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

  • Pedro A. Valdés-Hernández
  • Jihye Bae
  • Yinchen Song
  • Akira Sumiyoshi
  • Eduardo Aubert-Vázquez
  • Jorge J. Riera
Original Paper


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.


Preclinical models EEG source imaging EEG mini-cap Wistar rat FEM Rat MRI template Head model Electrode sensitivity Electrode resolution Cramér–Rao Localization error Somatosensory evoked potentials 





EEG source imaging


Magnetic resonance imaging (or magnetic resonance image)


Functional MRI


Finite element method


Lead field


Relative difference measure


Magnitude ratio


Anterior–posterior (rostro-caudal)




Inferior–superior (ventro-dorsal)


Half sensitive volume


Fifth sensitive volume


Cramér–Rao lower bound


Root-mean-square of the CRLB of the localization error


Forelimb region of the primary somatosensory (We’ll use the anatomical structures of the Paxinos and Watson atlas (Paxinos and Watson 2007).


Hindlimb region of the primary somatosensory


Barrel field of the primary somatosensory


Primary motor cortex


Secondary motor cortex


Posterior parietal cortex


Event related potential


Somatosensory evoked potential (somatosensory ERP)


Red–green–blue color code



We thank Lloyd Smith for his help on typos and English grammar; Dr. Eduardo Martinez Montes for his revision and suggestions and Joe Michel Lopez Inguanso for some useful searches in the Internet. We also thank Professor Pedro A. Valdés-Sosa for useful advices in the organization of the paper and the presentation of the main ideas.

Compliance with Ethical Standards

Conflict of Interest

Cortech Solution’s has licensed a patent (US 9,078,584 B2) for the EEG mini-cap named “The Riera High-Density Non-Invasive EEG Mini-Cap” after its principal inventor Jorge Riera, the corresponding author of this paper. The patent was licensed from Tohoku University (Sendai, Japan). Authors Jorge Riera and Akira Sumiyoshi might respectively receive 10 and 5 % of the patent-generated royalties due to intellectual property rights. All other co-authors have nothing to declare.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Pedro A. Valdés-Hernández
    • 1
    • 3
  • Jihye Bae
    • 2
  • Yinchen Song
    • 2
  • Akira Sumiyoshi
    • 3
  • Eduardo Aubert-Vázquez
    • 1
  • Jorge J. Riera
    • 2
  1. 1.Neuroimaging DepartmentCuban Neuroscience CenterHavanaCuba
  2. 2.Department of Biomedical EngineeringFlorida International UniversityMiamiUSA
  3. 3.Institute of Development, Aging and CancerTohoku UniversitySendaiJapan

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