The spectral diversity of resting-state fluctuations in the human brain.
In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spati...
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0093375 |
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| author | Klaudius Kalcher Roland N Boubela Wolfgang Huf Lucie Bartova Claudia Kronnerwetter Birgit Derntl Lukas Pezawas Peter Filzmoser Christian Nasel Ewald Moser |
| author_facet | Klaudius Kalcher Roland N Boubela Wolfgang Huf Lucie Bartova Claudia Kronnerwetter Birgit Derntl Lukas Pezawas Peter Filzmoser Christian Nasel Ewald Moser |
| author_sort | Klaudius Kalcher |
| collection | DOAJ |
| description | In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments. |
| format | Article |
| id | doaj-art-444bfa0dd72e4f69af1768796ef4e040 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-444bfa0dd72e4f69af1768796ef4e0402025-08-20T02:09:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0194e9337510.1371/journal.pone.0093375The spectral diversity of resting-state fluctuations in the human brain.Klaudius KalcherRoland N BoubelaWolfgang HufLucie BartovaClaudia KronnerwetterBirgit DerntlLukas PezawasPeter FilzmoserChristian NaselEwald MoserIn order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments.https://doi.org/10.1371/journal.pone.0093375 |
| spellingShingle | Klaudius Kalcher Roland N Boubela Wolfgang Huf Lucie Bartova Claudia Kronnerwetter Birgit Derntl Lukas Pezawas Peter Filzmoser Christian Nasel Ewald Moser The spectral diversity of resting-state fluctuations in the human brain. PLoS ONE |
| title | The spectral diversity of resting-state fluctuations in the human brain. |
| title_full | The spectral diversity of resting-state fluctuations in the human brain. |
| title_fullStr | The spectral diversity of resting-state fluctuations in the human brain. |
| title_full_unstemmed | The spectral diversity of resting-state fluctuations in the human brain. |
| title_short | The spectral diversity of resting-state fluctuations in the human brain. |
| title_sort | spectral diversity of resting state fluctuations in the human brain |
| url | https://doi.org/10.1371/journal.pone.0093375 |
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