Skip to main content

Advertisement

SpringerLink
Log in

All-optical interrogation of neural circuits in behaving mice

  • Protocol
  • Published:

From Nature Protocols

View current issue Submit your manuscript

Abstract

Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such ‘all-optical’ techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3–6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3–5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: Conceptual goals of all-optical interrogation experiments.
Fig. 2: Overview of experimental steps.
Fig. 3: System diagram.
Fig. 4: SLM calibration: mapping photostimulation targets to imaging coordinates.
Fig. 5: Inducing and checking expression of all-optical constructs.
Fig. 6: Choosing an appropriate behavioral paradigm.
Fig. 7: Mapping functional responses online.
Fig. 8: Mapping photoactivatable neurons.
Fig. 9: A worked example: probing the perceptual salience of sensory-responsive neurons in the L2/3 barrel cortex by using targeted two-photon optogenetic stimulation.
Fig. 10: Two-photon excitation and calibration of safe and effective stimulation parameters.

Similar content being viewed by others

Data availability

The main data discussed in this protocol are available in the supporting primary research papers (refs. 14,40,41). The raw datasets are available for research purposes from the corresponding authors upon reasonable request.

Code availability

Custom codes used for experimental control, data acquisition, behavioral training and analysis have been deposited at Naparm (https://github.com/llerussell/Naparm), PyBehaviour (https://github.com/llerussell/PyBehaviour), 3D SLM calibration (https://github.com/llerussell/SLMTransformMaker3D), STAMovieMaker (https://github.com/llerussell/STAMovieMaker), RawDataStream (https://github.com/llerussell/Bruker_PrairieLink), Objective rotation (https://github.com/llerussell/MONPangle) and TPBS (https://github.com/hwpdalgleish/TPBS). The code in this protocol has been peer reviewed.

References

  1. Jacobs, A. L. et al. Ruling out and ruling in neural codes. Proc. Natl Acad. Sci. USA. 106, 5936–5941 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Panzeri, S., Harvey, C. D., Piasini, E., Latham, P. E. & Fellin, T. Cracking the neural code for sensory perception by combining statistics, intervention and behavior. Neuron 93, 491–507 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. London, M., Roth, A., Beeren, L., Häusser, M. & Latham, P. E. Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466, 123–127 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Histed, M. H. & Maunsell, J. H. R. Cortical neural populations can guide behavior by integrating inputs linearly, independent of synchrony. Proc. Natl Acad. Sci. USA. 111, E178–E187 (2014).

    Article  CAS  PubMed  Google Scholar 

  5. Gollisch, T. & Meister, M. Rapid neural coding in the retina with relative spike latencies. Science 319, 1108–1112 (2008).

    Article  CAS  PubMed  Google Scholar 

  6. Panzeri, S., Petersen, R. S., Schultz, S. R., Lebedev, M. & Diamond, M. E. The role of spike timing in the coding of stimulus location in rat somatosensory cortex. Neuron 29, 769–777 (2001).

    Article  CAS  PubMed  Google Scholar 

  7. Doron, G., von Heimendahl, M., Schlattmann, P., Houweling, A. R. & Brecht, M. Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation. Neuron 81, 653–663 (2014).

    Article  CAS  PubMed  Google Scholar 

  8. Shusterman, R., Smear, M. C., Koulakov, A. A. & Rinberg, D. Precise olfactory responses tile the sniff cycle. Nat. Neurosci. 14, 1039–1044 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Huber, D. et al. Sparse optical microstimulation in barrel cortex drives learned behaviour in freely moving mice. Nature 451, 61–64 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Harris, K. D. & Mrsic-Flogel, T. D. Cortical connectivity and sensory coding. Nature 503, 51–58 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. Pinto, L. & Dan, Y. Cell-type-specific activity in prefrontal cortex during goal-directed behavior. Neuron 87, 437–450 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Packer, A. M., Russell, L. E., Dalgleish, H. W. P. & Hausser, M. Simultaneous all-optical manipulation and recording of neural circuit activity with cellular resolution in vivo. Nat. Methods 12, 140–146 (2015).

