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

Gott, Aimee and Eckley, Idris and Aston, John (2015) Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series. Statistics in Medicine, 34 (29). pp. 3901-3915. ISSN 0277-6715

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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.

Item Type:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Additional Information:
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.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
82031
Deposited By:
Deposited On:
08 Oct 2016 03:36
Refereed?:
Yes
Published?:
Published
Last Modified:
06 Aug 2020 02:50