title: Dynamic brightness induction in V1: analyzing simulated and empirically acquired fMRI data in a "common brain space" framework.
abstract: Computational neuromodeling may help to further our understanding of how empirical neuroimaging findings are generated by underlying neural mechanisms. Here, we used a simple computational model that simulates early visual processing of brightness changes in a dynamic, illusory display. The model accurately predicted illusory brightness changes in a grey area of constant luminance induced by (and in anti-phase to) luminance changes in its surroundings. Moreover, we were able to directly compare these predictions with recently observed fMRI results on the same brightness illusion by projecting predicted activity from our model onto empirically investigated brain regions. This new approach in which generated network activity and measured neuroimaging data are interfaced in a common representational "brain space" can contribute to the integration of computational and experimental neuroscience.
authors.affiliation: Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands. j.peters@nin.knaw.nl
authors.forename: Judith C
authors.initials: JC
authors.lastname: Peters
authors.forename: Bert
authors.initials: B
authors.lastname: Jans
authors.forename: Vincent
authors.initials: V
authors.lastname: van de Ven
authors.forename: Peter
authors.initials: P
authors.lastname: De Weerd
authors.forename: Rainer
authors.initials: R
authors.lastname: Goebel
mesh_terms: D006801:Humans; D008279:Magnetic Resonance Imaging; D008959:Models, Neurological; D016571:Neural Networks, Computer; D014793:Visual Cortex / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*