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Neuroimage. 2014 Nov 15;102 Pt 2:885-93. doi: 10.1016/j.neuroimage.2014.07.015. Epub 2014 Jul 17.

Discrimination of cortical laminae using MEG.

Author information

1
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, 12 Queen Square, London WC1N 3BG, UK. Electronic address: luzia.troebinger.11@ucl.ac.uk.
2
Electronic Engineering Department, Universidad de Antioquia, UdeA, Calle 70 No. 52-21, Medellín, Colombia.
3
LREN, Département des Neurosciences Cliniques, CHUV, University of Lausanne, Lausanne, Switzerland.
4
Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, UCL, Queen Square, London WC1N 3BG, UK.
5
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, 12 Queen Square, London WC1N 3BG, UK.

Abstract

Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2mm translation and 2° rotation at SNR > 11 dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2014) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm, and show that it is possible to discriminate between these cortical layer models in real data.

PMID:
25038441
PMCID:
PMC4229503
DOI:
10.1016/j.neuroimage.2014.07.015
[Indexed for MEDLINE]
Free PMC Article

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