    Article  CAS  PubMed  Google Scholar 

  15. Carrillo-Reid, L., Yang, W., Bando, Y., Peterka, D. S. & Yuste, R. Imprinting and recalling cortical ensembles. Science 353, 691–694 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Mardinly, A. R. et al. Precise multimodal optical control of neural ensemble activity. Nat. Neurosci. 21, 881–893 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Forli, A. et al. Two-photon bidirectional control and imaging of neuronal excitability with high spatial resolution in vivo. Cell Rep. 22, 3087–3098 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. dal Maschio, M., Donovan, J. C., Helmbrecht, T. O. & Baier, H. Linking neurons to network function and behavior by two-photon holographic optogenetics and volumetric imaging. Neuron 94, 774–789 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Chettih, S. N. & Harvey, C. D. Single-neuron perturbations reveal feature-specific competition in V1. Nature 567, 334–340 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Gill, J. V. et al. Precise holographic manipulation of olfactory circuits reveals coding features determining perceptual detection. Neuron 108, 1–12 (2020).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  27. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Rickgauer, J. P. & Tank, D. W. Two-photon excitation of channelrhodopsin-2 at saturation. Proc. Natl Acad. Sci. USA. 106, 15025–15030 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Prakash, R. et al. Two-photon optogenetic toolbox for fast inhibition, excitation and bistable modulation. Nat. Methods 9, 5–7 (2012).

    Article  CAS  Google Scholar 

  30. Packer, A. M. et al. Two-photon optogenetics of dendritic spines and neural circuits. Nat. Methods 9, 1202–1208 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Nikolenko, V. et al. SLM microscopy: scanless two-photon imaging and photostimulation with spatial light modulators. Front. Neural Circuits 2, 1–14 (2008).

    Article  Google Scholar 

  32. Papagiakoumou, E., de Sars, V., Oron, D. & Emiliani, V. Patterned two-photon illumination by spatiotemporal shaping of ultrashort pulses. Opt. Express 16, 22039–22047 (2008).

    Article  CAS  PubMed  Google Scholar 

  33. Papagiakoumou, E. et al. Scanless two-photon excitation of channelrhodopsin-2. Nat. Methods 7, 848–854 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Scanziani, M. & Häusser, M. Electrophysiology in the age of light. Nature 461, 930–939 (2009).

    Article  CAS  PubMed  Google Scholar 

  35. Pégard, N. C. et al. Three-dimensional scanless holographic optogenetics with temporal focusing (3D-SHOT). Nat. Commun. 8, 1–14 (2017).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Marshel, J. H. et al. Cortical layer–specific critical dynamics triggering perception. Science 365, 1–12 (2019).

    Article  CAS  Google Scholar 

  38. Szabo, V., Ventalon, C., DeSars, V., Bradley, J. & Emiliani, V. Spatially selective holographic photoactivation and functional fluorescence imaging in freely behaving mice with a fiberscope. Neuron 84, 1157–1169 (2014).

    Article  CAS  PubMed  Google Scholar 

  39. Shemesh, O. A. et al. Temporally precise single-cell-resolution optogenetics. Nat. Neurosci. 20, 1796–1806 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Dalgleish, H. W. P. et al. How many neurons are sufficient for perception of cortical activity? Elife 9, e58889 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Russell, L. E. et al. The influence of visual cortex on perception is modulated by behavioural state. Preprint at https://www.biorxiv.org/content/10.1101/706010v2 (2019).

  42. Daie, K., Svoboda, K. & Druckmann, S. Targeted photostimulation uncovers circuit motifs supporting short-term memory. Nat. Neurosci. 24, 259–265 (2021).

    Article  CAS  PubMed  Google Scholar 

  43. Robinson, N. T. M. et al. Targeted activation of hippocampal place cells drives memory-guided spatial behavior. Cell 183, 1586–1599.e10 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Carrillo-Reid, L. et al. Controlling visually guided behavior by holographic recalling of cortical ensembles. Cell 178, 1–11 (2019).

