{"id":{"repo_id":"aalto","oai_identifier":"oai:aaltodoc.aalto.fi:123456789/30490"},"canonical_url":"https://search.dev.ndltd.org/etd/aalto/oai:aaltodoc.aalto.fi:123456789/30490","repository":{"repo_id":"aalto","name":"Aalto University","base_url":"https://aaltodoc.aalto.fi/server/oai/request"},"display":{"title":"Locating functional brain areas with magnetic stimulation and electrophysiological neuroimaging","abstract":"In order to understand how the human brain works, a common step is to measure signals originating from neuronal activity, or to interfere with brain functioning via external stimulation. These techniques do not answer to the question how, per se, but they give vital information about where and when brain is activated due to the stimulation or during the task performance such as speech. This information can help us understand the investigated brain mechanisms and behavior. In this Thesis, I developed experimental and analysis techniques for navigated transcranial magnetic stimulation (nTMS) and for electro-/magnetoencephalography (EEG, MEG), with a particular focus on providing means to answer where in the brain the interesting processes take place. Navigated TMS allows us to interfere with brain activity non-invasively. As the navigation allows anatomically accurate targeting of the stimulation to a specific area in the brain, the stimulated target is causally linked to the evoked outcome measure, for example, word-production errors or hand movement. EEG and MEG are used to measure the electromagnetic signals generated by the brain with a set of sensors placed over the head. They provide useful information about the evoked brain activity, measured directly from the brain. We introduced a method for locating cortical language areas non-invasively with nTMS. When short TMS bursts are delivered to different brain areas time-locked with a picture-naming task, language areas are revealed by stimulation-evoked naming errors. This \"nTMS language mapping\" provides a spatial distribution of cortical areas related to language. This information is useful in language studies and also when the neurosurgeon needs to know which areas of the brain must be protected during operation. We applied nTMS during different naming tasks and in bilingual speakers of Finnish and Swedish, showing that task parameters affect the outcome of nTMS. We also developed novel source localization techniques to analyze EEG and MEG. These methods belong to the family of multiple signal classifiers (MUSIC). Two different method types were introduced for different applications; they were compared with other source localization methods in simulations and with measured MEG data. Conventional recursive MUSIC has been shown to be efficient in estimating temporally uncorrelated or weakly/moderately correlated sources, but the method can be unreliable when estimating the number of sources; our first method called TRAP-MUSIC solves this problem. On the other hand, if the data are also due to highly correlated and synchronous sources, neither conventional methods nor TRAP-MUSIC are sufficient. Our second method, RDS-MUSIC, provides a solution to this issue. The presented methods provide new possibilities to neuroscientists for investigating where the brain processes governing human behavior and actions, in particular, but not limited to, language, take place.","abstract_html":"In order to understand how the human brain works, a common step is to measure signals originating from neuronal activity, or to interfere with brain functioning via external stimulation. These techniques do not answer to the question how, per se, but they give vital information about where and when brain is activated due to the stimulation or during the task performance such as speech. This information can help us understand the investigated brain mechanisms and behavior. In this Thesis, I developed experimental and analysis techniques for navigated transcranial magnetic stimulation (nTMS) and for electro-/magnetoencephalography (EEG, MEG), with a particular focus on providing means to answer where in the brain the interesting processes take place. Navigated TMS allows us to interfere with brain activity non-invasively. As the navigation allows anatomically accurate targeting of the stimulation to a specific area in the brain, the