Simultaneous head tissue conductivity and EEG source location estimation

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-skul...

Full description

Saved in:
Bibliographic Details
Published inNeuroImage (Orlando, Fla.) Vol. 124; no. Pt A; pp. 168 - 180
Main Authors Akalin Acar, Zeynep, Acar, Can E., Makeig, Scott
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.01.2016
Elsevier Limited
Subjects
Online AccessGet full text
ISSN1053-8119
1095-9572
1095-9572
DOI10.1016/j.neuroimage.2015.08.032

Cover

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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm2-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 independent 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 acquired 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. •We propose Simultaneous Conductivity And Location Estimation (SCALE) for EEG data.•SCALE uses only EEG independent component sources and a subject head MR image.•In simulation studies, SCALE accurately estimated skull conductivity.•Applied to EEG from two subjects, SCALE converged regardless of initial condition.•SCALE may make noninvasive, high-resolution EEG source imaging feasible.
AbstractList 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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-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 independent 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 acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality.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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-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 independent 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 acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality.
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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm2-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 independent 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 acquired 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. •We propose Simultaneous Conductivity And Location Estimation (SCALE) for EEG data.•SCALE uses only EEG independent component sources and a subject head MR image.•In simulation studies, SCALE accurately estimated skull conductivity.•Applied to EEG from two subjects, SCALE converged regardless of initial condition.•SCALE may make noninvasive, high-resolution EEG source imaging feasible.
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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-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 independent 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 acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality.
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 localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm2-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 independent 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 acquired 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.
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 localization errors as large as 3 cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15 cm 2 -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 independent 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 acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm 2 -scale accurate 3-D functional cortical imaging modality.
Author Acar, Can E.
Makeig, Scott
Akalin Acar, Zeynep
AuthorAffiliation a Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla CA 92093-0559
b Qualcomm Technologies, Inc. 5775 Morehouse Drive, San Diego, CA 92121
AuthorAffiliation_xml – name: a Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla CA 92093-0559
– name: b Qualcomm Technologies, Inc. 5775 Morehouse Drive, San Diego, CA 92121
Author_xml – sequence: 1
  givenname: Zeynep
  surname: Akalin Acar
  fullname: Akalin Acar, Zeynep
  email: zeynep@sccn.ucsd.edu
  organization: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093-0559, USA
– sequence: 2
  givenname: Can E.
  surname: Acar
  fullname: Acar, Can E.
  email: canacar@canacar.net
  organization: Qualcomm Technologies, Inc., 5775 Morehouse Drive, San Diego, CA 92121, USA
– sequence: 3
  givenname: Scott
  surname: Makeig
  fullname: Makeig, Scott
  email: smakeig@ucsd.edu
  organization: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093-0559, USA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/26302675$$D View this record in MEDLINE/PubMed
BookMark eNqNkc9vFCEcxYmpsT_0XzCTePEyUxiGGbgYbbO2Jk08qGfCwpeWdRYqMJvsfy_Tbbfa0554CY9PHu-doiMfPCBUEdwQTPrzVeNhisGt1S00LSaswbzBtH2FTggWrBZsaI9mzWjNCRHH6DSlFcZYkI6_QcdtT3HbD-wEXf9w62nMykOYUnUHylTZpTRBpYM3k85u4_K2Ut5Ui8VVlcIUNVRj0Cq74CtIuYSY5Vv02qoxwbvH8wz9-rr4eXld33y_-nb55abWTAy5ptZaomyrl4YypkRXlDDKKsssNoq0PRNLxToDVnHeKdBa8I5yPhAjlkLQM_Rpx72flmswGnyOapT3seSIWxmUk__feHcnb8NGdj0jA8cF8PEREMOfqXxArl3SMI67DiQZGGkJa_v-ACtlAve0p8X64YV1VarypYkHF8UD7ubw7_8Nv0_9tEcx8J1Bx5BSBLu3ECzn6eVKPk8v5-kl5rJM_1zM_ql2-WGaUoMbDwFc7ABQ5ts4iDJpB16DcRF0lia4QyCfX0D06LzTavwN28MQfwGsiukw
CitedBy_id crossref_primary_10_1177_10738584211054742
crossref_primary_10_1016_j_jneumeth_2020_108740
crossref_primary_10_1016_j_neuroimage_2015_11_023
crossref_primary_10_3389_fnins_2019_01159
crossref_primary_10_1002_mrm_26283
crossref_primary_10_3389_fnhum_2023_1216758
crossref_primary_10_1016_j_crhy_2018_02_002
crossref_primary_10_1111_psyp_13392
crossref_primary_10_1371_journal_pone_0252431
crossref_primary_10_1088_1741_2552_adab20
crossref_primary_10_1002_hbm_23688
crossref_primary_10_1016_j_neuroscience_2023_01_021
crossref_primary_10_1109_TBME_2017_2777143
crossref_primary_10_1016_j_neuroimage_2018_08_001
crossref_primary_10_1088_2057_1976_aca20b
crossref_primary_10_1088_1361_6560_abc5aa
crossref_primary_10_1016_j_neuroimage_2018_03_016
crossref_primary_10_1007_s10548_018_0683_2
crossref_primary_10_1109_JBHI_2023_3315974
crossref_primary_10_7554_eLife_92254
crossref_primary_10_1016_j_neuroimage_2016_09_034
crossref_primary_10_1016_j_neuroimage_2017_03_030
crossref_primary_10_1109_TBME_2018_2828336
crossref_primary_10_1016_j_neuroimage_2017_07_013
crossref_primary_10_3390_app14062495
crossref_primary_10_1007_s11517_018_1845_9
crossref_primary_10_1016_j_neuroimage_2016_12_030
crossref_primary_10_1038_micronano_2016_66
crossref_primary_10_1038_s41598_020_62097_6
crossref_primary_10_1016_j_neuroimage_2019_116361
crossref_primary_10_1109_TMI_2019_2936921
crossref_primary_10_1093_braincomms_fcad023
crossref_primary_10_1109_TBME_2019_2933836
crossref_primary_10_1016_j_neuroimage_2016_06_017
crossref_primary_10_1152_jn_00346_2021
crossref_primary_10_1016_j_neuroimage_2017_01_032
crossref_primary_10_1109_LSP_2017_2669101
crossref_primary_10_1002_ima_22239
crossref_primary_10_1111_ejn_15131
crossref_primary_10_3389_fneur_2021_722986
crossref_primary_10_3389_fnhum_2024_1335212
crossref_primary_10_1002_hbm_24754
crossref_primary_10_3390_brainsci12010114
crossref_primary_10_1109_TNSRE_2023_3281356
crossref_primary_10_3389_fnins_2019_00531
crossref_primary_10_1016_j_dcn_2022_101092
crossref_primary_10_1371_journal_pone_0174462
crossref_primary_10_3389_fnhum_2021_669915
crossref_primary_10_1109_TBME_2022_3202751
crossref_primary_10_7554_eLife_92254_3
crossref_primary_10_1155_2019_5618303
crossref_primary_10_1007_s12021_022_09574_7
crossref_primary_10_1016_j_neuroimage_2020_117353
crossref_primary_10_1016_j_neuroimage_2023_120259
crossref_primary_10_3389_fnhum_2020_00082
crossref_primary_10_1002_hbm_23812
Cites_doi 10.1088/0031-9155/50/11/016
10.1007/BF02345748
10.1109/TBME.2008.923919
10.1007/s10548-013-0313-y
10.1007/s10548-012-0274-6
10.1142/S0218127403008156
10.1007/s10439-007-9343-5
10.1109/10.568913
10.1371/journal.pone.0030135
10.1007/BF02512476
10.1002/hbm.20714
10.1088/0967-3334/25/3/013
10.1097/00004691-199905000-00004
10.1023/A:1025606415858
10.1006/nimg.1998.0395
10.1371/journal.pcbi.1000092
10.1523/JNEUROSCI.0540-04.2004
10.1088/0031-9155/49/5/004
10.1007/BF02967147
10.1063/1.2398883
10.1016/S0379-0738(00)00447-3
10.1002/(SICI)1097-0193(1998)6:4<250::AID-HBM5>3.0.CO;2-2
10.1016/S1361-8415(96)80011-9
10.1023/A:1007882102297
10.1016/j.neuroimage.2012.05.006
10.1109/TBME.1980.326713
10.1109/TBME.2003.816072
10.1109/TMI.2003.812271
10.1109/TBME.2003.812164
10.1109/10.40805
10.1109/10.759053
10.1016/j.neuroimage.2006.01.029
10.1016/S1350-4533(99)00038-7
10.1109/JSTSP.2010.2042413
10.1002/hbm.10152
10.1016/j.neuroimage.2007.09.048
10.1109/TBME.2004.836507
10.1155/2010/397272
10.1016/j.cam.2013.09.001
10.1097/00001665-199909000-00004
10.1016/j.clinph.2004.08.017
10.1016/j.neuroimage.2008.02.059
10.1088/0031-9155/49/21/012
10.1016/j.neuroimage.2007.06.002
10.1109/10.887939
10.1126/science.1066168
10.1213/00000539-196811000-00016
10.1007/BF01191074
10.1109/79.962275
10.1109/TBME.2000.880100
10.1016/j.jneumeth.2010.04.031
10.1007/s00791-002-0098-0
10.1007/s11517-008-0316-0
10.1016/j.biopsych.2013.07.020
10.1016/j.tics.2004.03.008
10.1002/hbm.21114
10.1002/hbm.20159
10.1109/10.797987
10.1016/j.neuroimage.2012.01.021
ContentType Journal Article
Copyright 2015 Elsevier Inc.
Copyright © 2015 Elsevier Inc. All rights reserved.
Copyright Elsevier Limited Jan 1, 2016
Copyright_xml – notice: 2015 Elsevier Inc.
– notice: Copyright © 2015 Elsevier Inc. All rights reserved.
– notice: Copyright Elsevier Limited Jan 1, 2016
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
3V.
7TK
7X7
7XB
88E
88G
8AO
8FD
8FE
8FH
8FI
8FJ
8FK
ABUWG
AFKRA
AZQEC
BBNVY
BENPR
BHPHI
CCPQU
DWQXO
FR3
FYUFA
GHDGH
GNUQQ
HCIFZ
K9.
LK8
M0S
M1P
M2M
M7P
P64
PHGZM
PHGZT
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PSYQQ
Q9U
RC3
7X8
7QO
5PM
DOI 10.1016/j.neuroimage.2015.08.032
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
ProQuest Central (Corporate)
Neurosciences Abstracts
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
Psychology Database (Alumni)
ProQuest Pharma Collection
Technology Research Database
ProQuest SciTech Collection
ProQuest Natural Science Collection
ProQuest Hospital Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central
ProQuest Central UK/Ireland
ProQuest Central Essentials
Biological Science Collection
ProQuest Central
Natural Science Collection
ProQuest One Community College
ProQuest Central Korea
Engineering Research Database
ProQuest Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
ProQuest SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Biological Sciences
ProQuest Health & Medical Collection
Medical Database
Psychology Database
Biological Science Database
Biotechnology and BioEngineering Abstracts
Proquest Central Premium
ProQuest One Academic (New)
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest One Psychology
ProQuest Central Basic
Genetics Abstracts
MEDLINE - Academic
Biotechnology Research Abstracts
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
ProQuest One Psychology
ProQuest Central Student
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Natural Science Collection
ProQuest Pharma Collection
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Health & Medical Research Collection
Genetics Abstracts
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
Natural Science Collection
ProQuest Central Korea
Health & Medical Research Collection
Biological Science Collection
ProQuest Central (New)
ProQuest Medical Library (Alumni)
ProQuest Biological Science Collection
ProQuest Central Basic
ProQuest One Academic Eastern Edition
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Psychology Journals (Alumni)
Biological Science Database
ProQuest SciTech Collection
Neurosciences Abstracts
ProQuest Hospital Collection (Alumni)
Biotechnology and BioEngineering Abstracts
ProQuest Health & Medical Complete
ProQuest Medical Library
ProQuest Psychology Journals
ProQuest One Academic UKI Edition
Engineering Research Database
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
MEDLINE - Academic
Biotechnology Research Abstracts
DatabaseTitleList MEDLINE - Academic


MEDLINE
ProQuest One Psychology

Engineering Research Database
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 3
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1095-9572
EndPage 180
ExternalDocumentID PMC4651780
3873685551
26302675
10_1016_j_neuroimage_2015_08_032
S1053811915007442
Genre Research Support, Non-U.S. Gov't
Journal Article
Research Support, N.I.H., Extramural
GrantInformation_xml – fundername: NINDS NIH HHS
  grantid: 2R01 NS047293
– fundername: NINDS NIH HHS
  grantid: R01 NS047293
GroupedDBID ---
--K
--M
.1-
.FO
.~1
0R~
123
1B1
1RT
1~.
1~5
4.4
457
4G.
5RE
5VS
7-5
71M
7X7
88E
8AO
8FE
8FH
8FI
8FJ
8P~
9JM
AABNK
AAEDT
AAEDW
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AATTM
AAXKI
AAXLA
AAXUO
AAYWO
ABBQC
ABCQJ
ABFNM
ABFRF
ABIVO
ABJNI
ABMAC
ABMZM
ABUWG
ACDAQ
ACGFO
ACGFS
ACIEU
ACPRK
ACRLP
ACVFH
ADBBV
ADCNI
ADEZE
ADFRT
AEBSH
AEFWE
AEIPS
AEKER
AENEX
AEUPX
AFJKZ
AFKRA
AFPUW
AFRHN
AFTJW
AFXIZ
AGCQF
AGHFR
AGUBO
AGWIK
AGYEJ
AHHHB
AHMBA
AIEXJ
AIIUN
AIKHN
AITUG
AJRQY
AJUYK
AKBMS
AKRWK
AKYEP
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
ANKPU
ANZVX
AXJTR
AZQEC
BBNVY
BENPR
BHPHI
BKOJK
BLXMC
BNPGV
BPHCQ
BVXVI
CCPQU
CS3
DM4
DU5
DWQXO
EBS
EFBJH
EFKBS
EJD
EO8
EO9
EP2
EP3
F5P
FDB
FIRID
FNPLU
FYGXN
FYUFA
G-Q
GBLVA
GNUQQ
GROUPED_DOAJ
HCIFZ
HMCUK
IHE
J1W
KOM
LG5
LK8
LX8
M1P
M29
M2M
M2V
M41
M7P
MO0
MOBAO
N9A
O-L
O9-
OAUVE
OVD
OZT
P-8
P-9
P2P
PC.
PHGZM
PHGZT
PJZUB
PPXIY
PQGLB
PQQKQ
PROAC
PSQYO
PSYQQ
PUEGO
Q38
ROL
RPZ
SAE
SCC
SDF
SDG
SDP
SES
SSH
SSN
SSZ
T5K
TEORI
UKHRP
UV1
YK3
Z5R
ZU3
~G-
3V.
AACTN
AADPK
AAIAV
ABLVK
ABYKQ
AFKWA
AJBFU
AJOXV
AMFUW
C45
EFLBG
HMQ
LCYCR
RIG
SNS
ZA5
29N
53G
AAFWJ
AAQXK
AAYXX
ABXDB
ACRPL
ADFGL
ADMUD
ADNMO
ADVLN
ADXHL
AFPKN
AGQPQ
AGRNS
AIGII
AKRLJ
ALIPV
APXCP
ASPBG
AVWKF
AZFZN
CAG
CITATION
COF
FEDTE
FGOYB
G-2
HDW
HEI
HMK
HMO
HVGLF
HZ~
OK1
R2-
SEW
WUQ
XPP
ZMT
CGR
CUY
CVF
ECM
EIF
NPM
7TK
7XB
8FD
8FK
FR3
K9.
P64
PKEHL
PQEST
PQUKI
PRINS
Q9U
RC3
7X8
7QO
5PM
ID FETCH-LOGICAL-c597t-3fff1af2cbd355a942cb9dafaf5f0da12659ba54defa884aecc98438871d9b993
IEDL.DBID AIKHN
ISSN 1053-8119
1095-9572
IngestDate Thu Aug 21 18:18:00 EDT 2025
Thu Sep 04 18:08:44 EDT 2025
Fri Sep 05 05:05:46 EDT 2025
Wed Aug 13 04:07:05 EDT 2025
Mon Aug 11 07:11:18 EDT 2025
Tue Jul 01 03:01:44 EDT 2025
Thu Apr 24 23:09:55 EDT 2025
Fri Feb 23 02:25:08 EST 2024
Tue Aug 26 20:08:41 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue Pt A
Keywords Finite Element Method
Source localization
EEG
Sensitivity of EEG to skull conductivity
Skull conductivity estimation
Four-layer realistic head modeling
FEM
Language English
License Copyright © 2015 Elsevier Inc. All rights reserved.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c597t-3fff1af2cbd355a942cb9dafaf5f0da12659ba54defa884aecc98438871d9b993
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink https://www.ncbi.nlm.nih.gov/pmc/articles/4651780
PMID 26302675
PQID 1735307049
PQPubID 2031077
PageCount 13
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_4651780
proquest_miscellaneous_1751215266
proquest_miscellaneous_1735906363
proquest_journals_1735307049
pubmed_primary_26302675
crossref_primary_10_1016_j_neuroimage_2015_08_032
crossref_citationtrail_10_1016_j_neuroimage_2015_08_032
elsevier_sciencedirect_doi_10_1016_j_neuroimage_2015_08_032
elsevier_clinicalkey_doi_10_1016_j_neuroimage_2015_08_032
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2016-01-01
PublicationDateYYYYMMDD 2016-01-01
PublicationDate_xml – month: 01
  year: 2016
  text: 2016-01-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Amsterdam
PublicationTitle NeuroImage (Orlando, Fla.)
PublicationTitleAlternate Neuroimage
PublicationYear 2016
Publisher Elsevier Inc
Elsevier Limited
Publisher_xml – name: Elsevier Inc
– name: Elsevier Limited
References Ataseven, Akalin-Acar, Acar, Gencer (bb0040) 2008; 46
Ollikainen, Vauhkonen, Karjalainen, Kaipio (bb0270) 1999; 21
Studholme, Hill, Hawkes (bb0320) 1996; 1
Hwang, Kim, Baik (bb0195) 1999; 10
Anderson (bb0035) 1882; 74
Baillet, Mosher, Leahy (bb0055) 2001; 18
Akalin Acar, Worrell, Makeig (bb0015) 2009
Makeig, Debener, Onton, Delorme (bb0235) 2004; 8
Akalin Acar, Palmer, Worrell, Makeig (bb0020) 2011
Rush, Driscoll (bb0310) 1968; 47
Baillet, Garnero (bb0045) 1997; 44
Akalin Acar, Makeig (bb0010) 2013; 26
Mosher, Baillet, Leahy (bb0260) 1999; 16
Lai, van Drongelen, Ding, Hecox, Towle, Frim, He (bb0200) 2005; 116
Makeig, Bell, Jung, Sejnowski (bb0225) 1996; vol. 8
Goncalves, de Munck, Jeroen, Heethaar, da Silva (bb0150) 2003; 50
Palmer, Kreutz-Delgado, Makeig (bb0280) 2006
Akalin-Acar, Gençer (bb0025) 2004; 49
Cao, Akalin Acar, Kreutz-Delgado, Makeig (bb0075) 2012
Huiskamp, Vroeijenstijn, Van Dijk, Wieneke, Van Huffelen (bb0190) 1999; 46
Ulker Karbeyaz, Gencer (bb0335) 2003; 22
Friston, Harrison, Daunizeua, Henson, Flandin, Mattout (bb0130) 2008; 39
Ferree, Eriksen, Tucker (bb0115) 2000; 47
Dannhauer, Lanfer, Wolters, Knosche (bb0095) 2011; 32
Chakkalakal, Johnson, Harper, Katz (bb0080) 1980; 27
Wipf, Nagarajan (bb0355) 2009; 44
Bashar, Li, Wen (bb0060) 2010
Hoekema, Wieneke, Leijten, van Veelen, van Rijen, Huiskamp, Ansems, van Huffelen (bb0170) 2003; 16
Lanfer, Scherg, Dannhauer, Knosche, Burger, Wolters (bb0205) 2012; 62
Chauveau, Franceries, Doyon, Rigaud, Morucci, Celsis (bb0085) 2004; 21
Vanrumste, Van Hoey, Van de Walle, D'Havé, Lemahieu, Boon (bb0345) 2000; 38
Dale, Fischl, Sereno (bb0090) 1999; 9
Gao, Zhu, He (bb0140) 2005; 50
Gençer, Acar (bb0145) 2004; 49
Delorme, Palmer, Oostenveld, Makeig (bb0105) 2012
Akalin Acar, Makeig (bb0005) 2010; 190
Marin, Guerin, Baillet, Garnero, Meunier (bb0240) 1998; 6
Akhtari, Bryant, Mamelak, Heller, Shih, Mandelkern, Matlachov, Ranken, Best, Sutherling (bb0030) 2000; 13
Goncalves, de Munck, Verbunt, Heethaar, da Silva (bb0155) 2003; 50
Sadleir, Argibay (bb0315) 2007; 35
Hämäläinen, Ilmoniemi (bb0165) 1994; 32
Ramon, Schimpf, Haueisen (bb0305) 2006; 5
Beggs, Plenz (bb0070) 2004; 24
Huang, Song, Hagler, Podgorny, Jousmaki, Cui, Gaa, Harrington, Dale, Lee, Elman, Halgren (bb0180) 2007; 37
Vallaghe, Clerc, Badier (bb0340) 2007
Nunez, Srinivasan (bb0265) 2006
Makeig, Westerfield, Jung, Enghoff, Townsend, Courchesne, Sejnovski (bb0230) 2002; 295
Fischl (bb0120) 2012; 62
Lew, Wolters, Anwander, Makeig, MacLeod (bb0215) 2009; 30
Wipf, Nagarajan (bb0360) 2010; 4
Law (bb0210) 1993; 6
Meijs, Weier, Peters (bb0250) 1989; 36
Deco, Jirsa, Robinson, Breakspear, Friston (bb0100) 2008; 4
Huiskamp (bb0185) 2008; 10
Ramirez, Makeig (bb0300) 2006
Dogdas, Shattuck, Leahy (bb0110) 2005; 26
Freeman (bb0125) 2003; 13
Fu, Lewis, Kirby, Whitaker (bb0135) 2014; 257
Lynnerup (bb0220) 2001; 117
Turovets, Salman, Malony, Poolman, Davey, Tucker (bb0330) 2007; 14
Montes-Restrepo, van Mierlo, Strobbe, Staelens, Vandenberghe, Hallez (bb0255) 2014; 27
Oostendorp, Delbeke, Stegeman (bb0275) 2000; 47
Pasqual-Marqui (bb0290) 1999; 1
Zhang, van Drongelen, He (bb0370) 2006; 89
Wendel, Vaisanen, Seemann, Hyttinen, Malmivuo (bb0350) 2010; 2010
Palmer, Kreutz-Delgado, Rao, Makeig (bb0285) 2007
Baillet, Garnero, Marin, Hugonin (bb0050) 1999; 46
Gutierrez, Nehorai, Muravchik (bb0160) 2004; 51
Pasqual-Marqui, Esslen, Kochi, Lehmann (bb0295) 2002; 24
Huang, Dale, Song, Halgren, Harrington, Podgorny, Carnive, Lewis, Lee (bb0175) 2006; 31
McLoughlin, Palmer, Rijsdijk, Makeig (bb0245) 2014; 75
Tang, Fusheng, Cheng, Gao, Fu, Yang, Dong (bb0325) 2008; 55
Wolters, Kuhn, Anwander, Reitzinger (bb0365) 2002; 5
Baysal, Haueisen (bb0065) 2004; 25
Akalin Acar (10.1016/j.neuroimage.2015.08.032_bb0015) 2009
Makeig (10.1016/j.neuroimage.2015.08.032_bb0225) 1996; vol. 8
Baysal (10.1016/j.neuroimage.2015.08.032_bb0065) 2004; 25
Beggs (10.1016/j.neuroimage.2015.08.032_bb0070) 2004; 24
Huang (10.1016/j.neuroimage.2015.08.032_bb0180) 2007; 37
Ollikainen (10.1016/j.neuroimage.2015.08.032_bb0270) 1999; 21
Nunez (10.1016/j.neuroimage.2015.08.032_bb0265) 2006
Turovets (10.1016/j.neuroimage.2015.08.032_bb0330) 2007; 14
Dannhauer (10.1016/j.neuroimage.2015.08.032_bb0095) 2011; 32
Lanfer (10.1016/j.neuroimage.2015.08.032_bb0205) 2012; 62
Cao (10.1016/j.neuroimage.2015.08.032_bb0075) 2012
Delorme (10.1016/j.neuroimage.2015.08.032_bb0105) 2012
Freeman (10.1016/j.neuroimage.2015.08.032_bb0125) 2003; 13
Oostendorp (10.1016/j.neuroimage.2015.08.032_bb0275) 2000; 47
Akalin Acar (10.1016/j.neuroimage.2015.08.032_bb0005) 2010; 190
Huang (10.1016/j.neuroimage.2015.08.032_bb0175) 2006; 31
Goncalves (10.1016/j.neuroimage.2015.08.032_bb0150) 2003; 50
Anderson (10.1016/j.neuroimage.2015.08.032_bb0035) 1882; 74
Chakkalakal (10.1016/j.neuroimage.2015.08.032_bb0080) 1980; 27
Deco (10.1016/j.neuroimage.2015.08.032_bb0100) 2008; 4
Meijs (10.1016/j.neuroimage.2015.08.032_bb0250) 1989; 36
Palmer (10.1016/j.neuroimage.2015.08.032_bb0280) 2006
Chauveau (10.1016/j.neuroimage.2015.08.032_bb0085) 2004; 21
Baillet (10.1016/j.neuroimage.2015.08.032_bb0055) 2001; 18
Ferree (10.1016/j.neuroimage.2015.08.032_bb0115) 2000; 47
Akalin Acar (10.1016/j.neuroimage.2015.08.032_bb0020) 2011
Dale (10.1016/j.neuroimage.2015.08.032_bb0090) 1999; 9
Marin (10.1016/j.neuroimage.2015.08.032_bb0240) 1998; 6
Lew (10.1016/j.neuroimage.2015.08.032_bb0215) 2009; 30
Dogdas (10.1016/j.neuroimage.2015.08.032_bb0110) 2005; 26
Ramon (10.1016/j.neuroimage.2015.08.032_bb0305) 2006; 5
Vallaghe (10.1016/j.neuroimage.2015.08.032_bb0340) 2007
Gao (10.1016/j.neuroimage.2015.08.032_bb0140) 2005; 50
Makeig (10.1016/j.neuroimage.2015.08.032_bb0230) 2002; 295
Huiskamp (10.1016/j.neuroimage.2015.08.032_bb0190) 1999; 46
Gutierrez (10.1016/j.neuroimage.2015.08.032_bb0160) 2004; 51
Wipf (10.1016/j.neuroimage.2015.08.032_bb0360) 2010; 4
Wolters (10.1016/j.neuroimage.2015.08.032_bb0365) 2002; 5
Akalin-Acar (10.1016/j.neuroimage.2015.08.032_bb0025) 2004; 49
Mosher (10.1016/j.neuroimage.2015.08.032_bb0260) 1999; 16
Friston (10.1016/j.neuroimage.2015.08.032_bb0130) 2008; 39
Lynnerup (10.1016/j.neuroimage.2015.08.032_bb0220) 2001; 117
Fu (10.1016/j.neuroimage.2015.08.032_bb0135) 2014; 257
Makeig (10.1016/j.neuroimage.2015.08.032_bb0235) 2004; 8
Akhtari (10.1016/j.neuroimage.2015.08.032_bb0030) 2000; 13
