Back
High precision anatomy for MEG.
Journal article

High precision anatomy for MEG.

  • Troebinger L Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK. Electronic address: luzia.troebinger.11@ucl.ac.uk.
  • López JD Electronic Engineering Department, Universidad de Antioquia, Medellín, Colombia.
  • Lutti A Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK; Laboratoire de recherche en neuroimagerie, Département des neurosciences cliniques, CHUV, University of Lausanne, Lausanne, Switzerland.
  • Bradbury D Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK.
  • Bestmann S Sobell Department for Motor Neuroscience and Movement Disorders, University College London, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
  • Barnes G Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK.
Show more…
  • 2013-08-06
Published in:
  • NeuroImage. - 2014
3D printer
Coregistration
Head movement
Longitudinal MEG
MEG
MSP
Magnetoencephalography
Spatial resolution
Brain Mapping
Casts, Surgical
Equipment Design
Equipment Failure Analysis
Head Protective Devices
Humans
Image Enhancement
Magnetoencephalography
Reproducibility of Results
Restraint, Physical
Sensitivity and Specificity
English Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1mm. Estimates of relative co-registration error were <1.5mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG.
Language
  • English
Open access status
hybrid
Identifiers
Persistent URL
https://sonar.ch/global/documents/122903
Statistics
Document views: 56 File downloads: