Lopez, JD;
Valencia, F;
Flandin, G;
Penny, W;
Barnes, GR;
(2017)
Reconstructing anatomy from electro-physiological data.
NeuroImage
, 163
pp. 480-486.
10.1016/j.neuroimage.2017.06.049.
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Abstract
Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. We demonstrate that both empirical and simulated MEG data give rise to consistent and plausible anatomical estimates. Importantly, the estimation of structure from MEG data can be quantified in terms of millimetres from the true brain structure. We show, for simulated data, that the functional assumptions which are closer to the functional ground-truth give rise to anatomical estimates that are closer to the true anatomy.
| Type: | Article |
|---|---|
| Title: | Reconstructing anatomy from electro-physiological data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.neuroimage.2017.06.049 |
| Publisher version: | http://dx.doi.org/10.1016/j.neuroimage.2017.06.049 |
| Language: | English |
| Additional information: | © 2017 Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Neurosciences, Neuroimaging, Radiology, Nuclear Medicine & Medical Imaging, Neurosciences & Neurology, MEG/EEG brain imaging, Brain anatomy, Negative variational free energy, Fourier spherical harmonics, FREE-ENERGY, BRAIN, MEG, REPRESENTATION, APPROXIMATION, EEG |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1566046 |
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