Literature DB >> 32488635

Scanning Conditions in Functional Connectivity Magnetic Resonance Imaging: How to Standardise Resting-State for Optimal Data Acquisition and Visualisation?

Catarina Dinis Fernandes1, Ourania Varsou2, Michael Stringer3, Mary Joan Macleod4, Christian Schwarzbauer5.   

Abstract

Functional connectivity magnetic resonance imaging (fcMRI), performed during resting wakefulness without tasks or stimulation, is a non-invasive technique to assess and visualise functional brain networks in vivo. Acquisition of resting-state imaging data has become increasingly common in longitudinal studies to investigate brain health and disease. However, the scanning protocols vary considerably across different institutions creating challenges for comparability especially for the interpretation of findings in patient cohorts and establishment of diagnostic or prognostic imaging biomarkers. The aim of this chapter is to discuss the effect of two experimental conditions (i.e. a low cognitive demand paradigm and a pure resting-state fcMRI) on the reproducibility of brain networks between a baseline and a follow-up session, 30 (±5) days later, acquired from 12 right-handed volunteers (29 ± 5 yrs). A novel method was developed and used for a direct statistical comparison of the test-retest reliability using 28 well-established functional brain networks. Overall, both scanning conditions produced good levels of test-retest reliability. While the pure resting-state condition showed higher test-retest reliability for 18 of the 28 analysed networks, the low cognitive demand paradigm produced higher test-retest reliability for 8 of the 28 brain networks (i.e. visual, sensorimotor and frontal areas); in 2 of the 28 brain networks no significant changes could be detected. These results are relevant to planning of longitudinal studies, as higher test-retest reliability generally increases statistical power. This work also makes an important contribution to neuroimaging where optimising fcMRI experimental scanning conditions, and hence data visualisation of brain function, remains an on-going topic of interest. In this chapter, we provide a full methodological explanation of the two paradigms and our analysis so that readers can apply them to their own scanning protocols.

Entities:  

Keywords:  Brain; Functional connectivity; Magnetic resonance imaging; Resting-state

Year:  2020        PMID: 32488635     DOI: 10.1007/978-3-030-37639-0_3

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  2 in total

Review 1.  The Hidden Brain: Uncovering Previously Overlooked Brain Regions by Employing Novel Preclinical Unbiased Network Approaches.

Authors:  Sierra Simpson; Yueyi Chen; Emma Wellmeyer; Lauren C Smith; Brianna Aragon Montes; Olivier George; Adam Kimbrough
Journal:  Front Syst Neurosci       Date:  2021-04-21

2.  Diagnosis of Neural Activity among Abnormal Brain Regions in Patients with Major Depressive Disorder by Magnetic Resonance Imaging Features.

Authors:  Weicheng Wang; Shuang Jia; Qionghui Zhao; Lin Yang
Journal:  Comput Math Methods Med       Date:  2022-06-28       Impact factor: 2.809

  2 in total

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