Day2day investigating daily variability of magnetic resonance imaging measures over half a year

Standard

Day2day investigating daily variability of magnetic resonance imaging measures over half a year. / Filevich, Elisa; Lisofsky, Nina; Becker, Maxi; Butler, Oisin; Lochstet, Martyna; Martensson, Johan; Wenger, Elisabeth; Lindenberger, Ulman; Kühn, Simone.

in: BMC NEUROSCI, Jahrgang 18, Nr. 1, 24.08.2017, S. 65.

Publikationen: SCORING: Beitrag in Fachzeitschrift/ZeitungSCORING: ZeitschriftenaufsatzForschungBegutachtung

Harvard

Filevich, E, Lisofsky, N, Becker, M, Butler, O, Lochstet, M, Martensson, J, Wenger, E, Lindenberger, U & Kühn, S 2017, 'Day2day investigating daily variability of magnetic resonance imaging measures over half a year', BMC NEUROSCI, Jg. 18, Nr. 1, S. 65. https://doi.org/10.1186/s12868-017-0383-y

APA

Filevich, E., Lisofsky, N., Becker, M., Butler, O., Lochstet, M., Martensson, J., Wenger, E., Lindenberger, U., & Kühn, S. (2017). Day2day investigating daily variability of magnetic resonance imaging measures over half a year. BMC NEUROSCI, 18(1), 65. https://doi.org/10.1186/s12868-017-0383-y

Vancouver

Filevich E, Lisofsky N, Becker M, Butler O, Lochstet M, Martensson J et al. Day2day investigating daily variability of magnetic resonance imaging measures over half a year. BMC NEUROSCI. 2017 Aug 24;18(1):65. https://doi.org/10.1186/s12868-017-0383-y

Bibtex

@article{e250ee251749468485d483bbe1e3d422,
title = "Day2day investigating daily variability of magnetic resonance imaging measures over half a year",
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. 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.",
keywords = "Journal Article",
author = "Elisa Filevich and Nina Lisofsky and Maxi Becker and Oisin Butler and Martyna Lochstet and Johan Martensson and Elisabeth Wenger and Ulman Lindenberger and Simone K{\"u}hn",
year = "2017",
month = aug,
day = "24",
doi = "10.1186/s12868-017-0383-y",
language = "English",
volume = "18",
pages = "65",
journal = "BMC NEUROSCI",
issn = "1471-2202",
publisher = "BioMed Central Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Day2day investigating daily variability of magnetic resonance imaging measures over half a year

AU - Filevich, Elisa

AU - Lisofsky, Nina

AU - Becker, Maxi

AU - Butler, Oisin

AU - Lochstet, Martyna

AU - Martensson, Johan

AU - Wenger, Elisabeth

AU - Lindenberger, Ulman

AU - Kühn, Simone

PY - 2017/8/24

Y1 - 2017/8/24

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1186/s12868-017-0383-y

DO - 10.1186/s12868-017-0383-y

M3 - SCORING: Journal article

C2 - 28836958

VL - 18

SP - 65

JO - BMC NEUROSCI

JF - BMC NEUROSCI

SN - 1471-2202

IS - 1

ER -