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Identifying predictors of within-person variance in MRI-based brain volume estimates

Karch, Julian D (author)
Max Planck Institute for Human Development,Leiden University
Filevich, Elisa (author)
Max Planck Institute for Human Development,Bernstein Center for Computational Neuroscience Berlin,Humboldt University of Berlin
Wenger, Elisabeth (author)
Max Planck Institute for Human Development
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Lisofsky, Nina (author)
University Medical Center Hamburg-Eppendorf
Becker, Maxi (author)
University Medical Center Hamburg-Eppendorf
Butler, Oisin (author)
Max Planck Institute for Human Development
Mårtensson, Johan (author)
Lund University,Lunds universitet,Logopedi, foniatri och audiologi,Sektion IV,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Logopedics, Phoniatrics and Audiology,Section IV,Department of Clinical Sciences, Lund,Faculty of Medicine
Lindenberger, Ulman (author)
Max Planck Institute for Human Development
Brandmaier, Andreas M (author)
Max Planck Institute for Human Development
Kühn, Simone (author)
University Medical Center Hamburg-Eppendorf,Max Planck Institute for Human Development
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 (creator_code:org_t)
Elsevier BV, 2019
2019
English.
In: NeuroImage. - : Elsevier BV. - 1095-9572 .- 1053-8119. ; 200, s. 575-589
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24-31 years gathered at 40-50 occasions distributed over 6-8 months from the Day2day study. We explored the within-person associations between 21 variables covering physiological, affective, social, and environmental factors and global measures of brain volume estimated by VBM8 and FreeSurfer. Time since the first scan was reliably associated with Freesurfer estimates of grey matter volume and total cortex volume, in line with a rate of annual brain volume shrinkage of about 1 percent. For the same two structural measures, time of day also emerged as a reliable predictor with an estimated diurnal volume decrease of, again, about 1 percent. Furthermore, we found weak predictive evidence for the number of steps taken on the previous day and testosterone levels. The results suggest a need to control for time-of-day effects in sMRI research. In particular, we recommend that researchers interested in assessing longitudinal change in the context of intervention studies or longitudinal panels make sure that, at each measurement occasion, (a) a given participant is measured at the same time of day; (b) participants overall are measured at about the same time of day. Furthermore, the potential effects of physical activity, including moderate amounts of aerobic exercise, and testosterone levels on MRI-based measures of brain structure deserve further investigation.

Subject headings

SAMHÄLLSVETENSKAP  -- Psykologi -- Tillämpad psykologi (hsv//swe)
SOCIAL SCIENCES  -- Psychology -- Applied Psychology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Annan medicin och hälsovetenskap -- Övrig annan medicin och hälsovetenskap (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Other Medical and Health Sciences -- Other Medical and Health Sciences not elsewhere specified (hsv//eng)

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