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

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Biomedical Visualisation

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1235))

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.

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Acknowledgements

This study was funded by a grant from the NHS Grampian Endowments Trust under the project number 12/35. We would like to thank Professor Alison Murray for assessing the structural scans, Mr. Gordon Buchan for his contribution to the paradigm development and technical support during scanning, Dr. Jennifer Perrin for selecting the pictures used in the low-cognitive demand paradigm, the research radiographers (Mrs Baljit Jagpal, Mrs. Beverly Maclennan, Mrs. Nichola Crouch, and Mrs. Katrina Klaasen), the Aberdeen Biomedical Imaging Centre research staff, the research nurses (Mrs Anu Joyson and Mrs. Heather Gow) and above all the participants for their contribution to this study. The authors also acknowledge the assistance of Dr. Elena Allen for providing the component t-statistic thresholds applied in Allen et al. (2011) for application in this work. Finally the authors would like to note that this research work has been previously discussed in Dr. Varsou’s PhD and Miss Dinis Fernandes’ MSc theses and relevant sections have been referenced accordingly. The novel analysis approach described in this chapter, however, has not been published in a journal publication.

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Authors and Affiliations

  1. Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, Scotland, UK

    Catarina Dinis Fernandes

  2. School of Life Sciences, Anatomy Facility, University of Glasgow, Glasgow, Scotland, UK

    Ourania Varsou

  3. Edinburgh Imaging, University of Edinburgh, Edinburgh, Scotland, UK

    Michael Stringer

  4. The Institute of Medical Sciences, King’s College, University of Aberdeen, Aberdeen, Scotland, UK

    Mary Joan Macleod

  5. Faculty of Applied Sciences & Mechatronics, Munich University of Applied Sciences, Munich, Germany

    Christian Schwarzbauer

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  1. Catarina Dinis Fernandes
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  2. Ourania Varsou
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  3. Michael Stringer
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  4. Mary Joan Macleod
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  5. Christian Schwarzbauer
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  1. Anatomy Facility, School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK

    Paul M. Rea

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Dinis Fernandes, C., Varsou, O., Stringer, M., Macleod, M.J., Schwarzbauer, C. (2020). Scanning Conditions in Functional Connectivity Magnetic Resonance Imaging: How to Standardise Resting-State for Optimal Data Acquisition and Visualisation?. In: Rea, P. (eds) Biomedical Visualisation . Advances in Experimental Medicine and Biology, vol 1235. Springer, Cham. https://doi.org/10.1007/978-3-030-37639-0_3

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