.
      ], and stroke [
      • Meinzer M.
      • Darkow R.
      • Lindenberg R.
      • Flöel A.
      Electrical stimulation of the motor cortex enhances treatment outcome in post-stroke aphasia.
      ]. For more systematic reviews, see Refs. [
      • Fregni F.
      • El-Hagrassy M.M.
      • Pacheco-Barrios K.
      • Carvalho S.
      • Leite J.
      • Simis M.
      • Brunelin J.
      • Nakamura-Palacios E.M.
      • Marangolo P.
      • Venkatasubramanian G.
      • San-Juan D.
      • Caumo W.
      • Bikson M.
      • Brunoni A.R.
      Neuromodulation Center Working Group
      Evidence-based guidelines and secondary meta-analysis for the use of transcranial direct current stimulation in neurological and psychiatric disorders.
      ,
      • Lefaucheur J.-P.
      • Antal A.
      • Ayache S.S.
      • Benninger D.H.
      • Brunelin J.
      • Cogiamanian F.
      • Cotelli M.
      • De Ridder D.
      • Ferrucci R.
      • Langguth B.
      • Marangolo P.
      • Mylius V.
      • Nitsche M.A.
      • Padberg F.
      • Palm U.
      • Poulet E.
      • Priori A.
      • Rossi S.
      • Schecklmann M.
      • Vanneste S.
      • Ziemann U.
      • Garcia-Larrea L.
      • Paulus W.
      Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS).
      ]. The location of stimulation electrodes on the scalp and the exact dose of stimulating current contribute to the rigor and reproducibility of TES studies, as these factors directly determine the stimulation intensity and focality at the desired targets in the brain [
      • Bikson M.
      • Brunoni A.R.
      • Charvet L.E.
      • Clark V.P.
      • Cohen L.G.
      • Deng Z.-D.
      • Dmochowski J.
      • Edwards D.J.
      • Frohlich F.
      • Kappenman E.S.
      • Lim K.O.
      • Loo C.
      • Mantovani A.
      • McMullen D.P.
      • Parra L.C.
      • Pearson M.
      • Richardson J.D.
      • Rumsey J.M.
      • Sehatpour P.
      • Sommers D.
      • Unal G.
      • Wassermann E.M.
      • Woods A.J.
      • Lisanby S.H.
      Rigor and reproducibility in research with transcranial electrical stimulation: an NIMH-sponsored workshop.
      ]. Computational models have been heavily used for estimating electric field distribution in each individual head [
      • Datta A.
      • Bansal V.
      • Diaz J.
      • Patel J.
      • Reato D.
      • Bikson M.
      Gyri –precise head model of transcranial DC stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad.
      ,
      • Ruffini G.
      • Wendling F.
      • Merlet I.
      • Molaee-Ardekani B.
      • Mekonnen A.
      • Salvador R.
      • Soria-Frisch A.
      • Grau C.
      • Dunne S.
      • Miranda P.C.
      Transcranial current brain stimulation (tCS): models and technologies.
      ,
      • Windhoff M.
      • Opitz A.
      • Thielscher A.
      Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models.
      ]. However, these models are not readily accessible to medical doctors. Since the introduction of MRI-derived (i.e., individualized) models [
      • Datta A.
      • Bansal V.
      • Diaz J.
      • Patel J.
      • Reato D.
      • Bikson M.
      Gyri –precise head model of transcranial DC stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad.
      ] and model validation [
      • Huang Y.
      • Liu A.A.
      • Lafon B.
      • Friedman D.
      • Dayan M.
      • Wang X.
      • Bikson M.
      • Doyle W.K.
      • Devinsky O.
      • Parra L.C.
      Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation.
      ], the use of current-flow models has greatly expanded to increase the study rigor (Fig. 1). However, proprietary engineering modeling tools (e.g., COMSOL, Abaqus) are technically sophisticated and difficult to implement for most medical doctors [
      • Datta A.
      • Bansal V.
      • Diaz J.
      • Patel J.
      • Reato D.
      • Bikson M.
      Gyri –precise head model of transcranial DC stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad.
      ,
      • Ruffini G.
      • Wendling F.
      • Merlet I.
      • Molaee-Ardekani B.
      • Mekonnen A.
      • Salvador R.
      • Soria-Frisch A.
      • Grau C.
      • Dunne S.
      • Miranda P.C.
      Transcranial current brain stimulation (tCS): models and technologies.
      ,
      • Windhoff M.
      • Opitz A.
      • Thielscher A.
      Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models.
      ,
      • Huang Y.
      • Dmochowski J.P.
      • Su Y.
      • Datta A.
      • Rorden C.
      • Parra L.C.
      Automated MRI segmentation for individualized modeling of current flow in the human head.
      ]. Open-source software usually have a steep learning curve for researchers without a solid background in computer science (e.g., SciRun, [
      • Dannhauer M.
      • Brooks D.
      • Tucker D.
      • MacLeod R.
      A pipeline for the simulation of transcranial direct current stimulation for realistic human head models using SCIRun/BioMesh3D.
      ]. We recently released a realistic and volumetric approach to simulate TES (ROAST) which succeeds in terms of automation, ease-of-use, speed, and experimental validation [
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline.
      ]. Compared to the other major open-source software in the field, SimNIBS [
      • Windhoff M.
      • Opitz A.
      • Thielscher A.
      Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models.
      ,
      • Thielscher A.
      • Antunes A.
      • Saturnino G.B.
      Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS?.
      ], ROAST advocates volumetric and realistic modeling of the anatomy in the head tissues and performed on par with SimNIBS when tested out-of-box on validation data [
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline.
      ,
      • Puonti O.
      • Saturnino G.B.
      • Madsen K.H.
      • Thielscher A.
      Value and limitations of intracranial recordings for validating electric field modeling for transcranial brain stimulation.
      ].
      Fig. 1
      Fig. 1Number of publications in PubMed returned by searching “computational models transcranial electrical stimulation”. Major open-source software for TES modeling are noted at their time of release. Note the release time of the software may be earlier than the time of their corresponding publication.
      As a new software in the field of TES research, ROAST has gained hundreds of users in a short period of time (Fig. 2). It has been used to model over 1800 individual heads spanning across 12 applications (Table 1). By ensuring the accuracy and replicability throughout the entire modeling process including head segmentation, electrode location and placement, and dose of the stimulation, ROAST helped enhance the rigor and reproducibility of TES studies. Various montages were modeled and electric field magnitudes at the same brain areas under similar montages were reproducible across different studies (Table 2). This paper reviews the adoptions of this software and the use cases in detail, in the hope that future TES research and applications can have a reference on how to leverage readily available computational models to enhance rigor and reproducibility.
      Fig. 2
      Fig. 2Traffic data from Google Analytics for the hosting website of ROAST. (A) Daily downloads since the first release (V1.0). Time points of major version upgrades are noted by vertical gray lines. Note that traffic data are not available immediately after V1.0 as we did not set up traffic tracking until February 2018. (B) Geographical distributions of visitors.
      Table 1Clinical studies that used ROAST to model individual heads under different research contexts. Use purposes include: (I) ROI analysis of E-field against clinical outcomes; (II) Visualization of the E-field at ROI; (III) Voxel-based morphometry; (IV) Optimization of the stimulation; (V) Dose control; (VI) Visualization of electrode placement.
      ApplicationsNumber of Subjects Modeled (References)Use Purposes
      Aging effectsN = 587 [
      • Indahlastari A.
      • Albizu A.
      • O'Shea A.
      • Forbes M.A.
      • Nissim N.R.
      • Kraft J.N.
      • Evangelista N.D.
      • Hausman H.K.
      • Woods A.J.
      Modeling transcranial electrical stimulation in the aging brain.
      ]

      N = 130 [
      • Indahlastari A.
      • Albizu A.
      • Boutzoukas E.M.
      • O'Shea A.
      • Woods A.J.
      White matter hyperintensities affect transcranial electrical stimulation in the aging brain.
      ]

      N = 54 [
      • Lu H.
      • Li J.
      • Zhang L.
      • Chan S.S.M.
      • Lam L.C.W.
      for the Open Access Series of Imaging Studies
      Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling.
      ]
      (I), (III)

      (I), (II), (V)

      (I), (II), (III)
      Alzheimer/DementiaN = 2 [
      • Im J.J.
      • Jeong H.
      • Bikson M.
      • Woods A.J.
      • Unal G.
      • Oh J.K.
      • Na S.
      • Park J.-S.
      • Knotkova H.
      • Song I.-U.
      • Chung Y.-A.
      Effects of 6-month at-home transcranial direct current stimulation on cognition and cerebral glucose metabolism in Alzheimer's disease.
      ]

      N = 60 [
      • Sanches C.
      • Levy R.
      • Benisty S.
      • Volpe-Gillot L.
      • Habert M.-O.
      • Kas A.
      • Ströer S.
      • Pyatigorskaya N.
      • Kaglik A.
      • Bourbon A.
      • Dubois B.
      • Migliaccio R.
      • Valero-Cabré A.
      • Teichmann M.
      Testing the therapeutic effects of transcranial direct current stimulation (tDCS) in semantic dementia: a double blind, sham controlled, randomized clinical trial.
      ]
      (II), (III)

      (II), (III), (VI)
      Brain tumor/lesionN = 2 [
      • Lang S.T.
      • Gan L.S.
      • McLennan C.
      • Monchi O.
      • Kelly J.J.P.
      Impact of peritumoral edema during tumor treatment field therapy: a computational modelling study.
      ]

