nach oben

Erschienen in:

30.03.2016 | Original Paper

Validating Non-invasive EEG Source Imaging Using Optimal Electrode Configurations on a Representative Rat Head Model

verfasst von: Pedro A. Valdés-Hernández, Jihye Bae, Yinchen Song, Akira Sumiyoshi, Eduardo Aubert-Vázquez, Jorge J. Riera

Erschienen in: Brain Topography | Ausgabe 4/2019

Einloggen, um Zugang zu erhalten

Abstract

The curtain of technical limitations impeding rat multichannel non-invasive electroencephalography (EEG) has risen. Given the importance of this preclinical model, development and validation of EEG source imaging (ESI) is essential. We investigate the validity of well-known human ESI methodologies in rats which individual tissue geometries have been approximated by those extracted from an MRI template, leading also to imprecision in electrode localizations. With the half and fifth sensitivity volumes we determine both the theoretical minimum electrode separation for non-redundant scalp EEG measurements and the electrode sensitivity resolution, which vary over the scalp because of the head geometry. According to our results, electrodes should be at least ~3 to 3.5 mm apart for an optimal configuration. The sensitivity resolution is generally worse for electrodes at the boundaries of the scalp measured region, though, by analogy with human montages, concentrates the sensitivity enough to localize sources. Cramér–Rao lower bounds of source localization errors indicate it is theoretically possible to achieve ESI accuracy at the level of anatomical structures, such as the stimulus-specific somatosensory areas, using the template. More validation for this approximation is provided through the comparison between the template and the individual lead field matrices, for several rats. Finally, using well-accepted inverse methods, we demonstrate that somatosensory ESI is not only expected but also allows exploring unknown phenomena related to global sensory integration. Inheriting the advantages and pitfalls of human ESI, rat ESI will boost the understanding of brain pathophysiological mechanisms and the evaluation of ESI methodologies, new pharmacological treatments and ESI-based biomarkers.

Nur mit Berechtigung zugänglich

See notation in Appendix 1.

online at http://www.fil.ion.ucl.ac.uk/spm/software/spm8.

See (Valdés-Hernández et al. 2011) for details of the procedure with rats and our Template Set.

online at http://surfer.nmr.mgh.harvard.edu.

Note that \(\nabla {\mathbf{k}} = 0\). Thus the “volumetric LF flux density” is zero, i.e. \(1/G\mathop \smallint \limits_{G} {\mathbf{k}} \cdot d{\mathbf{G}} = 0\) for an arbitrarily small enough volume \(G\). This means that lead field lines do not diverge to form isotropic profiles.

online at http://www.fieldtriptoolbox.org/.

online at http://www.fil.ion.ucl.ac.uk/spm/software/spm8.

To avoid confusion: the Agm is considered by some authors as part of the primary motor cortex and M1 is called the Agranular Lateral Motor cortex (Agl) (Brecht et al. 2004). The whisker somatosensory motor region is suggested to be either at the Agm (Brecht et al. 2004) or in the boundary between and Agm and Agl (Smith and Alloway 2013).

Matrix \({\mathbf{A}}\) “no lower” than \({\mathbf{B}}\) means that \({\mathbf{A}} - {\mathbf{B}}\) is a semi-positive matrix.

Aghajani H, Zahedi E, Jalili M, Keikhosravi A, Vahdat BV (2013) Diagnosis of early Alzheimer’s disease based on EEG source localization and a standardized realistic head model. IEEE J Biomed Health Inform 17:1039–1045. doi:10.1109/JBHI.2013.2253326 CrossRefPubMed

Ashburner J, Friston KJ (2000) Voxel-based morphometry–the methods. Neuroimage 11:805–821. doi:10.1006/nimg.2000.0582 CrossRefPubMed

Ashburner J, Friston KJ (2005) Unified segmentation. Neuroimage 26:839–851. doi:10.1016/j.neuroimage.2005.02.018 CrossRefPubMed

Bae J, Deshmukh A, Song Y, Riera J (2015) Brain source imaging in preclinical rat models of focal epilepsy using high-resolution EEG recordings. J Vis Exp 100:e52700. doi:10.3791/52700 CrossRef

Beltrachini L, von Ellenrieder N, Muravchik CH (2011) General bounds for electrode mislocation on the EEG inverse problem. Comput Methods Programs Biomed 103:1–9. doi:10.1016/j.cmpb.2010.05.008 CrossRefPubMed

