Home > Research > Publications & Outputs > Estimating the population local wavelet spectru...

Electronic data

  • SIM_AcceptedVersion

    Rights statement: This is the peer reviewed version of the following article: Gott, A. N., Eckley, I. A., and Aston, J. A. D. (2015) Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series. Statist. Med., doi: 10.1002/sim.6592 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.6592/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 478 KB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series

Research output: Contribution to journalJournal article

Published
Close
<mark>Journal publication date</mark>20/12/2015
<mark>Journal</mark>Statistics in Medicine
Issue number29
Volume34
Number of pages15
Pages (from-to)3901-3915
Publication statusPublished
Early online date26/08/15
Original languageEnglish

Abstract

Functional Magnetic Resonance Imaging (fMRI) is a dynamic four-dimensional imaging modality. However, in almost all fMRI analyses, the time series elements of this data are assumed to be second order stationary. In this paper we examine, using time series spectral methods, whether such stationary assumptions can be made and whether estimates of non-stationarity can be used to gain understanding into fMRI experiments. A non-stationary version of replicated stationary time series analysis is proposed that takes into account the replicated time series that are available from nearby voxels in a region of interest (ROI). These are used to investigate non-stationarities in both the ROI itself and the variations within the ROI. The proposed techniques are applied to simulated data and to an anxiety inducing fMRI experiment.

Bibliographic note

This is the peer reviewed version of the following article: Gott, A. N., Eckley, I. A., and Aston, J. A. D. (2015) Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series. Statist. Med., doi: 10.1002/sim.6592 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.6592/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.