      N = 2 [
      • Arora Y.
      • Chowdhury S.R.
      Cortical excitability through anodal transcranial direct current stimulation: a computational approach.
      ]

      N = 8 [
      • Lang S.
      • Gan L.S.
      • McLennan C.
      • Kirton A.
      • Monchi O.
      • Kelly J.J.P.
      Preoperative transcranial direct current stimulation in glioma patients: a proof of concept pilot study.
      ]
      (I), (II)

      (II), (VI)

      (I), (II), (VI)
      Cerebellar stimulationN = 4 [
      • Zhang X.
      • Hancock R.
      • Santaniello S.
      Transcranial direct current stimulation of cerebellum alters spiking precision in cerebellar cortex: a modeling study of cellular responses.
      ]

      N = 12 [
      • Rezaee Z.
      • Ranjan S.
      • Solanki D.
      • Bhattacharya M.
      • Srivastava M.V.P.
      • Lahiri U.
      • Dutta A.
      Feasibility of combining functional near-infrared spectroscopy with electroencephalography to identify chronic stroke responders to cerebellar transcranial direct current stimulation—a computational modeling and portable neuroimaging methodological study.
      ]

      N = 18 [
      • Rezaee Z.
      • Dutta A.
      Lobule-specific dosage considerations for cerebellar transcranial direct current stimulation during healthy aging: a computational modeling study using age-specific magnetic resonance imaging templates.
      ]

      N = 10 [
      • Rezaee Z.
      • Kaura S.
      • Solanki D.
      • Dash A.
      • Srivastava M.V.P.
      • Lahiri U.
      • Dutta A.
      Deep cerebellar transcranial direct current stimulation of the dentate nucleus to facilitate standing balance in chronic stroke survivors—a pilot study.
      ]

      N = 12 [
      • Solanki D.
      • Rezaee Z.
      • Dutta A.
      • Lahiri U.
      Investigating the feasibility of cerebellar transcranial direct current stimulation to facilitate post-stroke overground gait performance in chronic stroke: a partial least-squares regression approach.
      ]

      N = 25 [
      • Moussa-Tooks A.B.
      • Cheng H.
      • Burroughs L.P.
      • Rejimon A.C.
      • Hetrick W.P.
      Cerebellar tDCS consistency and metabolite changes: a recommendation to decrease barriers to replicability.
      ]
      (I), (II), (VI)

      (I), (II), (VI)

      (I), (III), (IV)

      (I), (III), (IV)

      (I), (III), (IV)

      (I), (III), (IV)
      CognitionN = 16 [
      • Bhattacharjee S.
      • Kashyap R.
      • O'Brien B.A.
      • McCloskey M.
      • Oishi K.
      • Desmond J.E.
      • Rapp B.
      • Chen S.H.A.
      Reading proficiency influences the effects of transcranial direct current stimulation: evidence from selective modulation of dorsal and ventral pathways of reading in bilinguals.
      ]
      (I), (II), (VI)
      DepressionN = 151 [
      • Argyelan M.
      • Oltedal L.
      • Deng Z.-D.
      • Wade B.
      • Bikson M.
      • Joanlanne A.
      • Sanghani S.
      • Bartsch H.
      • Cano M.
      • Dale A.M.
      • Dannlowski U.
      • Dols A.
      • Enneking V.
      • Espinoza R.
      • Kessler U.
      • Narr K.L.
      • Oedegaard K.J.
      • Oudega M.L.
      • Redlich R.
      • Stek M.L.
      • Takamiya A.
      • Emsell L.
      • Bouckaert F.
      • Sienaert P.
      • Pujol J.
      • Tendolkar I.
      • van Eijndhoven P.
      • Petrides G.
      • Malhotra A.K.
      • Abbott C.
      Electric field causes volumetric changes in the human brain.
      ]
      (I)
      EpilepsyN = 2 [
      • Wang M.
      • Zhu S.
      • Guan H.
      • Jiang H.
      • Zhang J.
      • Zhang S.
      ]

      N = 12 [
      • Wang M.
      • Han J.
      • Jiang H.
      • Zhu J.
      • Feng W.
      • Chhatbar P.Y.
      • Zhang J.
      • Zhang S.
      Intracranial electric field recording during multichannel transcranial electrical stimulation.
      ]
      (I)

      (I), (II), (VI)
      Functional connectivityN = 10 [
      • Kar K.
      • Ito T.
      • Cole M.W.
      • Krekelberg B.
      Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity.
      ]
      (I), (II)
      Inter-individual variabilityN = 57 [
      • Kasten F.H.
      • Duecker K.
      • Maack M.C.
      • Meiser A.
      • Herrmann C.S.
      Integrating electric field modeling and neuroimaging to explain inter-individual variability of tACS effects.
      ]

      N = 50 [
      • Evans C.
      • Bachmann C.
      • Lee J.S.A.
      • Gregoriou E.
      • Ward N.
      • Bestmann S.
      Dose-controlled tDCS reduces electric field intensity variability at a cortical target site.
      ]

      N = 14 [
      • Albizu A.
      • Fang R.
      • Indahlastari A.
      • O'Shea A.
      • Stolte S.E.
      • See K.B.
      • Boutzoukas E.M.
      • Kraft J.N.
      • Nissim N.R.
      • Woods A.J.
      Machine learning and individual variability in electric field characteristics predict tDCS treatment response.
      ]

      N = 2 [
      • Johnstone A.
      • Zich C.
      • Evans C.
      • Lee J.
      • Ward N.
      • Bestmann S.
      The impact of brain lesions on tDCS-induced electric field magnitud.
      ]

      N = 32 [
      • Bhalerao G.V.
      • Sreeraj V.S.
      • Bose A.
      • Narayanaswamy J.C.
      • Venkatasubramanian G.
      Comparison of electric field modeling pipelines for transcranial direct current stimulation.
      ]

      N = 47 [
      • Filmer H.L.
      • Ballard T.
      • Ehrhardt S.E.
      • Bollmann S.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      Dissociable effects of tDCS polarity on latent decision processes are associated with individual differences in neurochemical concentrations and cortical morphology.
      ]

      N = 60 [
      • Zanto T.P.
      • Jones K.T.
      • Ostrand A.E.
      • Hsu W.-Y.
      • Campusano R.
      • Gazzaley A.
      Individual differences in neuroanatomy and neurophysiology predict effects of transcranial alternating current stimulation.
      ]

      N = 240 [
      • Bhattacharjee S.
      • Kashyap R.
      • Goodwill A.M.
      • O'Brien B.A.
      • Rapp B.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      Sex difference in tDCS current mediated by changes in cortical anatomy: a study across young, middle and older adults.
      ]

      N = 29 [
      • Caulfield K.A.
      • Badran B.W.
      • DeVries W.H.
      • Summers P.M.
      • Kofmehl E.
      • Li X.
      • Borckardt J.J.
      • Bikson M.
      • George M.S.
      Transcranial electrical stimulation motor threshold can estimate individualized tDCS dosage from reverse-calculation electric-field modeling.
      ]

      N = 47 [
      • Filmer H.L.
      • Ehrhardt S.E.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      The efficacy of transcranial direct current stimulation to prefrontal areas is related to underlying cortical morphology.
      ]

      N = 15 [
      • Kashyap R.
      • Bhattacharjee S.
      • Arumugam R.
      • Oishi K.
      • Desmond J.E.
      • Chen S.A.
      i-SATA: a MATLAB based toolbox to estimate current density generated by transcranial direct current stimulation in an individual brain.
      ]

      N = 90 [
      • Kashyap R.
      • Bhattacharjee S.
      • Arumugam R.
      • Bharath R.D.
      • Udupa K.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      • Guan C.
      Focality-oriented selection of current dose for transcranial direct current stimulation.
      ]
      (I), (II), (IV), (V) (VI)

      (I), (II), (V), (VI)

      (I), (II), (VI)

      (I), (IV)

      (II)

      (I)

      (I)

      (I), (II), (III), (VI)

      (I), (V)

      (I), (V)

      (II), (VI)

      (II), (V), (VI)
      SchizophreniaN = 21 [
      • Kantrowitz J.T.
      • Sehatpour P.
      • Avissar M.
      • Horga G.
      • Gwak A.
      • Hoptman M.J.
      • Beggel O.
      • Girgis R.R.
      • Vail B.
      • Silipo G.
      • Carlson M.
      • Javitt D.C.
      Significant improvement in treatment resistant auditory verbal hallucinations after 5 days of double-blind, randomized, sham controlled, fronto-temporal, transcranial direct current stimulation (tDCS): a replication/extension study.
      ]

      N = 17 [
      • Mondino M.
      • Fonteneau C.
      • Simon L.
      • Dondé C.
      • Haesebaert F.
      • Poulet E.
      • Brunelin J.
      Advancing clinical response characterization to frontotemporal transcranial direct current stimulation with electric field distribution in patients with schizophrenia and auditory hallucinations: a pilot study.
      ]
      (I), (II), (VI)

