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Optical Properties of Neural Tissue

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Optical Imaging of Neocortical Dynamics

Part of the book series: Neuromethods ((NM,volume 85))

Abstract

The optical properties of neural tissues play critical roles in all types of optical imaging methods. The wavelength-dependent absorption and scattering properties of tissue influence imaging resolution, penetration depth, and often provide sources of contrast. Therefore, quantitative interpretation of imaging data requires knowledge of the optical properties of neural tissues. Light scattering in tissue arises from nanometer-scale spatial variations in refractive index and requires a thorough electromagnetic description of light propagation through this complex medium. Unfortunately, the complexity of neural tissues and the difficulty in measuring refractive index values make such a complete description unrealistic. Therefore, approximations must be made in order to characterize the light scattering properties of neural tissue. This chapter summarizes the various approaches to assess and describe the optical properties of neural tissue and discusses their role for cortical imaging.

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References

  1. Villringer A, Chance B (1997) Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci 20(10):435–442

    Article  CAS  PubMed  Google Scholar 

  2. Bevilacqua F, Piguet D, Marquet P, Gross G, Tromberg B, Depeursinge C (1999) In vivo local determination of tissue optical properties: applications to human brain. Appl Optics 38(22):4939–4950

    Article  CAS  Google Scholar 

  3. Palmer KF, Williams D (1974) Optical properties of water in the near infrared. J Opt Soc Am 64(8):1107

    Article  CAS  Google Scholar 

  4. Beuthan J, Minet O, Helfman J, Muller G (1996) The spatial variation of the refractive index in biological cells. Phys Med Biol 41:369–382

    Article  CAS  PubMed  Google Scholar 

  5. Kohl M, Cope M (1994) Influence of glucose concentration on light scattering in tissue. Opt Lett 17:2170–2172

    Article  Google Scholar 

  6. Brunsting A, Mullaney P (1974) Differential light scattering from spherical mammalian cells. Biophys J 14:439–453

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Liu H, Beauvoit B, Kimura M, Chance B (1996) Dependence of tissue optical properties on solute-induced changes in refractive index and osmolarity. J Biomed Opt 1:200–211

    Article  CAS  PubMed  Google Scholar 

  8. Vitkin I, Woolsey J, Wilson B, Anderson R (1994) Optical and thermal characterization of natural (Sepia oficinalis) melanin. Photochem Photobiol 59:455–462

    Article  CAS  PubMed  Google Scholar 

  9. Lanni F, Waggoner A, Taylor D (1985) Internal reflection fluorescence microscopy. J Cell Biol 100:1091

    Article  CAS  PubMed  Google Scholar 

  10. Bereiter-Han J, Fox C, Thorell B (1979) Quantitative reflection contrast microscopy of living cells. J Cell Biol 82:767–779

    Article  Google Scholar 

  11. Barer R (1957) Refractometry and interferometry of living cells. J Opt Soc Am 47:545–556

    Article  CAS  PubMed  Google Scholar 

  12. Barer R, Joseph S (1954) Refractometry of living cells. Q J Microsc Sci 95:399–423

    CAS  Google Scholar 

  13. Dunn A, Richards-Kortum R (1996) Three-dimensional computation of light scattering from cells. IEEE J Sel Top Quantum Electron 2:898–905

    Article  CAS  Google Scholar 

  14. Starosta MS, Dunn AK (2010) Far-field superposition method for three-dimensional computation of light scattering from multiple cells. J Biomed Opt 15(5):055006

    Article  PubMed  Google Scholar 

  15. Arridge SR (1999) Optical tomography in medical imaging. Inverse Problems 15(2):R41–R93

    Article  Google Scholar 

  16. Barnett AH, Culver JP, Sorensen AG, Dale AM, Boas DA (2003) Robust inference of baseline optical properties from the human head with 3D segmentation from magnetic resonance imaging. Appl Optics 42:3095–3108

    Article  Google Scholar 

  17. Prahl SA, van Gemert MJC, Welch AJ (1993) Determining the optical properties of turbid mediaby using the adding–doubling method. Appl Optics 32(4):559

    Article  CAS  Google Scholar 

  18. Matcher SJ, Cope M, Delpy DT (1997) In vivo measurements of the wavelength dependence of tissue-scattering coefficients between 760 and 900 nm measured with time-resolved spectroscopy. Appl Optics 36(1):386–396

    Article  CAS  Google Scholar 

  19. Stepnoski R, LaPorta A, Raccuia-Behling F, Blonder G, Slusher R, Kleinfeld D (1991) Noninvasive detection of light changes in membrane potential in cultured neurons by light scattering. Proc Natl Acad Sci USA 88:9382–9386

    Article  CAS  PubMed  Google Scholar 

  20. Cohen LB, Keynes RD, Hille B (1968) Light scattering and birefringence changes during nerve activity. Nature 218(5140):438–441

    Article  CAS  PubMed  Google Scholar 

  21. Rector DM, Poe GR, Kristensen MP, Harper RM (1997) Light Scattering Changes Follow Evoked Potentials From Hippocampal Schaeffer Collateral Stimulation. J Neurophysiol 78(3):1707–1713

    CAS  PubMed  Google Scholar 

  22. Gratton G, Fabiani M, Friedman D, Franceschini MA, Fantini S, Corballis P, Gratton E (1995) Rapid changes of optical parameters in the human brain during a tapping task. J Cogn Neurosci 7(4):446–456

    Article  CAS  PubMed  Google Scholar 

  23. Franceschini MA, Boas DA (2004) Noninvasive measurement of neuronal activity with near-infrared optical imaging. Neuroimage 21(1):372–386

    Article  PubMed Central  PubMed  Google Scholar 

  24. Grinvald A, Lieke E, Frostig R, Gilbert C, Wiesel T (1986) Functional architecture of cortex revealed by optical imaging of intrinsic signals. Nature 324:361–364

    Article  CAS  PubMed  Google Scholar 

  25. Malonek D, Grinvald A (1996) Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping. Science 272(5261):551–554

    Article  CAS  PubMed  Google Scholar 

  26. Mayhew J, Johnston D, Berwick J, Jones M, Coffey P, Zheng Y (2000) Spectroscopic analysis of neural activity in brain: increased oxygen consumption following activation of barrel cortex. Neuroimage 12(6):664–675

    Article  CAS  PubMed  Google Scholar 

  27. Kohl M, Lindauer U, Royl G, Kuhl M, Gold L, Villringer A, Dirnagl U (2000) Physical model for the spectroscopic analysis of cortical intrinsic optical signals. Phys Med Biol 45(12):3749–3764

    Article  CAS  PubMed  Google Scholar 

  28. Dunn AK, Devor A, Bolay H, Andermann ML, Moskowitz MA, Dale AM, Boas DA (2003) Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation. Opt Lett 28:28–30

    Article  CAS  PubMed  Google Scholar 

  29. Drew PJ, Shih AY, Driscoll JD, Knutsen PM, Blinder P, Davalos D, Akassoglou K, Tsai PS, Kleinfeld D (2010) Chronic optical access through a polished and reinforced thinned skull. Nat Methods 7(12):5–10

    Article  Google Scholar 

  30. Prahl S, Jacques S, Welch AJ (1989) A Monte Carlo model of light propagation in tissue. Proc SPIE 5:102–111

    Google Scholar 

  31. Wang L, Jacques SL, Zheng L (1995) MCML—Monte Carlo modeling of light transport in multi-layered tissues. Comput Methods Programs Biomed 47(2):131–146

    Article  CAS  PubMed  Google Scholar 

  32. Jacques S, Wang L (1995) Monte Carlo modeling of light transport in tissue. In: Welch AJ, Gemert MV (eds) Optical-thermal response of laser irradiated tissue. Plenum, New York

    Google Scholar 

  33. Boas DA, Culver JP, Stott JJ, Dunn AK (2002) Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. Opt Express 10:159–170

    Article  PubMed  Google Scholar 

  34. Kumar AT, Skoch J, Bacskai BJ, Boas DA, Dunn AK (2005) Fluorescence-lifetime-based tomography for turbid media. Opt Lett 30(24):3347–3349

    Article  PubMed  Google Scholar 

  35. Davis MA, Shams Kazmi SM, Ponticorvo A, Dunn AK (2011) Depth dependence of vascular fluorescence imaging. Biomed Opt Express 2(12):3349–3362

    Article  PubMed Central  PubMed  Google Scholar 

  36. Pfefer TJ, Barton JK, Smithies D, Milner TE, van Gemert MJC, Nelson JS, Welch AJ (1999) Modeling laser treatment of port wine stains using a computer-reconstructed biopsy. Lasers Surg Med 24:151–166

