Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex

Chang Hwan Im, Arvind Gururajan, Nanyin Zhang, Wei Chen, Bin He

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39 Scopus citations

Abstract

The aim of the present study is to investigate the spatial resolution of electroencephalography (EEG) cortical source imaging by localizing the retinotopic organization in the human primary visual cortex (V1). Retinotopic characteristics in V1 obtained from functional magnetic resonance imaging (fMRI) study were used as reference to assess the spatial resolution of EEG since fMRI can discriminate small changes in activation in visual field. It is well known that the activation of the early C1 component in the visual evoked potential (VEP) elicited by pattern onset stimuli coincides well with the activation in the striate cortex localized by fMRI. In the present experiments, we moved small circular checkerboard stimuli along horizontal meridian and compared the activations localized by EEG cortical source imaging with those from fMRI. Both fMRI and EEG cortical source imaging identified spatially correlated activity within V1 in each subject studied. The mean location error, between the fMRI-determined activation centers in V1 and the EEG source imaging activation peak estimated at equivalent C1 components (peak latency: 74.8 ± 10.6 ms), was 7 mm (25% and 75% percentiles are 6.45 mm and 8.4 mm, respectively), which is less than the change in fMRI activation map by a 3° visual field change (7.8 mm). Moreover, the source estimates at the earliest major VEP component showed statistically good correlation with those obtained by fMRI. The present results suggest that the spatial resolution of the EEG cortical source imaging can correctly discriminate cortical activation changes in V1 corresponding to less than 3° visual field changes.

Original languageEnglish (US)
Pages (from-to)142-154
Number of pages13
JournalJournal of Neuroscience Methods
Volume161
Issue number1
DOIs
StatePublished - Mar 30 2007

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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