    Article  CAS  Google Scholar 

  45. Yang, W., Carrillo-Reid, L., Bando, Y., Peterka, D. S. & Yuste, R. Simultaneous two-photon imaging and two-photon optogenetics of cortical circuits in three dimensions. Elife 7, e32671 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Cohen, M. R. & Newsome, W. T. What electrical microstimulation has revealed about the neural basis of cognition. Curr. Opin. Neurobiol. 14, 169–177 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Murasugi, C. M., Salzman, C. D. & Newsome, W. T. Microstimulation in visual area MT: effects of varying pulse amplitude and frequency. J. Neurosci. 13, 1719–1729 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Salzman, C. D., Britten, K. H. & Newsome, W. T. Cortical microstimulation influences perceptual judgements of motion direction. Nature 346, 174 (1990).

    Article  CAS  PubMed  Google Scholar 

  49. Salzman, C. D., Murasugi, C. M., Britten, K. H. & Newsome, W. T. Microstimulation in visual area MT: effects on direction discrimination performance. J. Neurosci. 12, 2331–2355 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tanke, N., Borst, J. G. G. & Houweling, A. R. Single-cell stimulation in barrel cortex influences psychophysical detection performance. J. Neurosci. 38, 2057–2068 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Ceballo, S. et al. Cortical recruitment determines learning dynamics and strategy. Nat. Commun. 10, 1–12 (2019).

    Article  CAS  Google Scholar 

  52. Ceballo, S., Piwkowska, Z., Bourg, J., Daret, A. & Bathellier, B. Targeted cortical manipulation of auditory perception. Neuron 104, 1168–1179 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Znamenskiy, P. & Zador, A. M. Corticostriatal neurons in auditory cortex drive decisions during auditory discrimination. Nature 497, 482–485 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Anselmi, F., Ventalon, C., Bègue, A., Ogden, D. & Emiliani, V. Three-dimensional imaging and photostimulation by remote-focusing and holographic light patterning. Proc. Natl Acad. Sci. USA. 108, 19504–19509 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Dal Maschio, M. et al. Simultaneous two-photon imaging and photo-stimulation with structured light illumination. Opt. Express 18, 18720 (2010).

    Article  CAS  PubMed  Google Scholar 

  56. Lechasseur, Y. et al. A microprobe for parallel optical and electrical recordings from single neurons in vivo. Nat. Methods 8, 319–325 (2011).

    Article  CAS  PubMed  Google Scholar 

  57. Anikeeva, P. et al. Optetrode: a multichannel readout for optogenetic control in freely moving mice. Nat. Neurosci. 15, 163–170 (2012).

    Article  CAS  Google Scholar 

  58. Royer, S. et al. Multi-array silicon probes with integrated optical fibers: light-assisted perturbation and recording of local neural circuits in the behaving animal. Eur. J. Neurosci. 31, 2279–2291 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Lima, S. Q., Hromádka, 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).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Kravitz, A. V., Owen, S. F. & Kreitzer, A. C. Optogenetic identification of striatal projection neuron subtypes during in vivo recordings. Brain Res. 1511, 21–32 (2013).

    Article  CAS  PubMed  Google Scholar 

  61. Hossein Eybposh, M., Caira, N. W., Atisa, M., Chakravarthula, P. & Pégard, N. C. DeepCGH: 3D computer-generated holography using deep learning. Opt. Express 28, 26636 (2020).

    Article  CAS  PubMed  Google Scholar 

  62. Dana, H. et al. High-performance calcium sensors for imaging activity in neuronal populations and microcompartments. Nat. Methods 16, 649–657 (2019).

