A modelling study to inform specification and optimal electrode placement for imaging of neuronal depolarization during visual evoked responses by electrical and magnetic detection impedance tomography

  • Gilad O
  • Horesh L
  • Holder D
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Abstract

Electrical impedance tomography (EIT) has the potential to achieve non-invasive functional imaging of fast neuronal activity in the human brain due to opening of ion channels during neuronal depolarization. Local changes of resistance in the cerebral cortex are about 1%, but the size and location of changes recorded on the scalp are unknown. The purpose of this work was to develop an anatomically realistic finite element model of the adult human head and use it to predict the amplitude and topography of changes on the scalp, and so inform specification for an in vivo measuring system. A detailed anatomically realistic finite element (FE) model of the head was produced from high resolution MRI. Simulations were performed for impedance changes in the visual cortex during evoked activity with recording of scalp potentials by electrodes or magnetic flux density by magnetoencephalography (MEG) in response to current injected with electrodes. The predicted changes were validated by recordings in saline filled tanks and with boundary voltages measured on the human scalp. Peak changes were 1.03 +/- 0.75 microV (0.0039 +/- 0.0034%) and 27 +/- 13 fT (0.2 +/- 0.5%) respectively, which yielded an estimated peak signal-to-noise ratio of about 4 for in vivo averaging over 10 min and 1 mA current injection. The largest scalp changes were over the occipital cortex. This modelling suggests, for the first time, that reproducible changes could be recorded on the scalp in vivo in single channels, although a higher SNR would be desirable for accurate image production. The findings suggest that an in vivo study is warranted in order to determine signal size but methods to improve SNR, such as prolonged averaging or other signal processing may be needed for accurate image production.

Author-supplied keywords

  • Brain modelling
  • Electrical impedance tomography
  • Evoked responses
  • Finite elements
  • Neural imaging

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