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  An Analysis Approach for High-Field fMRI Data from Awake Non-Human Primates

Stoewer, S., Goense, J., Keliris, G., Bartels, A., Logothetis, N., Duncan, J., et al. (2012). An Analysis Approach for High-Field fMRI Data from Awake Non-Human Primates. PLoS One, 7(1), 1-13. doi:10.1371/journal.pone.0029697.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B850-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8A1B-6
Genre: Journal Article

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Stoewer, S1, 2, Author              
Goense, J1, 2, Author              
Keliris, GA1, 2, Author              
Bartels, A1, 2, Author              
Logothetis, NK1, 2, Author              
Duncan, J, Author
Sigala, N, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: fMRI experiments with awake non-human primates (NHP) have seen a surge of applications in recent years. However, the standard fMRI analysis tools designed for human experiments are not optimal for analysis of NHP fMRI data collected at high fields. There are several reasons for this, including the trial-based nature of NHP experiments, with inter-trial periods being of no interest, and segmentation artefacts and distortions that may result from field changes due to movement. We demonstrate an approach that allows us to address some of these issues consisting of the following steps: 1) Trial-based experimental design. 2) Careful control of subject movement. 3) Computer-assisted selection of trials devoid of artefacts and animal motion. 4) Nonrigid between-trial and rigid within-trial realignment of concatenated data from temporally separated trials and sessions. 5) Linear interpolation of inter-trial intervals and high-pass filtering of temporally continuous data 6) Removal of interpolated data and reconcatenation of datasets before statistical analysis with SPM. We have implemented a software toolbox, fMRI Sandbox (http://code.google.com/p/fmri-sandbox/), for semi-automated application of these processing steps that interfaces with SPM software. Here, we demonstrate that our methodology provides significant improvements for the analysis of awake monkey fMRI data acquired at high-field. The method may also be useful for clinical applications with subjects that are unwilling or unable to remain motionless for the whole duration of a functional scan.

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 Dates: 2012-01
 Publication Status: Published online
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 Identifiers: DOI: 10.1371/journal.pone.0029697
eDoc: e29697
BibTex Citekey: StoewerGKBLDS2012
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Title: PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 7 (1) Sequence Number: - Start / End Page: 1 - 13 Identifier: ISSN: 1932-6203
CoNE: /journals/resource/1000000000277850