Cargando…

Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging

Simultaneous MR-PET-EEG (magnetic resonance imaging - positron emission tomography – electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here for the first time. It enables the assessment of molecular metabolic information with high spatial...

Descripción completa

Detalles Bibliográficos
Autores principales: Shah, N. J., Arrubla, J., Rajkumar, R., Farrher, E., Mauler, J., Kops, E. Rota, Tellmann, L., Scheins, J., Boers, F., Dammers, J., Sripad, P., Lerche, C., Langen, K. J., Herzog, H., Neuner, I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5527085/
https://www.ncbi.nlm.nih.gov/pubmed/28743861
http://dx.doi.org/10.1038/s41598-017-05484-w
_version_ 1783252914710511616
author Shah, N. J.
Arrubla, J.
Rajkumar, R.
Farrher, E.
Mauler, J.
Kops, E. Rota
Tellmann, L.
Scheins, J.
Boers, F.
Dammers, J.
Sripad, P.
Lerche, C.
Langen, K. J.
Herzog, H.
Neuner, I.
author_facet Shah, N. J.
Arrubla, J.
Rajkumar, R.
Farrher, E.
Mauler, J.
Kops, E. Rota
Tellmann, L.
Scheins, J.
Boers, F.
Dammers, J.
Sripad, P.
Lerche, C.
Langen, K. J.
Herzog, H.
Neuner, I.
author_sort Shah, N. J.
collection PubMed
description Simultaneous MR-PET-EEG (magnetic resonance imaging - positron emission tomography – electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here for the first time. It enables the assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. Here, we characterize the brain’s default mode network (DMN) in healthy male subjects using multimodal fingerprinting by quantifying energy metabolism via 2- [(18)F]fluoro-2-desoxy-D-glucose PET (FDG-PET), the inhibition – excitation balance of neuronal activation via magnetic resonance spectroscopy (MRS), its functional connectivity via fMRI and its electrophysiological signature via EEG. The trimodal approach reveals a complementary fingerprint. Neuronal activation within the DMN as assessed with fMRI is positively correlated with the mean standard uptake value of FDG. Electrical source localization of EEG signals shows a significant difference between the dorsal DMN and sensorimotor network in the frequency range of δ, θ, α and β–1, but not with β–2 and β–3. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases.
format Online
Article
Text
id pubmed-5527085
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-55270852017-08-02 Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging Shah, N. J. Arrubla, J. Rajkumar, R. Farrher, E. Mauler, J. Kops, E. Rota Tellmann, L. Scheins, J. Boers, F. Dammers, J. Sripad, P. Lerche, C. Langen, K. J. Herzog, H. Neuner, I. Sci Rep Article Simultaneous MR-PET-EEG (magnetic resonance imaging - positron emission tomography – electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here for the first time. It enables the assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. Here, we characterize the brain’s default mode network (DMN) in healthy male subjects using multimodal fingerprinting by quantifying energy metabolism via 2- [(18)F]fluoro-2-desoxy-D-glucose PET (FDG-PET), the inhibition – excitation balance of neuronal activation via magnetic resonance spectroscopy (MRS), its functional connectivity via fMRI and its electrophysiological signature via EEG. The trimodal approach reveals a complementary fingerprint. Neuronal activation within the DMN as assessed with fMRI is positively correlated with the mean standard uptake value of FDG. Electrical source localization of EEG signals shows a significant difference between the dorsal DMN and sensorimotor network in the frequency range of δ, θ, α and β–1, but not with β–2 and β–3. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases. Nature Publishing Group UK 2017-07-25 /pmc/articles/PMC5527085/ /pubmed/28743861 http://dx.doi.org/10.1038/s41598-017-05484-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Shah, N. J.
Arrubla, J.
Rajkumar, R.
Farrher, E.
Mauler, J.
Kops, E. Rota
Tellmann, L.
Scheins, J.
Boers, F.
Dammers, J.
Sripad, P.
Lerche, C.
Langen, K. J.
Herzog, H.
Neuner, I.
Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title_full Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title_fullStr Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title_full_unstemmed Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title_short Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging
title_sort multimodal fingerprints of resting state networks as assessed by simultaneous trimodal mr-pet-eeg imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5527085/
https://www.ncbi.nlm.nih.gov/pubmed/28743861
http://dx.doi.org/10.1038/s41598-017-05484-w
work_keys_str_mv AT shahnj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT arrublaj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT rajkumarr multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT farrhere multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT maulerj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT kopserota multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT tellmannl multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT scheinsj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT boersf multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT dammersj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT sripadp multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT lerchec multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT langenkj multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT herzogh multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging
AT neuneri multimodalfingerprintsofrestingstatenetworksasassessedbysimultaneoustrimodalmrpeteegimaging