Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

EEG and functional ultrasound imaging in mobile rats

Nature Methods volume 12, pages 831–834 (2015)Cite this article

Subjects

Abstract

We developed an integrated experimental framework that extends the brain exploration capabilities of functional ultrasound imaging to awake and mobile rats. In addition to acquiring hemodynamic data, this method further allows parallel access to electroencephalography (EEG) recordings of neuronal activity. We illustrate this approach with two proofs of concept: a behavioral study on theta rhythm activation in a maze running task and a disease-related study on spontaneous epileptic seizures.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Awake mobile EEG-fUS procedure and acquisition protocols.
Figure 2: Comparison of EEG and hemodynamic signatures of natural events.

Similar content being viewed by others

References

  1. Logothetis, N.K. Nature 453, 869–878 (2008).

    Article  CAS  Google Scholar 

  2. Sada, N., Lee, S., Katsu, T., Otsuki, T. & Inoue, T. Science 347, 1362–1367 (2015).

    Article  CAS  Google Scholar 

  3. Kerr, J.N. & Nimmerjahn, A. Curr. Opin. Neurobiol. 22, 45–53 (2012).

    Article  CAS  Google Scholar 

  4. Packer, A.M., Russell, L.E., Dalgleish, H.W. & Häusser, M. Nat. Methods 12, 140–146 (2015).

    Article  CAS  Google Scholar 

  5. Macé, E. et al. Nat. Methods 8, 662–664 (2011).

    Article  Google Scholar 

  6. Macé, E. et al. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 60, 492–506 (2013).

    Article  Google Scholar 

  7. Osmanski, B.F., Pezet, S., Ricobaraza, A., Lenkei, Z. & Tanter, M. Nat. Commun. 5, 5023 (2014).

    Article  CAS  Google Scholar 

  8. Buzsáki, G. & Moser, E.I. Nat. Neurosci. 16, 130–138 (2013).

    Article  Google Scholar 

  9. David, O. et al. PLoS Biol. 6, 2683–2697 (2008).

    Article  CAS  Google Scholar 

  10. Zheng, T.W. et al. Epilepsia 53, 1948–1958 (2012).

    Article  Google Scholar 

  11. Jacobs, J. et al. Neuroimage 45, 1220–1231 (2009).

    Article  Google Scholar 

  12. Koehler, R.C., Roman, R.J. & Harder, D.R. Trends Neurosci. 32, 160–169 (2009).

    Article  CAS  Google Scholar 

  13. LaMendola, N.P. & Bever, T.G. Science 278, 483–486 (1997).

    Article  CAS  Google Scholar 

  14. Logothetis, N.K. et al. Nature 491, 547–553 (2012).

    Article  CAS  Google Scholar 

  15. Mishra, A.M. et al. J. Neurosci. 31, 15053–15064 (2011).

    Article  CAS  Google Scholar 

  16. Roche-Labarbe, N. et al. Epilepsia 51, 1374–1384 (2010).

    Article  Google Scholar 

  17. O'Neill, P.K., Gordon, J.A. & Sigurdsson, T. J. Neurosci. 33, 14211–14224 (2013).

    Article  CAS  Google Scholar 

  18. Brincat, S.L. & Miller, E.K. Nat. Neurosci. 18, 576–581 (2015).

    Article  CAS  Google Scholar 

  19. Paxinos, G. & Watson, C. The Rat Brain in Stereotaxic Coordinates 6th edn. (Academic Press, 2007).

  20. Montaldo, G., Tanter, M., Bercoff, J., Benech, N. & Fink, M. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56, 489–506 (2009).

