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Functional Monitoring and Imaging in Deep Brain Structures

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Handbook of Neuroengineering
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Abstract

Optical techniques are capable of cell-specific targeting, concurrent multimodal measurements, and multiscale measurements with high temporal and spatial resolution. However, the biggest limiting factor of optical techniques for functional brain monitoring is depth penetration, due to the highly scattering nature of the brain tissue. Without physical access into the brain, optical methods are limited to measuring from the surface, in general, down to about a millimeter in depth. This poses a great limitation for brain monitoring in commonly used animal models, considering a mouse brain is over 6 mm deep. By implanting small-diameter optical fiber probes, or gradient refractive index (GRIN) lenses to deliver and collect light from the brain regions of interest, optical methods can measure from the deep brain structures without hindering the animal from moving and behaving freely. In this chapter, we review hardware enabling optical functional monitoring of deep brain regions. We outline system design considerations, including optical contrast options, spatial resolution, hardware choices, considerations for applications in freely moving animals, and safety considerations. We review some recent work as examples of different system schemes for monitoring calcium signals, voltage signals, and hemodynamics from deep brain structures.

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Abbreviations

BOLD:

blood-oxygen-level-dependent

CCD:

charge coupled device

CMOS:

complementary metal oxide semiconductor

CW:

continuous wave

DBS:

deep brain stimulation

DMD:

digital micromirror device

DRS:

diffuse reflection spectroscopy

FAD:

flavin adenine dinucleotide

FD:

frequency domain

fMRI:

functional magnetic resonance imaging

GECI:

genetically encoded calcium indicator

GEVI:

genetically encoded voltage indicator

GFP:

green fluorescent protein

GPi:

globus pallidus pars interna

GRIN:

gradient refractive index

Hb:

deoxyhemoglobin

HbO:

oxyhemoglobin

LC-SLM:

liquid crystal spatial light modulator

LED:

light-emitting diode

NA:

numerical aperture

NAD:

nicotinamide adenine dinucleotide (oxidized form)

NADH:

nicotinamide adenine dinucleotide (reduced form)

NIR:

near-infrared

NIRS:

near-infrared spectroscopy

PDMS:

polydimethylsiloxane

PET:

positron emitting tomography

PMT:

photomultiplier tube

pO2 :

partial pressure of oxygen

PSF:

point spread function

sCMOS:

scientific complementary metal oxide semiconductor

SFRS:

single fiber reflectance spectroscopy

SiPM:

silicon photomultiplier

sO2 :

oxygen saturation

STN:

sub-thalamic nucleus

SV-PSF:

spatially variant point spread function

TD:

time domain

TEMPO:

trans-membrane electrical measurements performed optically

References

  1. Marshall, J.D., Li, J.Z., Zhang, Y., Gong, Y., St-Pierre, F., Lin, M.Z., Schnitzer, M.J.: Cell-type-specific optical recording of membrane voltage dynamics in freely moving mice. Cell 167, 1650–1662 (2016)

    Article  Google Scholar 

  2. Goense, J., Bohraus, Y., Logothetis, N.K.: fMRI at high spatial resolution: implications for bold-models. Front. Comput. Neurosci. 10, 66 (2016)

    Article  Google Scholar 

  3. Hillman, E.M.: Coupling mechanism and significance of the BOLD signal: a status report. Annu. Rev. Neurosci. 37, 161–181 (2014)

    Article  Google Scholar 

  4. Politis, M., Piccini, P.: Positron emission tomography imaging in neurological disorders. J. Neurol. 259, 1769–1780 (2012)

    Article  Google Scholar 

  5. Gao, Y.-R., Ma, Y., Zhang, Q., Winder, A.T., Liang, Z., Antinori, L., Drew, P.J., Zhang, N.: Time to wake up: studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal. NeuroImage 153, 382–398 (2017)

    Article  Google Scholar 

  6. Guo, Q., Zhou, J., Feng, Q., Lin, R., Gong, H., Luo, Q., Zeng, S., Luo, M., Fu, L.: Multi-channel fiber photometry for population neuronal activity recording, Biomed. Opt. Express 6, 3919–3931 (2015)

    Article  Google Scholar 

  7. Ma, Y., Shaik, M.A., Kim, S.H., Kozberg, M.G., Thibodeaux, D.N., Zhao, H.T., Yu, H., Hillman, E.M.: Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches. Philos. Trans. R. Soc. B: Biol. Sci. 371, 20150360 (2016)