      (I)
      Substance use disorderN = 5 [
      • Dutta A.
      • Ghosh A.
      • Singh S.
      Deep cerebellar transcranial electrical stimulation: hypothesis and theory for cannabis use disorder.
      ,
      • Walia P.
      • Ghosh A.
      • Singh S.
      • Dutta A.
      Portable neuroimaging-guided noninvasive brain stimulation of the cortico-cerebello-thalamo-cortical loop—hypothesis and theory in cannabis use disorder.
      ]
      (II), (IV), (V), (VI)
      Working memory and attentionN = 15 [
      • Indahlastari A.
      • Albizu A.
      • Kraft J.N.
      • O'Shea A.
      • Nissim N.R.
      • Dunn A.L.
      • Carballo D.
      • Gordon M.P.
      • Taank S.
      • Kahn A.T.
      • Hernandez C.
      • Zucker W.M.
      • Woods A.J.
      Individualized tDCS modeling predicts functional connectivity changes within the working memory network in older adults.
      ]
      (I), (II)
      TotalN = 1858
      Table 2Details in the studies reported in Table 1. Electrode names follow international 10/05 convention unless otherwise specified. N/A: data not reported in the paper. EEG: electroencephalography; CSF: cerebrospinal fluid; tDCS/tACS: transcranial direct/alternating current stimulation; ROI: region of interest; DLPFC/VLPFC: dorso/ventral lateral prefrontal cortex; M1: primary motor cortex; TPOJ: temporo-parietal-occipital junction.
      Number of Subjects Modeled (References)Electrode montage (high-definition (H) or conventional(C))Which brain area is specifically studied?E-field or current density output by ROAST at studied brain area (normalized to 1 mA stimulation)E-field correlates with the clinical outcome?Patients or healthy subjects?
      N = 587 [
      • Indahlastari A.
      • Albizu A.
      • O'Shea A.
      • Forbes M.A.
      • Nissim N.R.
      • Kraft J.N.
      • Evangelista N.D.
      • Hausman H.K.
      • Woods A.J.
      Modeling transcranial electrical stimulation in the aging brain.
      ]
      F3–F4 & C3-Fp2 (C)Entire brainAverage median were 0.007 A/m2 and 0.009 A/m2 for F3–F4, and 0.011 A/m2 and 0.012 A/m2 for C3-Fp2 montage in the older and young adult cohort, respectively.E-field inversely correlated with brain atrophyHealthy old and young adults
      N = 130 [
      • Indahlastari A.
      • Albizu A.
      • Boutzoukas E.M.
      • O'Shea A.
      • Woods A.J.
      White matter hyperintensities affect transcranial electrical stimulation in the aging brain.
      ]
      F3–F4 (C)White matter hyperintensities (WMH)WMH regions had a maximum of 1.77 V/m.Changes in E-field positively correlated with the total lesion volume.Healthy old adults
      N = 54 [
      • Lu H.
      • Li J.
      • Zhang L.
      • Chan S.S.M.
      • Lam L.C.W.
      for the Open Access Series of Imaging Studies
      Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling.
      ]
      F3 (C)Left M1 and DLPFCN/AE-field decreased with scalp-to-cortex distance in mild cognitive impairment converters.Normal aging and mild cognitive impairment converters
      N = 2 [
      • Im J.J.
      • Jeong H.
      • Bikson M.
      • Woods A.J.
      • Unal G.
      • Oh J.K.
      • Na S.
      • Park J.-S.
      • Knotkova H.
      • Song I.-U.
      • Chung Y.-A.
      Effects of 6-month at-home transcranial direct current stimulation on cognition and cerebral glucose metabolism in Alzheimer's disease.
      ]
      F3–F4 (C)Frontal cortexPeak E-field of 0.3 V/m.N/APatients with early stage Alzheimer's disease
      N = 60 [
      • Sanches C.
      • Levy R.
      • Benisty S.
      • Volpe-Gillot L.
      • Habert M.-O.
      • Kas A.
      • Ströer S.
      • Pyatigorskaya N.
      • Kaglik A.
      • Bourbon A.
      • Dubois B.
      • Migliaccio R.
      • Valero-Cabré A.
      • Teichmann M.
      Testing the therapeutic effects of transcranial direct current stimulation (tDCS) in semantic dementia: a double blind, sham controlled, randomized clinical trial.
      ]
      FT7-AF8 (C)Left anterior/middle temporal lobeN/AN/APatients with dementia
      N = 2 [
      • Lang S.T.
      • Gan L.S.
      • McLennan C.
      • Monchi O.
      • Kelly J.J.P.
      Impact of peritumoral edema during tumor treatment field therapy: a computational modelling study.
      ]
      Anterior-posterior and left-right array (H)Brain tumorAverage E-field at tumor is 0.17 V/m.Presence of peritumoral edema resulted in decreased E-field magnitude within the tumor.Patients with brain tumor
      N = 2 [
      • Arora Y.
      • Chowdhury S.R.
      Cortical excitability through anodal transcranial direct current stimulation: a computational approach.
      ]
      F3–F4, P3–P4 (C&H)Cortical surfacePeak E-field of 0.16 V/m.N/AHealthy and patient with multiple sclerosis
      N = 8 [
      • Lang S.
      • Gan L.S.
      • McLennan C.
      • Kirton A.
      • Monchi O.
      • Kelly J.J.P.
      Preoperative transcranial direct current stimulation in glioma patients: a proof of concept pilot study.
      ]
      C3-FP1 (C)Left M1Average E-field is 0.12 ± 0.03 V/m (range 0.08–0.17 V/m)E-field magnitude applied to the left M1 correlated with changes in global connectivity of the right M1.Patients with left-sided glioma
      N = 4 [
      • Zhang X.
      • Hancock R.
      • Santaniello S.
      Transcranial direct current stimulation of cerebellum alters spiking precision in cerebellar cortex: a modeling study of cellular responses.
      ]
      E133-E18 in EGI HCGSN-256 system (C); anode Iz - cathodes Oz, O2, P8, PO8 (H)Cerebellum0.2 V/m – 0.25 V/m under montage E133-E18; Average 0.1 V/m under montage anode Iz - cathodes Oz, O2, P8, PO8Amplitude and orientation of E-field is related to bursting and complex spiking in Purkinje cells in the cerebellum.Healthy subjects
      N = 12 [
      • Rezaee Z.
      • Ranjan S.
      • Solanki D.
      • Bhattacharya M.
      • Srivastava M.V.P.
      • Lahiri U.
      • Dutta A.
      Feasibility of combining functional near-infrared spectroscopy with electroencephalography to identify chronic stroke responders to cerebellar transcranial direct current stimulation—a computational modeling and portable neuroimaging methodological study.
      ]
      PO9h – PO10h Exx7 – Exx8 (H)CerebellumPeak E-field of 0.15 V/m.Mean E-field strength was a good predictor of the latent variables of oxy-hemoglobin (O2Hb) concentrations and log10-transformed EEG bandpower.Patients with hemiparetic chronic stroke
      N = 18 [
      • Rezaee Z.
      • Dutta A.
      Lobule-specific dosage considerations for cerebellar transcranial direct current stimulation during healthy aging: a computational modeling study using age-specific magnetic resonance imaging templates.
      ]
      Celnik montage (C)CerebellumPeak E-field of 0.15 V/m.E-Field increased significantly at the targeted cerebellar hemisphere at an old age.Healthy subjects
      N = 10 [
      • Rezaee Z.
      • Kaura S.
      • Solanki D.
      • Dash A.
      • Srivastava M.V.P.
      • Lahiri U.
      • Dutta A.
      Deep cerebellar transcranial direct current stimulation of the dentate nucleus to facilitate standing balance in chronic stroke survivors—a pilot study.
      ]
      PO9h–PO10h Exx7–Exx8 (H)CerebellumAverage ∼0.04 V/m.A linear relationship between successful functional reach in post-stroke balance rehabilitation and E-field strength was found.Patients with chronic stroke
      N = 12 [
      • Solanki D.
      • Rezaee Z.
      • Dutta A.
      • Lahiri U.
      Investigating the feasibility of cerebellar transcranial direct current stimulation to facilitate post-stroke overground gait performance in chronic stroke: a partial least-squares regression approach.
      ]
      PO9h-PO10h Exx7-Exx8 (H)CerebellumAverage ∼0.05 V/m.The changes in the quantitative gait parameters were found to be correlated to the mean E-field strength in the cerebellar lobules.Patients with chronic stroke
      N = 25 [
      • Moussa-Tooks A.B.
      • Cheng H.
      • Burroughs L.P.
      • Rejimon A.C.
      • Hetrick W.P.
      Cerebellar tDCS consistency and metabolite changes: a recommendation to decrease barriers to replicability.
      ]
      I1-Exx25 (C)CerebellumN/AtDCS-related metabolite changes may be related to the strength of the E-field induced at the region of interest.Healthy subjects
      N = 16 [
      • Bhattacharjee S.
      • Kashyap R.
      • O'Brien B.A.
      • McCloskey M.
      • Oishi K.
      • Desmond J.E.
      • Rapp B.
      • Chen S.H.A.
      Reading proficiency influences the effects of transcranial direct current stimulation: evidence from selective modulation of dorsal and ventral pathways of reading in bilinguals.
      ]
      CP5-CZLexical (ventral) and sublexical (dorsal) pathways for languageAverage ∼0.04 A/m2.Sub-lexical proficiency is associated with greater effects of tDCS stimulation.Healthy subjects
      TP7-TP8 (C)
      N = 151 [
      • Argyelan M.
      • Oltedal L.
      • Deng Z.-D.
      • Wade B.
      • Bikson M.
      • Joanlanne A.
      • Sanghani S.
      • Bartsch H.
      • Cano M.
      • Dale A.M.
      • Dannlowski U.
      • Dols A.
      • Enneking V.
      • Espinoza R.
      • Kessler U.
      • Narr K.L.
      • Oedegaard K.J.
      • Oudega M.L.
      • Redlich R.
      • Stek M.L.
      • Takamiya A.
      • Emsell L.
      • Bouckaert F.
      • Sienaert P.
      • Pujol J.
      • Tendolkar I.
      • van Eijndhoven P.
      • Petrides G.
      • Malhotra A.K.
      • Abbott C.
      Electric field causes volumetric changes in the human brain.
      ]
      C2-FT8 (H)Left amygdala and left hippocampusAverage ∼0.11 V/m.High electrical fields are strongly associated with robust volume changes in a dose-dependent fashion.Patients with depression
      N = 2 [
      • Wang M.
      • Zhu S.
      • Guan H.
      • Jiang H.
      • Zhang J.
      • Zhang S.
      ]
      Left and right earlobes and infra-auricular (H)Deep brain sampled by sEEG electrodesMaximum of 0.4 V/m.E-fields measured in vivo are highly correlated with the predicted ones.Patients with epilepsy
      N = 12 [
      • Wang M.
      • Han J.
      • Jiang H.
      • Zhu J.
      • Feng W.
      • Chhatbar P.Y.
      • Zhang J.
      • Zhang S.
      Intracranial electric field recording during multichannel transcranial electrical stimulation.
      ]
      Various montages such as T8, Oz - T7 (H)Deep brain sampled by sEEG electrodesMaximum of 0.5 V/m.E-fields measured in vivo are highly correlated with the predicted ones.Patients with epilepsy
      N = 10 [
      • Kar K.
      • Ito T.
      • Cole M.W.
      • Krekelberg B.
      Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity.
      ]
      PO7, PO3 - Cz (H)Motion areaAverage E-field magnitude on the left motion area is 0.16 V/m, and on the right motion area 0.09 V/m.Functional connectivity (between motion area and any other region of interest) increases in proportion to the E-field strength in the region of interest.Healthy subjects
      N = 57 [
      • Kasten F.H.
      • Duecker K.
      • Maack M.C.
      • Meiser A.
      • Herrmann C.S.
      Integrating electric field modeling and neuroimaging to explain inter-individual variability of tACS effects.
      ]
      Cz-Oz (C)Entire brainAverage E-field is 0.13 ± 0.05 V/m (min = 0.08 V/m, max = 0.36 V/m).Variability of power increase in alpha-oscillations was significantly predicted by E-field from individual modeling.Healthy subjects
      N = 50 [
      • Evans C.
      • Bachmann C.
      • Lee J.S.A.
      • Gregoriou E.
      • Ward N.
      • Bestmann S.
      Dose-controlled tDCS reduces electric field intensity variability at a cortical target site.
      ]
      Directional montage: CP5-FC1 (H); Conventional montage: C3-FP2 (H)Left M1Directional montage: 0.19 ± 0.04 V/m; Conventional montage: 0.18 ± 0.04 V/m.Fixed-dose tDCS yields substantially variable E-field intensities in left M1 due to inter-individual variability.Healthy subjects
      N = 14 [
      • Albizu A.
      • Fang R.
      • Indahlastari A.
      • O'Shea A.
      • Stolte S.E.
      • See K.B.
      • Boutzoukas E.M.
      • Kraft J.N.
      • Nissim N.R.
      • Woods A.J.
      Machine learning and individual variability in electric field characteristics predict tDCS treatment response.
      ]
      F3–F4 (C)Entire brainN/AMedian E-field in brain regions near the electrodes were positively related to tDCS intervention responses.Healthy older adults
      N = 2 [
      • Johnstone A.
      • Zich C.
      • Evans C.
      • Lee J.
      • Ward N.
      • Bestmann S.
      The impact of brain lesions on tDCS-induced electric field magnitud.
      ]
      Fp2-CCP3 (H)M1Fp2-CCP3: 0.16 V/m.Lesions that were larger, closer to the ROI, and had a higher conductance tended to have the greatest impact on E-field magnitude.Healthy subjects, with lesions added in the model
      Exx20-FFT7h or F7h (H)Broca's area (BA44)
      N = 32 [
      • Bhalerao G.V.
      • Sreeraj V.S.
      • Bose A.
      • Narayanaswamy J.C.
      • Venkatasubramanian G.
      Comparison of electric field modeling pipelines for transcranial direct current stimulation.
      ]
      AF3-CP5 (C)Entire brainN/AN/AHealthy subjects
      N = 47 [
      • Filmer H.L.
      • Ballard T.
      • Ehrhardt S.E.
      • Bollmann S.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      Dissociable effects of tDCS polarity on latent decision processes are associated with individual differences in neurochemical concentrations and cortical morphology.
      ]
      F3–F4 (C)Inferior frontal gyrusMedian of 0.047 V/m.Including E-field in the regressions did not change the effect of tDCS.Healthy subjects
      N = 60 [
      • Zanto T.P.
      • Jones K.T.
      • Ostrand A.E.
      • Hsu W.-Y.
      • Campusano R.
      • Gazzaley A.
      Individual differences in neuroanatomy and neurophysiology predict effects of transcranial alternating current stimulation.
      ]
      F3–F4 (H)Frontal cortex0.06–0.10 V/m.E-field accounted for 54%–65% of the variance in tACS-related performance improvements.Healthy old adults
      N = 240 [
      • Bhattacharjee S.
      • Kashyap R.
      • Goodwill A.M.
      • O'Brien B.A.
      • Rapp B.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      Sex difference in tDCS current mediated by changes in cortical anatomy: a study across young, middle and older adults.
      ]
      CP5-CZ (C)Inferior parietal lobule (IPL)Average ∼0.2 mA/m2.Across all age groups, CSF and gray matter volumes significantly predicted the E-field at the target sites.Healthy subjects
      F3-FP2 (C)Middle frontal gyrus (MFG)
      N = 29 [
      • Caulfield K.A.
      • Badran B.W.
      • DeVries W.H.
      • Summers P.M.
      • Kofmehl E.
      • Li X.
      • Borckardt J.J.
      • Bikson M.
      • George M.S.
      Transcranial electrical stimulation motor threshold can estimate individualized tDCS dosage from reverse-calculation electric-field modeling.
      ]
      Left motor hotspot and left neck (C)Motor cortexAverage 0.17 V/m.Transcranial electrical stimulation motor threshold significantly correlated with the ROI-based reverse-calculated tDCS dose determined by E-field modeling.Healthy subjects
      N = 47 [
      • Filmer H.L.
      • Ehrhardt S.E.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      The efficacy of transcranial direct current stimulation to prefrontal areas is related to underlying cortical morphology.
      ]
      1 cm posterior to F3–F4 (C)Left prefrontal cortexN/ACortical thickness in left prefrontal cortex correlates with anodal tDCS efficacy.Healthy subjects
      N = 15 [
      • Kashyap R.
      • Bhattacharjee S.
      • Arumugam R.
      • Oishi K.
      • Desmond J.E.
      • Chen S.A.
      i-SATA: a MATLAB based toolbox to estimate current density generated by transcranial direct current stimulation in an individual brain.
      ]
      CP5-Cz (C)Entire brainAverage ∼0.14 mA/m2N/AHealthy subjects
      N = 90 [
      • Kashyap R.
      • Bhattacharjee S.
      • Arumugam R.
      • Bharath R.D.
      • Udupa K.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      • Guan C.
      Focality-oriented selection of current dose for transcranial direct current stimulation.
      ]
      F3 and the right supraorbital (C)Left middle frontal gyrusAverage ∼0.12 mA/m2N/AHealthy subjects
      N = 21 [
      • Kantrowitz J.T.
      • Sehatpour P.
      • Avissar M.
      • Horga G.
      • Gwak A.
      • Hoptman M.J.
      • Beggel O.
      • Girgis R.R.
      • Vail B.
      • Silipo G.
      • Carlson M.
      • Javitt D.C.
      Significant improvement in treatment resistant auditory verbal hallucinations after 5 days of double-blind, randomized, sham controlled, fronto-temporal, transcranial direct current stimulation (tDCS): a replication/extension study.
      ]
      Anode: left DLPFC (between F3 & FP1

