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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 2, Iss. 11 — Nov. 1, 2011
  • pp: 3129–3134
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Swept source optical coherence tomography as a tool for real time visualization and localization of electrodes used in electrophysiological studies of brain in vivo

Hideyuki Watanabe, Uma Maheswari Rajagopalan, Yu Nakamichi, Kei M. Igarashi, Hirofumi Kadono, and Manabu Tanifuji  »View Author Affiliations


Biomedical Optics Express, Vol. 2, Issue 11, pp. 3129-3134 (2011)
http://dx.doi.org/10.1364/BOE.2.003129


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Abstract

In studies of in vivo extracellular recording, we usually penetrate electrodes almost blindly into the neural tissue, in order to detect the neural activity from an expected target location at a certain depth. After the recording, it is necessary for us to determine the position of the electrodes precisely. Generally, to identify the position of the electrode, one method is to examine the postmortem tissue sample at micron resolution. The other method is using MRI and it does not have enough resolution to resolve the neural structures. To solve such problems, we propose swept source optical coherence tomography (SS-OCT) as a tool to visualize the cross-sectional image of the neural target structure along with the penetrating electrode. We focused on a rodent olfactory bulb (OB) as the target. We succeeded in imaging both the OB layer structure and the penetrating electrode, simultaneously. The method has the advantage of detecting the electrode shape and the position in real time, in vivo. These results indicate the possibility of using SS-OCT as a powerful tool for guiding the electrode into the target tissue precisely in real time and localizing the electrode tip during electrophysiological recordings.

© 2011 OSA

1. Introduction

Recording neural activity and stimulation of specific neural elements such as neurons with microelectrodes are major methods for investigating neural systems in electrophysiology [1

1. A. L. Fantana, E. R. Soucy, and M. Meister, “Rat olfactory bulb mitral cells receive sparse glomerular inputs,” Neuron 59(5), 802–814 (2008). [CrossRef] [PubMed]

,2

2. S. Nagayama, Y. K. Takahashi, Y. Yoshihara, and K. Mori, “Mitral and tufted cells differ in the decoding manner of odor maps in the rat olfactory bulb,” J. Neurophysiol. 91(6), 2532–2540 (2004). [CrossRef] [PubMed]

]. Generally, in such studies, the penetration of the electrodes has been performed rather blindly to reach an expected specific location by using the stereotactic coordinates as the reference coordinates [2

2. S. Nagayama, Y. K. Takahashi, Y. Yoshihara, and K. Mori, “Mitral and tufted cells differ in the decoding manner of odor maps in the rat olfactory bulb,” J. Neurophysiol. 91(6), 2532–2540 (2004). [CrossRef] [PubMed]

,3

3. E. R. Griff, M. Mafhouz, A. Perrut, and M. A. Chaput, “Comparison of identified mitral and tufted cells in freely breathing rats: I. Conduction velocity and spontaneous activity,” Chem. Senses 33(9), 779–792 (2008). [CrossRef] [PubMed]

]. It is necessary for us to use either MRI or to examine the postmortem tissue sample [4

4. J. Chapuis, S. Garcia, B. Messaoudi, M. Thevenet, G. Ferreira, R. Gervais, and N. Ravel, “The way an odor is experienced during aversive conditioning determines the extent of the network recruited during retrieval: a multisite electrophysiological study in rats,” J. Neurosci. 29(33), 10287–10298 (2009). [CrossRef] [PubMed]

,5

5. T. Sato, G. Uchida, and M. Tanifuji, “Cortical columnar organization is reconsidered in inferior temporal cortex,” Cereb. Cortex 19(8), 1870–1888 (2009). [CrossRef] [PubMed]

] in order to determine the precise position of the electrode at the specific target. However, MRI does not support a few micrometer level of spatial resolution in localizing the electrode. In the case of postmortem tissue slicing, it is difficult to confirm the location of the electrode, in vivo.

