Individualized Computational Modeling of Transcranial Direct Current Stimulation

Marko Mikkonen

Individualized Computational Modeling of Transcranial Direct Current Stimulation

Julkaisun otsikon käännös: Transkraniaalisen tasavirtastimulaation yksilöllinen laskennallinen mallintaminen

Marko Mikkonen

Tutkimustuotos: Doctoral Thesis › Collection of Articles

Abstrakti

Erilaiset psykiatriset ja neurologiset sairaudet ovat suuri taakka yhteiskunnallemme. Tällaisia häiriöitä hoidetaan usein lääkkeillä riippumatta lääkkeiden sivuvaikutuksista ja korkeista kustannuksista. Lisäksi lääkkeet eivät ole kaikille yhtä tehokkaita. Viime vuosikymmeninä kajoamaton aivostimulaatio (NIBS) on noussut vaihtoehdoksi lääkehoidolle. NIBS pyrkii vaikuttamaan aivojen tilaan sähköisesti joko magneettikentän indusoimalla sähkövirralla tai asettamalla pään pinnalle elektrodeja, joiden läpi virta syötetään. Eräs NIBS-menetelmä on nimeltään transkraniaalinen tasavirtastimulaatio (tDCS), jossa pieni tasavirta johdetaan kajoamattomasti aivoihin pään pinnalle asetettujen elektrodien kautta. Tämän on osoitettu toimivan hoitona esimerkiksi masennukseen ja krooniseen kipuun. TDCS:ssä on kuitenkin huomattava ongelma, sillä sen tulokset vaihtelevat yksilöiden välillä. Tämä johtuu osittain tDCS:n dosimetriasta; tDCS-annos arvioidaan yleisesti syöttövirtaan perustuen, sillä se voidaan helposti asettaa samaksi yksilöiden välillä. Useat tutkimukset ovat kuitenkin huomauttaneet, että vaikka syöttövirta pidetään samana, aivojen kokemat sähkökentät vaihtelevat yksilöiden välillä anatomisista tekijöistä johtuen. Koska sähkökentän mittaaminen aivoissa stimulaation aikana sen käyttämiseksi annosmittana on lähes mahdotonta, mallintaminen on toteuttamiskelpoisin menetelmä päänsisäisten sähkökenttien tutkimiseksi. Tässä viidestä vertaisarvioidusta lehtiartikkelista koostuvassa väitöskirjassa tutkitaan tDCS-sähkökenttien yksilöidenvälistä vaihtelua anatomisesti realistisia päämalleja ja elementtime-netelmää (FEM) hyödyntäen. Väitöskirjani tavoitteena on sekä valaista tDCS:n yksilöiden välisen vaihtelun syitä että tukea ennustettujen sähkökenttien käyttöä tDCS:n dosimetrisena parametrina. Väitöskirjani julkaisussa I esitämme menetelmän, joka mahdollistaa tDCS:n sähkökenttien nykyistä laskennallisesti kevyemmän ja nopeamman ratkaisun elementtimenetelmällä. Julkaisussa II esitämme yhteyden transkraniaalisen magneettisen stimulaation (TMS) motorisen kynnyksen sekä ennustetun tDCS sähkökentän välillä, ja julkaisussa V näytämme yhteyden ennustetun sähkökentän normaalikomponentin ja tDCS:n tuloksen välillä. Julkaisut III ja IV tutkivat tDCS-sähkökenttien yksilöidenvälisen vaihtelun tekijöitä ja osoittavat, että sekä kehon asento että käytetyn elektrodiasetelman tuottaman sähkökentän tarkkuus vaikuttavat tDCS-sähkökenttien yksilöidenväliseen vaihteluun. Tämän väitöskirjan tulokset tarjoavat uutta tietoa tDCS:n yksilöidenvälisen vaihtelun syistä ja esittävät mahdollisia lähestymistapoja, jotta tämä vaihtelu voidaan huomioida paremmin. Lisäksi tulokset yhdistävät mallinnettujen sähkökenttien ja fysiologisesti mitattavissa olevien kajoa-mattomaan aivostimulaatioon liittyviä määreitä, mikä tukee edelleen näiden mallien hyödyllisyyttä tDCS:n tutkimuksessa.