stimulated target is causally linked to the evoked outcome measure, for example, word-production errors or hand movement. EEG and MEG are used to measure the electromagnetic signals generated by the brain with a set of sensors placed over the head. They provide useful information about the evoked brain activity, measured directly from the brain. We introduced a method for locating cortical language areas non-invasively with nTMS. When short TMS bursts are delivered to different brain areas time-locked with a picture-naming task, language areas are revealed by stimulation-evoked naming errors. This "nTMS language mapping" provides a spatial distribution of cortical areas related to language. This information is useful in language studies and also when the neurosurgeon needs to know which areas of the brain must be protected during operation. We applied nTMS during different naming tasks and in bilingual speakers of Finnish and Swedish, showing that task parameters affect the outcome of nTMS. We also developed novel source localization techniques to analyze EEG and MEG. These methods belong to the family of multiple signal classifiers (MUSIC). Two different method types were introduced for different applications; they were compared with other source localization methods in simulations and with measured MEG data. Conventional recursive MUSIC has been shown to be efficient in estimating temporally uncorrelated or weakly/moderately correlated sources, but the method can be unreliable when estimating the number of sources; our first method called TRAP-MUSIC solves this problem. On the other hand, if the data are also due to highly correlated and synchronous sources, neither conventional methods nor TRAP-MUSIC are sufficient. Our second method, RDS-MUSIC, provides a solution to this issue. The presented methods provide new possibilities to neuroscientists for investigating where the brain processes governing human behavior and actions, in particular, but not limited to, language, take place.","abstract_has_math":false,"creators":["Mäkelä, Niko"],"institution":"Aalto University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Neurotieteen ja lääketieteellisen tekniikan laitos","school":null,"contributors":["Aalto-yliopisto","Aalto University"],"advisors":["Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Sarvas, Jukka, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Stenroos, Matti, Doc., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland"],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018","date_published":"2018","updated_at":"2026-08-21T16:42:07Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://aaltodoc.aalto.fi/handle/123456789/30490","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"source_record":{"url":"https://aaltodoc.aalto.fi/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aaaltodoc.aalto.fi%3A123456789%2F30490","prefix":"dim"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Aalto-yliopisto","Aalto University"]},{"key":"dc:contributor.advisor","label":"Advisor","values":["Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Sarvas, Jukka, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Stenroos, Matti, Doc., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland"]},{"key":"dc:contributor.department","label":"Department","values":["Neurotieteen ja lääketieteellisen tekniikan laitos","Department of Neuroscience and Biomedical Engineering"]},{"key":"dc:contributor.supervisor","label":"Supervisor","values":["Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland"]},{"key":"dc:creator","label":"Author","values":["Mäkelä, Niko"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-03-29T09:02:45Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-03-29T09:02:45Z"]},{"key":"dc:date.issued","label":"Date","values":["2018"]},{"key":"dc:publisher","label":"Institution","values":["Aalto University","Aalto-yliopisto"]},{"key":"dc:type","label":"Dc Type","values":["G5 Artikkeliväitöskirja"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["text"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://aaltodoc.aalto.fi/handle/123456789/30490"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In order to understand how the human brain works, a common step is to measure signals originating from neuronal activity, or to interfere with brain