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Two-photon calcium imaging of neuronal activity

Nature Reviews Methods Primers volume 2, Article number: 67 (2022) Cite this article

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Abstract

In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.

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Fig. 1: The principles of fluorescence calcium imaging.
Fig. 2: Types of calcium indicators.
Fig. 3: Expressing GECIs in the brain and common window preparations for in vivo imaging.
Fig. 4: Components of a 2P microscope, adaptive optics and scanning approaches for high-speed and volumetric 2PCI.
Fig. 5: Examples of good and bad cranial windows and fields of view.
Fig. 6: Illustration of analysis pipeline concepts.

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References

  1. Grewe, B. F. & Helmchen, F. Optical probing of neuronal ensemble activity. Curr. Opin. Neurobiol. 19, 9042–9052 (2009).

    Google Scholar 

  2. Lecoq, J., Orlova, N. & Grewe, B. F. Wide. Fast. Deep: recent advances in multiphoton microscopy of in vivo neuronal activity. J. Neurosci. 39, 9042–9052 (2019).

    Google Scholar 

  3. Gobel, W. & Helmchen, F. In vivo calcium imaging of neural network function. Physiology 22, 358–365 (2007).

    Google Scholar 

  4. Grienberger, C. & Konnerth, A. Imaging calcium in neurons. Neuron 73, 862–885 (2012).

    Google Scholar 

  5. Wei, Z. et al. A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology. PLoS Comput. Biol. 16, e1008198 (2020).

    Google Scholar 

  6. Wilt, B. A. et al. Advances in light microscopy for neuroscience. Annu. Rev. Neurosci. 32, 435–506 (2009).

    Google Scholar 

  7. Kondo, M., Kobayashi, K., Ohkura, M., Nakai, J. & Matsuzaki, M. Two-photon calcium imaging of the medial prefrontal cortex and hippocampus without cortical invasion. eLife 6, e26839 (2017).

    Google Scholar 

  8. Grynkiewicz, G., Poenie, M. & Tsien, R. Y. A new generation of Ca2+ indicators with greatly improved fluorescence properties. J. Biol. Chem. 260, 3440–3450 (1985).

    Google Scholar 

  9. Tsien, R. Y. New calcium indicators and buffers with high selectivity against magnesium and protons: design, synthesis, and properties of prototype structures. Biochemistry 19, 2396–2404 (1980).

    Google Scholar 

  10. Paredes, R. M., Etzler, J. C., Watts, L. T., Zheng, W. & Lechleiter, J. D. Chemical calcium indicators. Methods 46, 143–151 (2008).

    Google Scholar 

  11. Helmchen, F., Borst, J. G. & Sakmann, B. Calcium dynamics associated with a single action potential in a CNS presynaptic terminal. Biophys. J. 72, 1458–1471 (1997).

    ADS  Google Scholar 

  12. Garaschuk, O., Milos, R. & Konnerth, A. Targeted bulk-loading of fluorescent indicators for two-photon brain imaging in vivo. Nat. Protoc. 1, 380–386 (2006).

    Google Scholar 

  13. Golshani, P. & Portera-Cailliau, C. In vivo 2-photon calcium imaging in layer 2/3 of mice. J. Vis. Exp. https://doi.org/10.3791/681 (2008).

    Article  Google Scholar 

  14. Tsien, R. Y. The green fluorescent protein. Annu. Rev. Biochem. 67, 509–544 (1998).

    Google Scholar 

  15. Mank, M. & Griesbeck, O. Genetically encoded calcium indicators. Chem. Rev. 108, 1550–1564 (2008).

    Google Scholar 

  16. Lutcke, H. et al. Optical recording of neuronal activity with a genetically-encoded calcium indicator in anesthetized and freely moving mice. Front. Neural Circuits 4, 9 (2010).

    Google Scholar 

  17. Looger, L. L. & Griesbeck, O. Genetically encoded neural activity indicators. Curr. Opin. Neurobiol. 22, 18–23 (2012).

    Google Scholar 

  18. Tian, L., Akerboom, J., Schreiter, E. R. & Looger, L. L. Neural activity imaging with genetically encoded calcium indicators. Prog. Brain Res. 196, 79–94 (2012).

    Google Scholar 

  19. Miyawaki, A. et al. Fluorescent indicators for Ca2+ based on green fluorescent proteins and calmodulin. Nature 388, 882–887 (1997).

    ADS  Google Scholar 

  20. Mank, M. et al. A genetically encoded calcium indicator for chronic in vivo two-photon imaging. Nat. Methods 5, 805–811 (2008).

    Google Scholar 

  21. Baird, G. S., Zacharias, D. A. & Tsien, R. Y. Circular permutation and receptor insertion within green fluorescent proteins. Proc. Natl Acad. Sci. USA 96, 11241–11246 (1999).

    ADS  Google Scholar 

  22. 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).

    Google Scholar 

  23. Zhang, Y. et al. Fast and sensitive GCaMP calcium indicators for imaging neural populations. Preprint at bioRxiv https://doi.org/10.1101/2021.11.08.467793 (2021).

    Article  Google Scholar 

  24. Dana, H. et al. Sensitive red protein calcium indicators for imaging neural activity. eLife 5, e12727 (2016).

    Google Scholar 

  25. Inoue, M. et al. Rational engineering of XCaMPs, a multicolor GECI suite for in vivo imaging of complex brain circuit dynamics. Cell 177, 1346–1360.e24 (2019).

    Google Scholar 

  26. Mohr, M. A. et al. jYCaMP: an optimized calcium indicator for two-photon imaging at fiber laser wavelengths. Nat. Methods 17, 694–697 (2020).

    Google Scholar 

  27. Shemesh, O. A. et al. Precision calcium imaging of dense neural populations via a cell-body-targeted calcium indicator. Neuron 107, 470–486.e11 (2020).

    Google Scholar 

  28. Chen, Y. et al. Soma-targeted imaging of neural circuits by ribosome tethering. Neuron 107, 454–469.e6 (2020).

    Google Scholar 

  29. Broussard, G. J. et al. In vivo measurement of afferent activity with axon-specific calcium imaging. Nat. Neurosci. 21, 1272–1280 (2018).

    Google Scholar 

  30. Lacefield, C. O., Pnevmatikakis, E. A., Paninski, L. & Bruno, R. M. Reinforcement learning recruits somata and apical dendrites across layers of primary sensory cortex. Cell Rep. 26, 2000–2008.e2 (2019).

    Google Scholar 

  31. Lee, K. S., Vandemark, K., Mezey, D., Shultz, N. & Fitzpatrick, D. Functional synaptic architecture of callosal inputs in mouse primary visual cortex. Neuron 101, 421–428.e5 (2019).

    Google Scholar 

  32. Keiser, M. S., Chen, Y. H. & Davidson, B. L. Techniques for intracranial stereotaxic injections of adeno-associated viral vectors in adult mice. Curr. Protoc. Mouse Biol. 8, e57 (2018).

