A biophysically constrained brain connectivity model based on stimulation-evoked potentials.
3D conductivity model
brain connectivity
intracranial recordings
pulse-evoked potentials
single-pulse electrical stimulation
tractography
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
06 Nov 2023
06 Nov 2023
Historique:
pubmed:
21
11
2023
medline:
21
11
2023
entrez:
21
11
2023
Statut:
epublish
Résumé
Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. Using intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Existing methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
Sections du résumé
Background
UNASSIGNED
Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies.
New Method
UNASSIGNED
Using intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features.
Results
UNASSIGNED
The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures.
Comparison with existing methods
UNASSIGNED
Existing methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences.
Conclusions
UNASSIGNED
These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
Identifiants
pubmed: 37986830
doi: 10.1101/2023.11.03.565525
pmc: PMC10659345
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NIMH NIH HHS
ID : R01 MH127006
Pays : United States
Organisme : NIMH NIH HHS
ID : R21 MH127842
Pays : United States
Commentaires et corrections
Type : UpdateIn
Déclaration de conflit d'intérêts
Declaration of Interest. S.A.S. is a consultant for Boston Scientific, Neuropace, Koh Young, Zimmer Biomet, Varian Medical, and Sensoria Therapeutics and co-founder of Motif Neurotech. The authors declare no other competing interests.
Références
Brain Stimul. 2022 May-Jun;15(3):554-565
pubmed: 35292403
ACS Nano. 2022 Nov 22;16(11):18951-18958
pubmed: 36314904
PLoS Biol. 2015 Jul 23;13(7):e1002203
pubmed: 26204162
IEEE Trans Med Imaging. 2001 Jan;20(1):45-57
pubmed: 11293691
Epilepsia. 2018 Jan;59(1):16-26
pubmed: 29143307
Insight J. 2006;2006:209
pubmed: 25364771
Magn Reson Med. 2003 Nov;50(5):1077-88
pubmed: 14587019
J Neurosci Methods. 2017 Apr 1;281:40-48
pubmed: 28192130
Seizure. 2017 Jan;44:27-36
pubmed: 27939100
Clin Neurophysiol. 2019 Oct;130(10):1833-1858
pubmed: 31401492
Brain Topogr. 2019 Sep;32(5):825-858
pubmed: 31054104
Brain Stimul. 2020 Sep - Oct;13(5):1232-1244
pubmed: 32504827
PLoS One. 2013 Nov 15;8(11):e80713
pubmed: 24348913
IEEE Trans Biomed Eng. 2019 Jun;66(6):1695-1704
pubmed: 30369435
Brain Stimul. 2022 Mar-Apr;15(2):491-508
pubmed: 35247646
J Neurosci. 2014 Jul 2;34(27):9152-63
pubmed: 24990935
Proc Natl Acad Sci U S A. 2015 May 26;112(21):E2820-8
pubmed: 25964365
Neuroimage. 2021 Aug 15;237:118094
pubmed: 33940142
Cereb Cortex. 2013 May;23(5):1208-17
pubmed: 22586139
Hum Brain Mapp. 2014 Sep;35(9):4267-81
pubmed: 24706574
Neuroimage. 2010 Oct 15;53(1):1-15
pubmed: 20547229
Physiol Meas. 2009 Mar;30(3):275-89
pubmed: 19202236
Neuroimage Clin. 2017 Jun 15;15:659-672
pubmed: 28664037
Clin Neurophysiol. 2019 Feb;130(2):270-279
pubmed: 30605889
Front Neurosci. 2021 Jul 30;15:694645
pubmed: 34393709
Biol Psychiatry. 2022 Aug 1;92(3):246-251
pubmed: 35063186
Front Hum Neurosci. 2021 Oct 07;15:721206
pubmed: 34690718
Proc Natl Acad Sci U S A. 2019 Oct 29;116(44):22071-22080
pubmed: 31619572
Magn Reson Med. 2012 Dec;68(6):1846-55
pubmed: 22334356
Proc Natl Acad Sci U S A. 2014 Nov 18;111(46):16574-9
pubmed: 25368179
Cortex. 2019 Nov;120:419-442
pubmed: 31442863
Med Image Anal. 2001 Jun;5(2):143-56
pubmed: 11516708
Neuromodulation. 2019 Jun;22(4):403-415
pubmed: 30775834
Phys Med Biol. 1980 Nov;25(6):1149-59
pubmed: 7208627
Neuroimage. 2003 Oct;20(2):870-88
pubmed: 14568458
Nat Neurosci. 2010 Oct;13(10):1283-91
pubmed: 20818384
Neuroimage. 1999 Feb;9(2):179-94
pubmed: 9931268
J Comp Neurol. 2007 Aug 1;503(4):550-9
pubmed: 17534935
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2023 Jun 25;40(3):401-408
pubmed: 37380377
Neuroimage. 2007 Jan 1;34(1):144-55
pubmed: 17070705
Brain Struct Funct. 2022 Apr;227(3):763-778
pubmed: 34791508
Brain Connect. 2011;1(3):169-83
pubmed: 22433046
Cortex. 2015 Jan;62:20-33
pubmed: 25131616
Magn Reson Med. 2011 Aug;66(2):456-66
pubmed: 21773985
Hum Brain Mapp. 2018 Mar;39(3):1449-1466
pubmed: 29266522
IEEE Trans Med Imaging. 2016 Jan;35(1):244-56
pubmed: 26302510
Biomed Phys Eng Express. 2023 Jun 02;9(4):
pubmed: 37160106
Neuromodulation. 2018 Feb;21(2):191-196
pubmed: 28653482
Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Sep;5(9):846-854
pubmed: 32513555
Brain. 2004 Oct;127(Pt 10):2316-30
pubmed: 15269116
Neuroimage. 2016 Jan 15;125:1063-1078
pubmed: 26481672
Neuroimage. 2020 Aug 15;217:116923
pubmed: 32407993
Neuroimage. 2012 Aug 15;62(2):774-81
pubmed: 22248573