Julkaisun otsikon käännös	Transkraniaalisen tasavirtastimulaation yksilöllinen laskennallinen mallintaminen
Alkuperäiskieli	Englanti
Pätevyys	Tohtorintutkinto
Myöntävä instituutio	Aalto-yliopisto
Valvoja/neuvonantaja	Laakso, Ilkka, Vastuuprofessori Laakso, Ilkka, Ohjaaja
Kustantaja	Aalto University
Painoksen ISBN	978-952-60-8980-5
Sähköinen ISBN	978-952-60-8981-2
Tila	Julkaistu - 2020
OKM-julkaisutyyppi	G5 Tohtorinväitöskirja (artikkeli)

Tutkimusalat

transkraniaalinen tasavirtastimulaatio
kajoamaton aivostimulaatio
yksilöllinen mallinnus
yksilöiden välinen vaihtelu
elementtimenetelmä

Pääsy asiakirjaan

http://urn.fi/URN:ISBN:978-952-60-8981-2

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@phdthesis{adcdc41714994ee99c771e4f0d1f5e24,

title = "Individualized Computational Modeling of Transcranial Direct Current Stimulation",

abstract = "Different psychiatric and neurologic illnesses are a great burden to our society. These kinds of disorders are often treated with pharmaceuticals, regardless of a wide variety of side-effects, poor suitability for many patients and high costs. During the recent decades, non-invasive brain stimulation (NIBS) has risen as a viable treatment alternative to the use of drugs. In NIBS, the state of the brain is affected via electric currents either induced by magnetic fields, or applied directly via electrodes on the scalp. One such method is called transcranial direct current stimulation (tDCS), where a small direct current is applied non-invasively to the brain via electrodes placed onto the scalp. This has, for instance, been shown to be a potential treatment for depression. There is, however, a significant flaw with tDCS in terms of variable efficacy between different patients (inter-individual variability). This arises partially from the dosimetry of tDCS. The tDCS dose is commonly estimated based on the input current, which can be easily set to be the same for a group of subjects. However, multiple studies have pointed out that although the ingoing current is kept the same, the electric field experienced by the brain varies between subjects due to anatomic factors. As it is highly impractical to measure the electric fields in the brain during the stimulation in order to use them as a dose measure, computational modeling therefore remains the only viable way of studying them.In this doctoral thesis comprising five peer-reviewed journal articles, the inter-individual variability of tDCS electric fields is studied using anatomically realistic head models in finite element analysis (FEA). The aim of this thesis is to shed light onto the causes of this variation, as well as to provide evidence to support the viability of using these predicted electric fields as a dosimetric parameter for tDCS. Publication I presents an approach that lowers the computational costs of tDCS electric field predictions using the finite element method. In Publication II, we present a connection between transcranial magnetic stimulation (TMS) motor thresholds and the predicted tDCS electric fields, and in Publication V a connection between predicted electric field normal components and the outcome of tDCS. Publication III and Publication IV study the determinants of the inter-individual variability in tDCS electric fields, and show that body position affects the tDCS electric fields and the focality of the electric field montage used has an effect on the inter-individual variability of those tDCS electric fields. These results provide new information on the causes of inter-individual variability and offer possible approaches to better take it into account with tDCS. Additionally, these results provide further links to connect the FEA-predicted electric fields into physiologically measurable quantities related to NIBS thus giving further support for the value of using these models in the study of tDCS.",

keywords = "non-invasive brain stimulation, transcranial direct current stimulation, interindividual variability, individualized models, finite element method, transkraniaalinen tasavirtastimulaatio, kajoamaton aivostimulaatio, yksil{\"o}llinen mallinnus, yksil{\"o}iden v{\"a}linen vaihtelu, elementtimenetelm{\"a}, non-invasive brain stimulation, transcranial direct current stimulation, interindividual variability, individualized models, finite element method",

author = "Marko Mikkonen",

year = "2020",

language = "English",

isbn = "978-952-60-8980-5",

series = "Aalto University publication series DOCTORAL DISSERTATIONS",

publisher = "Aalto University",

number = "25",

address = "Finland",

school = "Aalto University",

}

TY - THES

T1 - Individualized Computational Modeling of Transcranial Direct Current Stimulation