    Google Scholar 

  33. He, C. X., Arroyo, E. D., Cantu, D. A., Goel, A. & Portera-Cailliau, C. A versatile method for viral transfection of calcium indicators in the neonatal mouse brain. Front. Neural Circuits 12, 56 (2018).

    Google Scholar 

  34. Aschauer, D. F., Kreuz, S. & Rumpel, S. Analysis of transduction efficiency, tropism and axonal transport of AAV serotypes 1, 2, 5, 6, 8 and 9 in the mouse brain. PLoS ONE 8, e76310 (2013).

    ADS  Google Scholar 

  35. Graybuck, L. T. et al. Enhancer viruses for combinatorial cell-subclass-specific labeling. Neuron 109, 1449–1464.e13 (2021).

    Google Scholar 

  36. Mich, J. K. et al. Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex. Cell Rep. 34, 108754 (2021).

    Google Scholar 

  37. Haery, L. et al. Adeno-associated virus technologies and methods for targeted neuronal manipulation. Front. Neuroanat. 13, 93 (2019).

    Google Scholar 

  38. Daigle, T. L. et al. A suite of transgenic driver and reporter mouse lines with enhanced brain-cell-type targeting and functionality. Cell 174, 465–480.e22 (2018).

    Google Scholar 

  39. Challis, R. C. et al. Systemic AAV vectors for widespread and targeted gene delivery in rodents. Nat. Protoc. 14, 379–414 (2019).

    Google Scholar 

  40. Mathiesen, S. N., Lock, J. L., Schoderboeck, L., Abraham, W. C. & Hughes, S. M. CNS transduction benefits of AAV-PHP.eB over AAV9 are dependent on administration route and mouse strain. Mol. Ther. Methods Clin. Dev. 19, 447–458 (2020).

    Google Scholar 

  41. Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

    ADS  Google Scholar 

  42. Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881 (2009).

    Google Scholar 

  43. Dana, H. et al. Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PLoS ONE 9, e108697 (2014).

    ADS  Google Scholar 

  44. Madisen, L. et al. Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85, 942–958 (2015).

    Google Scholar 

  45. Steinmetz, N. A. et al. Aberrant cortical activity in multiple GCaMP6-expressing transgenic mouse lines. eNeuro 4, ENEURO.0207-17.2017 (2017).

    Google Scholar 

  46. Holtmaat, A. et al. Long-term, high-resolution imaging in the mouse neocortex through a chronic cranial window. Nat. Protoc. 4, 1128–1144 (2009).

    Google Scholar 

  47. 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, 201–208 (2010).

    Google Scholar 

  48. Xu, H. T., Pan, F., Yang, G. & Gan, W. B. Choice of cranial window type for in vivo imaging affects dendritic spine turnover in the cortex. Nat. Neurosci. 10, 549–551 (2007).

    Google Scholar 

  49. Isshiki, M. & Okabe, S. Evaluation of cranial window types for in vivo two-photon imaging of brain microstructures. Microscopy 63, 53–63 (2014).

    Google Scholar 

  50. Mostany, R. & Portera-Cailliau, C. A craniotomy surgery procedure for chronic brain imaging. J. Vis. Exp. https://doi.org/10.3791/680 (2008).

    Article  Google Scholar 

  51. Ghanbari, L. et al. Cortex-wide neural interfacing via transparent polymer skulls. Nat. Commun. 10, 1500 (2019).

    ADS  Google Scholar 

  52. Pak, N. et al. Closed-loop, ultraprecise, automated craniotomies. J. Neurophysiol. 113, 3943–3953 (2015).

    Google Scholar 

  53. Kim, T. H. et al. Long-term optical access to an estimated one million neurons in the live mouse cortex. Cell Rep. 17, 3385–3394 (2016).

    Google Scholar 

  54. Heo, C. et al. A soft, transparent, freely accessible cranial window for chronic imaging and electrophysiology. Sci. Rep. 6, 27818 (2016).

    ADS  Google Scholar 

  55. Low, R. J., Gu, Y. & Tank, D. W. Cellular resolution optical access to brain regions in fissures: imaging medial prefrontal cortex and grid cells in entorhinal cortex. Proc. Natl Acad. Sci. USA 111, 18739–18744 (2014).

    ADS  Google Scholar 

  56. Andermann, M. L. et al. Chronic cellular imaging of entire cortical columns in awake mice using microprisms. Neuron 80, 900–913 (2013).

    Google Scholar 

  57. El-Boustani, S. et al. Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices. Nat. Commun. 11, 3342 (2020).

    ADS  Google Scholar 

  58. Mizrahi, A., Crowley, J. C., Shtoyerman, E. & Katz, L. C. High-resolution in vivo imaging of hippocampal dendrites and spines. J. Neurosci. 24, 3147–3151 (2004).

    Google Scholar 

  59. Velasco, M. G. & Levene, M. J. In vivo two-photon microscopy of the hippocampus using glass plugs. Biomed. Opt. Express 5, 1700–1708 (2014).

    Google Scholar 

  60. Geiller, T. et al. Local circuit amplification of spatial selectivity in the hippocampus. Nature 601, 105–109 (2022).

    ADS  Google Scholar 

  61. Howe, M. W. & Dombeck, D. A. Rapid signalling in distinct dopaminergic axons during locomotion and reward. Nature 535, 505–510 (2016).

    ADS  Google Scholar 

  62. Barretto, R. P., Messerschmidt, B. & Schnitzer, M. J. In vivo fluorescence imaging with high-resolution microlenses. Nat. Methods 6, 511–512 (2009).

    Google Scholar 

  63. Adelsberger, H., Garaschuk, O. & Konnerth, A. Cortical calcium waves in resting newborn mice. Nat. Neurosci. 8, 988–990 (2005).

    Google Scholar 

  64. Grienberger, C. et al. Sound-evoked network calcium transients in mouse auditory cortex in vivo. J. Physiol. 590, 899–918 (2012).

    Google Scholar 

  65. Meng, G. et al. High-throughput synapse-resolving two-photon fluorescence microendoscopy for deep-brain volumetric imaging in vivo. eLife 8, e40805 (2019).

    Google Scholar 

  66. Otis, J. M. et al. Prefrontal cortex output circuits guide reward seeking through divergent cue encoding. Nature 543, 103–107 (2017).

    ADS  Google Scholar 

  67. Jennings, J. H. et al. Interacting neural ensembles in orbitofrontal cortex for social and feeding behaviour. Nature 565, 645–649 (2019).

    ADS  Google Scholar 

  68. Antonini, A. et al. Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness. eLife 9, e58882 (2020).

    Google Scholar 

  69. Flusberg, B. A., Jung, J. C., Cocker, E. D., Anderson, E. P. & Schnitzer, M. J. In vivo brain imaging using a portable 3.9 gram two-photon fluorescence microendoscope. Opt. Lett. 30, 2272–2274 (2005).

    ADS  Google Scholar 

  70. Zong, W. et al. Miniature two-photon microscopy for enlarged field-of-view, multi-plane and long-term brain imaging. Nat. Methods 18, 46–49 (2021).

    Google Scholar 

  71. Zhao, Y. J. et al. Skull optical clearing window for in vivo imaging of the mouse cortex at synaptic resolution. Light. Sci. Appl. 7, 17153 (2018).

    Google Scholar 

  72. Denk, W., Strickler, J. H. & Webb, W. W. Two-photon laser scanning fluorescence microscopy. Science 248, 73–76 (1990).

    ADS  Google Scholar 

  73. Svoboda, K. & Yasuda, R. Principles of two-photon excitation microscopy and its applications to neuroscience. Neuron 50, 823–839 (2006).

    Google Scholar 

  74. Denk, W. et al. Anatomical and functional imaging of neurons using 2-photon laser scanning microscopy. J. Neurosci. Methods 54, 151–162 (1994).

    Google Scholar 

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

    Google Scholar 

  76. Helmchen, F. & Denk, W. Deep tissue two-photon microscopy. Nat. Methods 2, 932–940 (2005).

    Google Scholar 

  77. Andresen, V. et al. Infrared multiphoton microscopy: subcellular-resolved deep tissue imaging. Curr. Opin. Biotechnol. 20, 54–62 (2009).

    Google Scholar 

  78. Kobat, D. et al. Deep tissue multiphoton microscopy using longer wavelength excitation. Opt. Express 17, 13354–13364 (2009).

    ADS  Google Scholar 

  79. Condylis, C. et al. Dense functional and molecular readout of a circuit hub in sensory cortex. Science 375, eabl5981 (2022).

    Google Scholar 

  80. Gobel, W., Kampa, B. M. & Helmchen, F. Imaging cellular network dynamics in three dimensions using fast 3D laser scanning. Nat. Methods 4, 73–79 (2007).

    Google Scholar 

  81. Duemani Reddy, G., Kelleher, K., Fink, R. & Saggau, P. Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity. Nat. Neurosci. 11, 713–720 (2008).

    Google Scholar 

  82. Nadella, K. M. et al. Random-access scanning microscopy for 3D imaging in awake behaving animals. Nat. Methods 13, 1001–1004 (2016).

    Google Scholar 

  83. Cheng, A., Gonçalves, J. T., Golshani, P., Arisaka, K. & Portera Cailliau, C. Simultaneous two-photon calcium imaging at different depths with spatiotemporal multiplexing. Nat. Methods 8, 139–142 (2011).

    Google Scholar 

  84. Pnevmatikakis, E. A. et al. Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron 89, 285–299 (2016).

    Google Scholar 

  85. Callamaras, N. & Parker, I. Construction of a confocal microscope for real-time x–y and x–z imaging. Cell Calcium 26, 271–279 (1999).

    Google Scholar 

  86. Bonin, V., Histed, M. H., Yurgenson, S. & Reid, R. C. Local diversity and fine-scale organization of receptive fields in mouse visual cortex. J. Neurosci. 31, 18506–18521 (2011).

    Google Scholar 

  87. Jia, H., Rochefort, N. L., Chen, X. & Konnerth, A. Dendritic organization of sensory input to cortical neurons in vivo. Nature 464, 1307–1312 (2010).

    ADS  Google Scholar 

  88. Fan, G. Y. et al. Video-rate scanning two-photon excitation fluorescence microscopy and ratio imaging with cameleons. Biophys. J. 76, 2412–2420 (1999).

    ADS  Google Scholar 

  89. Grienberger, C., Chen, X. & Konnerth, A. NMDA receptor-dependent multidendrite Ca2+ spikes required for hippocampal burst firing in vivo. Neuron 81, 1274–1281 (2014).

    Google Scholar 

  90. Nguyen, Q. T., Callamaras, N., Hsieh, C. & Parker, I. Construction of a two-photon microscope for video-rate Ca2+ imaging. Cell Calcium 30, 383–393 (2001).

    Google Scholar 

  91. Dombeck, D. A., Khabbaz, A. N., Collman, F., Adelman, T. L. & Tank, D. W. Imaging large-scale neural activity with cellular resolution in awake, mobile mice. Neuron 56, 43–57 (2007).

    Google Scholar 

  92. Goldey, G. J. et al. Removable cranial windows for long-term imaging in awake mice. Nat. Protoc. 9, 2515–2538 (2014).

    Google Scholar 

  93. Chen, J. L., Pfaffli, O. A., Voigt, F. F., Margolis, D. J. & Helmchen, F. Online correction of licking-induced brain motion during two-photon imaging with a tunable lens. J. Physiol. 591, 4689–4698 (2013).

    Google Scholar 

  94. Podgorski, K. & Ranganathan, G. Brain heating induced by near-infrared lasers during multiphoton microscopy. J. Neurophysiol. 116, 1012–1023 (2016).

    Google Scholar 

  95. Picot, A. et al. Temperature rise under two-photon optogenetic brain stimulation. Cell Rep. 24, 1243–1253.e5 (2018).

    Google Scholar 

  96. Pachitariu, M. et al. Suite2p: beyond 10,000 neurons with standard two-photon microscopy. Preprint at bioRxiv https://doi.org/10.1101/061507 (2017).

    Article  Google Scholar 

  97. Giovannucci, A. et al. CaImAn an open source tool for scalable calcium imaging data analysis. eLife 8, e38173 (2019).

    Google Scholar 

  98. Cantu, D. A. et al. EZcalcium: open-source toolbox for analysis of calcium imaging data. Front. Neural Circuits 14, 25 (2020).

    Google Scholar 

  99. Benisty, H., Song, A., Mishne, G. & Charles, A. Data processing of functional optical microscopy for neuroscience. Preprint at https://doi.org/10.48550/arXiv.2201.03537 (2022).

  100. Pnevmatikakis, E. A. Analysis pipelines for calcium imaging data. Curr. Opin. Neurobiol. 55, 15–21 (2019).

    Google Scholar 

  101. Stringer, C. & Pachitariu, M. Computational processing of neural recordings from calcium imaging data. Curr. Opin. Neurobiol. 55, 22–31 (2019).

    Google Scholar 

  102. Hurwitz, C., Kudryashova, N., Onken, A. & Hennig, M. H. Building population models for large-scale neural recordings: opportunities and pitfalls. Curr. Opin. Neurobiol. 70, 64–73 (2021).

    Google Scholar 

  103. Greenberg, D. S. & Kerr, J. N. Automated correction of fast motion artifacts for two-photon imaging of awake animals. J. Neurosci. Methods 176, 1–15 (2009).

    Google Scholar 

  104. Guizar-Sicairos, M., Thurman, S. T. & Fienup, J. R. Efficient subpixel image registration algorithms. Opt. Lett. 33, 156–158 (2008).

    ADS  Google Scholar 

  105. Pnevmatikakis, E. A. & Giovannucci, A. NoRMCorre: an online algorithm for piecewise rigid motion correction of calcium imaging data. J. Neurosci. Methods 291, 83–94 (2017).