In this study, we propose SS-OCT as a tool for real time monitoring of electrode penetration and localization of the electrode to the specific target neural layer, in vivo. MCL has been regarded as one of the important regions for understanding OB mechanism. MCL has been studied by electrophysiological methods with electrode. Therefore, in this study, we chose MCL (mitral cell body layer) as our specific target layer [1

1. A. L. Fantana, E. R. Soucy, and M. Meister, “Rat olfactory bulb mitral cells receive sparse glomerular inputs,” Neuron 59(5), 802–814 (2008). [CrossRef] [PubMed]

,2

2. S. Nagayama, Y. K. Takahashi, Y. Yoshihara, and K. Mori, “Mitral and tufted cells differ in the decoding manner of odor maps in the rat olfactory bulb,” J. Neurophysiol. 91(6), 2532–2540 (2004). [CrossRef] [PubMed]

,16

16. W. R. Chen, J. Midtgaard, and G. M. Shepherd, “Forward and backward propagation of dendritic impulses and their synaptic control in mitral cells,” Science 278(5337), 463–467 (1997). [CrossRef] [PubMed]

,17

17. H. Matsumoto, H. Kashiwadani, H. Nagao, A. Aiba, and K. Mori, “Odor-induced persistent discharge of mitral cells in the mouse olfactory bulb,” J. Neurophysiol. 101(4), 1890–1900 (2009). [CrossRef] [PubMed]

].

2. Experimental details

2.1. Experimental system

The probe part consisted of two components. One was the optical probe unit of the SS-OCT system mounted on an independent universal stand (Olympus, SZ2-STU2) with a focusing unit (Olympus, BXFM-F), and the other was the electrode penetration probe unit. The latter unit was mounted on an X-Y micrometer stage (Chuo-Seiki, LD-131-S1), along with a stereotactic frame for fixing the animal. The whole arrangement enabled us to adjust the relative position of the probe units independently. Further, as the rat and the electrode probe unit were moved by X-Y micrometer stage, it was possible to keep the relative spatial position. By using the rotatable focusing unit attached to the stand, it was possible for us to adjust the plane of the OCT image to the plane of the electrode penetration.

2.2. Animal preparation details

3. Result and discussion

3.1. Monitoring of electrode penetration to the neural layer structure

In order to reduce speckles, Fig. 4
Fig. 4 Five-frame averaged OCT B-scan images obtained during the electrode penetration process at different times (a) t = 0 sec; (b) t = 7 sec; (c) t = 10.5 sec; (d) t = 14 sec. The penetration process was clearly seen and finally reaching the target location of MCL. The arrows on the left corner indicate the anterior-posterior and dorsal-ventral parts of the rat. A, anterior; P, posterior; D, dorsal; V, ventral. Scale bar, 100 μm. Refer to the movie (Media 2) of five-frame averaged images.
shows 5-frame averaged OCT B-scan images obtained at different times during the penetration. The original data set was exactly same as shown in Fig. 3. Frame averaging clearly reduced the speckle noise. Here, we used linear scale for the calculation of averaging and then converted to logarithmic scale for display purposes to have enough dynamic range.

3.2 Localization of the electrode to the neural layer structure

When the electrode reached the target layer of MCL, the penetration was stopped, we took 50,000 B-scan images of OCT images. The B-scan images were corrected for any misalignment due to the movement of the brain through the process of cross-correlation. After that, all frames were averaged. Further, in order to reduce the artifacts of vertical shadow in the axial direction due to the vessels in the OCT images, we performed normalization of each vertical line by using the standard deviation of each A-scan OCT signal. The normalization process made the identification and the localization of the electrode easier and clearer. We succeeded in localizing the electrode at the MCL neural layer structure of OB in vivo in Fig. 5(a)
Fig. 5 (a) Averaged OCT B-scan image of OB with the stationary electrode being positioned at the target location MCL of OB. (b) Averaged OCT image same as (a) with inverted dynamic range to have a clear visualization of the target layer in relation to the electrode. Part below the electrode in the OCT signal was not detectable because the electrode practically reflected the sample beam. The arrows on the left corner indicate the anterior-posterior and dorsal-ventral parts of the rat. A, anterior; P, posterior; D, dorsal; V, ventral. Scale bar, 100 μm.
. Figure 5(b) was shown for clarity as an inverted intensity map of Fig. 5(a). As the tip diameter was almost close to the resolution limits of the SS-OCT system, the OCT signal was weak. It was necessary to increase the number of averaging of OCT images to improve the contrast of the image in identifying both the tip and the target location as shown in Fig. 5.

4. Summary

So far, the penetration of the electrodes has usually been performed rather blindly to the specific location by using the stereotactic coordinates, and it was necessary to inspect the postmortem slices for confirmation of the electrode after recording. To solve this problem, we showed that SS-OCT works as a tool to visualize and localize the electrode at the specific location of neural layer structure of OB under real time. We also showed that our proposed real time visualization of electrode by SS-OCT eliminates the necessity for confirmation through postmortem slice investigations.

In the current system, real time frame rate was limited by the signal processing, for instance FFT calculation. However, with the availability of the latest high-end hardware processing tools such as graphics processing unit (GPU), digital-signal-processing (DSP) and field programmable gate array (FPGA) [18

18. K. Zhang and J. U. Kang, “Real-time 4D signal processing and visualization using graphics processing unit on a regular nonlinear-k Fourier-domain OCT system,” Opt. Express 18(11), 11772–11784 (2010). [CrossRef] [PubMed]

,19

19. S. A. Boppart, “Optical coherence tomography: technology and applications for neuroimaging,” Psychophysiology 40(4), 529–541 (2003). [CrossRef] [PubMed]

], we expect processing speed to increase dramatically.

We believe, our approach is not only restricted to electrode penetration studies in vivo but also to microinjection experiments in neural layer structure where we inject small amount of foreign materials into the target location such as in anatomical tracing and local virus expression [20

20. M. Lalancette-Hébert, D. Phaneuf, G. Soucy, Y. C. Weng, and J. Kriz, “Live imaging of Toll-like receptor 2 response in cerebral ischaemia reveals a role of olfactory bulb microglia as modulators of inflammation,” Brain 132(4), 940–954 (2009). [CrossRef] [PubMed]

]. With the current system, there exists another possibility of using the system as a position-tracking tool for endoscopes (also OCT endoscopes). We also hope that a combination tool of SS-OCT with the conventional ones such as MRI, CT or cerebral ventriculography [21

21. S. Breit, J. B. Schulz, and A. L. Benabid, “Deep brain stimulation,” Cell Tissue Res. 318(1), 275–288 (2004). [CrossRef] [PubMed]

] may help in contributing to the study of brain diseases such as Parkinson’s disease.

Acknowledgments

We thank Mr. Takayuki Sato for his advice on electrode penetration. We would like to thank the staff members of Research Resources Center in taking care of the animals. We also thank Mr. Atsushi Morosawa and Mr. Takuya Suzuki of Santec Corporation (Aichi, Japan) for their technical assistance in customizing the SS-OCT system.

References and links

1.

A. L. Fantana, E. R. Soucy, and M. Meister, “Rat olfactory bulb mitral cells receive sparse glomerular inputs,” Neuron 59(5), 802–814 (2008). [CrossRef] [PubMed]

2.

S. Nagayama, Y. K. Takahashi, Y. Yoshihara, and K. Mori, “Mitral and tufted cells differ in the decoding manner of odor maps in the rat olfactory bulb,” J. Neurophysiol. 91(6), 2532–2540 (2004). [CrossRef] [PubMed]

3.

E. R. Griff, M. Mafhouz, A. Perrut, and M. A. Chaput, “Comparison of identified mitral and tufted cells in freely breathing rats: I. Conduction velocity and spontaneous activity,” Chem. Senses 33(9), 779–792 (2008). [CrossRef] [PubMed]

4.

J. Chapuis, S. Garcia, B. Messaoudi, M. Thevenet, G. Ferreira, R. Gervais, and N. Ravel, “The way an odor is experienced during aversive conditioning determines the extent of the network recruited during retrieval: a multisite electrophysiological study in rats,” J. Neurosci. 29(33), 10287–10298 (2009). [CrossRef] [PubMed]

5.

T. Sato, G. Uchida, and M. Tanifuji, “Cortical columnar organization is reconsidered in inferior temporal cortex,” Cereb. Cortex 19(8), 1870–1888 (2009). [CrossRef] [PubMed]

6.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991). [CrossRef] [PubMed]

7.

M. Wojtkowski, “High-speed optical coherence tomography: basics and applications,” Appl. Opt. 49(16), D30–D61 (2010). [CrossRef] [PubMed]

8.

W. Drexler and J. G. Fujimoto, eds., Optical Coherence Tomography (Springer-Verlag, 2008).

9.

B. E. Bouma and G. J. Tearney, eds., Handbook of Optical Coherence Tomography (Marcel Dekker, 2002).

10.

W. Suzuki, G. Hanazono, T. Nanjo, K. Ito, J. Nishiyama, M. Tanifuji, and K. Tsunoda, “Intrinsic signals in different layers of macaque retina revealed by optical coherence tomography (OCT),” Abstr. Soc. Neurosci. 171.19 (2010).

11.

R. U. Maheswari, H. Takaoka, H. Kadono, R. Homma, and M. Tanifuji, “Novel functional imaging technique from brain surface with optical coherence tomography enabling visualization of depth resolved functional structure in vivo,” J. Neurosci. Methods 124(1), 83–92 (2003). [CrossRef] [PubMed]

12.

Y. Chen, A. D. Aguirre, L. Ruvinskaya, A. Devor, D. A. Boas, and J. G. Fujimoto, “Optical coherence tomography (OCT) reveals depth-resolved dynamics during functional brain activation,” J. Neurosci. Methods 178(1), 162–173 (2009). [CrossRef] [PubMed]

13.

S. R. Chinn, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography using a frequency-tunable optical source,” Opt. Lett. 22(5), 340–342 (1997). [CrossRef] [PubMed]

14.

M. A. Choma, M. V. Sarunic, C. Yang, and J. A. Izatt, “Sensitivity advantage of swept source and Fourier domain optical coherence tomography,” Opt. Express 11(18), 2183–2189 (2003). [CrossRef] [PubMed]

15.

H. Watanabe, U. M. Rajagopalan, Y. Nakamichi, K. M. Igarashi, V. D. Madjarova, H. Kadono, and M. Tanifuji, “In vivo layer visualization of rat olfactory bulb by a swept source optical coherence tomography and its confirmation through electrocoagulation and anatomy,” Biomed. Opt. Express 2(8), 2279–2287 (2011). [CrossRef] [PubMed]

16.

W. R. Chen, J. Midtgaard, and G. M. Shepherd, “Forward and backward propagation of dendritic impulses and their synaptic control in mitral cells,” Science 278(5337), 463–467 (1997). [CrossRef] [PubMed]

17.

H. Matsumoto, H. Kashiwadani, H. Nagao, A. Aiba, and K. Mori, “Odor-induced persistent discharge of mitral cells in the mouse olfactory bulb,” J. Neurophysiol. 101(4), 1890–1900 (2009). [CrossRef] [PubMed]

18.

K. Zhang and J. U. Kang, “Real-time 4D signal processing and visualization using graphics processing unit on a regular nonlinear-k Fourier-domain OCT system,” Opt. Express 18(11), 11772–11784 (2010). [CrossRef] [PubMed]

19.

S. A. Boppart, “Optical coherence tomography: technology and applications for neuroimaging,” Psychophysiology 40(4), 529–541 (2003). [CrossRef] [PubMed]

20.

M. Lalancette-Hébert, D. Phaneuf, G. Soucy, Y. C. Weng, and J. Kriz, “Live imaging of Toll-like receptor 2 response in cerebral ischaemia reveals a role of olfactory bulb microglia as modulators of inflammation,” Brain 132(4), 940–954 (2009). [CrossRef] [PubMed]

21.

S. Breit, J. B. Schulz, and A. L. Benabid, “Deep brain stimulation,” Cell Tissue Res. 318(1), 275–288 (2004). [CrossRef] [PubMed]

OCIS Codes
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(170.4500) Medical optics and biotechnology : Optical coherence tomography
(170.5380) Medical optics and biotechnology : Physiology

ToC Category:
Ophthalmology Applications

History
Original Manuscript: August 27, 2011
Revised Manuscript: October 14, 2011
Manuscript Accepted: October 20, 2011
Published: October 25, 2011

Citation
Hideyuki Watanabe, Uma Maheswari Rajagopalan, Yu Nakamichi, Kei M. Igarashi, Hirofumi Kadono, and Manabu Tanifuji, "Swept source optical coherence tomography as a tool for real time visualization and localization of electrodes used in electrophysiological studies of brain in vivo," Biomed. Opt. Express 2, 3129-3134 (2011)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-2-11-3129