Bharadwaj S, Gofton TE (2015) EEG as a surrogate to brain imaging for diagnosing stroke in morbidly obese patients. J Neurosurg Anesthesiol 27:77–78. doi:10.1097/ANA.0000000000000074 CrossRefPubMed

Brecht M, Krauss A, Muhammad S, Sinai-Esfahani L, Bellanca S, Margrie TW (2004) Organization of rat vibrissa motor cortex and adjacent areas according to cytoarchitectonics, microstimulation, and intracellular stimulation of identified cells. J. Comp Neurol 479:360–373. doi:10.1002/cne.20306 CrossRefPubMed

Chapin JK, Sadeq M, Guise JL (1987) Corticocortical connections within the primary somatosensory cortex of the rat. J Comp Neurol 263:326–346. doi:10.1002/cne.902630303 CrossRefPubMed

Chen Y, Wiesel A, Hero AO (2011) Robust shrinkage estimation of high-dimensional covariance matrices. IEEE Trans Signal Process 59:4097–4107. doi:10.1109/TSP.2011.2138698 CrossRef

Choi JH, Koch KP, Poppendieck W, Lee M, Shin H-S (2010) High resolution electroencephalography in freely moving mice. J Neurophysiol 104:1825–1834. doi:10.1152/jn.00188.2010 CrossRefPubMed

Coben R, Mohammad-Rezazadeh I, Cannon RL (2014) Using quantitative and analytic EEG methods in the understanding of connectivity in autism spectrum disorders: a theory of mixed over- and under-connectivity. Front Hum Neurosci 8:45. doi:10.3389/fnhum.2014.00045 CrossRefPubMedPubMedCentral

Darvas F, Ermer JJ, Mosher JC, Leahy RM (2006) Generic head models for atlas-based EEG source analysis. Hum Brain Mapp 27:129–143. doi:10.1002/hbm.20171 CrossRefPubMed

Do Carmo S, Cuello A (2013) Modeling Alzheimer’s disease in transgenic rats. Mol Neurodegener 8:37. doi:10.1186/1750-1326-8-37 CrossRefPubMedPubMedCentral

Ferezou I, Haiss F, Gentet LJ, Aronoff R, Weber B, Petersen CCH (2007) Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice. Neuron 56:907–923. doi:10.1016/j.neuron.2007.10.007 CrossRefPubMed

Ferree TC, Clay MT, Tucker DM (2001) The spatial resolution of scalp EEG. Neurocomputing 38–40:1209–1216. doi:10.1016/S0925-2312(01)00568-9 CrossRef

Franceschini MA, Nissilä I, Wu W, Diamond SG, Bonmassar G, Boas DA (2008) Coupling between somatosensory evoked potentials and hemodynamic response in the rat. Neuroimage 41:189–203. doi:10.1016/j.neuroimage.2008.02.061 CrossRefPubMedPubMedCentral

Franceschini MA, Radhakrishnan H, Thakur K, Wu W, Ruvinskaya S, Carp S, Boas DA (2010) The effect of different anesthetics on neurovascular coupling. Neuroimage 51:1367–1377. doi:10.1016/j.neuroimage.2010.03.060 CrossRefPubMedPubMedCentral

Gevins A, Brickett P, Costales B, Le J, Reutter B (1990) Beyond topographic mapping: towards functional-anatomical imaging with 124-channel EEGs and 3-D MRIs. Brain Topogr. 3:53–64. doi:10.1007/BF01128862 CrossRefPubMed

Ghosh A, Sydekum E, Haiss F, Peduzzi S, Zorner B, Schneider R, Baltes C, Rudin M, Weber B, Schwab ME (2009) Functional and anatomical reorganization of the sensory-motor cortex after incomplete spinal cord injury in adult rats. J Neurosci 29:12210–12219. doi:10.1523/JNEUROSCI.1828-09.2009 CrossRefPubMedPubMedCentral

Gramfort A, Papadopoulo T, Olivi E, Clerc M (2011) Forward field computation with OpenMEEG. Comput Intell Neurosci 2011:1–13. doi:10.1155/2011/923703 CrossRef

Harmony T, Fernández-Bouzas A, Marosi E, Fernández T, Valdés P, Bosch J, Riera J, Bernal J, Rodríguez M, Reyes A (1995) Frequency source analysis in patients with brain lesions. Brain Topogr 8:109–117CrossRefPubMed