    Google Scholar 

  106. Dubbs, A., Guevara, J. & Yuste, R. moco: fast motion correction for calcium imaging. Front. Neuroinform. 10, 6 (2016).

    Google Scholar 

  107. Lagache, T., Hanson, A., Perez-Ortega, J. E., Fairhall, A. & Yuste, R. Tracking calcium dynamics from individual neurons in behaving animals. PLoS Comput. Biol. 17, e1009432 (2021).

    ADS  Google Scholar 

  108. Akemann, W. et al. Fast optical recording of neuronal activity by three-dimensional custom-access serial holography. Nat. Methods 19, 100–110 (2022).

    Google Scholar 

  109. Buchanan, E. et al. Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data. Preprint at bioRxiv https://doi.org/10.1101/334706 (2019).

    Article  Google Scholar 

  110. Lecoq, J. et al. Removing independent noise in systems neuroscience data using DeepInterpolation. Nat. Methods 18, 1401–1408 (2021).

    Google Scholar 

  111. Apthorpe, N. et al. in Advances in Neural Information Processing Systems, Annual Conference on Neural Information Processing Systems 3270–3278 (NIPS, 2016).

  112. Soltanian-Zadeh, S., Sahingur, K., Blau, S., Gong, Y. & Farsiu, S. Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning. Proc. Natl Acad. Sci. USA 116, 8554–8563 (2019).

    ADS  Google Scholar 

  113. Pachitariu, M., et al. in Advances in Neural Information Processing Systems 1745–1753 (NIPS, 2013).

  114. Diego, F. & Hamprecht, F. in Advances in Neural Information Processing Systems 64–72 (NIPS, 2014).

  115. Reynolds, S. et al. ABLE: an activity-based level set segmentation algorithm for two-photon calcium imaging data. eNeuro 4, ENEURO.0012-17.2017 (2017).

    Google Scholar 

  116. Spaen, Q. et al. HNCcorr: a novel combinatorial approach for cell identification in calcium-imaging movies. eNeuro 6, ENEURO.0304-18.2019 (2019).

    Google Scholar 

  117. Sheintuch, L. et al. Tracking the same neurons across multiple days in Ca2+ imaging data. Cell Rep. 21, 1102–1115 (2017).

    Google Scholar 

  118. Mukamel, E. A., Nimmerjahn, A. & Schnitzer, M. J. Automated analysis of cellular signals from large-scale calcium imaging data. Neuron 63, 747–760 (2009).

    Google Scholar 

  119. Helmchen, F. Calibration of fluorescent calcium indicators. Cold Spring Harb. Protoc. 2011, 923–930 (2011).

    Google Scholar 

  120. Song, A., Gauthier, J. L., Pillow, J. W., Tank, D. W. & Charles, A. S. Neural anatomy and optical microscopy (NAOMi) simulation for evaluating calcium imaging methods. J. Neurosci. Methods 358, 109173 (2021).

    Google Scholar 

  121. Berens, P. et al. Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. PLoS Comput. Biol. 14, e1006157 (2018).

    Google Scholar 

  122. Friedrich, J. & Paninski, L. in Advances In Neural Information Processing Systems 1984–1992 (NIPS, 2016).

  123. Deneux, T. et al. Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo. Nat. Commun. 7, 12190 (2016).

    ADS  Google Scholar 

  124. Rupprecht, P. et al. A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging. Nat. Neurosci. 24, 1324–1337 (2021).

    Google Scholar 

  125. Peron, S. P., Freeman, J., Iyer, V., Guo, C. & Svoboda, K. A cellular resolution map of barrel cortex activity during tactile behavior. Neuron 86, 783–799 (2015).

    Google Scholar 

  126. Kerr, J. N. et al. Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. J. Neurosci. 27, 13316–13328 (2007).

    Google Scholar 

  127. Golshani, P. et al. Internally mediated developmental desynchronization of neocortical network activity. J. Neurosci. 29, 10890–10899 (2009).

    Google Scholar 

  128. Margolis, D. J. et al. Reorganization of cortical population activity imaged throughout long-term sensory deprivation. Nat. Neurosci. 15, 1539–1546 (2012).

    Google Scholar 

  129. Musall, S. et al. Tactile frequency discrimination is enhanced by circumventing neocortical adaptation. Nat. Neurosci. 17, 1567–1573 (2014).

    Google Scholar 

  130. He, C. X. et al. Tactile defensiveness and impaired adaptation of neuronal activity in the Fmr1 knock-out mouse model of autism. J. Neurosci. 37, 6475–6487 (2017).

    Google Scholar 

  131. Chen, J. L., Carta, S., Soldado-Magraner, J., Schneider, B. L. & Helmchen, F. Behaviour-dependent recruitment of long-range projection neurons in somatosensory cortex. Nature 499, 336–340 (2013).

    ADS  Google Scholar 

  132. Urai, A. E., Doiron, B., Leifer, A. M. & Churchland, A. K. Large-scale neural recordings call for new insights to link brain and behavior. Nat. Neurosci. 25, 11–19 (2022).

    Google Scholar 

  133. Helmchen, F., Fee, M. S., Tank, D. W. & Denk, W. A miniature head-mounted two-photon microscope. High-resolution brain imaging in freely moving animals. Neuron 31, 903–912 (2001).

    Google Scholar 

  134. Wallace, D. J. et al. Rats maintain an overhead binocular field at the expense of constant fusion. Nature 498, 65–69 (2013).

    ADS  Google Scholar 

  135. Obenhaus, H. A. et al. Functional network topography of the medial entorhinal cortex. Proc. Natl Acad. Sci. USA 119, e2121655119 (2022).

    Google Scholar 

  136. Dombeck, D. A., Harvey, C. D., Tian, L., Looger, L. L. & Tank, D. W. Functional imaging of hippocampal place cells at cellular resolution during virtual navigation. Nat. Neurosci. 13, 1433–1440 (2010).

    Google Scholar 

  137. Morcos, A. S. & Harvey, C. D. History-dependent variability in population dynamics during evidence accumulation in cortex. Nat. Neurosci. 19, 1672–1681 (2016).

    Google Scholar 

  138. Tuncdemir, S. N. et al. Parallel processing of sensory cue and spatial information in the dentate gyrus. Cell Rep. 38, 110257 (2022).

    Google Scholar 

  139. Poort, J. et al. Learning and attention increase visual response selectivity through distinct mechanisms. Neuron 110, 686–697 e686 (2022).

    Google Scholar 

  140. Khan, A. G. et al. Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex. Nat. Neurosci. 21, 851–859 (2018).

    Google Scholar 

  141. Poort, J. et al. Learning enhances sensory and multiple non-sensory representations in primary visual cortex. Neuron 86, 1478–1490 (2015).

    Google Scholar 

  142. Grienberger, C. & Magee, J. C. Entorhinal cortex directs learning-related changes in CA1 representations. Preprint at bioRxiv https://doi.org/10.1101/2021.12.10.472158 (2021).

    Article  Google Scholar 

  143. Tervo, D. G. et al. A designer AAV variant permits efficient retrograde access to projection neurons. Neuron 92, 372–382 (2016).