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References

  1. A. L. Fantana, E. R. Soucy, and M. Meister, “Rat olfactory bulb mitral cells receive sparse glomerular inputs,” Neuron59(5), 802–814 (2008). [CrossRef] [PubMed]
  2. S. Nagayama, Y. K. Takahashi, Y. Yoshihara, and K. Mori, “Mitral and tufted cells differ in the decoding manner of odor maps in the rat olfactory bulb,” J. Neurophysiol.91(6), 2532–2540 (2004). [CrossRef] [PubMed]
  3. E. R. Griff, M. Mafhouz, A. Perrut, and M. A. Chaput, “Comparison of identified mitral and tufted cells in freely breathing rats: I. Conduction velocity and spontaneous activity,” Chem. Senses33(9), 779–792 (2008). [CrossRef] [PubMed]
  4. J. Chapuis, S. Garcia, B. Messaoudi, M. Thevenet, G. Ferreira, R. Gervais, and N. Ravel, “The way an odor is experienced during aversive conditioning determines the extent of the network recruited during retrieval: a multisite electrophysiological study in rats,” J. Neurosci.29(33), 10287–10298 (2009). [CrossRef] [PubMed]
  5. T. Sato, G. Uchida, and M. Tanifuji, “Cortical columnar organization is reconsidered in inferior temporal cortex,” Cereb. Cortex19(8), 1870–1888 (2009). [CrossRef] [PubMed]
  6. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991). [CrossRef] [PubMed]
  7. M. Wojtkowski, “High-speed optical coherence tomography: basics and applications,” Appl. Opt.49(16), D30–D61 (2010). [CrossRef] [PubMed]
  8. W. Drexler and J. G. Fujimoto, eds., Optical Coherence Tomography (Springer-Verlag, 2008).
  9. B. E. Bouma and G. J. Tearney, eds., Handbook of Optical Coherence Tomography (Marcel Dekker, 2002).
  10. W. Suzuki, G. Hanazono, T. Nanjo, K. Ito, J. Nishiyama, M. Tanifuji, and K. Tsunoda, “Intrinsic signals in different layers of macaque retina revealed by optical coherence tomography (OCT),” Abstr. Soc. Neurosci. 171.19 (2010).
  11. R. U. Maheswari, H. Takaoka, H. Kadono, R. Homma, and M. Tanifuji, “Novel functional imaging technique from brain surface with optical coherence tomography enabling visualization of depth resolved functional structure in vivo,” J. Neurosci. Methods124(1), 83–92 (2003). [CrossRef] [PubMed]
  12. Y. Chen, A. D. Aguirre, L. Ruvinskaya, A. Devor, D. A. Boas, and J. G. Fujimoto, “Optical coherence tomography (OCT) reveals depth-resolved dynamics during functional brain activation,” J. Neurosci. Methods178(1), 162–173 (2009). [CrossRef] [PubMed]
  13. S. R. Chinn, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography using a frequency-tunable optical source,” Opt. Lett.22(5), 340–342 (1997). [CrossRef] [PubMed]
  14. M. A. Choma, M. V. Sarunic, C. Yang, and J. A. Izatt, “Sensitivity advantage of swept source and Fourier domain optical coherence tomography,” Opt. Express11(18), 2183–2189 (2003). [CrossRef] [PubMed]
  15. H. Watanabe, U. M. Rajagopalan, Y. Nakamichi, K. M. Igarashi, V. D. Madjarova, H. Kadono, and M. Tanifuji, “In vivo layer visualization of rat olfactory bulb by a swept source optical coherence tomography and its confirmation through electrocoagulation and anatomy,” Biomed. Opt. Express2(8), 2279–2287 (2011). [CrossRef] [PubMed]
  16. W. R. Chen, J. Midtgaard, and G. M. Shepherd, “Forward and backward propagation of dendritic impulses and their synaptic control in mitral cells,” Science278(5337), 463–467 (1997). [CrossRef] [PubMed]
  17. H. Matsumoto, H. Kashiwadani, H. Nagao, A. Aiba, and K. Mori, “Odor-induced persistent discharge of mitral cells in the mouse olfactory bulb,” J. Neurophysiol.101(4), 1890–1900 (2009). [CrossRef] [PubMed]
  18. K. Zhang and J. U. Kang, “Real-time 4D signal processing and visualization using graphics processing unit on a regular nonlinear-k Fourier-domain OCT system,” Opt. Express18(11), 11772–11784 (2010). [CrossRef] [PubMed]
  19. S. A. Boppart, “Optical coherence tomography: technology and applications for neuroimaging,” Psychophysiology40(4), 529–541 (2003). [CrossRef] [PubMed]
  20. M. Lalancette-Hébert, D. Phaneuf, G. Soucy, Y. C. Weng, and J. Kriz, “Live imaging of Toll-like receptor 2 response in cerebral ischaemia reveals a role of olfactory bulb microglia as modulators of inflammation,” Brain132(4), 940–954 (2009). [CrossRef] [PubMed]
  21. S. Breit, J. B. Schulz, and A. L. Benabid, “Deep brain stimulation,” Cell Tissue Res.318(1), 275–288 (2004). [CrossRef] [PubMed]

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