Retinotopic mapping of the primary visual cortex - a challenge for MEG imaging of the human cortex

Gavin Perry, Peyman Adjamian, Ngoc J. Thai, Ian E. Holliday, Arjan Hillebrand, Gareth R. Barnes

Research output: Contribution to journalArticle

Abstract

Magnetoencephalography (MEG) can be used to reconstruct neuronal activity with high spatial and temporal resolution. However, this reconstruction problem is ill-posed, and requires the use of prior constraints in order to produce a unique solution. At present there are a multitude of inversion algorithms, each employing different assumptions, but one major problem when comparing the accuracy of these different approaches is that often the true underlying electrical state of the brain is unknown. In this study, we explore one paradigm, retinotopic mapping in the primary visual cortex (V1), for which the ground truth is known to a reasonable degree of accuracy, enabling the comparison of MEG source reconstructions with the true electrical state of the brain. Specifically, we attempted to localize, using a beanforming method, the induced responses in the visual cortex generated by a high contrast, retinotopically varying stimulus. Although well described in primate studies, it has been an open question whether the induced gamma power in humans due to high contrast gratings derives from V1 rather than the prestriate cortex (V2). We show that the beanformer source estimate in the gamma and theta bands does vary in a manner consistent with the known retinotopy of V1. However, these peak locations, although retinotopically organized, did not accurately localize to the cortical surface. We considered possible causes for this discrepancy and suggest that improved MEG/magnetic resonance imaging co-registration and the use of more accurate source models that take into account the spatial extent and shape of the active cortex may, in future, improve the accuracy of the source reconstructions.
Original languageEnglish
Pages (from-to)652-661
Number of pages10
JournalEuropean Journal of Neuroscience
Volume34
Issue number4
Early online date12 Jul 2011
DOIs
Publication statusPublished - Aug 2011

Bibliographical note

Creative Commons Attribution Non Commercial License

Keywords

  • algorithms
  • brain mapping
  • humans
  • computer-assisted image processing
  • magnetoencephalography
  • photic stimulation
  • visual cortex

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