    Google Scholar 

  144. Goel, A. et al. Impaired perceptual learning in a mouse model of Fragile X syndrome is mediated by parvalbumin neuron dysfunction and is reversible. Nat. Neurosci. 21, 1404–1411 (2018).

    Google Scholar 

  145. de Vries, S. E. J. et al. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex. Nat. Neurosci. 23, 138–151 (2020).

    Google Scholar 

  146. Steinmetz, N. A. et al. Neuropixels 2.0: a miniaturized high-density probe for stable, long-term brain recordings. Science 372, eabf4588 (2021).

    Google Scholar 

  147. Bajar, B. T. et al. A discrete neuronal population coordinates brain-wide developmental activity. Nature 602, 639–646 (2022).

    ADS  Google Scholar 

  148. Park, J. E. et al. Generation of transgenic marmosets expressing genetically encoded calcium indicators. Sci. Rep. 6, 34931 (2016).

    ADS  Google Scholar 

  149. Katlowitz, K. A., Picardo, M. A. & Long, M. A. Stable sequential activity underlying the maintenance of a precisely executed skilled behavior. Neuron 98, 1133–1140.e3 (2018).

    Google Scholar 

  150. Xie, Y. et al. Geometry of sequence working memory in macaque prefrontal cortex. Science 375, 632–639 (2022).

    ADS  Google Scholar 

  151. Trautmann, E. M. et al. Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain–computer interface. Nat. Commun. 12, 3689 (2021).

    ADS  Google Scholar 

  152. Petreanu, L., Huber, D., Sobczyk, A. & Svoboda, K. Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections. Nat. Neurosci. 10, 663–668 (2007).

    Google Scholar 

  153. Cossart, R., Aronov, D. & Yuste, R. Attractor dynamics of network UP states in the neocortex. Nature 423, 283–288 (2003).

    ADS  Google Scholar 

  154. Ikegaya, Y. et al. Synfire chains and cortical songs: temporal modules of cortical activity. Science 304, 559–564 (2004).

    ADS  Google Scholar 

  155. Motanis, H. & Buonomano, D. Decreased reproducibility and abnormal experience-dependent plasticity of network dynamics in Fragile X circuits. Sci. Rep. 10, 14535 (2020).

    ADS  Google Scholar 

  156. Samarasinghe, R. A. et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nat. Neurosci. 24, 1488–1500 (2021).

    Google Scholar 

  157. Buzsaki, G. Neural syntax: cell assemblies, synapsembles, and readers. Neuron 68, 362–385 (2010).

    Google Scholar 

  158. Churchland, M. M. et al. Neural population dynamics during reaching. Nature 487, 51–56 (2012).

    ADS  Google Scholar 

  159. Villette, V., Malvache, A., Tressard, T., Dupuy, N. & Cossart, R. Internally recurring hippocampal sequences as a population template of spatiotemporal information. Neuron 88, 357–366 (2015).

    Google Scholar 

  160. Yuste, R. From the neuron doctrine to neural networks. Nat. Rev. Neurosci. 16, 487–497 (2015).

    Google Scholar 

  161. Nikolenko, V. et al. SLM microscopy: scanless two-photon imaging and photostimulation with spatial light modulators. Front. Neural Circuits 2, 5 (2008).

    Google Scholar 

  162. Rickgauer, J. P., Deisseroth, K. & Tank, D. W. Simultaneous cellular-resolution optical perturbation and imaging of place cell firing fields. Nat. Neurosci. 17, 1816–1824 (2014).

    Google Scholar 

  163. Carrillo-Reid, L., Han, S., Yang, W., Akrouh, A. & Yuste, R. Controlling visually guided behavior by holographic recalling of cortical ensembles. Cell 178, 447–457.e5 (2019).

    Google Scholar 

  164. Clancy, K. B., Koralek, A. C., Costa, R. M., Feldman, D. E. & Carmena, J. M. Volitional modulation of optically recorded calcium signals during neuroprosthetic learning. Nat. Neurosci. 17, 807–809 (2014).

    Google Scholar 

  165. Cichon, J. & Gan, W. B. Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity. Nature 520, 180–185 (2015).

    ADS  Google Scholar 

  166. Harnett, M. T., Makara, J. K., Spruston, N., Kath, W. L. & Magee, J. C. Synaptic amplification by dendritic spines enhances input cooperativity. Nature 491, 599–602 (2012).

    ADS  Google Scholar 

  167. Kerlin, A. et al. Functional clustering of dendritic activity during decision-making. eLife 8, e46966 (2019).

    Google Scholar 

  168. Gambino, F. et al. Sensory-evoked LTP driven by dendritic plateau potentials in vivo. Nature 515, 116–119 (2014).

    ADS  Google Scholar 

  169. Fiser, A. et al. Experience-dependent spatial expectations in mouse visual cortex. Nat. Neurosci. 19, 1658–1664 (2016).

    Google Scholar 

  170. Penagarikano, O. et al. Absence of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, and core autism-related deficits. Cell 147, 235–246 (2011).

    Google Scholar 

  171. Goncalves, J. T., Anstey, J. E., Golshani, P. & Portera-Cailliau, C. Circuit level defects in the developing neocortex of fragile X mice. Nat. Neurosci. 16, 903–909 (2013).

    Google Scholar 

  172. La Fata, G. et al. FMRP regulates multipolar to bipolar transition affecting neuronal migration and cortical circuitry. Nat. Neurosci. 17, 1693–1700 (2014).

    Google Scholar 

  173. Chen, Q. et al. Dysfunction of cortical GABAergic neurons leads to sensory hyper-reactivity in a Shank3 mouse model of ASD. Nat. Neurosci. 23, 520–532 (2020).

    Google Scholar 

  174. Busche, M. A. et al. Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer’s disease. Science 321, 1686–1689 (2008).

    ADS  Google Scholar 

  175. Grienberger, C. et al. Staged decline of neuronal function in vivo in an animal model of Alzheimer’s disease. Nat. Commun. 3, 774 (2012).

    ADS  Google Scholar 

  176. Korzhova, V. et al. Long-term dynamics of aberrant neuronal activity in awake Alzheimer’s disease transgenic mice. Commun. Biol. 4, 1368 (2021).

    Google Scholar 

  177. Virani, S. S. et al. Heart disease and stroke statistics — 2021 update: a report from the American Heart Association. Circulation 143, e254–e743 (2021).

    Google Scholar 

  178. Fordsmann, J. C. et al. Spontaneous astrocytic Ca2+ activity abounds in electrically suppressed ischemic penumbra of aged mice. Glia 67, 37–52 (2019).

    Google Scholar 

  179. Shih, A. Y. et al. The smallest stroke: occlusion of one penetrating vessel leads to infarction and a cognitive deficit. Nat. Neurosci. 16, 55–63 (2013).

    Google Scholar 

  180. Rakers, C. & Petzold, G. C. Astrocytic calcium release mediates peri-infarct depolarizations in a rodent stroke model. J. Clin. Invest. 127, 511–516 (2017).

    Google Scholar 

  181. Murphy, T. H., Li, P., Betts, K. & Liu, R. Two-photon imaging of stroke onset in vivo reveals that NMDA-receptor independent ischemic depolarization is the major cause of rapid reversible damage to dendrites and spines. J. Neurosci. 28, 1756–1772 (2008).

    Google Scholar 

  182. Ding, S., Wang, T., Cui, W. & Haydon, P. G. Photothrombosis ischemia stimulates a sustained astrocytic Ca2+ signaling in vivo. Glia 57, 767–776 (2009).

    Google Scholar 

  183. Liu, L. et al. Microglial calcium waves during the hyperacute phase of ischemic stroke. Stroke 52, 274–283 (2021).

    Google Scholar 

  184. Brawek, B. & Garaschuk, O. Monitoring in vivo function of cortical microglia. Cell Calcium 64, 109–117 (2017).

    Google Scholar 

  185. Alarcon-Martinez, L. et al. Interpericyte tunnelling nanotubes regulate neurovascular coupling. Nature 585, 91–95 (2020).

    ADS  Google Scholar 

  186. Winship, I. R. & Murphy, T. H. In vivo calcium imaging reveals functional rewiring of single somatosensory neurons after stroke. J. Neurosci. 28, 6592–6606 (2008).

    Google Scholar 

  187. Zeiger, W. A. et al. Barrel cortex plasticity after photothrombotic stroke involves potentiating responses of pre-existing circuits but not functional remapping to new circuits. Nat. Commun. 12, 3972 (2021).

    ADS  Google Scholar 

  188. Tennant, K. A., Taylor, S. L., White, E. R. & Brown, C. E. Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain. Nat. Commun. 8, 15879 (2017).

    ADS  Google Scholar 

  189. Motaharinia, M. et al. Longitudinal functional imaging of VIP interneurons reveals sup-population specific effects of stroke that are rescued with chemogenetic therapy. Nat. Commun. 12, 6112 (2021).

    ADS  Google Scholar 

  190. Nimmerjahn, A., Kirchhoff, F., Kerr, J. N. & Helmchen, F. Sulforhodamine 101 as a specific marker of astroglia in the neocortex in vivo. Nat. Methods 1, 31–37 (2004).

    Google Scholar 

  191. Reeves, A. M., Shigetomi, E. & Khakh, B. S. Bulk loading of calcium indicator dyes to study astrocyte physiology: key limitations and improvements using morphological maps. J. Neurosci. 31, 9353–9358 (2011).

    Google Scholar 

  192. Jiang, R., Haustein, M. D., Sofroniew, M. V. & Khakh, B. S. Imaging intracellular Ca2+ signals in striatal astrocytes from adult mice using genetically-encoded calcium indicators. J. Vis. Exp. https://doi.org/10.3791/51972 (2014).

    Article  Google Scholar 

  193. Srinivasan, R. et al. New transgenic mouse lines for selectively targeting astrocytes and studying calcium signals in astrocyte processes in situ and in vivo. Neuron 92, 1181–1195 (2016).

    Google Scholar 

  194. Bjornstad, D. M. et al. Begonia — a two-photon imaging analysis pipeline for astrocytic Ca2+ signals. Front. Cell Neurosci. 15, 681066 (2021).

    Google Scholar 

  195. Eichhoff, G., Brawek, B. & Garaschuk, O. Microglial calcium signal acts as a rapid sensor of single neuron damage in vivo. Biochim. Biophys. Acta 1813, 1014–1024 (2011).

    Google Scholar 

  196. Tvrdik, P. et al. Calcium imaging of microglial network activity in stroke. Methods Mol. Biol. 2034, 267–279 (2019).

    Google Scholar 

  197. Tworig, J. M., Coate, C. J. & Feller, M. B. Excitatory neurotransmission activates compartmentalized calcium transients in Müller glia without affecting lateral process motility. eLife 10, e73202 (2021).

    Google Scholar 

  198. Tong, L. et al. Imaging and optogenetic modulation of vascular mural cells in the live brain. Nat. Protoc. 16, 472–496 (2021).

    Google Scholar 

  199. Hirase, H., Creso, J., Singleton, M., Bartho, P. & Buzsaki, G. Two-photon imaging of brain pericytes in vivo using dextran-conjugated dyes. Glia 46, 95–100 (2004).

    Google Scholar 

  200. Gilbert, T. L. & Ng, L. in Molecular-Genetic and Statistical Techniques for Behavioral and Neural Research (ed. Gerlai, R. T.) 51–72 (Academic, 2018).

  201. Sadovsky, A. J. et al. Heuristically optimal path scanning for high-speed multiphoton circuit imaging. J. Neurophysiol. 106, 1591–1598 (2011).

    Google Scholar 

  202. Otsu, Y. et al. Optical monitoring of neuronal activity at high frame rate with a digital random-access multiphoton (RAMP) microscope. J. Neurosci. Methods 173, 259–270 (2008).

    Google Scholar 

  203. Szalay, G. et al. Fast 3D imaging of spine, dendritic, and neuronal assemblies in behaving animals. Neuron 92, 723–738 (2016).

    Google Scholar 

  204. Grewe, B. F., Langer, D., Kasper, H., Kampa, B. M. & Helmchen, F. High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision. Nat. Methods 7, 399–405 (2010).

    Google Scholar 

  205. Chen, X., Leischner, U., Rochefort, N. L., Nelken, I. & Konnerth, A. Functional mapping of single spines in cortical neurons in vivo. Nature 475, 501–505 (2011).

    Google Scholar 

  206. Villette, V. et al. Ultrafast two-photon imaging of a high-gain voltage indicator in awake behaving mice. Cell 179, 1590–1608.e23 (2019).

    Google Scholar 

  207. Economo, M. N., Hansen, K. R. & Wachowiak, M. Control of mitral/tufted cell output by selective inhibition among olfactory bulb glomeruli. Neuron 91, 397–411 (2016).

    Google Scholar 

  208. Vladimirov, N. et al. Brain-wide circuit interrogation at the cellular level guided by online analysis of neuronal function. Nat. Methods 15, 1117–1125 (2018).

    Google Scholar 

  209. Sofroniew, N. J., Flickinger, D., King, J. & Svoboda, K. A large field of view two-photon mesoscope with subcellular resolution for in vivo imaging. eLife 5, e14472 (2016).

    Google Scholar 

  210. Stirman, J. N., Smith, I. T., Kudenov, M. W. & Smith, S. L. Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain. Nat. Biotechnol. 34, 857–862 (2016).

    Google Scholar 

  211. Tsai, P. S. et al. Ultra-large field-of-view two-photon microscopy. Opt. Express 23, 13833–13847 (2015).

    ADS  Google Scholar 

  212. Amir, W. et al. Simultaneous imaging of multiple focal planes using a two-photon scanning microscope. Opt. Lett. 32, 1731–1733 (2007).

    ADS  Google Scholar 

  213. Yu, C. H., Stirman, J. N., Yu, Y., Hira, R. & Smith, S. L. Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry. Nat. Commun. 12, 6639 (2021).

    ADS  Google Scholar 

  214. Chen, J. L., Voigt, F. F., Javadzadeh, M., Krueppel, R. & Helmchen, F. Long-range population dynamics of anatomically defined neocortical networks. eLife 5, e14679 (2016).

    Google Scholar 

  215. Zhang, T. et al. Kilohertz two-photon brain imaging in awake mice. Nat. Methods 16, 1119–1122 (2019).

    Google Scholar 

  216. Demas, J. et al. High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopy. Nat. Methods 18, 1103–1111 (2021).

    Google Scholar 

  217. Rumyantsev, O. I. et al. Fundamental bounds on the fidelity of sensory cortical coding. Nature 580, 100–105 (2020).

    ADS  Google Scholar 

  218. Yang, W. & Yuste, R. In vivo imaging of neural activity. Nat. Methods 14, 349–359 (2017).

    Google Scholar 

  219. Theer, P., Hasan, M. T. & Denk, W. Two-photon imaging to a depth of 1000 microm in living brains by use of a Ti:Al2O3 regenerative amplifier. Opt. Lett. 28, 1022–1024 (2003).

    ADS  Google Scholar 

  220. Ebina, T. et al. Two-photon imaging of neuronal activity in motor cortex of marmosets during upper-limb movement tasks. Nat. Commun. 9, 1879 (2018).

    ADS  Google Scholar 

  221. Sherman, L., Ye, J. Y., Albert, O. & Norris, T. B. Adaptive correction of depth-induced aberrations in multiphoton scanning microscopy using a deformable mirror. J. Microsc. 206, 65–71 (2002).

    MathSciNet  Google Scholar 

  222. Ji, N., Milkie, D. E. & Betzig, E. Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues. Nat. Methods 7, 141–147 (2010).

    Google Scholar 

  223. Wang, C. et al. Multiplexed aberration measurement for deep tissue imaging in vivo. Nat. Methods 11, 1037–1040 (2014).

    Google Scholar 

  224. Girkin, J. M., Poland, S. & Wright, A. J. Adaptive optics for deeper imaging of biological samples. Curr. Opin. Biotechnol. 20, 106–110 (2009).

    Google Scholar 

  225. Sun, W., Tan, Z., Mensh, B. D. & Ji, N. Thalamus provides layer 4 of primary visual cortex with orientation- and direction-tuned inputs. Nat. Neurosci. 19, 308–315 (2016).

    Google Scholar 

  226. Mittmann, W. et al. Two-photon calcium imaging of evoked activity from L5 somatosensory neurons in vivo. Nat. Neurosci. 14, 1089–1093 (2011).

    Google Scholar 

  227. Wang, T. et al. Three-photon imaging of mouse brain structure and function through the intact skull. Nat. Methods 15, 789–792 (2018).

    Google Scholar 

  228. Horton, N. G. et al. In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat. Photonics 7, 205–209 (2013).

    ADS  Google Scholar 

  229. Ouzounov, D. G. et al. In vivo three-photon imaging of activity of GCaMP6-labeled neurons deep in intact mouse brain. Nat. Methods 14, 388–390 (2017).

    Google Scholar 

  230. Streich, L. et al. High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy. Nat. Methods 18, 1253–1258 (2021).

    Google Scholar 

  231. Weisenburger, S. et al. Volumetric Ca2+ imaging in the mouse brain using hybrid multiplexed sculpted light microscopy. Cell 177, 1050–1066.e14 (2019).

    Google Scholar 

  232. Zong, W. et al. Large-scale two-photon calcium imaging in freely moving mice. Cell 185, 1240–1256.e30 (2022).

    Google Scholar 

  233. Paninski, L. & Cunningham, J. P. Neural data science: accelerating the experiment–analysis–theory cycle in large-scale neuroscience. Curr. Opin. Neurobiol. 50, 232–241 (2018).

    Google Scholar 

  234. Giovannucci, A., et al. in Advances in Neural Information Processing Systems (NIPS, 2017).

  235. Zhang, Z., Russell, L. E., Packer, A. M., Gauld, O. M. & Hausser, M. Closed-loop all-optical interrogation of neural circuits in vivo. Nat. Methods 15, 1037–1040 (2018).

    Google Scholar 

  236. O’Shea, D. J. et al. The need for calcium imaging in nonhuman primates: new motor neuroscience and brain–machine interfaces. Exp. Neurol. 287, 437–451 (2017).

    Google Scholar 

  237. Abdelfattah, A. S. et al. Bright and photostable chemigenetic indicators for extended in vivo voltage imaging. Science 365, 699–704 (2019).

    ADS  Google Scholar 

  238. Chien, M. P. et al. Photoactivated voltage imaging in tissue with an archaerhodopsin-derived reporter. Sci. Adv. 7, eabe3216 (2021).

    ADS  Google Scholar 

  239. Gong, Y. et al. High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor. Science 350, 1361–1366 (2015).

    ADS  Google Scholar 

  240. Piatkevich, K. D. et al. Population imaging of neural activity in awake behaving mice. Nature 574, 413–417 (2019).

    ADS  Google Scholar 

  241. Marvin, J. S. et al. Stability, affinity, and chromatic variants of the glutamate sensor iGluSnFR. Nat. Methods 15, 936–939 (2018).

    Google Scholar 

  242. Patriarchi, T. et al. Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors. Science 360, eaat4422 (2018).

    Google Scholar 

  243. Ji, N., Freeman, J. & Smith, S. L. Technologies for imaging neural activity in large volumes. Nat. Neurosci. 19, 1154–1164 (2016).

    Google Scholar 

  244. Charles, A. S. et al. Toward community-driven big open brain science: open big data and tools for structure, function, and genetics. Annu. Rev. Neurosci. 43, 441–464 (2020).

    Google Scholar 

  245. Emiliani, V., Cohen, A. E., Deisseroth, K. & Hausser, M. All-optical interrogation of neural circuits. J. Neurosci. 35, 13917–13926 (2015).

    Google Scholar 

  246. Cai, C., Dong, C., Rozsa, B., Pnevmatikakis, E. & Giovannucci, A. FIOLA: an accelerated pipeline for Fluorescence Imaging OnLine Analysis. Preprint at Res. Sq. https://doi.org/10.21203/rs.3.rs-800247/v1 (2021).

    Article  Google Scholar 

  247. Adesnik, H. & Abdeladim, L. Probing neural codes with two-photon holographic optogenetics. Nat. Neurosci. 24, 1356–1366 (2021).

    Google Scholar 

  248. Picardo, M. A. et al. Population-level representation of a temporal sequence underlying song production in the zebra finch. Neuron 90, 866–876 (2016).

    Google Scholar 

  249. Jun, J. J. et al. Fully integrated silicon probes for high-density recording of neural activity. Nature 551, 232–236 (2017).

    ADS  Google Scholar 

  250. Steinmetz, N. A., Koch, C., Harris, K. D. & Carandini, M. Challenges and opportunities for large-scale electrophysiology with Neuropixels probes. Curr. Opin. Neurobiol. 50, 92–100 (2018).

    Google Scholar 

  251. Lima, S. Q., Hromadka, T., Znamenskiy, P. & Zador, A. M. PINP: a new method of tagging neuronal populations for identification during in vivo electrophysiological recording. PLoS ONE 4, e6099 (2009).

    ADS  Google Scholar 

  252. Vollmer, K. M. et al. A novel assay allowing drug self-administration, extinction, and reinstatement testing in head-restrained mice. Front. Behav. Neurosci. 15, 744715 (2021).

    Google Scholar 

  253. Seidemann, E. et al. Calcium imaging with genetically encoded indicators in behaving primates. eLife 5, e16178 (2016).

    Google Scholar 

  254. Wilt, B. A., Fitzgerald, J. E. & Schnitzer, M. J. Photon shot noise limits on optical detection of neuronal spikes and estimation of spike timing. Biophys. J. 104, 51–62 (2013).

    ADS  Google Scholar 

  255. Anderson, M. A. et al. Astrocyte scar formation aids central nervous system axon regeneration. Nature 532, 195–200 (2016).

    ADS  Google Scholar 

  256. Sheffield, M. E. & Dombeck, D. A. Calcium transient prevalence across the dendritic arbour predicts place field properties. Nature 517, 200–204 (2015).

    ADS  Google Scholar 

  257. Theriault, G., Cottet, M., Castonguay, A., McCarthy, N. & De Koninck, Y. Extended two-photon microscopy in live samples with Bessel beams: steadier focus, faster volume scans, and simpler stereoscopic imaging. Front. Cell Neurosci. 8, 139 (2014).

    Google Scholar 

  258. Lu, R. et al. Video-rate volumetric functional imaging of the brain at synaptic resolution. Nat. Neurosci. 20, 620–628 (2017).

    Google Scholar 

  259. Song, A. et al. Volumetric two-photon imaging of neurons using stereoscopy (vTwINS). Nat. Methods 14, 420–426 (2017).

    Google Scholar 

  260. Prevedel, R. et al. Fast volumetric calcium imaging across multiple cortical layers using sculpted light. Nat. Methods 13, 1021–1028 (2016).

    Google Scholar 

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Acknowledgements

The authors thank N. Kourdougli and A. Suresh for providing some images for Fig. 5d. This work was supported by grants W81XWH2110493 from the Army Medical Research and Material Command Center (to C.P.-C.), R01HD054453 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; to C.P.-C.), R01NS117597 from the National Institute of Mental Health (to C.P.-C.), R01HD108370 from NICHD (to C.P.-C.), a Beckman Young Investigator Award (to A.G.), grant NRTS 2199 from the American Academy of Neurology (AAN; to W.Z.), grant K08NS114165-01A1 from the National Institute of Neurological Disorders and Stroke (NINDS; to W.Z.) and the Smith Family Awards Program for Excellence in Biomedical Research (to C.G.). Some figures contain images created with BioRender.com.

Author information

Authors and Affiliations

  1. Department of Biology and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA

    Christine Grienberger

  2. Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA

    Andrea Giovannucci

  3. UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Andrea Giovannucci

  4. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    William Zeiger & Carlos Portera-Cailliau

  5. Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Carlos Portera-Cailliau

Authors
  1. Christine Grienberger
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  2. Andrea Giovannucci
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  4. Carlos Portera-Cailliau
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Contributions

Introduction (C.P.-C.); Experimentation (W.Z., C.G. and C.P.-C.); Results (W.Z., C.G. and C.P.-C.); Applications (A.G., W.Z., C.G. and C.P.-C.); Reproducibility and data deposition (A.G.); Limitations and optimizations (W.Z., C.G., C.P.-C. and A.G.); Outlook (A.G.); Overview of the Primer (C.P.-C.).

Corresponding author

Correspondence to Carlos Portera-Cailliau.

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Competing interests

A.G. is an inventor on the patents ‘Exploiting GPU end-to-end graph optimization for complex analysis pipelines’ (US patent application 63/249,648 (2021)) and ‘Selective backpropagation through time’ (US patent application no. 63/262,704 (2021)). All other authors declare no competing interests.

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Nature Reviews Methods Primers thanks Susu Chen, James Otis and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Glossary

Two-photon (2P) microscopy

A type of fluorescence microscopy that relies on the simultaneous excitation of fluorophores by two photons of light with longer wavelengths than in standard one-photon excitation. 2P absorption is non-linear, such that its rate depends on the second power of the light intensity. Consequently, fluorophores are almost exclusively excited in a diffraction-limited focal spot, whereas out-of-focus excitation and bleaching are strongly reduced.

Fluorescent calcium indicators

A group of compounds, generally either small molecules or engineered proteins, that change some aspect of their fluorescence, either excitation or emission, or both, when bound to calcium ions compared with the unbound state.

Calcium trace

A continuous measurement of a calcium indicator’s fluorescence intensity over time. Changes in fluorescence can be quantified in several ways, but the most common is the ΔF / F measurement, in which fluorescence at any given time is represented as the ratio of the relative fluorescence change over the baseline fluorescence.

Genetically encoded calcium indicators

(GECIs). An engineered protein used for visualizing changes in intracellular calcium concentration ([Ca2+]i), which enables the detection of neuronal activity. GECIs typically possess two components, one that binds to calcium ions and another that emits fluorescence.

Adeno-associated viruses

(AAVs). Non-pathogenic, single-stranded DNA viruses that have been genetically engineered to infect mammalian cells and deliver DNA sequences of interest for expression in target cells.

Open skull window

A surgical approach to gain access to the brain of calvarial animals, which involves drilling a craniotomy and replacing it with a transparent material (such as glass or polymer) that functions as a window into the brain.

Thinned-skull preparation

Instead of an open skull cranial window, a small portion of the skull (<2 mm in diameter) is gradually thinned (but not entirely removed) with a drill until it is translucent (generally down to 20 μm thickness).

PMT gain

The photomultiplier tube (PMT) output charge per detected photon, which can be adjusted by adjusting the voltage applied to the PMT.

Light sheet microscopy

A fluorescence microscopy technique with optical sectioning capability in which the sample is illuminated perpendicularly to the direction of observation by a laser light sheet. Although light sheet microscopy is often used for calcium imaging of live zebrafish embryos, it is not discussed in detail in this Primer because it is technically not a form of two-photon calcium imaging.

Adaptive optics

Technology used to optimize the performance of optical systems by reducing distortions of the incoming wavefront of light using deformable mirrors. In two-photon microscopy, it helps correct for aberrations due to inhomogeneities in the biological specimen.

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Grienberger, C., Giovannucci, A., Zeiger, W. et al. Two-photon calcium imaging of neuronal activity. Nat Rev Methods Primers 2, 67 (2022). https://doi.org/10.1038/s43586-022-00147-1

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