Hughes JR, Ph D, John ER (1999) Conventional and quantitative electroencephalography in psychiatry. J Neuropsychiatry Clin Neurosci 11:190–208CrossRefPubMed

Kaiboriboon K, Lüders HO, Hamaneh M, Turnbull J, Lhatoo SD (2012) EEG source imaging in epilepsy—practicalities and pitfalls. Nat Rev Neurol 8:498–507. doi:10.1038/nrneurol.2012.150 CrossRef

Kay SM (1993) Fundamentals of Statistical Signal Processing: Estimation Theory, ser. Signal Processing

Ledoit O, Wolf M (2004) Honey, I shrunk the sample covariance matrix. J Portf Manag 30:110–119. doi:10.3905/jpm.2004.110 CrossRef

Lee M, Kim D, Shin H, Sung H, Choi JH (2011) High-density EEG recordings of the freely moving mice using polyimide-based microelectrode. J Vis Exp. doi:10.3791/2562 CrossRefPubMedPubMedCentral

Lippert MT, Takagaki K, Kayser C, Ohl FW (2013) Asymmetric multisensory interactions of visual and somatosensory responses in a region of the rat parietal cortex. PLoS One. doi:10.1371/journal.pone.0063631 CrossRefPubMedPubMedCentral

Litvak V, Friston K (2008) Electromagnetic source reconstruction for group studies. Neuroimage 42:1490–1498. doi:10.1016/j.neuroimage.2008.06.022 CrossRefPubMedPubMedCentral

Löscher W (2011) Critical review of current animal models of seizures and epilepsy used in the discovery and development of new antiepileptic drugs. Seizure 20:359–368. doi:10.1016/j.seizure.2011.01.003 CrossRefPubMed

MacRae I (2011) Preclinical stroke research—advantages and disadvantages of the most common rodent models of focal ischaemia. Br J Pharmacol 164:1062–1078. doi:10.1111/j.1476-5381.2011.01398.x CrossRefPubMedPubMedCentral

Malmivuo JA, Suihko VE (2004) Effect of skull resistivity on the spatial resolutions of EEG and MEG. IEEE Trans Biomed Eng 51:1276–1280. doi:10.1109/TBME.2004.827255 CrossRefPubMed

Malmivuo J, Suihko V, Eskola H (1997) Sensitivity distributions of EEG and MEG measurements. IEEE Trans Biomed Eng 44:196–208. doi:10.1109/10.554766 CrossRefPubMed

Mattout J, Henson RN, Friston KJ (2007) Canonical source reconstruction for MEG. Comput Intell Neurosci 2007:67613CrossRefPubMedCentral

Matyas F, Sreenivasan V, Marbach F, Wacongne C, Barsy B, Mateo C, Aronoff R, Petersen CCH (2010) Motor control by sensory cortex. Science 330:1240–1243. doi:10.1126/science.1195797 CrossRefPubMed

Mégevand P, Quairiaux C, Lascano AM, Kiss JZ, Michel CM (2008) A mouse model for studying large-scale neuronal networks using EEG mapping techniques. Neuroimage 42:591–602. doi:10.1016/j.neuroimage.2008.05.016 CrossRefPubMed

Meijs JWH, Weier OW, Peters MJ, Van Oosterom A (1989) On the numerical accuracy of the boundary element method. IEEE Trans Biomed Eng 36:1038–1049. doi:10.1109/10.40805 CrossRefPubMed

Morales-Botello ML, Aguilar J, Foffani G (2012) Imaging the spatio-temporal dynamics of supragranular activity in the rat somatosensory cortex in response to stimulation of the paws. PLoS One 7:e40174. doi:10.1371/journal.pone.0040174 CrossRefPubMedPubMedCentral

Mosher JC, Spencer ME, Leahy RM, Lewis PS (1993) Error bounds for EEG and MEG dipole source localization. Electroencephalogr Clin Neurophysiol 86:303–321. doi:10.1016/0013-4694(93)90043-U CrossRefPubMed

Pascual-Marqui RD (2007) Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. Math Phys. doi:10.1186/1744-9081-4-27 CrossRef

Paxinos G, Watson C (2007) The rat brain in stereotaxic coordinates, 6th edn. Elsevier, Amsterdam