    Article  CAS  PubMed  Google Scholar 

  63. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Yildirim, M., Sugihara, H., So, P. T. C. & Sur, M. Functional imaging of visual cortical layers and subplate in awake mice with optimized three-photon microscopy. Nat. Commun. 10, 1–12 (2019).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Inoue, M. et al. Rational design of a high-affinity, fast, red calcium indicator R-CaMP2. Nat. Methods 12, 64–70 (2015).

    Article  CAS  PubMed  Google Scholar 

  69. Zhao, Y. et al. An expanded palette of genetically encoded Ca2+ indicators. Cell 557, 1888–1891 (2011).

    Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Wang, K. et al. Direct wavefront sensing for high-resolution in vivo imaging in scattering tissue. Nat. Commun. 6, 1–6 (2015).

    Google Scholar 

  72. 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).

    Article  CAS  PubMed  Google Scholar 

  73. Levene, M. J., Dombeck, D. A., Kasischke, K. A., Molloy, R. P. & Webb, W. W. In vivo multiphoton microscopy of deep brain tissue. J. Neurophysiol. 91, 1908–1912 (2004).

    Article  PubMed  Google Scholar 

  74. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. 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).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. 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, 865–870 (2016).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Pachitariu, M. et al. Suite2p: beyond 10,000 neurons with standard two-photon microscopy. Preprint at https://www.biorxiv.org/content/10.1101/061507v2 (2016).

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

    Article  CAS  PubMed  Google Scholar 

  80. Wu, J. et al. Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo. Nat. Methods 17, 287–290 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Kazemipour, A. et al. Kilohertz frame-rate two-photon tomography. Nat. Methods 16, 778–786 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Yu, J. et al. Bright and photostable chemigenetic indicators for extended in vivo voltage imaging. Science 704, 699–704 (2019).

    Google Scholar 

  84. Adam, Y. et al. Voltage imaging and optogenetics reveal behaviour dependent changes in hippocampal dynamics. Nature 569, 413–417 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Fan, L. Z. et al. All-optical electrophysiology reveals the role of lateral inhibition in sensory processing in cortical layer 1. Cell 180, 1–15 (2020).

    Article  CAS  Google Scholar 

  88. Lou, S. et al. Genetically targeted all-optical electrophysiology with a transgenic cre-dependent optopatch mouse. J. Neurosci. 36, 11059–11073 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Adam, Y. All-optical electrophysiology in behaving animals. J. Neurosci. Methods 353, 109101 (2021).

    Article  PubMed  Google Scholar 

  90. Steinmetz, N. A. et al. Aberrant cortical activity in multiple GCaMP6-expressing transgenic mouse lines. eNeuro 4, 1–15 (2017).

    Article  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  93. Peron, S. & Svoboda, K. From cudgel to scalpel: toward precise neural control with optogenetics. Nat. Methods 8, 30–34 (2011).

    Article  CAS  PubMed  Google Scholar 

  94. Packer, A. M., Roska, B. & Häusser, M. Targeting neurons and photons for optogenetics. Nat. Neurosci. 16, 805–815 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Papagiakoumou, E., Ronzitti, E. & Emiliani, V. Scanless two-photon excitation with temporal focusing. Nat. Methods 17, 571–581 (2020).

    Article  CAS  PubMed  Google Scholar 

  96. Arrizón, V., Carreón, E. & Testorf, M. Implementation of Fourier array illuminators using pixelated SLM: efficiency limitations. Opt. Commun. 160, 207–213 (1999).

    Article  Google Scholar 

  97. Hernandez, O., Guillon, M., Papagiakoumou, E. & Emiliani, V. Zero-order suppression for two-photon holographic excitation. Opt. Lett. 39, 5953–5956 (2014).

    Article  PubMed  Google Scholar 

  98. Andermann, M. L., Kerlin, ΑM. & Reid, R. C. Chronic cellular imaging of mouse visual cortex during operant behavior and passive viewing. Front Cell. Νeurosci. 4, 3 (2010).

    Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Rose, T., Jaepel, J., Hübener, M. & Bonhoeffer, T. Cell-specific restoration of stimulus preference after monocular deprivation in the visual cortex. Science 352, 1319–1322 (2016).