functioning via external stimulation. These techniques do not answer to the question how, per se, but they give vital information about where and when brain is activated due to the stimulation or during the task performance such as speech. This information can help us understand the investigated brain mechanisms and behavior. In this Thesis, I developed experimental and analysis techniques for navigated transcranial magnetic stimulation (nTMS) and for electro-/magnetoencephalography (EEG, MEG), with a particular focus on providing means to answer where in the brain the interesting processes take place. Navigated TMS allows us to interfere with brain activity non-invasively. As the navigation allows anatomically accurate targeting of the stimulation to a specific area in the brain, the stimulated target is causally linked to the evoked outcome measure, for example, word-production errors or hand movement. EEG and MEG are used to measure the electromagnetic signals generated by the brain with a set of sensors placed over the head. They provide useful information about the evoked brain activity, measured directly from the brain. We introduced a method for locating cortical language areas non-invasively with nTMS. When short TMS bursts are delivered to different brain areas time-locked with a picture-naming task, language areas are revealed by stimulation-evoked naming errors. This \"nTMS language mapping\" provides a spatial distribution of cortical areas related to language. This information is useful in language studies and also when the neurosurgeon needs to know which areas of the brain must be protected during operation. We applied nTMS during different naming tasks and in bilingual speakers of Finnish and Swedish, showing that task parameters affect the outcome of nTMS. We also developed novel source localization techniques to analyze EEG and MEG. These methods belong to the family of multiple signal classifiers (MUSIC). Two different method types were introduced for different applications; they were compared with other source localization methods in simulations and with measured MEG data. Conventional recursive MUSIC has been shown to be efficient in estimating temporally uncorrelated or weakly/moderately correlated sources, but the method can be unreliable when estimating the number of sources; our first method called TRAP-MUSIC solves this problem. On the other hand, if the data are also due to highly correlated and synchronous sources, neither conventional methods nor TRAP-MUSIC are sufficient. Our second method, RDS-MUSIC, provides a solution to this issue. The presented methods provide new possibilities to neuroscientists for investigating where the brain processes governing human behavior and actions, in particular, but not limited to, language, take place.","Toiminnallisen aivokuvantamisen perimmäinen tarkoitus on auttaa meitä ymmärtämään miten aivot toimivat. Aivojen aktivaatiosta syntyneitä signaaleja voidaan mitata, tai aivotoimintaan voidaan vaikuttaa päänulkoisella stimulaatiolla. Nämä menetelmät eivät kuitenkaan vastaa suoraan siihen miten aivot toimivat; sen sijaan, ne tarjoavat arvokasta tietoa siitä, missä ja milloin aivot aktivoituvat kun suoritamme erilaisia tehtäviä, kuten tuotamme puhetta. Tämän tiedon perusteella voimme ymmärtää paremmin käyttäytymistämme ja sen taustalla olevia aivomekanismeja. Tässä väitöskirjatyössä kehitettiin mittaus- ja analyysimenetelmiä navigoidun magneettistimulaation sekä aivojen sähkö- ja magneettikäyrän (EEG, MEG) käyttöön ja tulkintaan. Menetelmien avulla voidaan selvittää missä päin aivoja kiinnostavat prosessit tapahtuvat. Navigoidulla transkraniaalisella magneettistimulaatiolla (nTMS) voidaan vaikuttaa aivojen toimintaan ei-invasiivisesti. Navigoinnin ansiosta stimulaatio voidaan kohdistaa anatomisen tarkasti haluttuun kohtaan aivoissa, jolloin stimuloidun alueen ja mitatun vasteen, kuten käden liikkeen tai puhehäiriöiden, välille saadaan syy–seuraussuhde. EEG ja MEG mittaavat aivotoiminnan tuottamia sähkö- ja magneettikenttiä suoraan aivoista pään pinnalle tai sen läheisyyteen sijoitetuilla antureilla. Väitöskirjassa esitellään nTMS-pohjainen aivokuoren puhealueiden paikannusmenetelmä. Kun nTMS kohdennetaan puheentuottoa prosessoivalle aivoalueelle koehenkilön suorittaessa kuvannimeämistehtävää, voidaan saada aikaan nimeämisvirheitä. Tällä nTMS-puhekartoitusmenetelmällä saatua tietoa aivojen puhealueiden sijainneista voidaan käyttää paitsi perustutkimuksessa, niin myös suunniteltaessa aivoleikkausta, jossa kirurgin tulee tietää mitä alueita pitää varjella operaation aikana. Osoitimme jatkotutkimuksissa, että nimeämistehtävän ominaisuudet, kuten suorituskieli, vaikuttavat aivojen nTMS-vasteeseen. Väitöstyössä kehitettiin myös parempia lähdepaikannusmenetelmiä EEG:n ja MEG:n tulkintaan. Kehitetyt menetelmät kuuluvat multiple signal classification -luokkaan (MUSIC), ja niitä verrattiin muihin paikannusalgoritmeihin simulaatioiden ja mittausdatan avulla. Kaksi erilaista lähdepaikannusmenetelmää kehitettiin ratkaisemaan kaksi aiemmissa menetelmissä havaittua ongelmaa. Perinteinen rekursiivinen MUSIC on tehokas löytämään ajassa heikosti tai ei ollenkaan korreloituneita lähteitä, mutta menetelmä ei arvioi luotettavasti lähteiden lukumäärää; väitöstyössä kehitetty TRAP-MUSIC-menetelmä korjaa tämän ongelman. Voimakkaasti korreloituneiden aivolähteiden paikannukseen perinteiset menetelmät tai TRAP-MUSIC eivät sovellu. Tällaisten lähteiden etsintään kehitimme RDS-MUSIC-menetelmän. Tässä väitöskirjassa esitetyt menetelmät tarjoavat uusia keinoja tutkia missä ihmisten käytöksen ja toiminnan taustalla olevat aivotoiminnot, kuten kielen prosessointi, tapahtuvat."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Locating functional brain areas with magnetic stimulation and electrophysiological neuroimaging","Toiminnallisten aivoalueiden paikannus magneettistimulaatiolla ja elektrofysiologisilla kuvantamismenetelmillä"]}]}],"canonical_facts":{"dc:contributor":["Aalto-yliopisto","Aalto University"],"dc:contributor.advisor":["Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Sarvas, Jukka, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland","Stenroos, Matti, Doc., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland"],"dc:contributor.department":["Neurotieteen ja lääketieteellisen tekniikan laitos","Department of Neuroscience and Biomedical Engineering"],"dc:contributor.supervisor":["Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland"],"dc:creator":["Mäkelä, Niko"],"dc:date.accessioned":["2018-03-29T09:02:45Z"],"dc:date.available":["2018-03-29T09:02:45Z"],"dc:date.issued":["2018"],"dc:description.abstract":["In order to understand how the human brain works, a common step is to measure signals originating from neuronal activity, or to interfere with brain functioning via external stimulation. These techniques do not answer to the question how, per se, but they give vital information about where and when brain is activated due to the stimulation or during the task performance such as speech. This information can help us understand the investigated brain mechanisms and behavior. In this Thesis, I developed experimental and analysis techniques for navigated transcranial magnetic stimulation (nTMS) and for electro-/magnetoencephalography (EEG, MEG), with a particular focus on providing means to answer where in the brain the interesting processes take place. Navigated TMS allows us to interfere with brain activity non-invasively. As the navigation allows anatomically accurate targeting of the stimulation to a specific area in the brain, the stimulated target is causally linked to the evoked outcome measure, for example, word-production errors or hand movement. EEG and MEG are used to measure the electromagnetic signals generated by the brain with a set of sensors placed over the head. They provide useful information about the evoked brain activity, measured directly from the brain. We introduced a method for locating cortical language areas non-invasively with nTMS. When short TMS bursts are delivered to different brain areas time-locked with a picture-naming task, language areas are revealed by stimulation-evoked naming errors. This \"nTMS language mapping\" provides a spatial distribution of cortical areas related to language. This information is useful in language studies and also when the neurosurgeon needs to know which areas of the brain must be protected during operation. We applied nTMS during different naming tasks and in bilingual speakers of Finnish and Swedish, showing that task parameters affect the outcome of nTMS. We also developed novel source localization techniques to