Petersen CCH, Grinvald A, Sakmann B (2003) Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions. J Neurosci 23:1298–1309CrossRefPubMed

Plis SM, George JS, Jun SC, Ranken DM, Volegov PL, Schmidt DM (2007) Probabilistic forward model for electroencephalography source analysis. Phys Med Biol 52:5309–5327. doi:10.1088/0031-9155/52/17/014 CrossRefPubMed

Quairiaux C, Mégevand P, Kiss JZ, Michel CM (2011) Functional development of large-scale sensorimotor cortical networks in the brain. J Neurosci 31:9574–9584. doi:10.1523/JNEUROSCI.5995-10.2011 CrossRefPubMedPubMedCentral

Riera J, Ogawa T, Goto T, Sumiyoshi A, Nonaka H, Evans A, Miyakawa H, Kawashima R (2012) Pitfalls in the dipolar model for the neocortical EEG sources. J Neurophysiol 108:956–975. doi:10.1152/jn.00098.2011 CrossRefPubMed

Rodrak S, Wongsawat Y (2013) EEG brain mapping and brain connectivity index for subtypes classification of attention deficit hyperactivity disorder children during the eye-opened period. Proc Annu Int Conf IEEE Eng Med Biol Soc EMBS. doi:10.1109/EMBC.2013.6611268 CrossRef

Rush S, Driscoll DA (1969) EEG electrode sensitivity–an application of reciprocity. IEEE Trans Biomed Eng 16:15–22. doi:10.1109/TBME.1969.4502598 CrossRefPubMed

Shevelkin AV, Ihenatu C, Pletnikov MV (2014) Pre-clinical models of neurodevelopmental disorders: focus on the cerebellum. Rev Neurosci 25:177–194. doi:10.1515/revneuro-2013-0049 CrossRefPubMedPubMedCentral

Smith JB, Alloway KD (2013) Rat whisker motor cortex is subdivided into sensory-input and motor-output areas. Front Neural Circuits 7:4. doi:10.3389/fncir.2013.00004 CrossRefPubMedPubMedCentral

Stoica P, Nehorai A (1989) Music, maximum likelihood, and cramer-rao bound. IEEE Trans Acoust Speech Signal Process 37:720–741CrossRef

Sumiyoshi A, Riera JJ, Ogawa T, Kawashima R (2011) A mini-cap for simultaneous EEG and fMRI recording in rodents. Neuroimage 54:1951–1965. doi:10.1016/j.neuroimage.2010.09.056 CrossRefPubMed

Tsytsarev V, Pope D, Pumbo E, Yablonskii A, Hofmann M (2010) Study of the cortical representation of whisker directional deflection using voltage-sensitive dye optical imaging. Neuroimage 53:233–238. doi:10.1016/j.neuroimage.2010.06.022 CrossRefPubMed

Umeda T, Takashima N, Nakagawa R, Maekawa M, Ikegami S, Yoshikawa T, Kobayashi K, Okanoya K, Inokuchi K, Osumi N (2010) Evaluation of Pax6 mutant rat as a model for autism. PLoS One 5:e15500. doi:10.1371/journal.pone.0015500 CrossRefPubMedPubMedCentral

Valdés-Hernández PA, von Ellenrieder N, Ojeda-Gonzalez A, Kochen S, Alemán-Gómez Y, Muravchik C, Valdés-Sosa PA (2009) Approximate average head models for EEG source imaging. J Neurosci Methods 185:125–132. doi:10.1016/j.jneumeth.2009.09.005 CrossRefPubMed

Valdés-Hernández PA, Sumiyoshi A, Nonaka H, Haga R, Aubert-Vázquez E, Ogawa T, Iturria-Medina Y, Riera JJ, Kawashima R (2011) An in vivo MRI template set for morphometry, tissue segmentation, and fMRI localization in rats. Front Neuroinform 5:1. doi:10.3389/fninf.2011.00026 CrossRef

van de Geer S, Bühlmann P, Ritov Y, Dezeure R (2014) On asymptotically optimal confidence regions and tests for high-dimensional models. Ann Stat 42:1166–1202. doi:10.1214/14-AOS1221 CrossRef

von Ellenrieder N, Muravchik CH, Nehorai A (2006) Effects of geometric head model perturbations on the EEG forward and inverse problems. IEEE Trans Biomed Eng 53:421–429. doi:10.1109/TBME.2005.869769 CrossRef

