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MAGMA. 2019 Feb 7. doi: 10.1007/s10334-018-00732-0. [Epub ahead of print]

A study of within-subject reliability of the brain's default-mode network.

Author information

1
Department of Neuroscience, University of Sheffield, Royal Hallamshire Hospital, Beech Hill Road, N Floor, Room N133, Sheffield, S10 2RX, UK.
2
Faculty of Earth and Life Sciences, VU University Amsterdam, Amsterdam, The Netherlands.
3
Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
4
Department of Neuroscience, University of Sheffield, Royal Hallamshire Hospital, Beech Hill Road, N Floor, Room N133, Sheffield, S10 2RX, UK. m.demarco@sheffield.ac.uk.

Abstract

OBJECTIVE:

Resting-state functional magnetic resonance imaging (fMRI) is promising for Alzheimer's disease (AD). This study aimed to examine short-term reliability of the default-mode network (DMN), one of the main haemodynamic patterns of the brain.

MATERIALS AND METHODS:

Using a 1.5 T Philips Achieva scanner, two consecutive resting-state fMRI runs were acquired on 69 healthy adults, 62 patients with mild cognitive impairment (MCI) due to AD, and 28 patients with AD dementia. The anterior and posterior DMN and, as control, the visual-processing network (VPN) were computed using two different methodologies: connectivity of predetermined seeds (theory-driven) and dual regression (data-driven). Divergence and convergence in network strength and topography were calculated with paired t tests, global correlation coefficients, voxel-based correlation maps, and indices of reliability.

RESULTS:

No topographical differences were found in any of the networks. High correlations and reliability were found in the posterior DMN of healthy adults and MCI patients. Lower reliability was found in the anterior DMN and in the VPN, and in the posterior DMN of dementia patients.

DISCUSSION:

Strength and topography of the posterior DMN appear relatively stable and reliable over a short-term period of acquisition but with some degree of variability across clinical samples.

KEYWORDS:

Brain imaging; Hemodynamics; Reproducibility of results; fMRI

PMID:
30730023
DOI:
10.1007/s10334-018-00732-0

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