    Article  CAS  PubMed  Google Scholar 

  104. Schoonover, C. E., Ohashi, S. N., Axel, R. & Fink, A. J. P. Representational drift in primary olfactory cortex. Nature 594, 541–546 (2021).

    Article  CAS  PubMed  Google Scholar 

  105. Ziv, Y. et al. Long-term dynamics of CA1 hippocampal place codes. Nat. Neurosci. 16, 264–266 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Driscoll, L. N., Pettit, N. L., Minderer, M., Chettih, S. N. & Harvey, C. D. Dynamic reorganization of neuronal activity patterns in parietal cortex. Cell 170, 986–999.e16 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Kentros, C. G., Agnihotri, N. T., Streater, S., Hawkins, R. D. & Kandel, E. R. Increased attention to spatial context increases both place field stability and spatial memory. Neuron 42, 283–295 (2004).

    Article  CAS  PubMed  Google Scholar 

  108. Huber, D. et al. Multiple dynamic representations in the motor cortex during sensorimotor learning. Nature 484, 473–478 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Gonzalez, W. G., Zhang, H., Harutyunyan, A. & Lois, C. Persistence of neuronal representations through time and damage in the hippocampus. Science 365, 821–825 (2019).

    Article  CAS  PubMed  Google Scholar 

  110. Marks, T. D. & Goard, M. J. Stimulus-dependent representational drift in primary visual cortex. Nat. Commun. 12, 1–16 (2021).

    CAS  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  112. Grosenick, L., Marshel, J. H. & Deisseroth, K. Closed-loop and activity-guided optogenetic control. Neuron 86, 106–139 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Yizhar, O. et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature 477, 171–178 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Venkatachalam, V. & Cohen, A. E. Imaging GFP-based reporters in neurons with multiwavelength optogenetic control. Biophys. J. 107, 1554–1563 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Ronzitti, E. et al. Submillisecond optogenetic control of neuronal firing with two-photon holographic photoactivation of chronos. J. Neurosci. 37, 10679–10689 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Chaigneau, E. et al. Two-photon holographic stimulation of ReaChR. Front. Cell. Neurosci. 10, 234 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  118. 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).

    Article  CAS  PubMed  Google Scholar 

  119. Forli, A., Pisoni, M., Printz, Y., Yizhar, O. & Fellin, T. Optogenetic strategies for high-efficiency all-optical interrogation using blue light-sensitive opsins. Elife 10, e63359 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Baker, C. A., Elyada, Y. M., Parra, A. & Bolton, M. Cellular resolution circuit mapping with temporal-focused excitation of soma-targeted channelrhodopsin. Elife 5, 1–15 (2016).

    Article  CAS  Google Scholar 

  121. Lim, S. T., Antonucci, D. E., Scannevin, R. H. & Trimmer, J. S. A novel targeting signal for proximal clustering of the Kv2.1 K+ channel in hippocampal neurons. Neuron 25, 385–397 (2000).

    Article  CAS  PubMed  Google Scholar 

  122. Sridharan, S. et al. High performance microbial opsins for spatially and temporally precise perturbations of large neuronal networks. Neuron 110, 1–17 (2021).

    Google Scholar 

  123. Antinucci, P. et al. A calibrated optogenetic toolbox of stable zebrafish opsin lines. Elife 9, 1–31 (2020).

    Article  Google Scholar 

  124. Wiegert, J. S., Mahn, M., Prigge, M., Printz, Y. & Yizhar, O. Silencing neurons: tools, applications, and experimental constraints. Neuron 95, 504–529 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Mattis, J. et al. Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins. Nat. Methods 9, 159–172 (2012).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  127. Bounds, H. A. et al. Multifunctional Cre-dependent transgenic mice for high-precision all-optical interrogation of neural circuits. Preprint at https://www.biorxiv.org/content/10.1101/2021.10.05.463223v2.article-info (2021).

  128. Koester, H. J., Baur, D., Uhl, R. & Hell, S. W. Ca2+ fluorescence imaging with pico- and femtosecond two-photon excitation: signal and photodamage. Biophys. J. 77, 2226–2236 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Hopt, A. & Neher, E. Highly nonlinear photodamage in two-photon fluorescence microscopy. Biophys. J. 80, 2029–2036 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Zhang, Z., You, Z. & Chu, D. Fundamentals of phase-only liquid crystal on silicon (LCOS) devices. Light Sci. Appl. 3, 1–10 (2014).

    Article  Google Scholar 

  131. Ahderom, S., Raisi, M., Lo, K., Alameh, K. E. & Mavaddat, R. Applications of liquid crystal spatial light modulators in optical communications. 5th IEEE International Conference on High Speed Networks and Multimedia Communication. 239–242 (2002).

  132. Gerchberg, R. W. & Saxton, W. O. A practical algorithm for the determination of phase from image and diffraction plane pictures. Opt. (Stuttg.). 35, 237–246 (1972).

    Google Scholar 

  133. Yang, W. et al. Simultaneous multi-plane imaging of neural circuits. Neuron 89, 269–284 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Thalhammer, G., Bowman, R. W., Love, G. D., Padgett, M. J. & Ritsch-Marte, M. Speeding up liquid crystal SLMs using overdrive with phase change reduction. Opt. Express 21, 1779–1797 (2013).

    Article  PubMed  Google Scholar 

  135. Love, G. D., Major, J. V. & Purvis, A. Liquid-crystal prisms for tip-tilt adaptive optics. Opt. Lett. 19, 1170 (1994).

    Article  CAS  PubMed  Google Scholar 

  136. Wu, S.-T. & Wu, C.-S. High-speed liquid-crystal modulators using transient nematic effect. J. Appl. Phys. 65, 527–532 (1989).

    Article  CAS  Google Scholar 

  137. Xun, X., Cho, D. J. & Cohn, R. W. Spiking voltages for faster switching of nematic liquid-crystal light modulators. Appl. Opt. 45, 3136–3143 (2006).

    Article  CAS  PubMed  Google Scholar 

  138. Hu, H. et al. Advanced single-frame overdriving for liquid-crystal spatial light modulators. Opt. Lett. 37, 3324–3326 (2012).

    Article  PubMed  Google Scholar 

  139. Bhatia, A., Moza, S. & Bhalla, U. S. Patterned optogenetic stimulation using a DMD projector. In Methods in Molecular Biology. Vol. 2191 173–188 (Humana Press Inc., 2021).

  140. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Miller, L. R. et al. Considering sex as a biological variable in preclinical research. FASEB J. 31, 29–34 (2017).

    Article  CAS  PubMed  Google Scholar 

  142. Guo, Z. V. et al. Procedures for behavioral experiments in head-fixed mice. PLoS One 9, e88678 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  143. Di Leonardo, R., Ianni, F. & Ruocco, G. Computer generation of optimal holograms for optical trap arrays. Opt. Express 15, 1913 (2007).

    Article  PubMed  Google Scholar 

  144. Holtmaat, A. et al. Long-term, high-resolution imaging in the mouse neocortex through a chronic cranial window. Nat. Protoc. 4, 1128–1244 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Cetin, A., Komai, S., Eliava, M., Seeburg, P. H. & Osten, P. Stereotaxic gene delivery in the rodent brain. Nat. Protoc. 1, 3166–3173 (2006).

    Article  CAS  PubMed  Google Scholar 

  146. Luo, L., Callaway, E. M. & Svoboda, K. Genetic dissection of neural circuits. Neuron 57, 634–660 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Ehrengruber, M. U. et al. Gene transfer into neurons from hippocampal slices: comparison of recombinant Semliki Forest virus, adenovirus, adeno-associated virus, lentivirus, and measles virus. Mol. Cell. Neurosci. 17, 855–871 (2001).