Vorwerk J, Cho JH, Rampp S, Hamer H, Knösche TR, Wolters CH (2014) A guideline for head volume conductor modeling in EEG and MEG. Neuroimage 100:590–607. doi:10.1016/j.neuroimage.2014.06.040 CrossRef

Wendel K, Narra NG, Hannula M, Kauppinen P, Malmivuo J (2008) The influence of CSF on EEG sensitivity distributions of multilayered head models. IEEE Trans Biomed Eng 55:1454–1456. doi:10.1109/TBME.2007.912427 CrossRefPubMed

Wiesel A, Hero AO (2010) Robust shrinkage estimation of high-dimensional covariance matrices 189–192

Williams KA, Magnuson M, Majeed W, LaConte SM, Peltier SJ, Hu X, Keilholz SD (2010) Comparison of α-chloralose, medetomidine and isoflurane anesthesia for functional connectivity mapping in the rat. Magn Reson Imaging 28:995–1003. doi:10.1016/j.mri.2010.03.007 CrossRefPubMedPubMedCentral

Wolters CH, Grasedyck L, Hackbusch W (2004) Efficient computation of lead field bases and influence matrix for the FEM-based EEG and MEG inverse problem. Inverse Probl 20:1099–1116. doi:10.1088/0266-5611/20/4/007 CrossRef

Zhang C-H, Zhang SS (2014) Confidence intervals for low dimensional parameters in high dimensional linear models. J R Stat Soc Ser B 76:217–242. doi:10.1111/rssb.12026 CrossRef

Titel: Validating Non-invasive EEG Source Imaging Using Optimal Electrode Configurations on a Representative Rat Head Model
verfasst von: Pedro A. Valdés-Hernández
Jihye Bae
Yinchen Song
Akira Sumiyoshi
Eduardo Aubert-Vázquez
Jorge J. Riera
Publikationsdatum: 30.03.2016
Verlag: Springer US
Erschienen in: Brain Topography / Ausgabe 4/2019
Print ISSN: 0896-0267
Elektronische ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-016-0484-4

Leitlinien kompakt für die Neurologie

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Neurologie

Schützt Olivenöl vor dem Tod durch Demenz?

10.05.2024 Morbus Alzheimer Nachrichten

Konsumieren Menschen täglich 7 Gramm Olivenöl, ist ihr Risiko, an einer Demenz zu sterben, um mehr als ein Vierten reduziert – und dies weitgehend unabhängig von ihrer sonstigen Ernährung. Dafür sprechen Auswertungen zweier großer US-Studien.

Bluttest erkennt Parkinson schon zehn Jahre vor der Diagnose

10.05.2024 Parkinson-Krankheit Nachrichten

Ein Bluttest kann abnorm aggregiertes Alpha-Synuclein bei einigen Menschen schon zehn Jahre vor Beginn der motorischen Parkinsonsymptome nachweisen. Mit einem solchen Test lassen sich möglicherweise Prodromalstadien erfassen und die Betroffenen früher behandeln.

Darf man die Behandlung eines Neonazis ablehnen?

08.05.2024 Gesellschaft Nachrichten

In einer Leseranfrage in der Zeitschrift Journal of the American Academy of Dermatology möchte ein anonymer Dermatologe bzw. eine anonyme Dermatologin wissen, ob er oder sie einen Patienten behandeln muss, der eine rassistische Tätowierung trägt.

Wartezeit nicht kürzer, aber Arbeit flexibler

Psychotherapie Medizin aktuell

Fünf Jahren nach der Neugestaltung der Psychotherapie-Richtlinie wurden jetzt die Effekte der vorgenommenen Änderungen ausgewertet. Das Hauptziel der Novellierung war eine kürzere Wartezeit auf Therapieplätze. Dieses Ziel wurde nicht erreicht, es gab jedoch positive Auswirkungen auf andere Bereiche.

Update Neurologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Klimawandel und Gesundheit: Was Sie in der Hausarztpraxis wissen müssen und tun können

Springer Medizin

Abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 4/2019

Bayesian Modelling of Induced Responses and Neuronal Rhythms

Mapping Brain Activity with Electrocorticography: Resolution Properties and Robustness of Inverse Solutions

Critical Comments on EEG Sensor Space Dynamical Connectivity Analysis

ERP Source Analysis Guided by fMRI During Familiar Face Processing

A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies