Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation

Juha Koikkalainen, Mervi Könönen, Jari Karhu, Jarmo Ruohonen, Eini Niskanen, Jyrki Lötjönen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

Transcranial Magnetic Stimulation (TMS) is a technique to stimulate the brain non-invasively. The applications range from accurate localization of the primary motor areas to potential treatment of disorders such as tinnitus, severe depression, and pain. Stereotactic guidance requires individual MR images of the subject's head, which is in some applications typically omitted due to financial motivations. In this paper, we introduce a method that offers improved TMS pulse targeting also to those subjects who do not have MR examinations. A probabilistic brain model was constructed by spatially normalizing the locations of the functional brain areas in a study population, and modeling the distributions and estimates of the locations of the functional brain regions using probabilistic methods. The application of the probabilistic brain model to the target subject was based on a point set determined from the scalp and facial skin of the target subject. The methods were evaluated using data from four functional brain areas from 56 healthy subjects. The accuracy of the estimates of the locations of the functional brain regions was about nine millimeters.
Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2008
EditorsD. Metaxas, L. Axel, G. Fichtinger, G. Székely
Place of PublicationBerlin
PublisherSpringer
Pages543-550
ISBN (Electronic)978-3-5408-5988-8
ISBN (Print)978-3-5408-5987-1
DOIs
Publication statusPublished - 2008
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Medical Image Computing and Computer-Assisted Intervention - New York, United States
Duration: 6 Sep 200810 Sep 2008

Publication series

SeriesLecture Notes in Computer Science
Volume5241
ISSN0302-9743

Conference

ConferenceInternational Conference on Medical Image Computing and Computer-Assisted Intervention
CountryUnited States
CityNew York
Period6/09/0810/09/08

Fingerprint

Transcranial Magnetic Stimulation
Atlases
Brain
Statistical Models
Tinnitus
Motor Cortex
Scalp
Motivation
Healthy Volunteers
Head
Demography
Depression
Pain
Skin

Keywords

  • TMS
  • functional atlas
  • point-based registration

Cite this

Koikkalainen, J., Könönen, M., Karhu, J., Ruohonen, J., Niskanen, E., & Lötjönen, J. (2008). Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. In D. Metaxas, L. Axel, G. Fichtinger, & G. Székely (Eds.), Proceedings: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008 (pp. 543-550). Berlin: Springer. Lecture Notes in Computer Science, Vol.. 5241 https://doi.org/10.1007/978-3-540-85988-8_65
Koikkalainen, Juha ; Könönen, Mervi ; Karhu, Jari ; Ruohonen, Jarmo ; Niskanen, Eini ; Lötjönen, Jyrki. / Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. Proceedings: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008. editor / D. Metaxas ; L. Axel ; G. Fichtinger ; G. Székely. Berlin : Springer, 2008. pp. 543-550 (Lecture Notes in Computer Science, Vol. 5241).
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Koikkalainen, J, Könönen, M, Karhu, J, Ruohonen, J, Niskanen, E & Lötjönen, J 2008, Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. in D Metaxas, L Axel, G Fichtinger & G Székely (eds), Proceedings: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008. Springer, Berlin, Lecture Notes in Computer Science, vol. 5241, pp. 543-550, International Conference on Medical Image Computing and Computer-Assisted Intervention, New York, United States, 6/09/08. https://doi.org/10.1007/978-3-540-85988-8_65

Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. / Koikkalainen, Juha; Könönen, Mervi; Karhu, Jari; Ruohonen, Jarmo; Niskanen, Eini; Lötjönen, Jyrki.

Proceedings: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008. ed. / D. Metaxas; L. Axel; G. Fichtinger; G. Székely. Berlin : Springer, 2008. p. 543-550 (Lecture Notes in Computer Science, Vol. 5241).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AU - Könönen, Mervi

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AU - Lötjönen, Jyrki

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N2 - Transcranial Magnetic Stimulation (TMS) is a technique to stimulate the brain non-invasively. The applications range from accurate localization of the primary motor areas to potential treatment of disorders such as tinnitus, severe depression, and pain. Stereotactic guidance requires individual MR images of the subject's head, which is in some applications typically omitted due to financial motivations. In this paper, we introduce a method that offers improved TMS pulse targeting also to those subjects who do not have MR examinations. A probabilistic brain model was constructed by spatially normalizing the locations of the functional brain areas in a study population, and modeling the distributions and estimates of the locations of the functional brain regions using probabilistic methods. The application of the probabilistic brain model to the target subject was based on a point set determined from the scalp and facial skin of the target subject. The methods were evaluated using data from four functional brain areas from 56 healthy subjects. The accuracy of the estimates of the locations of the functional brain regions was about nine millimeters.

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Koikkalainen J, Könönen M, Karhu J, Ruohonen J, Niskanen E, Lötjönen J. Dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. In Metaxas D, Axel L, Fichtinger G, Székely G, editors, Proceedings: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008. Berlin: Springer. 2008. p. 543-550. (Lecture Notes in Computer Science, Vol. 5241). https://doi.org/10.1007/978-3-540-85988-8_65