    Article  CAS  PubMed  Google Scholar 

  149. Zhang, F., Wang, L. P., Boyden, E. S. & Deisseroth, K. Channelrhodopsin-2 and optical control of excitable cells. Nat. Methods 3, 785–792 (2006).

    Article  CAS  PubMed  Google Scholar 

  150. Wekselblatt, J. B., Flister, E. D., Piscopo, D. M. & Niell, C. M. Large-scale imaging of cortical dynamics during sensory perception and behavior. J. Neurophysiol. 115, 2852–2866 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Carandini, M. & Churchland, A. K. Probing perceptual decisions in rodents. Nat. Neurosci. 16, 824–831 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Issa, J. B. et al. Multiscale optical Ca2+ imaging of tonal organization in mouse auditory cortex. Neuron 83, 944–959 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Marshel, J. H., Garrett, M. E., Nauhaus, I. & Callaway, E. M. Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040–1054 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Couto, J. et al. Chronic, cortex-wide imaging of specific cell populations during behavior. Nat. Protoc. 16, 3241–3263 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Chen, J. L., Pfäffli, 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. 19, 4689–4698 (2013).

    Article  CAS  Google Scholar 

  156. Zhang, F. et al. The microbial opsin family of optogenetic tools. Cell 147, 1446–1457 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Peron, S. et al. Recurrent interactions in local cortical circuits. Nature 579, 256–259 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Hillel Adesnik, Isaac Bianco, Spencer Brown, Jacques Carolan, Valentina Emiliani, Darcy Peterka, Evelyn Wong and Zihui Zhang for comments on the manuscript; Theshika Jeyaratnam for CA1/CA3 behavioral training and surgeries; Soyon Chun, Agnieszka Jucht and Olivia Houghton for mouse breeding; Selmaan Chettih and Christopher Harvey for developing and sharing the somatically restricted C1V1 opsin; and Bruker Corporation for technical support. This work was supported by grants from the Wellcome Trust, Gatsby Charitable Foundation, ERC, MRC and the BBSRC.

Author information

Author notes

  1. These authors contributed equally: Lloyd E. Russell, Henry W. P. Dalgleish.

Authors and Affiliations

  1. Wolfson Institute for Biomedical Research, University College London, London, UK

    Lloyd E. Russell, Henry W. P. Dalgleish, Rebecca Nutbrown, Oliver M. Gauld, Dustin Herrmann, Mehmet Fişek, Adam M. Packer & Michael Häusser

  2. Sainsbury Wellcome Centre, University College London, London, UK

    Henry W. P. Dalgleish

  3. Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK

    Adam M. Packer

Authors
  1. Lloyd E. Russell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Henry W. P. Dalgleish
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rebecca Nutbrown
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Oliver M. Gauld
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dustin Herrmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mehmet Fişek
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Adam M. Packer
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael Häusser
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

L.E.R., H.W.P.D., R.N., O.M.G., D.H., M.F. and A.M.P. built experimental apparatus, wrote software, performed surgeries, trained animals, carried out experiments and analyzed data. L.E.R. and H.W.P.D. wrote the manuscript, with input from A.M.P. and M.H., and all authors jointly edited and revised the protocol.

Corresponding authors

Correspondence to Adam M. Packer or Michael Häusser.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Protocols thanks Andrew Hires, Jinho Kim, Luis Carrillo-Reid, Weijian Yang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

Dalgleish, H. W. et al. eLife 9, e58889 (2020): https://doi.org/10.7554/eLife.58889

Packer, A. M. et al. Nat. Methods 12, 140–146 (2015): https://doi.org/10.1038/nmeth.3217

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Russell, L.E., Dalgleish, H.W.P., Nutbrown, R. et al. All-optical interrogation of neural circuits in behaving mice. Nat Protoc 17, 1579–1620 (2022). https://doi.org/10.1038/s41596-022-00691-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-022-00691-w

  • Springer Nature Limited

This article is cited by

Search

Navigation