Day2day : Investigating daily variability of magnetic resonance imaging measures over half a year
(2017) In BMC Neuroscience 18(1).- Abstract
Background: Most studies of brain structure and function, and their relationships to cognitive ability, have relied on inter-individual variability in magnetic resonance (MR) images. Intra-individual variability is often ignored or implicitly assumed to be equivalent to the former. Testing this assumption empirically by collecting enough data on single individuals is cumbersome and costly. We collected a dataset of multiple MR sequences and behavioural covariates to quantify and characterize intra-individual variability in MR images for multiple individuals. Methods and design: Eight participants volunteered to undergo brain scanning 40-50 times over the course of 6 months. Six participants completed the full set of sessions.... (More)
Background: Most studies of brain structure and function, and their relationships to cognitive ability, have relied on inter-individual variability in magnetic resonance (MR) images. Intra-individual variability is often ignored or implicitly assumed to be equivalent to the former. Testing this assumption empirically by collecting enough data on single individuals is cumbersome and costly. We collected a dataset of multiple MR sequences and behavioural covariates to quantify and characterize intra-individual variability in MR images for multiple individuals. Methods and design: Eight participants volunteered to undergo brain scanning 40-50 times over the course of 6 months. Six participants completed the full set of sessions. T1-weighted, T2*-weighted during rest, T2-weighted high-resolution hippocampus, diffusion-tensor imaging (DTI), and proton magnetic resonance spectroscopy sequences were collected, along with a rich set of stable and time-varying physical, behavioural and physiological variables. Participants did not change their lifestyle or participated in any training programs during the period of data collection. Conclusion: This imaging dataset provides a large number of MRI scans in different modalities for six participants. It enables the analysis of the time course and correlates of intra-individual variability in structural, chemical, and functional aspects of the human brain.
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- author
- Filevich, Elisa ; Lisofsky, Nina ; Becker, Maxi ; Butler, Oisin ; Lochstet, Martyna ; Martensson, Johan LU ; Wenger, Elisabeth ; Lindenberger, Ulman and Kühn, Simone
- organization
- publishing date
- 2017-08-24
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Ergodicity, Longitudinal design, MRI, Reliability, Resting state, Structural imaging, Variability
- in
- BMC Neuroscience
- volume
- 18
- issue
- 1
- article number
- 65
- publisher
- BioMed Central (BMC)
- external identifiers
-
- pmid:28836958
- wos:000408459500001
- scopus:85020443668
- ISSN
- 1471-2202
- DOI
- 10.1186/s12868-017-0383-y
- language
- English
- LU publication?
- yes
- id
- 146c9d19-db6d-442a-88c8-61d634e1863a
- date added to LUP
- 2018-01-12 15:18:20
- date last changed
- 2024-04-15 00:02:53
@article{146c9d19-db6d-442a-88c8-61d634e1863a,
abstract = {{<p>Background: Most studies of brain structure and function, and their relationships to cognitive ability, have relied on inter-individual variability in magnetic resonance (MR) images. Intra-individual variability is often ignored or implicitly assumed to be equivalent to the former. Testing this assumption empirically by collecting enough data on single individuals is cumbersome and costly. We collected a dataset of multiple MR sequences and behavioural covariates to quantify and characterize intra-individual variability in MR images for multiple individuals. Methods and design: Eight participants volunteered to undergo brain scanning 40-50 times over the course of 6 months. Six participants completed the full set of sessions. T1-weighted, T2*-weighted during rest, T2-weighted high-resolution hippocampus, diffusion-tensor imaging (DTI), and proton magnetic resonance spectroscopy sequences were collected, along with a rich set of stable and time-varying physical, behavioural and physiological variables. Participants did not change their lifestyle or participated in any training programs during the period of data collection. Conclusion: This imaging dataset provides a large number of MRI scans in different modalities for six participants. It enables the analysis of the time course and correlates of intra-individual variability in structural, chemical, and functional aspects of the human brain.</p>}},
author = {{Filevich, Elisa and Lisofsky, Nina and Becker, Maxi and Butler, Oisin and Lochstet, Martyna and Martensson, Johan and Wenger, Elisabeth and Lindenberger, Ulman and Kühn, Simone}},
issn = {{1471-2202}},
keywords = {{Ergodicity; Longitudinal design; MRI; Reliability; Resting state; Structural imaging; Variability}},
language = {{eng}},
month = {{08}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Neuroscience}},
title = {{Day2day : Investigating daily variability of magnetic resonance imaging measures over half a year}},
url = {{http://dx.doi.org/10.1186/s12868-017-0383-y}},
doi = {{10.1186/s12868-017-0383-y}},
volume = {{18}},
year = {{2017}},
}