AU - Mikkonen, Marko

PY - 2020

Y1 - 2020

N2 - Different psychiatric and neurologic illnesses are a great burden to our society. These kinds of disorders are often treated with pharmaceuticals, regardless of a wide variety of side-effects, poor suitability for many patients and high costs. During the recent decades, non-invasive brain stimulation (NIBS) has risen as a viable treatment alternative to the use of drugs. In NIBS, the state of the brain is affected via electric currents either induced by magnetic fields, or applied directly via electrodes on the scalp. One such method is called transcranial direct current stimulation (tDCS), where a small direct current is applied non-invasively to the brain via electrodes placed onto the scalp. This has, for instance, been shown to be a potential treatment for depression. There is, however, a significant flaw with tDCS in terms of variable efficacy between different patients (inter-individual variability). This arises partially from the dosimetry of tDCS. The tDCS dose is commonly estimated based on the input current, which can be easily set to be the same for a group of subjects. However, multiple studies have pointed out that although the ingoing current is kept the same, the electric field experienced by the brain varies between subjects due to anatomic factors. As it is highly impractical to measure the electric fields in the brain during the stimulation in order to use them as a dose measure, computational modeling therefore remains the only viable way of studying them.In this doctoral thesis comprising five peer-reviewed journal articles, the inter-individual variability of tDCS electric fields is studied using anatomically realistic head models in finite element analysis (FEA). The aim of this thesis is to shed light onto the causes of this variation, as well as to provide evidence to support the viability of using these predicted electric fields as a dosimetric parameter for tDCS. Publication I presents an approach that lowers the computational costs of tDCS electric field predictions using the finite element method. In Publication II, we present a connection between transcranial magnetic stimulation (TMS) motor thresholds and the predicted tDCS electric fields, and in Publication V a connection between predicted electric field normal components and the outcome of tDCS. Publication III and Publication IV study the determinants of the inter-individual variability in tDCS electric fields, and show that body position affects the tDCS electric fields and the focality of the electric field montage used has an effect on the inter-individual variability of those tDCS electric fields. These results provide new information on the causes of inter-individual variability and offer possible approaches to better take it into account with tDCS. Additionally, these results provide further links to connect the FEA-predicted electric fields into physiologically measurable quantities related to NIBS thus giving further support for the value of using these models in the study of tDCS.

AB - Different psychiatric and neurologic illnesses are a great burden to our society. These kinds of disorders are often treated with pharmaceuticals, regardless of a wide variety of side-effects, poor suitability for many patients and high costs. During the recent decades, non-invasive brain stimulation (NIBS) has risen as a viable treatment alternative to the use of drugs. In NIBS, the state of the brain is affected via electric currents either induced by magnetic fields, or applied directly via electrodes on the scalp. One such method is called transcranial direct current stimulation (tDCS), where a small direct current is applied non-invasively to the brain via electrodes placed onto the scalp. This has, for instance, been shown to be a potential treatment for depression. There is, however, a significant flaw with tDCS in terms of variable efficacy between different patients (inter-individual variability). This arises partially from the dosimetry of tDCS. The tDCS dose is commonly estimated based on the input current, which can be easily set to be the same for a group of subjects. However, multiple studies have pointed out that although the ingoing current is kept the same, the electric field experienced by the brain varies between subjects due to anatomic factors. As it is highly impractical to measure the electric fields in the brain during the stimulation in order to use them as a dose measure, computational modeling therefore remains the only viable way of studying them.In this doctoral thesis comprising five peer-reviewed journal articles, the inter-individual variability of tDCS electric fields is studied using anatomically realistic head models in finite element analysis (FEA). The aim of this thesis is to shed light onto the causes of this variation, as well as to provide evidence to support the viability of using these predicted electric fields as a dosimetric parameter for tDCS. Publication I presents an approach that lowers the computational costs of tDCS electric field predictions using the finite element method. In Publication II, we present a connection between transcranial magnetic stimulation (TMS) motor thresholds and the predicted tDCS electric fields, and in Publication V a connection between predicted electric field normal components and the outcome of tDCS. Publication III and Publication IV study the determinants of the inter-individual variability in tDCS electric fields, and show that body position affects the tDCS electric fields and the focality of the electric field montage used has an effect on the inter-individual variability of those tDCS electric fields. These results provide new information on the causes of inter-individual variability and offer possible approaches to better take it into account with tDCS. Additionally, these results provide further links to connect the FEA-predicted electric fields into physiologically measurable quantities related to NIBS thus giving further support for the value of using these models in the study of tDCS.

KW - non-invasive brain stimulation

KW - transcranial direct current stimulation

KW - interindividual variability

KW - individualized models

KW - finite element method

KW - transkraniaalinen tasavirtastimulaatio

KW - kajoamaton aivostimulaatio

KW - yksilöllinen mallinnus

KW - yksilöiden välinen vaihtelu

KW - elementtimenetelmä

KW - non-invasive brain stimulation

KW - transcranial direct current stimulation

KW - interindividual variability

KW - individualized models

KW - finite element method

M3 - Doctoral Thesis

SN - 978-952-60-8980-5

T3 - Aalto University publication series DOCTORAL DISSERTATIONS

PB - Aalto University

ER -

Individualized Computational Modeling of Transcranial Direct Current Stimulation

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