Pinotsis, DA;
Friston, KJ;
(2014)
Extracting novel information from neuroimaging data using neural fields.
EPJ Nonlinear Biomedical Physics
, 2
, Article 5. 10.1140/epjnbp18.
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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 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 |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1418676 |
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