@article{discovery1418676,
           month = {May},
          volume = {2},
            note = {{\copyright} 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.},
           title = {Extracting novel information from neuroimaging data using neural fields},
            year = {2014},
         journal = {EPJ Nonlinear Biomedical Physics},
        keywords = {Neural field theory; Dynamic causal modelling; Attention; Connectivity; Gamma oscillations; V1; Electrocorticography; Visual cortex; Electrophysiology},
             url = {http://dx.doi.org/10.1140/epjnbp18},
        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.},
          author = {Pinotsis, DA and Friston, KJ}
}