    Article  Google Scholar 

  21. Bercoff, J. et al. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 58, 134–147 (2011).

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge E. Yeramian and A. Bonnot for critical discussions and help with the manuscript. The research leading to these results has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 339244-FUSIMAGINE. This work was also partly supported by the Agence Nationale de la Recherche under the program “Future Investments” with the reference Laboratory of Excellence ANR-10-LABX-24 LABEX WIFI within the French Program “Investments for the Future” under reference ANR-10-IDEX-0001-02 PSL, the program “Investissements d'avenir” ANR-10-IAIHU-06 and a PhD fellowship from the University Paris Diderot FdV Bettencourt PhD program.

Author information

Authors and Affiliations

  1. Institut de Biologie Paris-Seine, INSERM U1130, CNRS UMR 8246, University Pierre et Marie Curie UMCR18, Paris, France

    Lim-Anna Sieu, Antoine Bergel & Ivan Cohen

  2. Institut des Neurosciences Translationnelles de Paris, Paris, France

    Lim-Anna Sieu

  3. Ecole Doctorale Frontières du Vivant (FdV), Programme Bettencourt, Universite´ Paris Diderot, Sorbonne Paris Cite, Paris, France

    Antoine Bergel

  4. Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles de la ville de Paris ParisTech, Paris Sciences et Lettres Research University, CNRS UMR 7587, INSERM U979, Paris, France

    Elodie Tiran, Thomas Deffieux, Mathieu Pernot, Jean-Luc Gennisson & Mickaël Tanter

Authors
  1. Lim-Anna Sieu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antoine Bergel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elodie Tiran
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Deffieux
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mathieu Pernot
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jean-Luc Gennisson
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mickaël Tanter
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ivan Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

L.-A.S. designed the surgical procedure and prosthetic skull and performed and analyzed epilepsy experiments; A.B. designed the intrahippocampal recording procedure and performed and analyzed navigation experiments; E.T. and T.D. developed the burst-mode ultrasound recording sequence; M.P. and J.-L.G. developed the continuous-mode ultrasound recording sequence; J.-L.G. and M.T. designed and supervised the ultrasound scanner and probe; I.C. designed and supervised the experiments, designed the probe holder, and programmed acquisition and analysis software; I.C., L.-A.S. and A.B. wrote the paper.

Corresponding author

Correspondence to Ivan Cohen.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Comparison of static and awake mobile fUS

The mfUS method is based on incremental improvements over functional ultrasound imaging on anesthetized rats.

(a, b) show side and front views of static fUS on anesthetized rat with open or thinned-bone craniotomy 5, 7. The rat is sedated and fixed in a stereotaxic frame.

(c) the PMP prosthesis surgical procedure and a first downsized ultrasound probe provide images in awake condition although the animal is highly constrained by the weight of the probe.

(d) a second generation, smaller and lighter, probe allows the animal to move and EEG to be recorded.

(e) comparison of second and third generation of probe show a further gain in size and weight.

(f) miniature motorized design allows to scan multiple planes without directly interacting with the animal, while the mechanical constraint is minimal. All the navigation and epilepsy measures presented here were performed with this smaller design.

Supplementary Figure 2 Surgical procedure

The surgical procedure to prepare the rat for simultaneous EEG and fUS recording proceeds in successive steps. First, a large bone flap is removed. Then electrodes are moved to the target position by stereotaxic micromotion, and they are anchored to the edge of the flap with a droplet of resin (a). For clarity, only one electrode is shown. Following sequential insertion of all the electrodes, the skull is replaced by an ultrasound clear prosthesis made of PMP. Finally, the prosthesis is sealed to the skull with resin and nuts are embedded in the resin for later attachment of the probe holder (b).

Supplementary Figure 3 Hippocampal electrodes

Hippocampal electrodes are made from a bundle of insulated tungsten wires soldered to a miniature connector at one end. Under binocular control the 50 µm reference electrode is juxtaposed with five 25 µm recording electrodes. The wires tips are positioned at fixed spacing in order to reach anatomical structures encompassing the dorsal hippocampus (a) and they are glued with cyanoacrylate in the upper part of the bundle to avoid accidentally covering the recording tips. A millimeter scale and microscope scale slide (total length 1 mm) are used to precisely set the spacing. Atlas from Paxinos19 (b). Differential recording from electrode tips 2-4, that show the typical theta band activation in relation with spatial navigation and phase reversal along the dorso-ventral axis are retained for analysis.

