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  Laminar signal extraction over extended cortical areas by means of a spatial GLM

van Mourik, T., van der Eerden, J. P. J. M., Bazin, P.-L., & Norris, D. G. (2019). Laminar signal extraction over extended cortical areas by means of a spatial GLM. PLoS One, 14(3): e0212493. doi:10.1371/journal.pone.0212493.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-5422-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-8955-3
Genre: Journal Article

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 Creators:
van Mourik, Tim 1, Author
van der Eerden, Jan P. J. M. 1, Author
Bazin, Pierre-Louis2, Author              
Norris, David G.1, Author              
Affiliations:
1Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands, ou_persistent22              
2Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Free keywords: Article; Brain cortex; Contamination; Controlled study; Ex vivo study; Extraction; Functional magnetic resonance imaging; Human; Human tissue; In vivo study; Noisepartial volume (imaging); Simulation; Thickness
 Abstract: There is converging evidence that distinct neuronal processes leave distinguishable footprints in the laminar BOLD response. However, even though the achievable spatial resolution in functional MRI has much improved over the years, it is still challenging to separate signals arising from different cortical layers. In this work, we propose a new method to extract laminar signals. We use a spatial General Linear Model in combination with the equivolume principle of cortical layers to unmix laminar signals instead of interpolating through and integrating over a cortical area: thus reducing partial volume effects. Not only do we provide a mathematical framework for extracting laminar signals with a spatial GLM, we also illustrate that the best case scenarios of existing methods can be seen as special cases within the same framework. By means of simulation, we show that this approach has a sharper point spread function, providing better signal localisation. We further assess the partial volume contamination in cortical profiles from high resolution human ex vivo and in vivo structural data, and provide a full account of the benefits and potential caveats. We eschew here any attempt to validate the spatial GLM on the basis of fMRI data as a generally accepted ground-truth pattern of laminar activation does not currently exist. This approach is flexible in terms of the number of layers and their respective thickness, and naturally integrates spatial regularisation along the cortex, while preserving laminar specificity. Care must be taken, however, as this procedure of unmixing is susceptible to sources of noise in the data or inaccuracies in the laminar segmentation.

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Language(s): eng - English
 Dates: 2018-04-042019-02-052019-03-27
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pone.0212493
PMID: 30917123
Other: eCollection 2019
 Degree: -

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Funding program : KNAW Academy Professor Prize 2012
Funding organization : Koninklijke Nederlandse Akademie van Wetenschappen (KNAW)
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Grant ID : 016.Vici.185.052
Funding program : -
Funding organization : Netherlands Organisation for Scientific Research (NWO)

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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: 14 (3) Sequence Number: e0212493 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850