Ramirez (10.1016/j.neuroimage.2015.08.032_bb0300) 2006
Lai (10.1016/j.neuroimage.2015.08.032_bb0200) 2005; 116
Akalin Acar (10.1016/j.neuroimage.2015.08.032_bb0010) 2013; 26
Huiskamp (10.1016/j.neuroimage.2015.08.032_bb0185) 2008; 10
Ulker Karbeyaz (10.1016/j.neuroimage.2015.08.032_bb0335) 2003; 22
Law (10.1016/j.neuroimage.2015.08.032_bb0210) 1993; 6
Ataseven (10.1016/j.neuroimage.2015.08.032_bb0040) 2008; 46
Palmer (10.1016/j.neuroimage.2015.08.032_bb0285) 2007
McLoughlin (10.1016/j.neuroimage.2015.08.032_bb0245) 2014; 75
Hwang (10.1016/j.neuroimage.2015.08.032_bb0195) 1999; 10
Studholme (10.1016/j.neuroimage.2015.08.032_bb0320) 1996; 1
Goncalves (10.1016/j.neuroimage.2015.08.032_bb0155) 2003; 50
Vanrumste (10.1016/j.neuroimage.2015.08.032_bb0345) 2000; 38
Gençer (10.1016/j.neuroimage.2015.08.032_bb0145) 2004; 49
Rush (10.1016/j.neuroimage.2015.08.032_bb0310) 1968; 47
Wipf (10.1016/j.neuroimage.2015.08.032_bb0355) 2009; 44
Baillet (10.1016/j.neuroimage.2015.08.032_bb0045) 1997; 44
Tang (10.1016/j.neuroimage.2015.08.032_bb0325) 2008; 55
Pasqual-Marqui (10.1016/j.neuroimage.2015.08.032_bb0295) 2002; 24
Sadleir (10.1016/j.neuroimage.2015.08.032_bb0315) 2007; 35
Bashar (10.1016/j.neuroimage.2015.08.032_bb0060) 2010
Montes-Restrepo (10.1016/j.neuroimage.2015.08.032_bb0255) 2014; 27
Wendel (10.1016/j.neuroimage.2015.08.032_bb0350) 2010; 2010
Baillet (10.1016/j.neuroimage.2015.08.032_bb0050) 1999; 46
Zhang (10.1016/j.neuroimage.2015.08.032_bb0370) 2006; 89
Fischl (10.1016/j.neuroimage.2015.08.032_bb0120) 2012; 62
Pasqual-Marqui (10.1016/j.neuroimage.2015.08.032_bb0290) 1999; 1
Hoekema (10.1016/j.neuroimage.2015.08.032_bb0170) 2003; 16
Hämäläinen (10.1016/j.neuroimage.2015.08.032_bb0165) 1994; 32
References_xml – volume: 75
  start-page: 238
  year: 2014
  end-page: 247
  ident: bb0245
  article-title: Genetic overlap between evoked frontocentral theta-band phase variability, reaction time variability, and attention-deficit/hyperactivity disorder symptoms in a twin study
  publication-title: Biol. Psychiatry
– start-page: 1036
  year: 2007
  end-page: 1039
  ident: bb0340
  article-title: In vivo conductivity estimation using somatosensory evoked potentials and cortical constraint on the source
  publication-title: ISBI
– volume: 89
  year: 2006
  ident: bb0370
  article-title: Estimation of in vivo brain-to-skull conductivity ratio in humans
  publication-title: Appl. Phys. Lett.
– volume: 24
  start-page: 5216
  year: 2004
  end-page: 5229
  ident: bb0070
  article-title: Neuronal avalanches are diverse and precise activity patterns that are stable for many hours in cortical slice cultures
  publication-title: J. Neurosci.
– start-page: 23
  year: 2010
  end-page: 27
  ident: bb0060
  article-title: Effects of the local skull and spongiosum conductivities on realistic head modeling
  publication-title: IEEE/ICME Int. Conf. on Complex Med. Eng.
– year: 2009
  ident: bb0015
  article-title: Patch-Based Cortical Source Localization in Epilepsy
  publication-title: Proc. of IEEE EMBC
– volume: 25
  start-page: 737
  year: 2004
  end-page: 748
  ident: bb0065
  article-title: Use of a priori information in estimating tissue resistivities—application to human data in vivo
  publication-title: Physiol. Meas.
– volume: 46
  start-page: 1281
  year: 1999
  end-page: 1287
  ident: bb0190
  article-title: The need for correct realistic geometry in the inverse EEG problem
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 49
  start-page: 701
  year: 2004
  end-page: 717
  ident: bb0145
  article-title: Sensitivity of EEG and MEG measurements to tissue conductivity
  publication-title: Phys. Med. Biol.
– volume: 18
  start-page: 14
  year: 2001
  end-page: 30
  ident: bb0055
  article-title: Electromagnetic brain mapping
  publication-title: IEEE Signal Process. Mag.
– volume: 47
  start-page: 717
  year: 1968
  end-page: 723
  ident: bb0310
  article-title: Current distribution in the brain from the surface electrodes
  publication-title: Anesth. Analg.
– volume: 21
  start-page: 143
  year: 1999
  end-page: 154
  ident: bb0270
  article-title: Effects of local skull inhomogeneities on EEG source estimation
  publication-title: Med. Eng. Phys.
– volume: 55
  start-page: 2286
  year: 2008
  end-page: 2292
  ident: bb0325
  article-title: Correlation between structure and resistivity variations of the live human skull
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 295
  start-page: 690
  year: 2002
  end-page: 694
  ident: bb0230
  article-title: Dynamic brain sources of visual evoked responses
  publication-title: Science
– year: 2007
  ident: bb0285
  article-title: Modeling and estimation of dependent subspaces
  publication-title: Proceedings of the 7th International Conference on Independent Component Analysis and Signal Separation
– volume: 5
  year: 2006
  ident: bb0305
  article-title: Influence of head models on eeg simulations and inverse source localizations
  publication-title: Biomed. Eng. Online
– year: 2006
  ident: bb0300
  article-title: Neuroelectromagnetic Source Imaging Using Multiscale Geodesic Neural Bases and Sparse Bayesian Learning
  publication-title: Proc. of HBM
– volume: 32
  start-page: 1383
  year: 2011
  end-page: 1399
  ident: bb0095
  article-title: Modeling of the human skull in EEG source analysis
  publication-title: Hum. Brain Mapp.
– volume: 6
  start-page: 99
  year: 1993
  end-page: 109
  ident: bb0210
  article-title: Thickness and resistivity variations over the upper surface of the human skull
  publication-title: Brain Topogr.
– volume: 13
  start-page: 29
  year: 2000
  end-page: 42
  ident: bb0030
  article-title: Conductivities of three-layer human skull
  publication-title: Brain Topogr.
– volume: 26
  start-page: 378
  year: 2013
  end-page: 396
  ident: bb0010
  article-title: Effects of forward model errors on EEG source localization
  publication-title: Brain Topogr.
– volume: 74
  start-page: 270
  year: 1882
  end-page: 280
  ident: bb0035
  article-title: Observation on the thickness of human skull
  publication-title: Dublin J. Med. Sci.
– volume: 50
  start-page: 1124
  year: 2003
  end-page: 1128
  ident: bb0155
  article-title: In vivo measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 46
  start-page: 671
  year: 2008
  end-page: 679
  ident: bb0040
  article-title: Parallel implementation of the accelerated BEM approach for EMSI of the human brain
  publication-title: Med. Biol. Eng. Comput.
– volume: 39
  start-page: 1104
  year: 2008
  end-page: 1120
  ident: bb0130
  article-title: Multiple sparse priors for the M/EEG inverse problem
  publication-title: Neuroimage
– volume: 116
  start-page: 456
  year: 2005
  end-page: 465
  ident: bb0200
  article-title: Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings
  publication-title: Clin. Neurophysiol.
– volume: 10
  year: 1999
  ident: bb0195
  article-title: The thickness of the skull in Korean adults
  publication-title: J. Craniofac. Surg.
– volume: 26
  start-page: 273
  year: 2005
  end-page: 285
  ident: bb0110
  article-title: Segmentation of skull and scalp in 3-d human MRI using mathematical morphology
  publication-title: Hum. Brain Mapp.
– volume: 21
  start-page: 86
  year: 2004
  end-page: 97
  ident: bb0085
  article-title: Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three-dimensional resistor mesh model
  publication-title: Hum. Brain Mapp.
– volume: 50
  start-page: 2675
  year: 2005
  end-page: 2687
  ident: bb0140
  article-title: Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement
  publication-title: Phys. Med. Biol.
– volume: 9
  start-page: 179
  year: 1999
  end-page: 194
  ident: bb0090
  article-title: Cortical surface-based analysis: 1. segmentation and surface reconstruction
  publication-title: Neuroimage
– volume: 1
  start-page: 163
  year: 1996
  end-page: 175
  ident: bb0320
  article-title: Automated 3-D registration of MR and CT images of the head
  publication-title: Med. Image Anal.
– volume: 31
  start-page: 1025
  year: 2006
  end-page: 1037
  ident: bb0175
  article-title: Vector-based spatial–temporal minimum l1-norm solution for MEG
  publication-title: Neuroimage
– volume: 27
  start-page: 95
  year: 1980
  end-page: 100
  ident: bb0080
  article-title: Dielectric properties of fluid-saturated bone
  publication-title: IEEE Trans. Biomed. Eng
– volume: 44
  start-page: 947
  year: 2009
  end-page: 966
  ident: bb0355
  article-title: A unified Bayesian framework for MEG/EEG source imaging
  publication-title: Neuroimage
– volume: 37
  start-page: 731
  year: 2007
  end-page: 748
  ident: bb0180
  article-title: A novel integrated MEG and EEG analysis method for dipolar sources
  publication-title: Neuroimage
– volume: 47
  start-page: 1487
  year: 2000
  end-page: 1492
  ident: bb0275
  article-title: The conductivity of the human skull: results of in vivo and in vitro measurements
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 2010
  year: 2010
  ident: bb0350
  article-title: The influence of age and skull conductivity on surface and subnormal bipolar EEG leads
  publication-title: Comput. Intell. Neurosci.
– volume: 44
  start-page: 374
  year: 1997
  end-page: 385
  ident: bb0045
  article-title: A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 30
  start-page: 2862
  year: 2009
  end-page: 2878
  ident: bb0215
  article-title: Improved EEG source analysis using low-resolution conductivity estimation in a four-compartment finite element head model
  publication-title: Hum. Brain Mapp.
– volume: 35
  start-page: 1699
  year: 2007
  end-page: 1712
  ident: bb0315
  article-title: Modeling skull electrical properties
  publication-title: Ann. Biomed. Eng.
– volume: 4
  year: 2008
  ident: bb0100
  article-title: The dynamic brain: from spiking neurons to neural masses and cortical fields
  publication-title: PLoS Comput. Biol.
– year: 2006
  ident: bb0280
  article-title: Super-gaussian mixture source model for ICA
  publication-title: Proceedings of the 6th International Symposium on Independent Component Analysis
– volume: 46
  start-page: 522
  year: 1999
  end-page: 534
  ident: bb0050
  article-title: Electromagnetic brain mapping
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 62
  start-page: 774
  year: 2012
  end-page: 781
  ident: bb0120
  article-title: Freesurfer
  publication-title: Neuroimage
– volume: 38
  start-page: 528
  year: 2000
  end-page: 534
  ident: bb0345
  article-title: Dipole location errors in electroencephalogram source analysis due to volume conductor model errors
  publication-title: Med. Biol. Eng. Comput.
– volume: 14
  start-page: 3854
  year: 2007
  end-page: 3857
  ident: bb0330
  article-title: Anatomically constrained conductivity estimation of the human head tissues in vivo: computational procedure and preliminary experiments
  publication-title: IFMBE Proceedings
– volume: 190
  start-page: 258
  year: 2010
  end-page: 270
  ident: bb0005
  article-title: Neuroelectromagnetic forward head modeling toolbox
  publication-title: J. Neurosci. Methods
– volume: 13
  start-page: 2513
  year: 2003
  end-page: 2535
  ident: bb0125
  article-title: A neurobiological theory of meaning in perception part ii: spatial patterns of phase in gamma EEGs from primary sensory cortices reveal the dynamics of mesoscopic wave packets
  publication-title: Int. J. Bifurcation Chaos
– year: 2012
  ident: bb0105
  article-title: Independent EEG sources are dipolar
  publication-title: PLoS One
– volume: 22
  start-page: 627
  year: 2003
  end-page: 635
  ident: bb0335
  article-title: Electrical conductivity imaging via contactless measurements: an experimental study
  publication-title: IEEE Trans. Med. Imaging
– volume: 27
  start-page: 95
  year: 2014
  end-page: 111
  ident: bb0255
  article-title: Influence of skull modeling approaches on EEG source localization
  publication-title: Brain Topogr.
– year: 2012
  ident: bb0075
  article-title: A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization
  publication-title: 34th Annual International IEEE EMBS Conference, San Diego
– volume: 51
  start-page: 2113
  year: 2004
  end-page: 2122
  ident: bb0160
  article-title: Estimating brain conductivities and dipole source signals with EEG arrays
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 16
  start-page: 225
  year: 1999
  end-page: 238
  ident: bb0260
  article-title: EEG source localization and imaging using multiple signal classification approaches
  publication-title: J. Clin. Neurophysiol.
– volume: 24
  start-page: 91
  year: 2002
  end-page: 95
  ident: bb0295
  article-title: Functional imaging with low resolution brain electromagnetic tomography (LORETA): a review
  publication-title: Methods Find. Exp. Clin. Pharmacol.
– volume: 1
  start-page: 75
  year: 1999
  end-page: 86
  ident: bb0290
  article-title: Review of methods for solving the EEG inverse problem
  publication-title: Int. J. Bioelectromagn.
– volume: 4
  start-page: 317
  year: 2010
  end-page: 329
  ident: bb0360
  article-title: Iterative reweighted l1 and l2 methods for finding sparse solutions
  publication-title: IEEE J. Sel. Top. Sign. Proces.
– year: 2011
  ident: bb0020
  article-title: Electrocortical Source Imaging of Intracranial EEG Data in Epilepsy
  publication-title: Proc. of IEEE EMBC
– volume: 47
  start-page: 1584
  year: 2000
  end-page: 1592
  ident: bb0115
  article-title: Regional head tissue conductivity estimation for improved EEG analysis
  publication-title: IEEE Trans. Biomed. Eng.
– volume: vol. 8
  year: 1996
  ident: bb0225
  publication-title: Independent component analysis of electroencephalographic data
– year: 2006
  ident: bb0265
  article-title: Electric Fields of the Brain
– volume: 10
  start-page: 25
  year: 2008
  end-page: 30
  ident: bb0185
  article-title: Interindividual variability of skull conductivity: an EEG–MEG analysis
  publication-title: Int. J. Bioelectromagn.
– volume: 16
  start-page: 29
  year: 2003
  end-page: 38
  ident: bb0170
  article-title: Measurement of the conductivity of skull, temporarily removed during epilepsy surgery
  publication-title: Brain Topogr.
– volume: 257
  start-page: 195
  year: 2014
  end-page: 211
  ident: bb0135
  article-title: Architecting the finite element method pipeline for the GPU
  publication-title: J. Comput. Appl. Math.
– volume: 117
  start-page: 45
  year: 2001
  end-page: 51
  ident: bb0220
  article-title: Cranial thickness in relation to age, sex, and general body build in a Danish forensic sample
  publication-title: Forensic Sci. Int.
– volume: 49
  start-page: 5011
  year: 2004
  end-page: 5028
  ident: bb0025
  article-title: An advanced boundary element method (BEM) implementation for the forward problem of electromagnetic source imaging
  publication-title: Phys. Med. Biol.
– volume: 50
  start-page: 754
  year: 2003
  end-page: 767
  ident: bb0150
  article-title: In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 32
  start-page: 35
  year: 1994
  end-page: 42
  ident: bb0165
  article-title: Interpreting magnetic fields of the brain
  publication-title: Med. Biol. Eng. Comput.
– volume: 36
  start-page: 1038
  year: 1989
  end-page: 1049
  ident: bb0250
  article-title: On the numerical accuracy of the boundary element method
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 8
  start-page: 204
  year: 2004
  end-page: 210
  ident: bb0235
  article-title: Mining event-related brain dynamics
  publication-title: Trends Cogn. Sci.
– volume: 6
  start-page: 250
  year: 1998
  end-page: 269
  ident: bb0240
  article-title: Influence of skull anisotropy for the forward and inverse problem in EEG: simulation studies using fem on realistic head models
  publication-title: Hum. Brain Mapp.
– volume: 5
  start-page: 165
  year: 2002
  end-page: 177
  ident: bb0365
  article-title: A parallel algebraic multigrid solver for finite element method based source localization in the human brain
  publication-title: Comput. Vis. Sci.
– volume: 62
  start-page: 418
  year: 2012
  end-page: 431
  ident: bb0205
  article-title: Influences of skull segmentation inaccuracies on EEG source analysis
  publication-title: Neuroimage
– volume: 50
  start-page: 2675
  year: 2005
  ident: 10.1016/j.neuroimage.2015.08.032_bb0140
  article-title: Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement
  publication-title: Phys. Med. Biol.
  doi: 10.1088/0031-9155/50/11/016
– volume: 38
  start-page: 528
  year: 2000
  ident: 10.1016/j.neuroimage.2015.08.032_bb0345
  article-title: Dipole location errors in electroencephalogram source analysis due to volume conductor model errors
  publication-title: Med. Biol. Eng. Comput.
  doi: 10.1007/BF02345748
– volume: 55
  start-page: 2286
  year: 2008
  ident: 10.1016/j.neuroimage.2015.08.032_bb0325
  article-title: Correlation between structure and resistivity variations of the live human skull
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2008.923919
– volume: 27
  start-page: 95
  year: 2014
  ident: 10.1016/j.neuroimage.2015.08.032_bb0255
  article-title: Influence of skull modeling approaches on EEG source localization
  publication-title: Brain Topogr.
  doi: 10.1007/s10548-013-0313-y
– volume: 26
  start-page: 378
  year: 2013
  ident: 10.1016/j.neuroimage.2015.08.032_bb0010
  article-title: Effects of forward model errors on EEG source localization
  publication-title: Brain Topogr.
  doi: 10.1007/s10548-012-0274-6
– volume: 13
  start-page: 2513
  year: 2003
  ident: 10.1016/j.neuroimage.2015.08.032_bb0125
  article-title: A neurobiological theory of meaning in perception part ii: spatial patterns of phase in gamma EEGs from primary sensory cortices reveal the dynamics of mesoscopic wave packets
  publication-title: Int. J. Bifurcation Chaos
  doi: 10.1142/S0218127403008156
– volume: 35
  start-page: 1699
  issue: 10
  year: 2007
  ident: 10.1016/j.neuroimage.2015.08.032_bb0315
  article-title: Modeling skull electrical properties
  publication-title: Ann. Biomed. Eng.
  doi: 10.1007/s10439-007-9343-5
– volume: 44
  start-page: 374
  year: 1997
  ident: 10.1016/j.neuroimage.2015.08.032_bb0045
  article-title: A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.568913
– year: 2012
  ident: 10.1016/j.neuroimage.2015.08.032_bb0105
  article-title: Independent EEG sources are dipolar
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0030135
– volume: 32
  start-page: 35
  issue: 1
  year: 1994
  ident: 10.1016/j.neuroimage.2015.08.032_bb0165
  article-title: Interpreting magnetic fields of the brain
  publication-title: Med. Biol. Eng. Comput.
  doi: 10.1007/BF02512476
– volume: 30
  start-page: 2862
  year: 2009
  ident: 10.1016/j.neuroimage.2015.08.032_bb0215
  article-title: Improved EEG source analysis using low-resolution conductivity estimation in a four-compartment finite element head model
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.20714
– volume: 25
  start-page: 737
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0065
  article-title: Use of a priori information in estimating tissue resistivities—application to human data in vivo
  publication-title: Physiol. Meas.
  doi: 10.1088/0967-3334/25/3/013
– volume: 16
  start-page: 225
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0260
  article-title: EEG source localization and imaging using multiple signal classification approaches
  publication-title: J. Clin. Neurophysiol.
  doi: 10.1097/00004691-199905000-00004
– year: 2011
  ident: 10.1016/j.neuroimage.2015.08.032_bb0020
  article-title: Electrocortical Source Imaging of Intracranial EEG Data in Epilepsy
– volume: 16
  start-page: 29
  issue: 1
  year: 2003
  ident: 10.1016/j.neuroimage.2015.08.032_bb0170
  article-title: Measurement of the conductivity of skull, temporarily removed during epilepsy surgery
  publication-title: Brain Topogr.
  doi: 10.1023/A:1025606415858
– volume: 9
  start-page: 179
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0090
  article-title: Cortical surface-based analysis: 1. segmentation and surface reconstruction
  publication-title: Neuroimage
  doi: 10.1006/nimg.1998.0395
– volume: 4
  issue: 8
  year: 2008
  ident: 10.1016/j.neuroimage.2015.08.032_bb0100
  article-title: The dynamic brain: from spiking neurons to neural masses and cortical fields
  publication-title: PLoS Comput. Biol.
  doi: 10.1371/journal.pcbi.1000092
– volume: 24
  start-page: 5216
  issue: 22
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0070
  article-title: Neuronal avalanches are diverse and precise activity patterns that are stable for many hours in cortical slice cultures
  publication-title: J. Neurosci.
  doi: 10.1523/JNEUROSCI.0540-04.2004
– volume: 49
  start-page: 701
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0145
  article-title: Sensitivity of EEG and MEG measurements to tissue conductivity
  publication-title: Phys. Med. Biol.
  doi: 10.1088/0031-9155/49/5/004
– volume: 5
  year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0305
  article-title: Influence of head models on eeg simulations and inverse source localizations
  publication-title: Biomed. Eng. Online
– volume: vol. 8
  year: 1996
  ident: 10.1016/j.neuroimage.2015.08.032_bb0225
– volume: 74
  start-page: 270
  year: 1882
  ident: 10.1016/j.neuroimage.2015.08.032_bb0035
  article-title: Observation on the thickness of human skull
  publication-title: Dublin J. Med. Sci.
  doi: 10.1007/BF02967147
– volume: 89
  year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0370
  article-title: Estimation of in vivo brain-to-skull conductivity ratio in humans
  publication-title: Appl. Phys. Lett.
  doi: 10.1063/1.2398883
– volume: 117
  start-page: 45
  year: 2001
  ident: 10.1016/j.neuroimage.2015.08.032_bb0220
  article-title: Cranial thickness in relation to age, sex, and general body build in a Danish forensic sample
  publication-title: Forensic Sci. Int.
  doi: 10.1016/S0379-0738(00)00447-3
– volume: 6
  start-page: 250
  year: 1998
  ident: 10.1016/j.neuroimage.2015.08.032_bb0240
  article-title: Influence of skull anisotropy for the forward and inverse problem in EEG: simulation studies using fem on realistic head models
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/(SICI)1097-0193(1998)6:4<250::AID-HBM5>3.0.CO;2-2
– volume: 1
  start-page: 163
  year: 1996
  ident: 10.1016/j.neuroimage.2015.08.032_bb0320
  article-title: Automated 3-D registration of MR and CT images of the head
  publication-title: Med. Image Anal.
  doi: 10.1016/S1361-8415(96)80011-9
– volume: 13
  start-page: 29
  year: 2000
  ident: 10.1016/j.neuroimage.2015.08.032_bb0030
  article-title: Conductivities of three-layer human skull
  publication-title: Brain Topogr.
  doi: 10.1023/A:1007882102297
– volume: 62
  start-page: 418
  year: 2012
  ident: 10.1016/j.neuroimage.2015.08.032_bb0205
  article-title: Influences of skull segmentation inaccuracies on EEG source analysis
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2012.05.006
– volume: 27
  start-page: 95
  year: 1980
  ident: 10.1016/j.neuroimage.2015.08.032_bb0080
  article-title: Dielectric properties of fluid-saturated bone
  publication-title: IEEE Trans. Biomed. Eng
  doi: 10.1109/TBME.1980.326713
– start-page: 1036
  year: 2007
  ident: 10.1016/j.neuroimage.2015.08.032_bb0340
  article-title: In vivo conductivity estimation using somatosensory evoked potentials and cortical constraint on the source
– volume: 10
  start-page: 25
  year: 2008
  ident: 10.1016/j.neuroimage.2015.08.032_bb0185
  article-title: Interindividual variability of skull conductivity: an EEG–MEG analysis
  publication-title: Int. J. Bioelectromagn.
– volume: 50
  start-page: 1124
  year: 2003
  ident: 10.1016/j.neuroimage.2015.08.032_bb0155
  article-title: In vivo measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2003.816072
– volume: 22
  start-page: 627
  year: 2003
  ident: 10.1016/j.neuroimage.2015.08.032_bb0335
  article-title: Electrical conductivity imaging via contactless measurements: an experimental study
  publication-title: IEEE Trans. Med. Imaging
  doi: 10.1109/TMI.2003.812271
– volume: 50
  start-page: 754
  year: 2003
  ident: 10.1016/j.neuroimage.2015.08.032_bb0150
  article-title: In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2003.812164
– volume: 36
  start-page: 1038
  year: 1989
  ident: 10.1016/j.neuroimage.2015.08.032_bb0250
  article-title: On the numerical accuracy of the boundary element method
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.40805
– volume: 46
  start-page: 522
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0050
  article-title: Electromagnetic brain mapping
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.759053
– year: 2012
  ident: 10.1016/j.neuroimage.2015.08.032_bb0075
  article-title: A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization
– volume: 31
  start-page: 1025
  year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0175
  article-title: Vector-based spatial–temporal minimum l1-norm solution for MEG
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2006.01.029
– year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0265
– volume: 1
  start-page: 75
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0290
  article-title: Review of methods for solving the EEG inverse problem
  publication-title: Int. J. Bioelectromagn.
– volume: 21
  start-page: 143
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0270
  article-title: Effects of local skull inhomogeneities on EEG source estimation
  publication-title: Med. Eng. Phys.
  doi: 10.1016/S1350-4533(99)00038-7
– volume: 14
  start-page: 3854
  year: 2007
  ident: 10.1016/j.neuroimage.2015.08.032_bb0330
  article-title: Anatomically constrained conductivity estimation of the human head tissues in vivo: computational procedure and preliminary experiments
– volume: 4
  start-page: 317
  issue: 2
  year: 2010
  ident: 10.1016/j.neuroimage.2015.08.032_bb0360
  article-title: Iterative reweighted l1 and l2 methods for finding sparse solutions
  publication-title: IEEE J. Sel. Top. Sign. Proces.
  doi: 10.1109/JSTSP.2010.2042413
– volume: 21
  start-page: 86
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0085
  article-title: Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three-dimensional resistor mesh model
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.10152
– volume: 39
  start-page: 1104
  issue: 3
  year: 2008
  ident: 10.1016/j.neuroimage.2015.08.032_bb0130
  article-title: Multiple sparse priors for the M/EEG inverse problem
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2007.09.048
– volume: 51
  start-page: 2113
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0160
  article-title: Estimating brain conductivities and dipole source signals with EEG arrays
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2004.836507
– volume: 2010
  year: 2010
  ident: 10.1016/j.neuroimage.2015.08.032_bb0350
  article-title: The influence of age and skull conductivity on surface and subnormal bipolar EEG leads
  publication-title: Comput. Intell. Neurosci.
  doi: 10.1155/2010/397272
– year: 2009
  ident: 10.1016/j.neuroimage.2015.08.032_bb0015
  article-title: Patch-Based Cortical Source Localization in Epilepsy
– volume: 257
  start-page: 195
  year: 2014
  ident: 10.1016/j.neuroimage.2015.08.032_bb0135
  article-title: Architecting the finite element method pipeline for the GPU
  publication-title: J. Comput. Appl. Math.
  doi: 10.1016/j.cam.2013.09.001
– volume: 10
  issue: 5
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0195
  article-title: The thickness of the skull in Korean adults
  publication-title: J. Craniofac. Surg.
  doi: 10.1097/00001665-199909000-00004
– volume: 116
  start-page: 456
  year: 2005
  ident: 10.1016/j.neuroimage.2015.08.032_bb0200
  article-title: Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings
  publication-title: Clin. Neurophysiol.
  doi: 10.1016/j.clinph.2004.08.017
– volume: 44
  start-page: 947
  year: 2009
  ident: 10.1016/j.neuroimage.2015.08.032_bb0355
  article-title: A unified Bayesian framework for MEG/EEG source imaging
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2008.02.059
– volume: 49
  start-page: 5011
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0025
  article-title: An advanced boundary element method (BEM) implementation for the forward problem of electromagnetic source imaging
  publication-title: Phys. Med. Biol.
  doi: 10.1088/0031-9155/49/21/012
– start-page: 23
  year: 2010
  ident: 10.1016/j.neuroimage.2015.08.032_bb0060
  article-title: Effects of the local skull and spongiosum conductivities on realistic head modeling
– volume: 37
  start-page: 731
  year: 2007
  ident: 10.1016/j.neuroimage.2015.08.032_bb0180
  article-title: A novel integrated MEG and EEG analysis method for dipolar sources
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2007.06.002
– volume: 47
  start-page: 1584
  year: 2000
  ident: 10.1016/j.neuroimage.2015.08.032_bb0115
  article-title: Regional head tissue conductivity estimation for improved EEG analysis
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.887939
– year: 2007
  ident: 10.1016/j.neuroimage.2015.08.032_bb0285
  article-title: Modeling and estimation of dependent subspaces
– volume: 295
  start-page: 690
  year: 2002
  ident: 10.1016/j.neuroimage.2015.08.032_bb0230
  article-title: Dynamic brain sources of visual evoked responses
  publication-title: Science
  doi: 10.1126/science.1066168
– volume: 47
  start-page: 717
  year: 1968
  ident: 10.1016/j.neuroimage.2015.08.032_bb0310
  article-title: Current distribution in the brain from the surface electrodes
  publication-title: Anesth. Analg.
  doi: 10.1213/00000539-196811000-00016
– volume: 6
  start-page: 99
  year: 1993
  ident: 10.1016/j.neuroimage.2015.08.032_bb0210
  article-title: Thickness and resistivity variations over the upper surface of the human skull
  publication-title: Brain Topogr.
  doi: 10.1007/BF01191074
– volume: 18
  start-page: 14
  year: 2001
  ident: 10.1016/j.neuroimage.2015.08.032_bb0055
  article-title: Electromagnetic brain mapping
  publication-title: IEEE Signal Process. Mag.
  doi: 10.1109/79.962275
– volume: 47
  start-page: 1487
  year: 2000
  ident: 10.1016/j.neuroimage.2015.08.032_bb0275
  article-title: The conductivity of the human skull: results of in vivo and in vitro measurements
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2000.880100
– volume: 24
  start-page: 91
  year: 2002
  ident: 10.1016/j.neuroimage.2015.08.032_bb0295
  article-title: Functional imaging with low resolution brain electromagnetic tomography (LORETA): a review
  publication-title: Methods Find. Exp. Clin. Pharmacol.
– volume: 190
  start-page: 258
  year: 2010
  ident: 10.1016/j.neuroimage.2015.08.032_bb0005
  article-title: Neuroelectromagnetic forward head modeling toolbox
  publication-title: J. Neurosci. Methods
  doi: 10.1016/j.jneumeth.2010.04.031
– volume: 5
  start-page: 165
  year: 2002
  ident: 10.1016/j.neuroimage.2015.08.032_bb0365
  article-title: A parallel algebraic multigrid solver for finite element method based source localization in the human brain
  publication-title: Comput. Vis. Sci.
  doi: 10.1007/s00791-002-0098-0
– year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0300
  article-title: Neuroelectromagnetic Source Imaging Using Multiscale Geodesic Neural Bases and Sparse Bayesian Learning
– volume: 46
  start-page: 671
  year: 2008
  ident: 10.1016/j.neuroimage.2015.08.032_bb0040
  article-title: Parallel implementation of the accelerated BEM approach for EMSI of the human brain
  publication-title: Med. Biol. Eng. Comput.
  doi: 10.1007/s11517-008-0316-0
– volume: 75
  start-page: 238
  year: 2014
  ident: 10.1016/j.neuroimage.2015.08.032_bb0245
  article-title: Genetic overlap between evoked frontocentral theta-band phase variability, reaction time variability, and attention-deficit/hyperactivity disorder symptoms in a twin study
  publication-title: Biol. Psychiatry
  doi: 10.1016/j.biopsych.2013.07.020
– volume: 8
  start-page: 204
  issue: 5
  year: 2004
  ident: 10.1016/j.neuroimage.2015.08.032_bb0235
  article-title: Mining event-related brain dynamics
  publication-title: Trends Cogn. Sci.
  doi: 10.1016/j.tics.2004.03.008
– year: 2006
  ident: 10.1016/j.neuroimage.2015.08.032_bb0280
  article-title: Super-gaussian mixture source model for ICA
– volume: 32
  start-page: 1383
  year: 2011
  ident: 10.1016/j.neuroimage.2015.08.032_bb0095
  article-title: Modeling of the human skull in EEG source analysis
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.21114
– volume: 26
  start-page: 273
  year: 2005
  ident: 10.1016/j.neuroimage.2015.08.032_bb0110
  article-title: Segmentation of skull and scalp in 3-d human MRI using mathematical morphology
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.20159
– volume: 46
  start-page: 1281
  year: 1999
  ident: 10.1016/j.neuroimage.2015.08.032_bb0190
  article-title: The need for correct realistic geometry in the inverse EEG problem
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.797987
– volume: 62
  start-page: 774
  year: 2012
  ident: 10.1016/j.neuroimage.2015.08.032_bb0120
  article-title: Freesurfer
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2012.01.021
SSID ssj0009148
Score 2.4444904
Snippet Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the...
SourceID pubmedcentral
proquest
pubmed
crossref
elsevier
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 168
SubjectTerms Adult
Algorithms
Cerebral Cortex - physiology
Conductivity
Data Interpretation, Statistical
EEG
Electric Conductivity
Electrodes
Electroencephalography - methods
FEM
Finite Element Method
Four-layer realistic head modeling
Humans
Image Processing, Computer-Assisted
Localization
Male
Models, Neurological
Scalp - physiology
Sensitivity of EEG to skull conductivity
Skull - physiology
Skull conductivity estimation
Source localization
Tomography
Young Adult
SummonAdditionalLinks – databaseName: Health & Medical Collection
  dbid: 7X7
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8QwEA4-QLyIb9cXEbwWt03SbvAgIquLoBcV9haSpsEVra_1_zuTpF0fKHsrNAPtZDL5knz5hpBDiJvMsW6ZZJpXCSp6QR5EilWZM2PLsjDOs3yv88EdvxyKYdxwe4-0yiYn-kRtn0vcIz9KCyYwPrk8eXlNsGoUnq7GEhqzZN5Ll0E8F8NiIrqb8nAVTsAXQIPI5An8Lq8XOXqCUYsEL-GFPFn21_T0G37-ZFF-mZbOl8lSxJP0NATACpmp6lWycBVPzNfI4GaEnEFdV7DEp5B5LR17X1NYCKPWqy8eQXVtab9_QcNePsUZDnuMogZHuNy4Tu7O-7dngyRWT0hKWCSME-acS7XLSmMBU2jJ4Ula7bQTrmt1muVCGi24rZzu9biGvpQ9ziDppFYagC0bZK5-rqstQh0somzqTGqZ5NoKmTvjuLOFySXPueyQonGaKqO0OFa4eFQNh-xBTdyt0N0Ki1-yrEPS1vIlyGtMYSObflHN9VFIeArmgClsj1vbCDECdJjSercJAxWH-ruaBGaHHLSvYZDiyUvoXd9GAhjM2X9tBCp9AGDqkM0QWa1LspxhpTABjv4Wc20DFAn__qYe3XuxcKx1X_S62_9_-g5ZhP-Me0u7ZG789lHtAdoam30_pD4BCJwtEg
  priority: 102
  providerName: ProQuest
Title Simultaneous head tissue conductivity and EEG source location estimation
URI https://www.clinicalkey.com/#!/content/1-s2.0-S1053811915007442
https://dx.doi.org/10.1016/j.neuroimage.2015.08.032
https://www.ncbi.nlm.nih.gov/pubmed/26302675
https://www.proquest.com/docview/1735307049
https://www.proquest.com/docview/1735906363
https://www.proquest.com/docview/1751215266
https://pubmed.ncbi.nlm.nih.gov/PMC4651780
Volume 124
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bb9MwFLZGJyFepnHvGJWReA2t40tq8bRVHeVWTRuT-mbZcawFQTZB98pv55zYySgIVImXXH2k5Phck-PvEPIS5CYPfFJmuRVVhoheYAexxKpU3PmyLFxoq3yXanEh3q3kaofMurUwWFaZbH-06a21TlfGiZvj67oen0NkAO4G8g2JflCAHd7NuVZyQHaP3r5fLG-xd5mIK-IkPAgQpIKeWObVwkbWX0F5sc5LtniePP-bl_ozCv29mPIX73SyT_ZSWEmP4pPfJztV84Dc_Zh-nD8ki_MaSwdtU0GmT8EAe7puWU4hH0bI17aHBLWNp_P5Gxo_6VN0dDhxFKE44hrHR-TiZP5ptshSE4WshFxhnfEQArMhL52H0MJqAUfa22CDDBNvWa6kdlYKXwU7nQoLU6qngoPtYV47iF4ek0Fz1VRPCQ2QS3kWHPNcC-ulVsEFEXzhlBZK6CEpOqaZMiGMY6OLL6YrJftsbtltkN0Ge2DyfEhYT3kdUTa2oNHdvJhuFSnYPQOuYAva1z3thrRtSX3YiYFJGv_dsIJLtJ_Ihhf9bdBV_AETZ7cdoyEmVPxfYyQCfkDcNCRPomT1LMkVx4ZhEhi9IXP9AMQK37zT1JctZji2vC-mk4P_evFn5B6cpS9Qh2Sw_nZTPYeYbO1G5M6rHwy2xaoYgf7Nzj6cjpIewv54vjw9-wkZfj7h
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwED9NnQS8THxTGMNI8BhRxx-phRAC1tGxrUKwSXszThxrRZAO2gnxT_E3chcnKQMx9WVvkeKT4vP5d-f47ncAT9Bu0iAGRZI6WSbE6IU4SClWhRa5L4osD3WW70SPj-S7Y3W8Br_aWhhKq2wxsQZqPyvoH_kznglF9inNy9NvCXWNotvVtoVGNIu98ucPPLLNX-xu4_o-TdOd0eGbcdJ0FUgKDJ4XiQghcBfSIvfoa52R-GS8Cy6oMPCOp1qZ3Cnpy-CGQ-lwjmYoBW5G7k1uiHwJIX9dUkVrD9ZfjybvPyxpfrmMxXcK58y5aXKHYkZZzVA5_Yo4QSllqqYOFen_HOK_Ae_feZt_OMKd67DRRLDsVTS5G7BWVjfhykFzR38Lxh-nlKXoqnJ2NmeI9Z4t6tVlePQmdtm6XQVzlWej0VsWbw8Y-VSyEUasH7Gc8jYcXYpm70CvmlXlPWABj22eh5x7YaTzyuiQBxl8lmsjtTR9yFql2aIhM6eeGl9sm7X22S7VbUndltptirQPvJM8jYQeK8iYdl1sW7CKEGvR66wg-7yTbYKaGKysKL3ZmoFtwGVul1uhD4-71wgLdNcTV7ceYzD81OKiMYq4RTBE68PdaFmdSlItqDeZQkWfs7luANGSn39TTU9qenKpFc-Gg_sXf_ojuDo-PNi3-7uTvQdwDefc_NnahN7i-1n5EGO9Rb7VbDAGny57T_8Gh6RuAQ
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1baxQxFA6lQvFFvLtaNYI-Dt1cZ4OIiN11a7UIWti3mEwmuKKz1d0i_jV_neckM7NWsexL3wYmByYn55bJl-8Q8hjshkcxrAruZF0goxfEQYRYVVr4UFWljwnle6Snx_L1TM22yK_uLgzCKruYmAJ1WFT4j3yPlUKhfUqzF1tYxLv9yfOTbwV2kMKT1q6dRjaRw_rnD9i-LZ8d7MNaP-F8Mv7wclq0HQaKCgrpVSFijMxFXvkAedcZCU8muOiiisPgGNfKeKdkqKMbjaSD-ZqRFOCYLBhvkIgJwv8l-LQhbvzKWbkm_GUyX8NTMHvGTIsiytiyxFU5_woRA8FlKpGICv6_1Phv6fs3gvOPlDi5Sq60tSx9kY3vGtmqm-tk5217Wn-DTN_PEa_omnpxuqQQ9QNdpXWmsAlHntnUuIK6JtDx-BXN5wgUsytaC0X-j3yx8iY5vhC93iLbzaKp7xAaYQMXWPQsCCNdUEZHH2UMpddGamkGpOyUZquW1hy7a3yxHX7ts12r26K6LTbeFHxAWC95kqk9NpAx3brY7uoqBFsL-WcD2ae9bFve5LJlQ-ndzgxsG2aWdu0UA_Kofw0BAk998uqmMQYKUS3OG6OQZQSKtQG5nS2rVwnXAruUKVD0GZvrByBB-dk3zfxTIiqXWrFyNLx7_qc_JDvgyfbNwdHhPXIZptz-4tol26vvp_V9KPpW_kHyLko-XrQ7_wb6j3DI
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Simultaneous+head+tissue+conductivity+and+EEG+source+location+estimation&rft.jtitle=NeuroImage+%28Orlando%2C+Fla.%29&rft.au=Akalin+Acar%2C+Zeynep&rft.au=Acar%2C+Can+E&rft.au=Makeig%2C+Scott&rft.date=2016-01-01&rft.issn=1095-9572&rft.eissn=1095-9572&rft.volume=124&rft.issue=Pt+A&rft.spage=168&rft_id=info:doi/10.1016%2Fj.neuroimage.2015.08.032&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-8119&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-8119&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-8119&client=summon