PMID- 18629625
OWN - NLM
STAT- MEDLINE
DCOM- 20081103
LR  - 20080922
IS  - 1573-6792 (Electronic)
IS  - 0896-0267 (Linking)
VI  - 21
IP  - 1
DP  - 2008 Sep
TI  - Cortical imaging on a head template: a simulation study using a resistor mesh 
      model (RMM).
PG  - 52-60
LID - 10.1007/s10548-008-0059-0 [doi]
AB  - The T1 head template model used in Statistical Parametric Mapping Version 2000 
      (SPM2), was segmented into five layers (scalp, skull, CSF, grey and white matter) 
      and implemented in 2 mm voxels. We designed a resistor mesh model (RMM), based on 
      the finite volume method (FVM) to simulate the electrical properties of this head 
      model along the three axes for each voxel. Then, we introduced four dipoles of 
      high eccentricity (about 0.8) in this RMM, separately and simultaneously, to 
      compute the potentials for two sets of conductivities. We used the direct 
      cortical imaging technique (CIT) to recover the simulated dipoles, using 60 or 
      107 electrodes and with or without addition of Gaussian white noise (GWN). The 
      use of realistic conductivities gave better CIT results than standard 
      conductivities, lowering the blurring effect on scalp potentials and displaying 
      more accurate position areas when CIT was applied to single dipoles. Simultaneous 
      dipoles were less accurately localized, but good qualitative and stable 
      quantitative results were obtained up to 5% noise level for 107 electrodes and up 
      to 10% noise level for 60 electrodes, showing that a compromise must be found to 
      optimize both the number of electrodes and the noise level. With the RMM defined 
      in 2 mm voxels, the standard 128-electrode cap and 5% noise appears to be the 
      upper limit providing reliable source positions when direct CIT is used. The 
      admittance matrix defining the RMM is easy to modify so as to adapt to different 
      conductivities. The next step will be the adaptation of individual real head T2 
      images to the RMM template and the introduction of anisotropy using diffusion 
      imaging (DI).
FAU - Chauveau, Nicolas
AU  - Chauveau N
AD  - Neurology Department, INSERM, UMRS 825, Purpan Hospital, Toulouse, France. 
      nicolas.chauveau@inserm.fr
FAU - Franceries, Xavier
AU  - Franceries X
FAU - Aubry, Florent
AU  - Aubry F
FAU - Celsis, Pierre
AU  - Celsis P
FAU - Rigaud, Bernard
AU  - Rigaud B
LA  - eng
PT  - Journal Article
DEP - 20080716
PL  - United States
TA  - Brain Topogr
JT  - Brain topography
JID - 8903034
SB  - IM
MH  - *Algorithms
MH  - Brain/anatomy & histology/physiology
MH  - Brain Mapping/*methods
MH  - Cerebral Cortex/*physiology
MH  - Diagnostic Imaging/methods
MH  - Electric Impedance
MH  - Electroencephalography/methods
MH  - Electrophysiology/methods
MH  - Humans
MH  - Image Processing, Computer-Assisted/methods
MH  - Models, Anatomic
MH  - Models, Neurological
MH  - Models, Statistical
MH  - Reproducibility of Results
MH  - Scalp/anatomy & histology/physiology
MH  - Skull/anatomy & histology/*physiology
EDAT- 2008/07/17 09:00
MHDA- 2008/11/04 09:00
CRDT- 2008/07/17 09:00
PHST- 2008/01/23 00:00 [received]
PHST- 2008/07/02 00:00 [accepted]
PHST- 2008/07/17 09:00 [pubmed]
PHST- 2008/11/04 09:00 [medline]
PHST- 2008/07/17 09:00 [entrez]
AID - 10.1007/s10548-008-0059-0 [doi]
PST - ppublish
SO  - Brain Topogr. 2008 Sep;21(1):52-60. doi: 10.1007/s10548-008-0059-0. Epub 2008 Jul 
      16.