    Article  Google Scholar 

  8. Scott, B.B., Thiberge, S.Y., Guo, C., Tervo, D.G.R., Brody, C.D., Karpova, A.Y., Tank, D.W.: Imaging cortical dynamics in GCaMP transgenic rats with a head-mounted widefield macroscope. Neuron 100, 1045–1058 (2018)

    Article  Google Scholar 

  9. Liang, Z., Ma, Y., Watson, G.D., Zhang, N.: Simultaneous GCaMP6-based fiber photometry and fMRI in rats. J. Neurosci. Methods 289, 31–38 (2017)

    Article  Google Scholar 

  10. Issa, J.B., Haeffele, B.D., Agarwal, A., Bergles, D.E., Young, E.D., Yue, D.T.: Multiscale optical ca2+ imaging of tonal organization in mouse auditory cortex. Neuron 83, 944–959 (2014)

    Article  Google Scholar 

  11. Quaresima, V., Ferrari, M.: Functional near-infrared spectroscopy (fNIRS) for assessing cerebral cortex function during human behavior in natural/social situations: a concise review. Organ. Res. Methods 22, 46–68 (2019)

    Article  Google Scholar 

  12. Ohayon, S., Caravaca-Aguirre, A., Piestun, R., DiCarlo, J.J.: Minimally invasive multimode optical fiber microendoscope for deep brain fluorescence imaging. Biomed. Opt. Express 9, 1492–1509 (2018)

    Article  Google Scholar 

  13. Xu, M., Wang, L.V.: Photoacoustic imaging in biomedicine. Rev. Sci. Instrum. 77, 041101 (2006)

    Article  Google Scholar 

  14. Yao, J., Wang, L.V.: Photoacoustic brain imaging: from microscopic to macroscopic scales. Neurophotonics 1, 011003 (2014)

    Article  Google Scholar 

  15. Zhang, P., Li, L., Lin, L., Hu, P., Shi, J., He, Y., Zhu, L., Zhou, Y., Wang, L.V.: High-resolution deep functional imaging of the whole mouse brain by photoacoustic computed tomography in vivo. J. Biophotonics 11, e201700024 (2018)

    Article  Google Scholar 

  16. Lv, J., Li, S., Zhang, J., Duan, F., Wu, Z., Chen, R., Chen, M., Huang, S., Ma, H., Nie, L.: In vivo photoacoustic imaging dynamically monitors the structural and functional changes of ischemic stroke at a very early stage. Theranostics 10, 816 (2020)

    Article  Google Scholar 

  17. Rao, B., Zhang, R., Li, L., Shao, J.-Y., Wang, L.V.: Photoacoustic imaging of voltage responses beyond the optical diffusion limit. Sci. Rep. 7, 1–10 (2017)

    Article  Google Scholar 

  18. Tang, J., Coleman, J.E., Dai, X., Jiang, H.: Wearable 3-d photoacoustic tomography for functional brain imaging in behaving rats. Sci. Rep. 6, 25470 (2016)

    Article  Google Scholar 

  19. Chen, Q., Xie, H., Xi, L.: Wearable optical resolution photoacoustic microscopy. J. Biophotonics 12, e201900066 (2019)

    Article  Google Scholar 

  20. Sparta, D.R., Stamatakis, A.M., Phillips, J.L., Hovelsø, N., Van Zessen, R., Stuber, G.D.: Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits. Nat. Protoc. 7, 12 (2012)

    Article  Google Scholar 

  21. Resendez, S.L., Jennings, J.H., Ung, R.L., Namboodiri, V.M.K., Zhou, Z.C., Otis, J.M., Nomura, H., McHenry, J.A., Kosyk, O., Stuber, G.D.: Visualization of cortical, subcortical and deep brain neural circuit dynamics during naturalistic mammalian behavior with head-mounted microscopes and chronically implanted lenses. Nat. Protoc. 11, 566 (2016)

    Article  Google Scholar 

  22. Keiser, G.: Biophotonics. Springer, Singapore (2016)

    Book  Google Scholar 

  23. Calabro, K.W., Bigio, I.J.: Influence of the phase function in generalized diffuse reflectance models: review of current formalisms and novel observations. J. Biomed. Opt. 19, 075005 (2014)

    Article  Google Scholar 

  24. Cohen, L., Keynes, R., Hille, B.: Light scattering and birefringence changes during nerve activity. Nature 218, 438 (1968)

    Article  Google Scholar 

  25. Foust, A.J., Rector, D.M.: Optically teasing apart neural swelling and depolarization. Neuroscience 145, 887–899 (2007)

    Article  Google Scholar 

  26. Badreddine, A.H., Jordan, T., Bigio, I.J.: Real-time imaging of action potentials in nerves using changes in birefringence. Biomed. Opt. Express 7, 1966–1973 (2016)

    Article  Google Scholar 

  27. Liu, H., Radhakrishnan, H., Senapati, A.K., Hagains, C.E., Peswani, D., Mathker, A., Peng, Y.B.: Near infrared and visible spectroscopic measurements to detect changes in light scattering and hemoglobin oxygen saturation from rat spinal cord during peripheral stimulation. NeuroImage 40, 217–227 (2008)

    Article  Google Scholar 

  28. Sharma, V., He, J.-W., Narvenkar, S., Peng, Y.B., Liu, H.: Quantification of light reflectance spectroscopy and its application: determination of hemodynamics on the rat spinal cord and brain induced by electrical stimulation. NeuroImage 56, 1316–1328 (2011)

    Article  Google Scholar 

  29. He, J.-W., Liu, H., Peng, Y.: Hemodynamic and light-scattering changes of rat spinal cord and primary somatosensory cortex in response to innocuous and noxious stimuli. Brain Sci. 5, 400–418 (2015)

    Article  Google Scholar 

  30. Gratton, G., Fabiani, M.: Fast optical imaging of human brain function. Front. Hum. Neurosci. 4, 52 (2010)

    Google Scholar 

  31. Zhang, Y., Yao, L., Yang, F., Yang, S., Edathodathil, A., Xi, W., Roe, A.W., Li, P.: INS-fOCT: a label-free, all-optical method for simultaneously manipulating and mapping brain function, Neurophotonics 7, 015014 (2020)

    Article  Google Scholar 

  32. Delpy, D.T., Cope, M., van der Zee, P., Arridge, S., Wray, S., Wyatt, J.: Estimation of optical pathlength through tissue from direct time of flight measurement. Phys. Med. Biol. 33, 1433 (1988)

    Article  Google Scholar 

  33. Cuccia, D., Frostig, R.D., Abookasis, D., Tromberg, B.J.: Quantitative in vivo imaging of tissue absorption, scattering, and hemoglobin concentration in rat cortex using spatially modulated structured light. In: In Vivo Optical Imaging of Brain Function. CRC Press/Taylor & Francis, Boca Raton (2009)

    Book  Google Scholar 

  34. Scholkmann, F., Kleiser, S., Metz, A.J., Zimmermann, R., Pavia, J.M., Wolf, U., Wolf, M.: A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. NeuroImage 85, 6–27 (2014)

    Article  Google Scholar 

  35. Prahl, S.: Assorted spectra. https://omlc.org/spectra/. Accessed 03 May 2020

  36. Mason, M.G., Nicholls, P., Cooper, C.E.: Re-evaluation of the near infrared spectra of mitochondrial cytochrome c oxidase: implications for non invasive in vivo monitoring of tissues. Biochimica et Biophysica Acta (BBA)-Bioenergetics 1837, 1882–1891 (2014)

    Google Scholar 

  37. Hillman, E.M.: Optical brain imaging in vivo: techniques and applications from animal to man. J. Biomed. Opt. 12, 051402 (2007)

    Article  Google Scholar 

  38. Noor, M.S., Yu, L., Murari, K., Kiss, Z.H.: Neurovascular coupling during deep brain stimulation. Brain Stimulation 13, 916–927 (2020)

    Article  Google Scholar 

  39. Weber, B., Helmchen, F.: Optical Imaging of Neocortical Dynamics. Springer, New York (2014)

    Book  Google Scholar 

  40. Nakai, J., Ohkura, M., Imoto, K.: A high signal-to-noise Ca2+ probe composed of a single green fluorescent protein. Nat. Biotechnol. 19, 137–141 (2001)

    Article  Google Scholar 

  41. Chen, T.-W., Wardill, T.J., Sun, Y., Pulver, S.R., Renninger, S.L., Baohan, A., Schreiter, E.R., Kerr, R.A., Orger, M.B., Jayaraman, V., et al.: Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013)

    Article  Google Scholar 

  42. Dana, H., Sun, Y., Mohar, B., Hulse, B.K., Kerlin, A.M., Hasseman, J.P., Tsegaye, G., Tsang, A., Wong, A., Patel, R., et al.: High-performance calcium sensors for imaging activity in neuronal populations and microcompartments. Nat. Methods 16, 649–657 (2019)

    Article  Google Scholar 

  43. Dana, H., Mohar, B., Sun, Y., Narayan, S., Gordus, A., Hasseman, J.P., Tsegaye, G., Holt, G.T., Hu, A., Walpita, D., et al.: Sensitive red protein calcium indicators for imaging neural activity. Elife 5, e12727 (2016)

    Article  Google Scholar 

  44. Akemann, W., Mutoh, H., Knöpfel, T.: Fluorescent indicators for functional optical imaging. In: Optical Imaging of Neocortical Dynamics, pp. 53–72. Springer, New York (2014)

    Google Scholar 

  45. Hamel, E.J., Grewe, B.F., Parker, J.G., Schnitzer, M.J.: Cellular level brain imaging in behaving mammals: an engineering approach. Neuron 86, 140–159 (2015)

    Article  Google Scholar 

  46. Xu, Y., Zou, P., Cohen, A.E.: Voltage imaging with genetically encoded indicators. Curr. Opin. Chem. Biol. 39, 1–10 (2017)

    Article  Google Scholar 

  47. Knöpfel, T., Song, C.: Optical voltage imaging in neurons: moving from technology development to practical tool. Nat. Rev. Neurosci. 20, 719–727 (2019)

    Article  Google Scholar 

  48. Monici, M.: Cell and tissue autofluorescence research and diagnostic applications. Biotechnol. Annu. Rev. 11, 227–256 (2005)

    Article  Google Scholar 

  49. Jones, J.D., Ramser, H.E., Woessner, A.E., Quinn, K.P.: In vivo multiphoton microscopy detects longitudinal metabolic changes associated with delayed skin wound healing. Commun. Biol. 1, 1–8 (2018)

    Article  Google Scholar 

  50. Yaseen, M.A., Sakadžić, S., Wu, W., Becker, W., Kasischke, K.A., Boas, D.A.: In vivo imaging of cerebral energy metabolism with two-photon fluorescence lifetime microscopy of nadh. Biomed. Opt. Express 4, 307–321 (2013)

    Article  Google Scholar 

  51. Griffiths, J., Robinson, S.: The OxyLite: a fibre-optic oxygen sensor. Br. J. Radiol. 72, 627–630 (1999)

    Article  Google Scholar 

  52. Sakadžić, S., Roussakis, E., Yaseen, M.A., Mandeville, E.T., Srinivasan, V.J., Arai, K., Ruvinskaya, S., Devor, A., Lo, E.H., Vinogradov, S.A., et al.: Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue, Nat. Methods 7, 755–759 (2010)

    Article  Google Scholar 

  53. Yizhar, O., Fenno, L.E., Davidson, T.J., Mogri, M., Deisseroth, K.: Optogenetics in neural systems. Neuron 71, 9–34 (2011)

    Article  Google Scholar 

  54. Gunaydin, L.A., Grosenick, L., Finkelstein, J.C., Kauvar, I.V., Fenno, L.E., Adhikari, A., Lammel, S., Mirzabekov, J.J., Airan, R.D., Zalocusky, K.A., Tye, K.M., Anikeeva, P., Malenka, R.C., Deisseroth, K.: Natural neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014)

    Article  Google Scholar 

  55. Lee, K., Bohnert, S., Wu, Y., Vair, C., Mikler, J., Teskey, G.C., Dunn, J.F.: Assessment of brain oxygenation imbalance following soman exposure in rats. Neurotoxicology 65, 28–37 (2018)

    Article  Google Scholar 

  56. Musolino, S.T., Schartner, E.P., Hutchinson, M.R., Salem, A.: Improved method for optical fiber temperature probe implantation in brains of free-moving rats. J. Neurosci. Methods 313, 24–28 (2019)

    Article  Google Scholar 

  57. Cui, G., Jun, S.B., Jin, X., Luo, G., Pham, M.D., Lovinger, D.M., Vogel, S.S., Costa, R.M.: Deep brain optical measurements of cell type–specific neural activity in behaving mice. Nat. Protoc. 9, 1213–1228 (2014)

    Article  Google Scholar 

  58. Simone, K., Füzesi, T., Rosenegger, D., Bains, J.S., Murari, K.: Open-source, cost-effective system for low-light in vivo fiber photometry. Neurophotonics 5, 025006 (2018)

    Article  Google Scholar 

  59. Meng, C., Zhou, J., Papaneri, A., Peddada, T., Xu, K., Cui, G.: Spectrally resolved fiber photometry for multi-component analysis of brain circuits. Neuron 98, 707–717 (2018)

    Article  Google Scholar 

  60. Jobsis, F.F.: Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science 198, 1264–1267 (1977)

    Article  Google Scholar 

  61. Vo-Dinh, T.: Biomedical Photonics Handbook. CRC Press, Boca Raton (2014)

    Book  Google Scholar 

  62. Johns, M., Giller, C.A., German, D.C., Liu, H.: Determination of reduced scattering coefficient of biological tissue from a needle-like probe. Opt. Express 13, 4828–4842 (2005)

    Article  Google Scholar 

  63. Tabrizi, S.H., Farzaneh, F., Aghamiri, S.M.R., Arab, M., Hosseini, M., Ashrafganjoei, T., Chehrazi, M.: Comparison between performance of single-fiber reflectance spectroscopy (SFRS) system and colposcopy: a phase III trial. Lasers Med. Sci. 32, 2139–2144 (2017)

    Article  Google Scholar 

  64. Piao, D., Ritchey, J.W., Holyoak, G.R., Wall, C.R., Sultana, N., Murray, J.K., Bartels, K.E.: In vivo percutaneous reflectance spectroscopy of fatty liver development in rats suggests that the elevation of the scattering power is an early indicator of hepatic steatosis. J. Innov. Opt. Health Sci. 11, 1850019 (2018)

    Article  Google Scholar 

  65. Rejmstad, P., Zsigmond, P., Wårdell, K.: Oxygen saturation estimation in brain tissue using diffuse reflectance spectroscopy along stereotactic trajectories. Opt. Express 25, 8192–8201 (2017)

    Article  Google Scholar 

  66. DePaoli, D., Goetz, L., Gagnon, D., Maranon, G., Prud’homme, M., Cantin, L., Parent, M., Côté, D.C.: Intraoperative fiber optic guidance during chronic electrode implantation in deep brain stimulation neurosurgery: proof of concept in primates. J. Neurosurg. 1, 1–10 (2019)

    Google Scholar 

  67. Yu, L., Wu, Y., Dunn, J.F., Murari, K.: In-vivo monitoring of tissue oxygen saturation in deep brain structures using a single fiber optical system. Biomed. Opt. Express 7, 4685–4694 (2016)

    Article  Google Scholar 

  68. Delpy, D., Cope, M.: Quantification in tissue near–infrared spectroscopy. Philos. Trans. R. Soc. Lond. Ser. B: Biol. Sci. 352, 649–659 (1997)

    Article  Google Scholar 

  69. Kanick, S.C., Van der Leest, C., Aerts, J.G., Hoogsteden, H.C., Kaščáková, S., Sterenborg, H.J., Amelink, A.: Integration of single-fiber reflectance spectroscopy into ultrasound-guided endoscopic lung cancer staging of mediastinal lymph nodes. J. Biomed. Opt. 15, 017004–017004 (2010)

    Article  Google Scholar 

  70. Denkçeken, T., Şimşek, T., Erdoğan, G., Peştereli, E., Karaveli, Ş, Özel, D., Bilge, U., Canpolat, M.: Elastic light single-scattering spectroscopy for the detection of cervical precancerous ex vivo. IEEE Trans. Biomed. Eng. 60, 123–127 (2012)

    Article  Google Scholar 

  71. Piao, D., McKeirnan, K.L., Sultana, N., Breshears, M.A., Zhang, A., Bartels, K.E.: Percutaneous single-fiber reflectance spectroscopy of canine intervertebral disc: is there a potential for in situ probing of mineral degeneration? Lasers Surg. Med. 46, 508–519 (2014)

    Article  Google Scholar 

  72. Zhang, X.U., Faber, D.J., Post, A.L., van Leeuwen, T.G., Sterenborg, H.J.: Refractive index measurement using single fiber reflectance spectroscopy. J. Biophotonics 12, e201900019 (2019)

    Article  Google Scholar 

  73. Yu, L., Thurston, E.M., Hashem, M., Dunn, J.F., Whelan, P.J., Murari, K.: Fiber photometry for monitoring cerebral oxygen saturation in freely-moving rodents. Biomed. Opt. Express 11, 3491–3506 (2020)

    Article  Google Scholar 

  74. Tang, Q., Tsytsarev, V., Liang, C.-P., Akkentli, F., Erzurumlu, R.S., Chen, Y.: In vivo voltage-sensitive dye imaging of subcortical brain function. Sci. Rep. 5, 17325 (2015)

    Article  Google Scholar 

  75. Almog, I.F., Chen, F.-D., Senova, S., Fomenko, A., Gondard, E., Sacher, W.D., Lozano, A.M., Poon, J.K.: Full-field swept-source optical coherence tomography and neural tissue classification for deep brain imaging. 13 (2020). https://onlinelibrary.wiley.com/doi/full/10.1002/jbio.201960083

  76. Yuan, W., Chen, D., Sarabia-Estrada, R., Guerrero-Cázares, H., Li, D., Quiñones-Hinojosa, A., Li, X.: Theranostic OCT microneedle for fast ultrahigh-resolution deep-brain imaging and efficient laser ablation in vivo. Sci. Adv. 6, eaaz9664 (2020)

    Google Scholar 

  77. Bocarsly, M.E., Jiang, W.-C., Wang, C., Dudman, J.T., Ji, N., Aponte, Y.: Minimally invasive microendoscopy system for in vivo functional imaging of deep nuclei in the mouse brain. Biomed. Opt. Express 6, 4546–4556 (2015)

    Article  Google Scholar 

  78. Sato, M., Motegi, Y., Yagi, S., Gengyo-Ando, K., Ohkura, M., Nakai, J.: Fast varifocal two-photon microendoscope for imaging neuronal activity in the deep brain. Biomed. Opt. Express 8, 4049–4060 (2017)

    Article  Google Scholar 

  79. Meng, G., Liang, Y., Sarsfield, S., Jiang, W.-C., Lu, R., Dudman, J.T., Aponte, Y., Ji, N.: High-throughput synapse-resolving two-photon fluorescence microendoscopy for deep-brain volumetric imaging in vivo. Elife 8, e40805 (2019)

    Article  Google Scholar 

  80. Barbera, G., Liang, B., Zhang, L., Li, Y., Lin, D.-T.: A wireless miniscope for deep brain imaging in freely moving mice. J. Neurosci. Methods 323, 56–60 (2019)

    Article  Google Scholar 

  81. Vasquez-Lopez, S.A., Turcotte, R., Koren, V., Plöschner, M., Padamsey, Z., Booth, M.J., Čižmár, T., Emptage, N.J.: Subcellular spatial resolution achieved for deep-brain imaging in vivo using a minimally invasive multimode fiber. Light: Sci. Appl. 7, 110 (2018)

    Article  Google Scholar 

  82. Kim, G., Nagarajan, N., Pastuzyn, E., Jenks, K., Capecchi, M., Shepherd, J., Menon, R.: Deep-brain imaging via epi-fluorescence computational cannula microscopy. Sci. Rep. 7, 44791 (2017)

    Article  Google Scholar 

  83. Yang, G., Pan, F., Parkhurst, C.N., Grutzendler, J., Gan, W.-B.: Thinned-skull cranial window technique for long-term imaging of the cortex in live mice. Nat. Protoc. 5, 201 (2010)

    Article  Google Scholar 

  84. Shih, A.Y., Mateo, C., Drew, P.J., Tsai, P.S., Kleinfeld, D.: A polished and reinforced thinned-skull window for long-term imaging of the mouse brain. JoVE (J. Vis. Exp.) (61) (2012). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3460568/pdf/jove-61-3742.pdf

  85. Kyweriga, M., Sun, J., Wang, S., Kline, R., Mohajerani, M.H.: A large lateral craniotomy procedure for mesoscale wide-field optical imaging of brain activity. JoVE (J. Vis. Exp.) (123) (2017). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607895/pdf/jove-123-52642.pdf

