Towards a mesoscale physical modeling framework for stereotactic-EEG recordings

Objective. Stereotactic-EEG (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMM). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combini...

Full description

Saved in:
Bibliographic Details
Published inbioRxiv
Main Authors Mercadal, Borja, Lopez-Sola, Edmundo, Galan-Gadea, Adrià, Mariam Al Harrach, Sanchez, Roser, Salvador, Ricardo, Bartolomei, Fabrice, Wendling, Fabrice, Ruffini, Giulio
Format Paper
LanguageEnglish
Published Cold Spring Harbor Cold Spring Harbor Laboratory Press 05.11.2022
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Objective. Stereotactic-EEG (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMM). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements. Approach. We provide a framework combining the multi- compartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept. Main results. CSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of neural mass models is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer). Significance. Our results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.Competing Interest StatementBM, ELS, ADGG, RST, RS and GR work for Neuroelectrics, a company dedicated to the development of model-driven brain stimulation solutions. GR is a co-founder of Neuroelectrics.Footnotes* minor fixes
AbstractList Objective. Stereotactic-EEG (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMM). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements. Approach. We provide a framework combining the multi- compartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept. Main results. CSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of neural mass models is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer). Significance. Our results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.Competing Interest StatementBM, ELS, ADGG, RST, RS and GR work for Neuroelectrics, a company dedicated to the development of model-driven brain stimulation solutions. GR is a co-founder of Neuroelectrics.Footnotes* minor fixes
Author Wendling, Fabrice
Mercadal, Borja
Bartolomei, Fabrice
Mariam Al Harrach
Ruffini, Giulio
Lopez-Sola, Edmundo
Salvador, Ricardo
Galan-Gadea, Adrià
Sanchez, Roser
Author_xml – sequence: 1
  givenname: Borja
  surname: Mercadal
  fullname: Mercadal, Borja
– sequence: 2
  givenname: Edmundo
  surname: Lopez-Sola
  fullname: Lopez-Sola, Edmundo
– sequence: 3
  givenname: Adrià
  surname: Galan-Gadea
  fullname: Galan-Gadea, Adrià
– sequence: 4
  fullname: Mariam Al Harrach
– sequence: 5
  givenname: Roser
  surname: Sanchez
  fullname: Sanchez, Roser
– sequence: 6
  givenname: Ricardo
  surname: Salvador
  fullname: Salvador, Ricardo
– sequence: 7
  givenname: Fabrice
  surname: Bartolomei
  fullname: Bartolomei, Fabrice
– sequence: 8
  givenname: Fabrice
  surname: Wendling
  fullname: Wendling, Fabrice
– sequence: 9
  givenname: Giulio
  surname: Ruffini
  fullname: Ruffini, Giulio
BookMark eNotjrFOwzAURT3AAIUPYLPEnOD3nDj2iKpQkCp1aefKeXmBQBIXO1XF3xMJpnuHo3vurbiawsRCPIDKARQ8oULMVZUrkxfOWjQ3YrcPFx_bJL0cOYVEfmB5-vhJ_dLkGFoe-ulddtGPfAnxS3YhyjRz5DB7mnvK6nojI1OI7QKmO3Hd-SHx_X-uxOGl3q9fs-1u87Z-3mYE4EymnTPQIHSm7ajz0FgsnC-ZSquoQHYlsa2g1MVy01LVELYEjbOMoCqt9Uo8_u2eYvg-c5qPn-Ecp0V5RGNNga5E1L9ns0vf
CitedBy_id crossref_primary_10_1088_1741_2552_ac8ba8
crossref_primary_10_1088_1741_2552_ac8fb4
crossref_primary_10_1016_j_neuroimage_2023_119938
ContentType Paper
Copyright 2022. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: 2022. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID 8FE
8FH
AAFGM
AAMXL
ABOIG
ABUWG
ADZZV
AFKRA
AFLLJ
AFOLM
AGAJT
AQTIP
AZQEC
BBNVY
BENPR
BHPHI
CCPQU
DWQXO
GNUQQ
HCIFZ
LK8
M7P
PIMPY
PQCXX
PQEST
PQQKQ
PQUKI
PRINS
DOI 10.1101/2022.07.06.498826
DatabaseName ProQuest SciTech Collection
ProQuest Natural Science Collection
ProQuest Central Korea - hybrid linking
Natural Science Collection - hybrid linking
Biological Science Collection - hybrid linking
ProQuest Central (Alumni)
ProQuest Central (Alumni) - hybrid linking
ProQuest Central UK/Ireland
SciTech Premium Collection - hybrid linking
ProQuest Central Student - hybrid linking
ProQuest Central Essentials - hybrid linking
ProQuest Women's & Gender Studies - hybrid linking
ProQuest Central Essentials
Biological Science Collection
AUTh Library subscriptions: ProQuest Central
ProQuest Natural Science Collection
ProQuest One Community College
ProQuest Central
ProQuest Central Student
SciTech Premium Collection (Proquest) (PQ_SDU_P3)
Biological Sciences
Biological Science Database
Publicly Available Content Database
ProQuest Central - hybrid linking
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
DatabaseTitle Publicly Available Content Database
ProQuest Central Student
ProQuest Biological Science Collection
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Natural Science Collection
Biological Science Database
ProQuest SciTech Collection
ProQuest Central China
ProQuest Central
ProQuest One Academic UKI Edition
Natural Science Collection
ProQuest Central Korea
Biological Science Collection
ProQuest One Academic
DatabaseTitleList Publicly Available Content Database
Database_xml – sequence: 1
  dbid: BENPR
  name: AUTh Library subscriptions: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Genre Working Paper/Pre-Print
GroupedDBID 8FE
8FH
ABUWG
AFKRA
AZQEC
BBNVY
BENPR
BHPHI
CCPQU
DWQXO
GNUQQ
HCIFZ
LK8
M7P
PIMPY
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c1196-39961b21f6dfcfa1b8249a5ec580c42e95ce8715348828c7bc2dc1b98e2107333
IEDL.DBID BENPR
IngestDate Thu Oct 10 16:51:08 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1196-39961b21f6dfcfa1b8249a5ec580c42e95ce8715348828c7bc2dc1b98e2107333
OpenAccessLink https://www.proquest.com/docview/2686429522?pq-origsite=%requestingapplication%
PQID 2686429522
PQPubID 2050091
ParticipantIDs proquest_journals_2686429522
PublicationCentury 2000
PublicationDate 20221105
PublicationDateYYYYMMDD 2022-11-05
PublicationDate_xml – month: 11
  year: 2022
  text: 20221105
  day: 05
PublicationDecade 2020
PublicationPlace Cold Spring Harbor
PublicationPlace_xml – name: Cold Spring Harbor
PublicationTitle bioRxiv
PublicationYear 2022
Publisher Cold Spring Harbor Laboratory Press
Publisher_xml – name: Cold Spring Harbor Laboratory Press
Score 1.7190133
Snippet Objective. Stereotactic-EEG (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMM). However, the relationship...
SourceID proquest
SourceType Aggregation Database
SubjectTerms EEG
Mathematical models
Pyramidal cells
Title Towards a mesoscale physical modeling framework for stereotactic-EEG recordings
URI https://www.proquest.com/docview/2686429522
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV07T8MwELagXdhAgHgU5IHVkFzsxJ6QQCkVEqVCrdStii_2RlNI-f-cjSsGJGZP_nSP796M3QBmPssQBXrthVQgSaUMChIeBYggVVz2_DItJwv5vFTLlHDrU1vlziZGQ912GHLkd1BqosqG6ML95kOEq1GhuppOaOyzIeQylGmHD_V09pbKlyRuIbiHuJ6zvJWG6GT5x-hGTzI-ZMNZs3GfR2zPrY_Z6zx2rfa84e-u73oCzPFNgo7HKzXkWrjfdVBxopg8rDZw3TZON4m6fuI_iZaQ8j5hi3E9f5yIdOJAYE6yL4gelLmF3JetR9_kVlM41CiHSmcowRmFjkIaVZCegcbKIrSYW6MdhWpVURSnbLDu1u6M8dYarBqJbSFbWRlvvcVMe_CNIbUEPGej3b9XSU771S-qF_8_X7KDgGScwlMjNth-frkrcsdbe50w_wZqFY0j
link.rule.ids 786,790,21416,27956,33777,43838
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV07T8MwELagHWADAeJRwAOrIXHsxJ6QQCkF2lKhVupWxRd7oylN-f-cjSsGJGZP_nSP796E3HBIXJIAMHDKMSG5QJXSwFB4JAfgQoZlz6NxPpiJl7mcx4RbG9sqtzYxGOq6AZ8jv-O5QqqskS7crz6Zvxrlq6vxhMYu6fqVm6pDug_lePIey5cobj6452E9Z34rNNLJ_I_RDZ6kf0C6k2pl14dkxy6PyNs0dK22tKIftm1aBMzSVYSOhis16Fqo23ZQUaSY1K82sM0mTDexsnyiP4kWn_I-JrN-OX0csHjigEGKss-QHuSp4anLaweuSo3CcKiSFqRKQHCrJVgMaWSGesYVFAZ4DanRymKoVmRZdkI6y2ZpTwmtjYaiElBnohaFdsYZSJTjrtKolhzOSG_770WU03bxi-r5_8_XZG8wHQ0Xw-fx6wXZ96iGiTzZI53N-steomvemKuI_zc6FJAZ
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=Towards+a+mesoscale+physical+modeling+framework+for+stereotactic-EEG+recordings&rft.jtitle=bioRxiv&rft.au=Mercadal%2C+Borja&rft.au=Lopez-Sola%2C+Edmundo&rft.au=Galan-Gadea%2C+Adri%C3%A0&rft.au=Mariam+Al+Harrach&rft.date=2022-11-05&rft.pub=Cold+Spring+Harbor+Laboratory+Press&rft_id=info:doi/10.1101%2F2022.07.06.498826