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While regions of the lateral occipital cortex (LOC) are known to be selective for objects relative to feature-matched controls, it is not known what set of cues or configurations are used to promote this selectivity. Many theories of perceptual organization have emphasized the figure-ground relationship as being especially important in object-level processing. In the present work we studied the role...
We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal...
There is theoretical and experimental evidence that the spatial extent of mass neural activity is an important factor of brain response in neuroimaging studies. Direct estimation of the surface area of activated regions would importantly complement the quantitative analysis of amplitude variations of cortical currents. These latter are accessible at the regional scale through source modeling of magnetoencephalographic...
We introduce a new model selection procedure (MiMS) to the MEG source estimation problem, based on a multireso-lution approach. The technique uses an explicit piecewise image model of cortical currents that is iteratively updated through increasing spatial resolution according to the generalized cross-validation (GCV) error principle. The method is illustrated on MEG data testing for the somatotopic...
Detection of activity from the primary visual cortex is a difficult challenge to magneto-encephalography (MEG) source imaging techniques: the geometry of the visual cortex is intricate, with structured visual field maps extending deeper along the calcarine fissure. This questions the very sensitivity of MEG to the corresponding neural responses of visual stimuli and the usage of MEG source imaging...
We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal...
MEG source imaging is an underdetermined inverse problem that suffers from a large number of unknown source parameters in realistic source settings. While linear source estimators offer poor spatial resolution, most recent non-linear approaches still lead to untractable computational costs. We propose a new multiresolution approach using an explicit piecewise image model of the distribution of neural...
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