[Eeglablist] Paper on skull conductivity estimation

[Zeynep Akalin Acar]

Dear EEGLAB users,

I'm happy to announce that our recent paper on skull conductivity
estimation is now accepted for publication in Neuroimage.

You can find the accepted version at:

Preprint of the accepted version
<http://sccn.ucsd.edu/%7Escott/pdf/AkalinAcar_SCALE_NeuroImage_in_press_0815.pdf>

*Title*: Simultaneous head tissue conductivity and EEG source location
estimation

*Authors*: Z. Akalin Acar, C. Acar, S. Makeig

*Abstract*:
Accurate electroencephalographic (EEG) source localization requires an
electrical head model incorporating accurate geometries and conductivity
values for the major head tissues. While consistent conductivity values
have been reported for scalp, brain, and cerebrospinal fluid, measured
brain-to- skull conductivity ratio (BSCR) estimates have varied between 8
and 80, likely reflecting both inter-subject and measurement method
differences. In simulations, mis-estimation of skull conductivity can
produce source local- ization errors as large as 3 cm. Here, we describe an
iterative gradient-based approach to Simultaneous tissue Conductivity And
source Location Estima- tion (SCALE). The scalp projection maps used by
SCALE are obtained from near-dipolar effective EEG sources found by
adequate independent compo- nent analysis (ICA) decomposition of sufficient
high-density EEG data. We applied SCALE to simulated scalp projections of
15 cm2-scale cortical patch sources in an MR image-based electrical head
model with simulated BSCR of 30. Initialized either with a BSCR of 80 or
20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA)
decompositions of (45-min, 128-channel) EEG data from two young adults we
identified sets of 13 in- dependent components having near-dipolar scalp
maps compatible with a single cortical source patch. Again initialized with
either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two
subjects respectively. The ability to accurately estimate skull
conductivity non-invasively from any well-recorded EEG data in combination
with a stable and non-invasively ac- quired MR imaging-derived electrical
head model could remove a critical barrier to using EEG as a sub-cm2-scale
accurate 3-D functional cortical imaging modality.

Thank you,
Zeynep Akalin Acar
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