analyze EEG and MEG. These methods belong to the family of multiple signal classifiers (MUSIC). Two different method types were introduced for different applications; they were compared with other source localization methods in simulations and with measured MEG data. Conventional recursive MUSIC has been shown to be efficient in estimating temporally uncorrelated or weakly/moderately correlated sources, but the method can be unreliable when estimating the number of sources; our first method called TRAP-MUSIC solves this problem. On the other hand, if the data are also due to highly correlated and synchronous sources, neither conventional methods nor TRAP-MUSIC are sufficient. Our second method, RDS-MUSIC, provides a solution to this issue. The presented methods provide new possibilities to neuroscientists for investigating where the brain processes governing human behavior and actions, in particular, but not limited to, language, take place.","Toiminnallisen aivokuvantamisen perimmäinen tarkoitus on auttaa meitä ymmärtämään miten aivot toimivat. Aivojen aktivaatiosta syntyneitä signaaleja voidaan mitata, tai aivotoimintaan voidaan vaikuttaa päänulkoisella stimulaatiolla. Nämä menetelmät eivät kuitenkaan vastaa suoraan siihen miten aivot toimivat; sen sijaan, ne tarjoavat arvokasta tietoa siitä, missä ja milloin aivot aktivoituvat kun suoritamme erilaisia tehtäviä, kuten tuotamme puhetta. Tämän tiedon perusteella voimme ymmärtää paremmin käyttäytymistämme ja sen taustalla olevia aivomekanismeja. Tässä väitöskirjatyössä kehitettiin mittaus- ja analyysimenetelmiä navigoidun magneettistimulaation sekä aivojen sähkö- ja magneettikäyrän (EEG, MEG) käyttöön ja tulkintaan. Menetelmien avulla voidaan selvittää missä päin aivoja kiinnostavat prosessit tapahtuvat. Navigoidulla transkraniaalisella magneettistimulaatiolla (nTMS) voidaan vaikuttaa aivojen toimintaan ei-invasiivisesti. Navigoinnin ansiosta stimulaatio voidaan kohdistaa anatomisen tarkasti haluttuun kohtaan aivoissa, jolloin stimuloidun alueen ja mitatun vasteen, kuten käden liikkeen tai puhehäiriöiden, välille saadaan syy–seuraussuhde. EEG ja MEG mittaavat aivotoiminnan tuottamia sähkö- ja magneettikenttiä suoraan aivoista pään pinnalle tai sen läheisyyteen sijoitetuilla antureilla. Väitöskirjassa esitellään nTMS-pohjainen aivokuoren puhealueiden paikannusmenetelmä. Kun nTMS kohdennetaan puheentuottoa prosessoivalle aivoalueelle koehenkilön suorittaessa kuvannimeämistehtävää, voidaan saada aikaan nimeämisvirheitä. Tällä nTMS-puhekartoitusmenetelmällä saatua tietoa aivojen puhealueiden sijainneista voidaan käyttää paitsi perustutkimuksessa, niin myös suunniteltaessa aivoleikkausta, jossa kirurgin tulee tietää mitä alueita pitää varjella operaation aikana. Osoitimme jatkotutkimuksissa, että nimeämistehtävän ominaisuudet, kuten suorituskieli, vaikuttavat aivojen nTMS-vasteeseen. Väitöstyössä kehitettiin myös parempia lähdepaikannusmenetelmiä EEG:n ja MEG:n tulkintaan. Kehitetyt menetelmät kuuluvat multiple signal classification -luokkaan (MUSIC), ja niitä verrattiin muihin paikannusalgoritmeihin simulaatioiden ja mittausdatan avulla. Kaksi erilaista lähdepaikannusmenetelmää kehitettiin ratkaisemaan kaksi aiemmissa menetelmissä havaittua ongelmaa. Perinteinen rekursiivinen MUSIC on tehokas löytämään ajassa heikosti tai ei ollenkaan korreloituneita lähteitä, mutta menetelmä ei arvioi luotettavasti lähteiden lukumäärää; väitöstyössä kehitetty TRAP-MUSIC-menetelmä korjaa tämän ongelman. Voimakkaasti korreloituneiden aivolähteiden paikannukseen perinteiset menetelmät tai TRAP-MUSIC eivät sovellu. Tällaisten lähteiden etsintään kehitimme RDS-MUSIC-menetelmän. Tässä väitöskirjassa esitetyt menetelmät tarjoavat uusia keinoja tutkia missä ihmisten käytöksen ja toiminnan taustalla olevat aivotoiminnot, kuten kielen prosessointi, tapahtuvat."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://aaltodoc.aalto.fi/handle/123456789/30490"],"dc:language.iso":["en"],"dc:publisher":["Aalto University","Aalto-yliopisto"],"dc:title":["Locating functional brain areas with magnetic stimulation and electrophysiological neuroimaging","Toiminnallisten aivoalueiden paikannus magneettistimulaatiolla ja elektrofysiologisilla kuvantamismenetelmillä"],"dc:type":["G5 Artikkeliväitöskirja"],"dc:type.dcmitype":["text"]},"updated_at":"2026-08-21T16:42:07Z"}