eprintid: 1418676
rev_number: 26
eprint_status: archive
userid: 608
dir: disk0/01/41/86/76
datestamp: 2014-02-04 19:45:54
lastmod: 2020-06-10 17:50:33
status_changed: 2014-02-04 19:45:54
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Pinotsis, DA
creators_name: Friston, KJ
title: Extracting novel information from neuroimaging data using neural fields
ispublished: pub
divisions: UCL
divisions: A01
divisions: B02
divisions: C07
keywords: Neural field theory; Dynamic causal modelling; Attention; Connectivity; Gamma oscillations; V1; Electrocorticography; Visual cortex; Electrophysiology
note: © 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.
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.
date: 2014-05-09
official_url: http://dx.doi.org/10.1140/epjnbp18
vfaculties: VFBRS
oa_status: green
full_text_type: pub
primo: open
primo_central: open_green
article_type_text: Article
verified: verified_manual
elements_source: Manually entered
elements_id: 925398
doi: 10.1140/epjnbp18
lyricists_name: Pinotsis, Dimitrios
lyricists_id: DPINO08
full_text_status: public
publication: EPJ Nonlinear Biomedical Physics
volume: 2
article_number: 5
citation:        Pinotsis, DA;    Friston, KJ;      (2014)    Extracting novel information from neuroimaging data using neural fields.                   EPJ Nonlinear Biomedical Physics , 2     , Article 5.  10.1140/epjnbp18 <https://doi.org/10.1140/epjnbp18>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1418676/1/epjnbp18.pdf