    Article  CAS  PubMed  Google Scholar 

  37. Barton JK, Pfefer TJ, Welch AJ, Smithies DJ, Nelson J, Gemert MJV (1998) Optical Monte Carlo modeling of a true portwine stain anatomy. Opt Express 2:391–396

    Article  CAS  PubMed  Google Scholar 

  38. Starosta MS, Dunn AK (2009) Three-dimensional computation of focused beam propagation through multiple biological cells. Opt Express 17(15):12455–12469

    Article  CAS  PubMed  Google Scholar 

  39. Yee K (1966) Numerical solutions of initial boundary value problems involving Maxwell’s equations in isotropic media. IEEE Trans Antennas Propagat AP-14:302–307

    Google Scholar 

  40. Taflove A (1995) Computational electrodynamics: the finite-difference time-domain method. Artech House, Norwood

    Google Scholar 

  41. Drezek R, Dunn A, Richards-Kortum R (1999) Light scattering from cells: finite-difference time-domain simulations and goniometric measurements. Appl Optics 38(16):3651–3661

    Article  CAS  Google Scholar 

  42. Tian P, Devor A, Sakadžić S, Dale AM, Boas DA (2011) Monte Carlo simulation of the spatial resolution and depth sensitivity of two-dimensional optical imaging of the brain. J Biomed Opt 16(1):016006

    Article  PubMed  Google Scholar 

  43. Tian P, Teng IC, May LD, Kurz R, Lu K, Scadeng M, Hillman EM, De Crespigny AJ, D’Arceuil HE, Mandeville JB, Marota JJ, Rosen BR, Liu TT, Boas DA, Buxton RB, Dale AM, Devor A (2010) Cortical depth-specific microvascular dilation underlies laminar differences in blood oxygenation level-dependent functional MRI signal. Proc Natl Acad Sci USA 107:15246–15251

    Google Scholar 

  44. Sakadzić S, Yuan S, Dilekoz E, Ruvinskaya S, Vinogradov SA, Ayata C, Boas DA (2009) Simultaneous imaging of cerebral partial pressure of oxygen and blood flow during functional activation and cortical spreading depression. Appl Optics 48(10): D169–D177

    Article  Google Scholar 

  45. Ponticorvo A, Dunn AK (2010) Simultaneous imaging of oxygen tension and blood flow in animals using a digital micromirror device. Opt Express 18(8):8160–8170

    Article  CAS  PubMed  Google Scholar 

  46. Shonat RD, Wachman ES, Niu W, Koretsky AP, Farkas DL (1997) Near-simultaneous hemoglobin saturation and oxygen tension maps in mouse brain using an AOTF microscope. Biophys J 73(3):1223–1231

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  47. Raabe A, Beck J, Gerlach R, Zimmermann M, Seifert V (2003) Near-infrared indocyanine green video angiography: a new method for intraoperative assessment of vascular flow. Neurosurgery 52(1):132–139; discussion 139

    PubMed  Google Scholar 

  48. Dunn AK, Wallace VP, Coleno M, Berns MW, Tromberg BJ (2000) Influence of optical properties on two-photon fluorescence imaging in turbid samples. Appl Optics 39:1194–1201

    Article  CAS  Google Scholar 

  49. Oheim M, Beaurepaire E, Chaigneau E, Mertz J, Charpak S (2001) Two-photon microscopy in brain tissue: parameters influencing the imaging depth. J Neurosci Methods 111(1):29–37

    Article  CAS  PubMed  Google Scholar 

  50. Gan X, Gu M (1999) Effective point-spread function for fast image modeling and processing in microscopic imaging through turbid media. Opt Lett 24:741–743

    Article  CAS  PubMed  Google Scholar 

  51. Theer P, Denk W (2006) On the fundamental imaging-depth limit in two-photon microscopy. J Opt Soc Am 23(12):3139–3149

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA

    Andrew K. Dunn

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  1. Andrew K. Dunn
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Editor information

Editors and Affiliations

  1. University of Zurich, Switzerland

    Bruno Weber

  2. University of Zurich, Switzerland

    Fritjof Helmchen

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Dunn, A.K. (2014). Optical Properties of Neural Tissue. In: Weber, B., Helmchen, F. (eds) Optical Imaging of Neocortical Dynamics. Neuromethods, vol 85. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-785-3_3

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  • DOI: https://doi.org/10.1007/978-1-62703-785-3_3

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-784-6

  • Online ISBN: 978-1-62703-785-3

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