Studying memory processes at different levels with simultaneous depth and surface EEG recordings.
EEG
multivariate pattern analysis
recognition memory
simultaneous recordings
stereo-EEG
Journal
Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954
Informations de publication
Date de publication:
2023
2023
Historique:
received:
30
01
2023
accepted:
06
03
2023
medline:
21
4
2023
pubmed:
21
4
2023
entrez:
21
04
2023
Statut:
epublish
Résumé
Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.
Identifiants
pubmed: 37082152
doi: 10.3389/fnhum.2023.1154038
pmc: PMC10110965
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1154038Informations de copyright
Copyright © 2023 Barborica, Mindruta, López-Madrona, Alario, Trébuchon, Donos, Oane, Pistol, Mihai and Bénar.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Références
J Cogn Neurosci. 2017 Apr;29(4):677-697
pubmed: 27779910
Neuroimage. 2022 Feb 1;246:118789
pubmed: 34890794
Proc Natl Acad Sci U S A. 2015 Nov 17;112(46):14378-83
pubmed: 26578784
Neuroimage. 2014 Feb 1;86:446-60
pubmed: 24161808
J Neurosci. 2021 Apr 21;41(16):3665-3678
pubmed: 33727333
Nature. 2009 May 28;459(7246):534-9
pubmed: 19489117
Neuron. 2006 Mar 16;49(6):805-13
pubmed: 16543129
IEEE Trans Med Imaging. 2009 Apr;28(4):508-22
pubmed: 19273000
Neuroimage. 2014 Feb 15;87:96-110
pubmed: 24239590
Hum Brain Mapp. 2022 Oct 15;43(15):4733-4749
pubmed: 35766240
Psychophysiology. 2019 Jun;56(6):e13335
pubmed: 30657176
Neurophysiol Clin. 2018 Feb;48(1):5-13
pubmed: 29277357
J Neurosci Methods. 2015 Mar 15;242:118-26
pubmed: 25614386
Front Neurosci. 2018 Jul 03;12:368
pubmed: 30018529
Neuroimage Clin. 2021;32:102838
pubmed: 34624636
Stereotact Funct Neurosurg. 2021;99(1):17-24
pubmed: 33227801
J Neurophysiol. 2003 Aug;90(2):1314-23
pubmed: 12904510
J Neuroeng Rehabil. 2008 Nov 07;5:25
pubmed: 18990257
Front Neuroinform. 2014 Feb 21;8:14
pubmed: 24600388
IEEE Trans Biomed Eng. 1997 Sep;44(9):867-80
pubmed: 9282479
Clin Neurophysiol. 2007 Jan;118(1):69-79
pubmed: 17126071
Neuropsychologia. 2016 Dec;93(Pt A):128-141
pubmed: 27693702
Neuroimage. 2018 Oct 1;179:79-91
pubmed: 29902585
Nat Commun. 2019 Feb 27;10(1):971
pubmed: 30814498
Nat Commun. 2014 Apr 28;5:3675
pubmed: 24770473
Acta Neurol Scand Suppl. 1994;152:56-67, discussion 68-9
pubmed: 8209659
World Neurosurg. 2018 Jan;109:82-88
pubmed: 28951181
Brain Topogr. 2015 Jan;28(1):5-20
pubmed: 25432598
Biomed Eng Online. 2006 Feb 08;5:10
pubmed: 16466570
Epilepsia. 2016 Nov;57(11):1735-1747
pubmed: 27677490
Neuron. 2009 Apr 30;62(2):281-90
pubmed: 19409272
Elife. 2020 Jul 20;9:
pubmed: 32687054
J Neurosurg. 2018 Nov 1;129(5):1173-1181
pubmed: 29243976
PLoS Comput Biol. 2015 Apr 08;11(4):e1004066
pubmed: 25853490
Dev Cogn Neurosci. 2022 Apr;54:101094
pubmed: 35248819
Neuroimage. 2016 May 15;132:59-70
pubmed: 26899210
Science. 2001 Sep 28;293(5539):2425-30
pubmed: 11577229
Front Neurosci. 2022 Oct 18;16:983602
pubmed: 36330341
Science. 2021 Apr 16;372(6539):
pubmed: 33859006
Cereb Cortex. 2020 May 14;30(5):2961-2971
pubmed: 31821411
J Neurosci Methods. 2007 Aug 15;164(1):177-90
pubmed: 17517438
PLoS Comput Biol. 2022 Jan 28;18(1):e1009827
pubmed: 35089915
Neuroimage. 2005 Nov 1;28(2):507-19
pubmed: 16139528
Sci Data. 2020 Apr 28;7(1):127
pubmed: 32345974
Seizure. 2019 Jan;64:8-15
pubmed: 30502684
Epilepsia. 2005 May;46(5):669-76
pubmed: 15857432
Front Neurosci. 2022 Sep 26;16:946240
pubmed: 36225734
Hum Brain Mapp. 2009 Jun;30(6):1857-65
pubmed: 19235884
Comput Math Methods Med. 2020 Apr 3;2020:5076865
pubmed: 32328152
Q J Exp Psychol (Hove). 2018 Apr;71(4):808-816
pubmed: 28326995
Neuroimage. 2012 Aug 15;62(2):774-81
pubmed: 22248573
Neuron. 2009 Oct 29;64(2):267-80
pubmed: 19874793
Front Neurosci. 2013 Dec 26;7:267
pubmed: 24431986
J Neurosci Methods. 2004 Mar 15;134(1):9-21
pubmed: 15102499