henhaobio
Sign in

Brain TopographyNeurosciencePeer-reviewed journal article

Requirements for coregistration accuracy in on-scalp MEG

Rasmus ZetteriD, Joonas IivanaineniD, Matti StenroosiD, Lauri T. ParkkoneniD

PDFDOIPreprint

Abstract

Recent advances in magnetic sensing has made on-scalp magnetoencephalography (MEG) possible. In particular, optically-pumped magnetometers (OPMs) have reached sensitivity levels that enable their use in MEG. In contrast to the SQUID sensors used in current MEG systems, OPMs do not require cryogenic cooling and can thus be placed within millimetres from the head, enabling the construction of sensor arrays that conform to the shape of an individuals head. To properly estimate the location of neural sources within the brain, one must accurately know the position and orientation of sensors in relation to the head. With the adaptable on-scalp MEG sensor arrays, this coregistration becomes more challenging than in current SQUID-based MEG systems that use rigid sensor arrays.\n\nHere, we used simulations to quantify how accurately one needs to know the position and orientation of sensors in an on-scalp MEG system. The effects that different types of localisation errors have on forward modelling and source estimates obtained by minimum-norm estimation, dipole fitting, and beamforming are detailed.\n\nWe found that sensor position errors generally have a larger effect than orientation errors and that these errors affect the localisation accuracy of superficial sources the most. To obtain similar or higher accuracy than with current SQUID-based MEG systems, RMS sensor position and orientation errors should be < 4 mm and < 10{degrees}, respectively.

Citations
56
FWCI
2.20
Field percentile
top 11%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISIivanainen '16Zetter '19Pfeiffer '20Tierney '20Jas '26Iivanainen '19
86% semantic matchNeuroscience
Joonas Iivanainen, Matti Stenroos, Lauri T. Parkkonen·NeuroImage·Dec 19, 2016· 295 citations