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Extracting novel information from neuroimaging data using neural fields

Pinotsis, DA; Friston, KJ; (2014) Extracting novel information from neuroimaging data using neural fields. EPJ Nonlinear Biomedical Physics , 2 , Article 5. 10.1140/epjnbp18. Green open access

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Abstract

We showcase three case studies that illustrate how neural fields can be useful in the analysis of neuroimaging data. In particular, we argue that neural fields allow one to: (i) compare evidences for alternative hypotheses regarding neurobiological determinants of stimulus-specific response variability; (ii) make inferences about between subject variability in cortical function and microstructure using non-invasive data and (iii) estimate spatial parameters describing cortical sources, even without spatially resolved data.

Type: Article
Title: Extracting novel information from neuroimaging data using neural fields
Open access status: An open access version is available from UCL Discovery
DOI: 10.1140/epjnbp18
Publisher version: http://dx.doi.org/10.1140/epjnbp18
Additional information: © 2014 Pinotsis and Friston; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
Keywords: Neural field theory; Dynamic causal modelling; Attention; Connectivity; Gamma oscillations; V1; Electrocorticography; Visual cortex; Electrophysiology
UCL classification: UCL > Provost and Vice Provost Offices
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/1418676
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