Supplementary Figure 4 Probe, holder and motor

Photographs of the miniature ultrasound probe (a), micromotor (b). The probe holder (c) is composed of a plate fixed onto the head (right) and a translation stage (left).

Supplementary Figure 5 CAD drawing of probe and holder parts

Front, side and top views of the base plate fixed to the head, mobile holder part and probe that fits into the mobile part. The base plate is attached to the head with M2 conical head screws. The probe and motor are secured with M2 headless screws. The sliding surface is lubricated with teflon spray. Digital information to reproduce the parts is provided as Supplementary Material 1.

Supplementary Figure 6 Motor controller circuit

The motor controller circuit is based on an Arduino Uno open-source electronic platform. Requests for mechanical translation are received from the ultrasound scanner through a USB to serial converter based on a PL2303 chip. The Arduino turns on a DC-to-DC step down converter through the "ENABLE" pin to power the servomotor with optimal 3.7V voltage. Simultaneously the position information is sent by PWM modulation to the command line. Motor power is turned off. An LCD provides status information. Arduino microcode is provided in Supplementary Note.

Supplementary Figure 7 Comparison of "continuous" and "burst" modes

The continuous and burst modes make distinct usage of the ultrasound scanner acquisition and processing power. The main task is to transfer and process the large amount of high frequency plane wave scans into an fUltrasound images, which is saved as an array of single precision encoded pixel Power Doppler intensity corresponding to CBV. The reduction in data size is 1000 fold since 200 scans composed of repeats at 5 angles are used to generate one fUltrasound image.

The "continuous" mode has the advantage to permit acquisition of virtually unlimited duration. For this mode, the Ultrafast acquisition is set to form a single fUS image (200 ms). The transfer and processing time (here 2 seconds) limits the final rate of CBV maps.

The "burst" mode has the advantage to sustain the Ultrafast frame rate up to the filling of the RAM memories (here 12 s), allowing to capture short behavioral events such as maze crossing. CBV maps are reconstructed every 200 ms, but for this limited 12 s duration. Data is transferred in parallel with acquisition, and when buffer memory is full data is processed (40 s) to form a series of fUltrasound images. Thus duration of acquisition is limited by memory size, and interval duration is limited by processing speed.

The use of two modes is only due to technical limitations of current electronic boards of the ultrasound system. With improving bus technology and high end GPU boards it should be possible in theory today to build an Ultrafast ultrasound scanner with transfer and processing rates fast enough to work in the continuous mode during unlimited amount of time.

Supplementary Figure 8 Effect of recording procedure on running and seizures

(a, b) Maze experiment comparative distributions between mfUS-EEG (blue) and control untethered, surgery free, rats (red) show cumulative distance travelled in the maze is reduced by 36-44% while maximum speed is moderately reduced by 1-13%. Graphs show mean, median, center quartiles, 1 and 99 percentiles. (c, d) Genetic absence rats (GAERS, blue) show equivalent seizing time fraction and seizure duration distribution compared to EEG-only recordings (red). Graph c shows mean+/- s.d., 1 and 99 percentiles.

Detailed statistics are given in the Supplementary tables.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1–3 and Supplementary Note (PDF 995 kb)

Supplementary Data

Probe Holder Manufacturing Template (PDF 301 kb)

Supplementary Software 1

Matlab code (ZIP 6 kb)

Supplementary Software 2

Labview VI code (ZIP 16558 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sieu, LA., Bergel, A., Tiran, E. et al. EEG and functional ultrasound imaging in mobile rats. Nat Methods 12, 831–834 (2015). https://doi.org/10.1038/nmeth.3506

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.3506

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing