Electrical Source Imaging in Freely Moving Rats: Evaluation of a 12-Electrode Cortical Electroencephalography System

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dc.contributor.authorJiříček, Stanislavcs
dc.contributor.authorKoudelka, Vlastimilcs
dc.contributor.authorLáčík, Jaroslavcs
dc.contributor.authorVejmola, Čestmírcs
dc.contributor.authorKuřátko, Davidcs
dc.contributor.authorWójcik, Daniel Krzysztofcs
dc.contributor.authorRaida, Zbyněkcs
dc.contributor.authorHlinka, Jaroslavcs
dc.contributor.authorPáleníček, Tomášcs
dc.coverage.issue1cs
dc.coverage.volume14cs
dc.date.accessioned2021-05-06T14:55:31Z
dc.date.available2021-05-06T14:55:31Z
dc.date.issued2021-01-25cs
dc.description.abstractThis work presents and evaluates a 12-electrode intracranial electroencephalography system developed at the National Institute of Mental Health (Klecany, Czech Republic) in terms of an electrical source imaging (ESI) technique in rats. The electrode system was originally designed for translational research purposes. This study demonstrates that it is also possible to use this well-established system for ESI, and estimates its precision, accuracy, and limitations. Furthermore, this paper sets a methodological basis for future implants. Source localization quality is evaluated using three approaches based on surrogate data, physical phantom measurements, and in vivo experiments. The forward model for source localization is obtained from the FieldTrip-SimBio pipeline using the finite-element method. Rat brain tissue extracted from a magnetic resonance imaging template is approximated by a single-compartment homogeneous tetrahedral head model. Four inverse solvers were tested: standardized low-resolution brain electromagnetic tomography, exact low-resolution brain electromagnetic tomography (eLORETA), linear constrained minimum variance (LCMV), and dynamic imaging of coherent sources. Based on surrogate data, this paper evaluates the accuracy and precision of all solvers within the brain volume using error distance and reliability maps. The mean error distance over the whole brain was found to be the lowest in the eLORETA solution through signal to noise ratios (SNRs) (0.2 mm for 25 dB SNR). The LCMV outperformed eLORETA under higher SNR conditions, and exhibiting higher spatial precision. Both of these inverse solvers provided accurate results in a phantom experiment (1.6 mm mean error distance across shallow and 2.6 mm across subcortical testing dipoles). Utilizing the developed technique in freely moving rats, an auditory steady-state response experiment provided results in line with previously reported findings. The obtained results support the idea of utilizing a 12-electrode system for ESI and using it as a solid basis for the development of future ESI dedicated implants.en
dc.formattextcs
dc.format.extent1-22cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationFrontiers in Neuroinformatics. 2021, vol. 14, issue 1, p. 1-22.en
dc.identifier.doi10.3389/fninf.2020.589228cs
dc.identifier.issn1662-5196cs
dc.identifier.other168939cs
dc.identifier.urihttp://hdl.handle.net/11012/196713
dc.language.isoencs
dc.publisherFrontierscs
dc.relation.ispartofFrontiers in Neuroinformaticscs
dc.relation.urihttps://www.frontiersin.org/articles/10.3389/fninf.2020.589228/fullcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1662-5196/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectElectroencephalographyen
dc.subjectpreclinical modelsen
dc.subjectelectrical source imagingen
dc.subjecttranslational researchen
dc.subjectauditory steady-state response experimenten
dc.subjectfieldtripen
dc.titleElectrical Source Imaging in Freely Moving Rats: Evaluation of a 12-Electrode Cortical Electroencephalography Systemen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-168939en
sync.item.dbtypeVAVen
sync.item.insts2021.06.25 12:52:51en
sync.item.modts2021.06.25 12:14:10en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav radioelektronikycs
thesis.grantorVysoké učení technické v Brně. . Národní ústav duševního zdravícs
thesis.grantorVysoké učení technické v Brně. . Fakulta elektrotechnickács
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