  86. Heo, C., Park, H., Kim, Y.-T., Baeg, E., Kim, Y.H., Kim, S.-G., Suh, M.: A soft, transparent, freely accessible cranial window for chronic imaging and electrophysiology. Sci. Rep. 6, 1–11 (2016)

    Article  Google Scholar 

  87. de Groot, A., van den Boom, B.J., van Genderen, R.M., Coppens, J., van Veldhuijzen, J., Bos, J., Hoedemaker, H., Negrello, M., Willuhn, I., De Zeeuw, C.I., et al.: NINscope, a versatile miniscope for multi-region circuit investigations. eLife 9, e49987 (2020)

    Article  Google Scholar 

  88. Nazempour, R., Zhang, Q., Fu, R., Sheng, X.: Biocompatible and implantable optical fibers and waveguides for biomedicine. Materials 11, 1283 (2018)

    Article  Google Scholar 

  89. Werner, L.: Biocompatibility of intraocular lens materials. Curr. Opin. Ophthalmol. 19, 41–49 (2008)

    Article  Google Scholar 

  90. Senova, S., Scisniak, I., Chiang, C.-C., Doignon, I., Palfi, S., Chaillet, A., Martin, C., Pain, F.: Experimental assessment of the safety and potential efficacy of high irradiance photostimulation of brain tissues. Sci. Rep. 7, 43997 (2017)

    Article  Google Scholar 

  91. Chernov, M.M., Chen, G., Roe, A.W.: Histological assessment of thermal damage in the brain following infrared neural stimulation. Brain Stimulation 7, 476–482 (2014)

    Article  Google Scholar 

  92. Ilic, S., Leichliter, S., Streeter, J., Oron, A., DeTaboada, L., Oron, U.: Effects of power densities, continuous and pulse frequencies, and number of sessions of low-level laser therapy on intact rat brain. Photomed. Laser Ther. 24, 458–466 (2006)

    Article  Google Scholar 

  93. Yarmolenko, P.S., Moon, E.J., Landon, C., Manzoor, A., Hochman, D.W., Viglianti, B.L., Dewhirst, M.W.: Thresholds for thermal damage to normal tissues: an update, Int. J. Hyperth. 27, 320–343 (2011)

    Article  Google Scholar 

  94. Godley, B.F., Shamsi, F.A., Liang, F.-Q., Jarrett, S.G., Davies, S., Boulton, M.: Blue light induces mitochondrial DNA damage and free radical production in epithelial cells. J. Biol. Chem. 280, 21061–21066 (2005)

    Article  Google Scholar 

  95. Kuse, Y., Ogawa, K., Tsuruma, K., Shimazawa, M., Hara, H.: Damage of photoreceptor-derived cells in culture induced by light emitting diode-derived blue light. Sci. Rep. 4, 5223 (2014)

    Article  Google Scholar 

  96. Stockley, J.H., Evans, K., Matthey, M., Volbracht, K., Agathou, S., Mukanowa, J., Burrone, J., Káradóttir, R.T.: Surpassing light-induced cell damage in vitro with novel cell culture media. Sci. Rep. 7, 1–11 (2017)

    Article  Google Scholar 

  97. Dixit, R., Cyr, R.: Cell damage and reactive oxygen species production induced by fluorescence microscopy: effect on mitosis and guidelines for non-invasive fluorescence microscopy. Plant J. 36, 280–290 (2003)

    Article  Google Scholar 

  98. Yu, H., Senarathna, J., Tyler, B.M., Thakor, N.V., Pathak, A.P.: Miniaturized optical neuroimaging in unrestrained animals. NeuroImage 113, 397–406 (2015)

    Article  Google Scholar 

  99. Zong, W., Wu, R., Li, M., Hu, Y., Li, Y., Li, J., Rong, H., Wu, H., Xu, Y., Lu, Y., et al.: Fast high-resolution miniature two-photon microscopy for brain imaging in freely behaving mice. Nat. Methods 14, 713 (2017)

    Article  Google Scholar 

  100. Liberti III, W.A., Perkins, L.N., Leman, D.P., Gardner, T.J.: An open source, wireless capable miniature microscope system. J. Neural Eng. 14, 045001 (2017)

    Article  Google Scholar 

  101. Jacob, A.D., Ramsaran, A.I., Mocle, A.J., Tran, L.M., Yan, C., Frankland, P.W., Josselyn, S.A.: A compact head-mounted endoscope for in vivo calcium imaging in freely behaving mice. Curr. Protoc. Neurosci. 84, e51 (2018)

    Article  Google Scholar 

  102. Zhang, L., Liang, B., Barbera, G., Hawes, S., Zhang, Y., Stump, K., Baum, I., Yang, Y., Li, Y., Lin, D.-T.: Miniscope GRIN lens system for calcium imaging of neuronal activity from deep brain structures in behaving animals. Curr. Protoc. Neurosci. 86, e56 (2019)

    Article  Google Scholar 

  103. Cai, D.J., Aharoni, D., Shuman, T., Shobe, J., Biane, J., Song, W., Wei, B., Veshkini, M., La-Vu, M., Lou, J., et al.: A shared neural ensemble links distinct contextual memories encoded close in time. Nature 534, 115–118 (2016)

    Article  Google Scholar 

  104. Skocek, O., Nöbauer, T., Weilguny, L., Traub, F.M., Xia, C.N., Molodtsov, M.I., Grama, A., Yamagata, M., Aharoni, D., Cox, D.D., et al.: High-speed volumetric imaging of neuronal activity in freely moving rodents. Nat. Methods 15, 429 (2018)

    Article  Google Scholar 

  105. Miao, P., Tong, S., Lu, H., Liu, Q., Li, Y.: Laser speckle contrast imaging of cerebral blood flow in freely moving animals, J. Biomed. Opt. 16, 090502 (2011)

    Article  Google Scholar 

  106. Senarathna, J., Yu, H., Deng, C., Zou, A.L., Issa, J.B., Hadjiabadi, D.H., Gil, S., Wang, Q., Tyler, B.M., Thakor, N.V., et al.: A miniature multi-contrast microscope for functional imaging in freely behaving animals. Nat. Commun. 10, 99 (2019)

    Article  Google Scholar 

  107. Musolino, S., Schartner, E.P., Tsiminis, G., Salem, A., Monro, T.M., Hutchinson, M.R.: Portable optical fiber probe for in vivo brain temperature measurements. Biomedical Opt. Express 7, 3069–3077 (2016)

    Article  Google Scholar 

  108. Photometry systems. http://doriclenses.com/life-sciences/315-photometry-systems. Accessed 03 May 2020

  109. Pisano, F., Pisanello, M., Lee, S.J., Lee, J., Maglie, E., Balena, A., Sileo, L., Spagnolo, B., Bianco, M., Hyun, M., et al.: Depth-resolved fiber photometry with a single tapered optical fiber implant. Nat. Methods 16, 1185–1192 (2019)

    Article  Google Scholar 

  110. Pisanello, F., Mandelbaum, G., Pisanello, M., Oldenburg, I.A., Sileo, L., Markowitz, J.E., Peterson, R.E., Della Patria, A., Haynes, T.M., Emara, M.S., et al.: Dynamic illumination of spatially restricted or large brain volumes via a single tapered optical fiber. Nat. Neurosci. 20, 1180–1188 (2017)

    Article  Google Scholar 

  111. Yu, L., Noor, M.S., Kiss, Z.H., Murari, K.: Hemodynamic monitoring in different cortical layers with a single fiber optical system. In: Neural Imaging and Sensing 2018, vol. 10481, p. 104811H. International Society for Optics and Photonics. SPIE location is Bellingham, Washington (2018)

    Google Scholar 

  112. Miniature microscope solutions for circuit neuroscience. https://www.inscopix.com/. Accessed 03 May 2020

  113. Miniaturized fluorescence microscopy. http://doriclenses.com/life-sciences/280-miniaturized-fluorescence-microscopy. Accessed 03 May 2020

  114. Aharoni, D.B., Hoogland, T.: Circuit investigations with open-source miniaturized microscopes: past, present and future. Front. Cell. Neurosci. 13, 141 (2019)

    Article  Google Scholar 

  115. Canales, A., Jia, X., Froriep, U.P., Koppes, R.A., Tringides, C.M., Selvidge, J., Lu, C., Hou, C., Wei, L., Fink, Y., et al.: Multifunctional fibers for simultaneous optical, electrical and chemical interrogation of neural circuits in vivo. Nat. Biotechnol. 33, 277–284 (2015)

    Article  Google Scholar 

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Yu, L., Murari, K. (2021). Functional Monitoring and Imaging in Deep Brain Structures. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_135-1

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