      Cathode: left TPOJ (between T3 & P3) (C)
      TPOJ and auditory association regionsAverage ∼0.25 V/m.E-field strength at anterior regions correlated significantly with less robust clinical response.Patients with schizophrenia
      N = 17 [
      • Mondino M.
      • Fonteneau C.
      • Simon L.
      • Dondé C.
      • Haesebaert F.
      • Poulet E.
      • Brunelin J.
      Advancing clinical response characterization to frontotemporal transcranial direct current stimulation with electric field distribution in patients with schizophrenia and auditory hallucinations: a pilot study.
      ]
      Anode: left DLPFC (between F3 & FP1

      Cathode: left TPOJ (between T3 & P3) (C)
      Left transverse temporal gyrusN/AtDCS responders displayed higher E-field strength in the left transverse temporal gyrus at baseline compared to nonresponders.Patients with schizophrenia
      N = 5 [
      • Dutta A.
      • Ghosh A.
      • Singh S.
      Deep cerebellar transcranial electrical stimulation: hypothesis and theory for cannabis use disorder.
      ,
      • Walia P.
      • Ghosh A.
      • Singh S.
      • Dutta A.
      Portable neuroimaging-guided noninvasive brain stimulation of the cortico-cerebello-thalamo-cortical loop—hypothesis and theory in cannabis use disorder.
      ]
      OI2-E145 in EGI HCGSN-256 system (H)CerebellumAverage ∼0.12 V/m.N/APatients with stroke
      N = 15 [
      • Indahlastari A.
      • Albizu A.
      • Kraft J.N.
      • O'Shea A.
      • Nissim N.R.
      • Dunn A.L.
      • Carballo D.
      • Gordon M.P.
      • Taank S.
      • Kahn A.T.
      • Hernandez C.
      • Zucker W.M.
      • Woods A.J.
      Individualized tDCS modeling predicts functional connectivity changes within the working memory network in older adults.
      ]
      F3–F4 (C)Left DLPFC and left VLPFCAverage median at left DLPFC was 0.0407 A/m2, and at left VLPFC was 0.0265 A/m2.E-field in the left DLPFC under active stimulation positively correlated with the beta values as measured functional connectivity metrics.Healthy old adults
      N = 1858

      2. Methods

      2.1 Literature search

      To find out the trend in the literature that utilized modeling for TES research, keywords “computational models transcranial electrical stimulation” were used to search the literature on PubMed. Number of publications by year was returned and plotted.

      2.2 Adoptions of ROAST

      Shortly after the release of ROAST, we have been tracking user downloads on the website that hosts ROAST (https://www.parralab.org/roast/) by Google Analytics. Daily downloads and geographic locations were stored and plotted.

      2.3 Citation report

      All the papers found on Google Scholar that cited ROAST publications [
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline.
      ,
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      ROAST: an open-source, fully-automated, realistic volumetric-approach-based simulator for TES.
      ] were reviewed in April 2022. For each paper, we looked up the number of subjects that were modeled by ROAST, the clinical applications of the subjects that were studied, and the purpose of computational modeling in that study.

      2.4 Rigor and reproducibility

      A workshop organized by the National Institute of Mental Health in 2016 discussed major factors contributing to the rigor and reproducibility of TES research [
      • Bikson M.
      • Brunoni A.R.
      • Charvet L.E.
      • Clark V.P.
      • Cohen L.G.
      • Deng Z.-D.
      • Dmochowski J.
      • Edwards D.J.
      • Frohlich F.
      • Kappenman E.S.
      • Lim K.O.
      • Loo C.
      • Mantovani A.
      • McMullen D.P.
      • Parra L.C.
      • Pearson M.
      • Richardson J.D.
      • Rumsey J.M.
      • Sehatpour P.
      • Sommers D.
      • Unal G.
      • Wassermann E.M.
      • Woods A.J.
      • Lisanby S.H.
      Rigor and reproducibility in research with transcranial electrical stimulation: an NIMH-sponsored workshop.
      ]. The factors that relate to computational modeling include locations of the placed electrodes on the scalp and the dosing of the stimulation. To show how ROAST helps to enhance rigor and reproducibility in those clinical studies found on Google Scholar that used ROAST for modeling more than one individual head, we extracted the following information and compared them across studies: electrode montage and electrode type (conventional (C) vs. high-definition (HD)), stimulated brain areas, achieved intensity of electric field at the stimulated areas (normalized to 1 mA dose), correlation between modeled electric field and clinical outcomes, and subject characteristics (patients vs. healthy).

      3. Results

      3.1 Computational models of TES tend to be widely adopted

      It is obvious that more and more TES studies start to use computational models (Fig. 1), especially since the introduction of individualized modeling from MRIs [
      • Datta A.
      • Bansal V.
      • Diaz J.
      • Patel J.
      • Reato D.
      • Bikson M.
      Gyri –precise head model of transcranial DC stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad.
      ]. SimNIBS, SciRun, and ROAST all helped push the adoption of current-flow models in the literature. Specifically, ROAST has been downloaded 1598 times (1414 unique downloads; see Fig. 2) by April 2022.

      3.2 ROAST has been heavily used for individualized TES modeling

      According to Google Scholar, the papers in which ROAST was published [
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline.
      ,
      • Huang Y.
      • Datta A.
      • Bikson M.
      • Parra L.C.
      ROAST: an open-source, fully-automated, realistic volumetric-approach-based simulator for TES.
      ] had been cited 225 times by April 2022. Among these, 15 are dissertations and 24 are reviews and book chapters. We reviewed the remaining 186 papers, and found 94 clinical TES studies that used ROAST for computational modeling. Table 1 summarizes all the results for each specific clinical application. As a reference, note that SimNIBS [
      • Windhoff M.
      • Opitz A.
      • Thielscher A.
      Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models.
      ,
      • Thielscher A.
      • Antunes A.
      • Saturnino G.B.
      Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS?.
      ] has been cited over 800 times, and SciRun for TES simulation [
      • Dannhauer M.
      • Brooks D.
      • Tucker D.
      • MacLeod R.
      A pipeline for the simulation of transcranial direct current stimulation for realistic human head models using SCIRun/BioMesh3D.
      ] has been cited 57 times. One of the studies in Table 1 also used SimNIBS to model the 32 heads but did not find any significant difference in predicted electric field compared to ROAST [
      • Bhalerao G.V.
      • Sreeraj V.S.
      • Bose A.
      • Narayanaswamy J.C.
      • Venkatasubramanian G.
      Comparison of electric field modeling pipelines for transcranial direct current stimulation.
      ].
      It is clear from Table 1 that ROAST has been applied in clinical studies spanning across 12 applications and modeled 1858 individual heads, thanks to its scripting feature that allows easy batch processing. Most of these studies used ROAST to visualize the stimulation electrodes and the electric field distribution at the region of interests (ROI), and to correlate the simulated electric field intensities at the ROIs with clinical outcomes. Some of these studies used ROAST to calculate the dosing of stimulation, optimize the stimulation montage, or perform voxel-based morphometry using the generated tissue segmentation. The study that modeled the most subjects was [
      • Indahlastari A.
      • Albizu A.
      • O'Shea A.
      • Forbes M.A.
      • Nissim N.R.
      • Kraft J.N.
      • Evangelista N.D.
      • Hausman H.K.
      • Woods A.J.
      Modeling transcranial electrical stimulation in the aging brain.
      ]; where N = 587 healthy older adults under TES were modeled. The results showed that the amount of stimulation current that reaches the brain decreases with increasing atrophy, suggesting that adjusting current dose in older adults based on degree of atrophy may be necessary to achieve desired stimulation benefits. It was not possible to perform TES modeling studies with rigor and reproducibility for over 500 subjects before ROAST was created, as one had to run head segmentation, electrode placement, and electric field computation by hand in various software [
      • Datta A.
      • Bansal V.
      • Diaz J.
      • Patel J.
      • Reato D.
      • Bikson M.
      Gyri –precise head model of transcranial DC stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad.
      ,
      • Huang Y.
      • Dmochowski J.P.
      • Su Y.
      • Datta A.
      • Rorden C.
      • Parra L.C.
      Automated MRI segmentation for individualized modeling of current flow in the human head.
      ,
      • Datta A.
      • Truong D.
      • Minhas P.
      • Parra L.C.
      • Bikson M.
      Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models.
      ], where uncertainties may be introduced by manual operations of these software in the modeling process. Other representative studies include: Ref. [
      • Sanches C.
      • Levy R.
      • Benisty S.
      • Volpe-Gillot L.
      • Habert M.-O.
      • Kas A.
      • Ströer S.
      • Pyatigorskaya N.
      • Kaglik A.
      • Bourbon A.
      • Dubois B.
      • Migliaccio R.
      • Valero-Cabré A.
      • Teichmann M.
      Testing the therapeutic effects of transcranial direct current stimulation (tDCS) in semantic dementia: a double blind, sham controlled, randomized clinical trial.
      ] simulated N = 60 dementia patients to correlate the model-predicted electric field at ROIs with clinical data to evaluate the therapeutic efficacy of a multi-day TES regime on language impairment in patients with semantic dementia. Ref. [
      • Lang S.
      • Gan L.S.
      • McLennan C.
      • Kirton A.
      • Monchi O.
      • Kelly J.J.P.
      Preoperative transcranial direct current stimulation in glioma patients: a proof of concept pilot study.
      ] used ROAST to model N = 8 glioma patients in their study of TES feasibility on these patients. They showed that patient-specific modeling of electric field in the presence of tumor may contribute to understanding the dose-response relationship of this intervention. Ref. [
      • Rezaee Z.
      • Dutta A.
      Lobule-specific dosage considerations for cerebellar transcranial direct current stimulation during healthy aging: a computational modeling study using age-specific magnetic resonance imaging templates.
      ] modeled N = 18 subjects at different ages for cerebellar transcranial direct current stimulation and found that cerebellar shrinkage and increasing thickness of the highly conductive CSF during healthy aging can lead to the dispersion of the current away from the lobules underlying the active electrode. Ref. [
      • Bhattacharjee S.
      • Kashyap R.
      • O'Brien B.A.
      • McCloskey M.
      • Oishi K.
      • Desmond J.E.
      • Rapp B.
      • Chen S.H.A.
      Reading proficiency influences the effects of transcranial direct current stimulation: evidence from selective modulation of dorsal and ventral pathways of reading in bilinguals.
      ] built individualized models for N = 16 subjects to help determine the best montage for selective modulation of dorsal and ventral pathways of reading in bilinguals. Ref. [
      • Argyelan M.
      • Oltedal L.
      • Deng Z.-D.
      • Wade B.
      • Bikson M.
      • Joanlanne A.
      • Sanghani S.
      • Bartsch H.
      • Cano M.
      • Dale A.M.
      • Dannlowski U.
      • Dols A.
      • Enneking V.
      • Espinoza R.
      • Kessler U.
      • Narr K.L.
      • Oedegaard K.J.
      • Oudega M.L.
      • Redlich R.
      • Stek M.L.
      • Takamiya A.
      • Emsell L.
      • Bouckaert F.
      • Sienaert P.
      • Pujol J.
      • Tendolkar I.
      • van Eijndhoven P.
      • Petrides G.
      • Malhotra A.K.
      • Abbott C.
      Electric field causes volumetric changes in the human brain.
      ] used ROAST to calculate the electric field intensities in N = 151 patients with severe depression undergoing electroconvulsive therapy (ECT) and found that the electric fields predicted by ROAST positively correlate with the volumetric changes of the brain due to ECT. Ref. [
      • Wang M.
      • Han J.
      • Jiang H.
      • Zhu J.
      • Feng W.
      • Chhatbar P.Y.
      • Zhang J.
      • Zhang S.
      Intracranial electric field recording during multichannel transcranial electrical stimulation.
      ] compared in vivo measured electric fields during TES on N = 12 epilepsy patients with their individual models generated by ROAST to validate the models. Ref. [
      • Kar K.
      • Ito T.
      • Cole M.W.
      • Krekelberg B.
      Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity.
      ] built N = 10 individualized models using ROAST to study if electric field intensities at the ROIs positively correlate with functional connectivity. Another relatively large study [
      • Bhattacharjee S.
      • Kashyap R.
      • Goodwill A.M.
      • O'Brien B.A.
      • Rapp B.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      Sex difference in tDCS current mediated by changes in cortical anatomy: a study across young, middle and older adults.
      ] leveraged ROAST to model N = 240 individuals to study the effects of cortical anatomical parameters such as volumes, dimension, and torque on simulated TES current density in healthy young, middle-aged, and older males and females. Ref. [
      • Kantrowitz J.T.
      • Sehatpour P.
      • Avissar M.
      • Horga G.
      • Gwak A.
      • Hoptman M.J.
      • Beggel O.
      • Girgis R.R.
      • Vail B.
      • Silipo G.
      • Carlson M.
      • Javitt D.C.
      Significant improvement in treatment resistant auditory verbal hallucinations after 5 days of double-blind, randomized, sham controlled, fronto-temporal, transcranial direct current stimulation (tDCS): a replication/extension study.
      ] modeled N = 21 individual heads to assess the target engagement in their study of TES on antipsychotic-resistant auditory verbal hallucinations in schizophrenia. Refs. [
      • Dutta A.
      • Ghosh A.
      • Singh S.
      Deep cerebellar transcranial electrical stimulation: hypothesis and theory for cannabis use disorder.
      ,
      • Walia P.
      • Ghosh A.
      • Singh S.
      • Dutta A.
      Portable neuroimaging-guided noninvasive brain stimulation of the cortico-cerebello-thalamo-cortical loop—hypothesis and theory in cannabis use disorder.
      ] built individualized head models for N = 5 subjects to compute the optimal electrode montage to target the cortico-cerebello-thalamo-cortical loop for improving substance use disorder. Ref. [
      • Indahlastari A.
      • Albizu A.
      • Kraft J.N.
      • O'Shea A.
      • Nissim N.R.
      • Dunn A.L.
      • Carballo D.
      • Gordon M.P.
      • Taank S.
      • Kahn A.T.
      • Hernandez C.
      • Zucker W.M.
      • Woods A.J.
      Individualized tDCS modeling predicts functional connectivity changes within the working memory network in older adults.
      ] modeled N = 15 subjects to predict significant changes of functional connectivity observed in the working memory network from an acute TES application.
      In addition, many studies run the models on the example head included with ROAST or an individual sample from the investigators. These work cover various clinical applications including: attention-deficit hyperactivity disorder [
      • Dallmer-Zerbe I.
      • Popp F.
      • Lam A.P.
      • Philipsen A.
      • Herrmann C.S.
      Transcranial alternating current stimulation (tACS) as a tool to modulate P300 amplitude in attention deficit hyperactivity disorder (ADHD): preliminary findings.
      ,
      • Klomjai W.
      • Siripornpanich V.
      • Aneksan B.
      • Vimolratana O.
      • Permpoonputtana K.
      • Tretriluxana J.
      • Thichanpiang P.
      Effects of cathodal transcranial direct current stimulation on inhibitory and attention control in children and adolescents with attention-deficit hyperactivity disorder: a pilot randomized sham-controlled crossover study.
      ], aging [
      • Tan S.J.
      • Filmer H.L.
      • Dux P.E.
      Age-related differences in the role of the prefrontal cortex in sensory-motor training gains: a tDCS study.
      ], associative memory [
      • Bjekić J.
      • Vulić K.
      • Živanović M.
      • Vujičić J.
      • Ljubisavljević M.
      • Filipović S.R.
      The immediate and delayed effects of single tDCS session over posterior parietal cortex on face-word associative memory.
      ,
      • Luckey A.M.
      • McLeod S.L.
      • Mohan A.
      • Vanneste S.
      Potential role for peripheral nerve stimulation on learning and long-term memory: a comparison of alternating and direct current stimulations.
      ], attention [
      • Federica C.
      • Edwards G.
      • Tyler S.
      • Parrott D.
      • Grossman E.
      • Lorella B.
      Attention network modulation via tRNS correlates with attention gain.
      ,
      • Kasten F.H.
      • Wendeln T.
      • Stecher H.I.
      • Herrmann C.S.
      Hemisphere-specific, differential effects of lateralized, occipital–parietal α- versus γ-tACS on endogenous but not exogenous visual-spatial attention.
      ,
      • Luna F.G.
      • Román-Caballero R.
      • Barttfeld P.
      • Lupiáñez J.
      • Martín-Arévalo E.
      A High-Definition tDCS and EEG study on attention and vigilance: brain stimulation mitigates the executive but not the arousal vigilance decrement.
      ], body awareness [
      • Takeuchi N.
      • Sudo T.
      • Oouchida Y.
      • Mori T.
      • Izumi S.-I.
      Synchronous neural oscillation between the right inferior fronto-parietal cortices contributes to body awareness.
      ], cognitive control and function [
      • Bhattacharjee S.
      • Kashyap R.
      • Rapp B.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      Simulation analyses of tDCS montages for the investigation of dorsal and ventral pathways.
      ]; Fusco et al. [

      Fusco, G., Fusaro, M., Aglioti, S.M., n.d. Midfrontal-occipital θ-tACS modulates cognitive conflicts related to bodily stimuli 10.

      ]; [
      • Labree B.
      • Corrie H.
      • Karolis V.
      • Didino D.
      • Cappelletti M.
      Parietal alpha-based inhibitory abilities are causally linked to numerosity discrimination.
      ,
      • Li N.
      • Wang Y.
      • Jing F.
      • Zha R.
      • Wei Z.
      • Yang L.-Z.
      • Geng X.
      • Tanaka K.
      • Zhang X.
      A role of the lateral prefrontal cortex in the congruency sequence effect revealed by transcranial direct current stimulation.
      ], connectivity [
      • Tesche C.D.
      • Houck J.M.
      Discordant alpha-band transcranial alternating current stimulation affects cortico-cortical and cortico-cerebellar connectivity.
      ], decision making [
      • Ehrhardt S.E.
      • Filmer H.L.
      • Wards Y.
      • Mattingley J.B.
      • Dux P.E.
      The influence of tDCS intensity on decision-making training and transfer outcomes.
      ,
      • Garofalo S.
      • Battaglia S.
      • Starita F.
      • di Pellegrino G.
      Modulation of cue-guided choices by transcranial direct current stimulation.
      ,
      • Hu Y.
      • Philippe R.
      • Guigon V.
      • Zhao S.
      • Derrington E.
      • Corgnet B.
      • Bonaiuto J.J.
      • Dreher J.-C.
      ,
      • Manuel A.L.
      • Murray N.W.G.
      • Piguet O.
      Transcranial direct current stimulation (tDCS) over vmPFC modulates interactions between reward and emotion in delay discounting.
      ]; Schulreich and Schwabe [

      Schulreich, S., Schwabe, L., n.d. Causal role of the dorsolateral prefrontal cortex in belief updating under uncertainty. Cerebr Cortex. https://doi.org/10.1093/cercor/bhaa219.

      ], declarative learning [
      • Ergo K.
      • Loof E.D.
      • Debra G.
      • Pastötter B.
      • Verguts T.
      Failure to modulate reward prediction errors in declarative learning with theta (6 Hz) frequency transcranial alternating current stimulation.
      ], depressive disorder [
      • Riddle J.
      • Alexander M.L.
      • Schiller C.E.
      • Rubinow D.R.
      • Frohlich F.
      Reduction in left frontal alpha oscillations by transcranial alternating current stimulation in major depressive disorder is context dependent in a randomized clinical trial.
      ], electroencephalography (EEG) research [
      • Gebodh N.
      • Esmaeilpour Z.
      • Datta A.
      • Bikson M.
      Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation.
      ,
      • Jones K.T.
      • Johnson E.L.
      • Tauxe Z.S.
      • Rojas D.C.
      Modulation of auditory gamma-band responses using transcranial electrical stimulation.
      ,
      • Lazarev V.V.
      • Gebodh N.
      • Tamborino T.
      • Bikson M.
      • Caparelli-Daquer E.M.
      Experimental-design specific changes in spontaneous EEG and during intermittent photic stimulation by high definition transcranial direct current stimulation.
      ,
      • Popp F.
      • Dallmer-Zerbe I.
      • Philipsen A.
      • Herrmann C.S.
      Challenges of P300 modulation using transcranial alternating current stimulation (tACS).
      ], imitation [
      • Takeuchi N.
      • Terui Y.
      • Izumi S.-I.
      Oscillatory entrainment of neural activity between inferior frontoparietal cortices alters imitation performance.
      ], memory retrieval [
      • Huang Y.
      • Mohan A.
      • McLeod S.L.
      • Luckey A.M.
      • Hart J.
      • Vanneste S.
      Polarity-specific high-definition transcranial direct current stimulation of the anterior and posterior default mode network improves remote memory retrieval.
      ,
      • Koolschijn R.S.
      • Emir U.E.
      • Pantelides A.C.
      • Nili H.
      • Behrens T.E.J.
      • Barron H.C.
      The Hippocampus and neocortical inhibitory engrams protect against memory interference.
      ,
      • Pyke W.
      • Vostanis A.
      • Javadi A.-H.
      Electrical brain stimulation during a retrieval-based learning task can impair long-term memory.
      ], mind wandering [
      • Filmer H.L.
      • Griffin A.
      • Dux P.E.
      For a minute there, I lost myself … dosage dependent increases in mind wandering via prefrontal tDCS.
      ,
      • Filmer H.L.
      • Marcus L.H.
      • Dux P.E.
      Stimulating task unrelated thoughts: tDCS of prefrontal and parietal cortices leads to polarity specific increases in mind wandering.
      ], motor learning [
      • Ashcroft J.
      • Patel R.
      • Woods A.J.
      • Darzi A.
      • Singh H.
      • Leff D.R.
      Prefrontal transcranial direct-current stimulation improves early technical skills in surgery.
      ,
      • Caesley H.
      • Sewell I.
      • Gogineni N.
      • Javadi A.-H.
      Transcranial direct current stimulation does not improve performance in a whole-body movement task.
      ,
      • Greeley B.
      • Barnhoorn J.S.
      • Verwey W.B.
      • Seidler R.D.
      Multi-session transcranial direct current stimulation over primary motor cortex facilitates sequence learning, chunking, and one year retention.
      ,
      • Greeley B.
      • Seidler R.D.
      Differential effects of left and right prefrontal cortex anodal transcranial direct current stimulation during probabilistic sequence learning.
      ,
      • King B.R.
      • Rumpf J.-J.
      • Heise K.-F.
      • Veldman M.P.
      • Peeters R.
      • Doyon J.
      • Classen J.
      • Albouy G.
      • Swinnen S.P.
      Lateralized effects of post-learning transcranial direct current stimulation on motor memory consolidation in older adults: an fMRI investigation.
      ,
      • Sehatpour P.
      • Donde C.
      • Hoptman M.J.
      • Kreither J.
      • Adair D.
      • Dias E.
      • Vail B.
      • Rohrig S.
      • Silipo G.
      • Lopez-Calderon J.
      • Martinez A.
      • Javitt D.C.
      Network-level mechanisms underlying effects of transcranial direct current stimulation (tDCS) on visuomotor learning.
      ], motor skills [
      • Boukarras S.
      • Özkan D.G.
      • Era V.
      • Moreau Q.
      • Tieri G.
      • Candidi M.
      Midfrontal theta tACS facilitates motor coordination in dyadic human-avatar interactions.
      ,
      • Patel R.
      • Suwa Y.
      • Kinross J.
      • von Roon A.
      • Woods A.J.
      • Darzi A.
      • Singh H.
      • Leff D.R.
      Neuroenhancement of surgeons during robotic suturing.
      ,
      • Walia P.
      • Fu Y.
      • Schwaitzberg S.D.
      • Intes X.
      • De S.
      • Cavuoto L.
      • Dutta A.
      Neuroimaging guided tES to facilitate complex laparoscopic surgical tasks - insights from functional near-infrared spectroscopy.
      ], neurorehabilitation [
      • Wang S.-M.S.
      • Huang Y.-J.
      • Chen J.-J.J.
      • Wu C.-W.
      • Chen C.-A.
      • Lin C.-W.
      • Nguyen V.-T.
      • Peng C.-W.
      Designing and pilot testing a novel high-definition transcranial burst electrostimulation device for neurorehabilitation.
      ], neurovascular coupling [
      • Arora Y.
      • Dutta A.
      Transcranial electrical stimulation effects on neurovascular coupling.
      ], obsessive-compulsive disorder [
      • Frohlich F.
      • Riddle J.
      • Abramowitz J.S.
      Transcranial alternating current stimulation for the treatment of obsessive-compulsive disorder?.
      ], phantom limb pain [
      • Damercheli S.
      • Ramne M.
      • Ortiz-Catalan M.
      Transcranial direct current stimulation (tDCS) for the treatment and investigation of phantom limb pain (PLP).
      ], post-anoxic leukoencephalopathy [
      • Garcia S.
      • Hampstead B.M.
      HD-tDCS as a neurorehabilitation technique for a case of post-anoxic leukoencephalopathy.
      ], reading speed [
      • Reyes C.
      • Padrón I.
      • Nila Yagual S.
      • Marrero H.
      Personality traits modulate the effect of tDCS on reading speed of social sentences.
      ], schizophrenia [
      • Sreeraj V.S.
      • Suhas S.
      • Parlikar R.
      • Selvaraj S.
      • Dinakaran D.
      • Shivakumar V.
      • Narayanaswamy J.C.
      • Venkatasubramanian G.
      Effect of add-on transcranial alternating current stimulation (tACS) on persistent delusions in schizophrenia.
      ], social anxiety disorder [
      • Jafari E.
      • Alizadehgoradel J.
      • Pourmohseni Koluri F.
      • Nikoozadehkordmirza E.
      • Refahi M.
      • Taherifard M.
      • Nejati V.
      • Hallajian A.-H.
      • Ghanavati E.
      • Vicario C.M.
      • Nitsche M.A.
      • Salehinejad M.A.
      Intensified electrical stimulation targeting lateral and medial prefrontal cortices for the treatment of social anxiety disorder: a randomized, double-blind, parallel-group, dose-comparison study.
      ], stroke [
      • Bao S.-C.
      • Wong W.-W.
      • Leung T.W.H.
      • Tong K.-Y.
      Cortico-muscular coherence modulated by high-definition transcranial direct current stimulation in people with chronic stroke.
      ], visual perception [
      • He Q.
      • Yang X.-Y.
      • Gong B.
      • Bi K.
      • Fang F.
      Boosting visual perceptual learning by transcranial alternating current stimulation over the visual cortex at alpha frequency.
      ,
      • Zhu M.
      • Hardstone R.
      • He B.J.
      Neural oscillations promoting perceptual stability and perceptual memory during bistable perception.
      ], and working memory [
      • Cerreta A.G.B.
      • Mruczek R.E.B.
      • Berryhill M.E.
      Predicting working memory training benefits from transcranial direct current stimulation using resting-state fMRI.
      ,
      • Johnson E.L.
      • Arciniega H.
      • Jones K.T.
      • Kilgore-Gomez A.
      • Berryhill M.E.
      Individual predictors and electrophysiological signatures of working memory enhancement in aging.
      ,
      • Jones K.T.
      • Johnson E.L.
      • Berryhill M.E.
      Frontoparietal theta-gamma interactions track working memory enhancement with training and tDCS.
      ,
      • Murphy O.W.
      • Hoy K.E.
      • Wong D.
      • Bailey N.W.
      • Fitzgerald P.B.
      • Segrave R.A.
      Transcranial random noise stimulation is more effective than transcranial direct current stimulation for enhancing working memory in healthy individuals: behavioural and electrophysiological evidence.
      ,
      • Nikolin S.
      • Lauf S.
      • Loo C.K.
      • Martin D.
      Effects of high-definition transcranial direct current stimulation (HD-tDCS) of the intraparietal sulcus and dorsolateral prefrontal cortex on working memory and divided attention.
      ,
      • Nissim N.R.
      • O'Shea A.
      • Indahlastari A.
      • Kraft J.N.
      • von Mering O.
      • Aksu S.
      • Porges E.
      • Cohen R.
      • Woods A.J.
      Effects of transcranial direct current stimulation paired with cognitive training on functional connectivity of the working memory network in older adults.
      ,
      • Thompson L.
      • Khuc J.
      • Saccani M.S.
      • Zokaei N.
      • Cappelletti M.
      Gamma oscillations modulate working memory recall precision.
      ].
      Note that for those studies that involved subjects with pathological head anatomies (e.g., tumor or lesion), customized segmentation was performed and integrated into the ROAST pipeline to account for these anatomies [
      • Im J.J.
      • Jeong H.
      • Bikson M.
      • Woods A.J.
      • Unal G.
      • Oh J.K.
      • Na S.
      • Park J.-S.
      • Knotkova H.
      • Song I.-U.
      • Chung Y.-A.
      Effects of 6-month at-home transcranial direct current stimulation on cognition and cerebral glucose metabolism in Alzheimer's disease.
      ,
      • Lang S.
      • Gan L.S.
      • McLennan C.
      • Kirton A.
      • Monchi O.
      • Kelly J.J.P.
      Preoperative transcranial direct current stimulation in glioma patients: a proof of concept pilot study.
      ]. This is because the segmentation function in ROAST [
      • Ashburner J.
      • Friston K.J.
      Unified segmentation.
      ] was developed for normal head anatomy only.

      3.3 ROAST helps to enhance the rigor and reproducibility

      From Table 2, we can see that ROAST has been used to model various electrode montages to stimulate different brain areas. 29 out of the 35 studies in Table 2 used bipolar montages, and 21 of these bipolar montages are conventional pad electrodes. Most of the studies in Table 2 were interested in stimulating the primary motor cortex (M1), frontal cortex and cerebellum. For the primary motor cortex, Ref. [
      • Lang S.
      • Gan L.S.
      • McLennan C.
      • Kirton A.
      • Monchi O.
      • Kelly J.J.P.
      Preoperative transcranial direct current stimulation in glioma patients: a proof of concept pilot study.
      ] used bipolar montage C3-FP1 with conventional electrodes and achieved an average electric field of 0.12 V/m at the left M1 with 1 mA stimulating current. Ref. [
      • Evans C.
      • Bachmann C.
      • Lee J.S.A.
      • Gregoriou E.
      • Ward N.
      • Bestmann S.
      Dose-controlled tDCS reduces electric field intensity variability at a cortical target site.
      ] obtained an average of 0.19 V/m under montage CP5-FC1 with high-definition electrodes, and 0.18 V/m under montage C3-FP2. Ref. [
      • Johnstone A.
      • Zich C.
      • Evans C.
      • Lee J.
      • Ward N.
      • Bestmann S.
      The impact of brain lesions on tDCS-induced electric field magnitud.
      ] achieved 0.16 V/m averaged electric field with high-definition electrodes Fp2-CCP3. For the frontal cortex, Ref. [
      • Im J.J.
      • Jeong H.
      • Bikson M.
      • Woods A.J.
      • Unal G.
      • Oh J.K.
      • Na S.
      • Park J.-S.
      • Knotkova H.
      • Song I.-U.
      • Chung Y.-A.
      Effects of 6-month at-home transcranial direct current stimulation on cognition and cerebral glucose metabolism in Alzheimer's disease.
      ] obtained a peak electric field of 0.3 V/m with montage F3–F4 using conventional electrodes. With the same montage, Ref. [
      • Filmer H.L.
      • Ballard T.
      • Ehrhardt S.E.
      • Bollmann S.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      Dissociable effects of tDCS polarity on latent decision processes are associated with individual differences in neurochemical concentrations and cortical morphology.
      ] achieved a median electric field of 0.047 V/m at inferior frontal gyrus. Also with the same montage but high-definition electrodes, Ref. [
      • Zanto T.P.
      • Jones K.T.
      • Ostrand A.E.
      • Hsu W.-Y.
      • Campusano R.
      • Gazzaley A.
      Individual differences in neuroanatomy and neurophysiology predict effects of transcranial alternating current stimulation.
      ] showed an electric field in the range of 0.06–0.10 V/m in the frontal cortex. With montage F3 and the right supraorbital, Ref. [
      • Kashyap R.
      • Bhattacharjee S.
      • Arumugam R.
      • Bharath R.D.
      • Udupa K.
      • Oishi K.
      • Desmond J.E.
      • Chen S.H.A.
      • Guan C.
      Focality-oriented selection of current dose for transcranial direct current stimulation.
      ] outputs an average current density of 0.12 mA/m2 at the left middle frontal gyrus. For the cerebellum, both [
      • Rezaee Z.
      • Kaura S.
      • Solanki D.
      • Dash A.
      • Srivastava M.V.P.
      • Lahiri U.
      • Dutta A.
      Deep cerebellar transcranial direct current stimulation of the dentate nucleus to facilitate standing balance in chronic stroke survivors—a pilot study.
      ,
      • Solanki D.
      • Rezaee Z.
      • Dutta A.
      • Lahiri U.
      Investigating the feasibility of cerebellar transcranial direct current stimulation to facilitate post-stroke overground gait performance in chronic stroke: a partial least-squares regression approach.
      ] report an average of about 0.05 V/m under the same montage of PO9h–PO10h using high-definition electrodes. These results suggest that ROAST may help to enhance the rigor of TES models as similar electric field intensities were reproducible across different studies at the same brain area under same or similar stimulation montages.
      In Table 2, 21 out of the 35 studies focus on healthy subjects including old and young adults. The other 14 studies in Table 2 build models for patients with the corresponding clinical applications in Table 1. For all the studies in Table 1 with Use Purpose (I), i.e., ROI analysis of E-field against clinical outcomes, we noted in Table 2 the detailed correlation between the predicted electric field and the studied clinical outcome/metric. Except one study [
      • Filmer H.L.
      • Ballard T.
      • Ehrhardt S.E.
      • Bollmann S.
      • Shaw T.B.
      • Mattingley J.B.
      • Dux P.E.
      Dissociable effects of tDCS polarity on latent decision processes are associated with individual differences in neurochemical concentrations and cortical morphology.
      ], all the other studies in Table 2 report significant correlations between the electric field intensity and the outcome of stimulation or the inter-individual variability.

      4. Discussions and conclusions

      It is clear that computational models are becoming more and more intensively used in the research and clinical applications of TES to enhance rigor and reproducibility. As a new modeling tool in the TES community, ROAST can be improved in several ways to further strengthen study rigor and reproducibility: (1) ROI analysis: a function that allows users to automatically read out electric fields at the ROIs either in the individual head or the standard head space [
      • Evans A.C.
      • Collins D.L.
      • Mills S.R.
      • Brown E.D.
      • Kelly R.L.
      • Peters T.M.
      3D statistical neuroanatomical models from 305 MRI volumes.
      ]. (2) Interface with other open-source software. For example, researchers in source imaging using electroencephalography/magnetoencephalography (EEG/MEG) rely on the same forward models that ROAST generates [
      • Rush S.
      • Driscoll D.A.
      EEG electrode sensitivity--an application of reciprocity.
      ]. We have developed an interface [] that allows users to import the models of a standard head from ROAST into Brainstorm, a popular software for EEG/MEG source localization [
      • Tadel F.
      • Baillet S.
      • Mosher J.C.
      • Pantazis D.
      • Leahy R.M.
      Brainstorm: a user-friendly application for MEG/EEG analysis.
      ]. (3) Interface of customized segmentation. This will allow users to add additional, customized geometry in the model. (4) Integration of modern deep-learning engine for segmentation of pathological head anatomies mostly presented in clinical populations [
      • Hirsch L.
      • Huang Y.
      • Parra L.C.
      Segmentation of MRI head anatomy using deep volumetric networks and multiple spatial priors.
      ]. This will significantly expand the clinical adoptions of this software, as the conventional segmentation algorithm used by ROAST [
      • Ashburner J.
      • Friston K.J.
      Unified segmentation.
      ] is not capable of handling pathological heads. (5) Development of a platform that allows calibration of tissue conductivities for more accurate and personalized modeling. TES models overestimate the electric field compared to intracranial electrical recordings [
      • Huang Y.
      • Liu A.A.
      • Lafon B.
      • Friedman D.
      • Dayan M.
      • Wang X.
      • Bikson M.
      • Doyle W.K.
      • Devinsky O.
      • Parra L.C.
      Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation.
      ], but underestimate the magnetic field induced by the stimulation current compared to actual measurements [
      • Jog M.
      • Jann K.
      • Yan L.
      • Huang Y.
      • Parra L.
      • Narr K.
      • Bikson M.
      • Wang D.J.J.
      Concurrent imaging of markers of current flow and neurophysiological changes during tDCS.
      ]. Future work will leverage state-of-the-art recording techniques such as in-vivo stereotactic EEG electrodes inserted into the deep brain [
      • Louviot S.
      • Tyvaert L.
      • Maillard L.G.
      • Colnat-Coulbois S.
      • Dmochowski J.
      • Koessler L.
      Transcranial Electrical Stimulation generates electric fields in deep human brain structures.
      ], or in-vivo imaging of magnetic fields in the head induced by the stimulation current [
      • Eroglu H.H.
      • Puonti O.
      • Göksu C.
      • Gregersen F.
      • Siebner H.R.
      • Hanson L.G.
      • Thielscher A.
      Human in-vivo magnetic resonance current density imaging of the brain by optimizing head tissue conductivities.
      ] to calibrate the models and derive individualized tissue conductivities. This will facilitate more precise dosing and spatial targeting for the stimulation.
      In conclusion, the era of precise medicine has come including clinical applications of TES where highly individualized and accurate computational models are becoming more readily accessible with constantly improved software and computational power.

      Declaration of competing interest

      We report no relevant conflicts of interest or industry support.

      Declaration of competing interest

      We report no relevant conflicts of interest or industry support.

      Acknowledgements

      This work was supported by the National Institutes of Health through grants P30CA008748 and R01CA247910 . Support was also provided by the Memorial Sloan Kettering Cancer Center Department of Radiology.

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