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Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits

Nature Methods volume 17, pages 107–113 (2020)Cite this article

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Abstract

Spontaneous and sensory-evoked activity propagates across varying spatial scales in the mammalian cortex, but technical challenges have limited conceptual links between the function of local neuronal circuits and brain-wide network dynamics. We present a method for simultaneous cellular-resolution two-photon calcium imaging of a local microcircuit and mesoscopic widefield calcium imaging of the entire cortical mantle in awake mice. Our multi-scale approach involves a microscope with an orthogonal axis design where the mesoscopic objective is oriented above the brain and the two-photon objective is oriented horizontally, with imaging performed through a microprism. We also introduce a viral transduction method for robust and widespread gene delivery in the mouse brain. These approaches allow us to identify the behavioral state-dependent functional connectivity of pyramidal neurons and vasoactive intestinal peptide-expressing interneurons with long-range cortical networks. Our imaging system provides a powerful strategy for investigating cortical architecture across a wide range of spatial scales.

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Fig. 1: Design of a dual-axis microscope for simultaneous mesoscopic and two-photon imaging.
Fig. 2: Analysis of simultaneously acquired micro- and meso-scale calcium imaging data.
Fig. 3: Simultaneous imaging reveals the functional connectivity of single neurons with large-scale cortical networks.
Fig. 4: Systemic AAV9 produces robust GCaMP expression in the brain.
Fig. 5: CCNs vary by neuronal class and sensitivity to arousal.
Fig. 6: Behavioral state is linked to CCN reorganization for a subset of neurons.

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Data availability

The data that support the findings of this study are available from the corresponding authors upon request.

Code availability

All code used for analyses is available through Code Ocean.

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Acknowledgements

The authors thank all members of the Multiscale Imaging of Spontaneous Activity in Cortex collaboration at Yale University for input during all stages of this project. We thank X. Ge, E. Lake, L. Tang, D. Scheinost and E. Mohns for input on data analysis, K. Zhang for assistance with data preprocessing, Y. Zhang for assistance with animal husbandry and maintenance and members of the Cardin, Constable, Crair and Higley laboratories for helpful comments during the preparation of this manuscript. We thank D. Kim and the GENIE Project (Janelia Research Campus) for GCaMP6s and GCaMP6f plasmids. We thank H. Zeng (Allen Institute) for the TIGRE2 transgenic mice. This work was supported by funding from the NIH (grant nos. MH099045 to M.J.H., EY022951 to J.A.C., NS094358 to M.C.C. and R.T.C., EY026878 to M.C.C., MH111424 to R.T.C. and M.C.C., EY029581 to D.B., GM007205 to D.B., NS007224 to D.B., EY028869 to A.S.H.). M.C.C. was supported by the William Ziegler III family.

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Author notes

  1. Gyorgy Lur

    Present address: Department of Neurobiology and Behavior, University of California, Irvine, CA, USA

  2. These authors contributed equally: Daniel Barson, Ali S. Hamodi.

Authors and Affiliations

  1. Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA

    Daniel Barson, Ali S. Hamodi, Gyorgy Lur, Jessica A. Cardin, Michael C. Crair & Michael J. Higley

  2. Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA

    Daniel Barson & R. Todd Constable

  3. MD/PhD Program, Yale School of Medicine, New Haven, CT, USA

    Daniel Barson

  4. Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA

    Xilin Shen & R. Todd Constable

  5. Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA

    R. Todd Constable

  6. Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA

    Jessica A. Cardin, Michael C. Crair & Michael J. Higley

  7. Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA

    Michael C. Crair

  8. Program in Cellular Neuroscience, Neurodegeneration and Repair, New Haven, CT, USA

    Michael J. Higley

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Contributions

All authors contributed to the overall study design. D.B., A.S.H. and J.A.C. collected the data. D.B., A.S.H., X.S. and J.A.C. analyzed the data. D.B., A.S.H., X.S., M.C.C. and M.J.H. wrote the manuscript. R.T.C., J.A.C., M.C.C. and M.J.H. supervised the project.

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Correspondence to Michael C. Crair or Michael J. Higley.

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Supplementary Figure 1 Two-photon imaging resolution through a glass microprism.

a, Example images of fluorescent beads imaged using either a 1.0 NA water objective through cover glass (Zeiss, left), an 0.4 NA air objective through cover glass (Mitutoyo, center), or the same 0.4 NA objective through the microprism (right). b, Point-spread function sizes, measured as the full-width at half-maximum amplitude, for the three imaging approaches shown in (a). Lateral (left) and axial (right) data are shown. Lateral mean±SEM: water/CG: 0.81 ± 0.01, air/CG: 1.08 ± 0.01, air/prism: 1.00 ± 0.02; axial mean±SEM: water/CG: 6.76 ± 0.21, air/CG: 9.55 ± 0.36, air/prism: 13.67 ± 0.35; n = 22, 24, and 20 beads, respectively. c, Distribution of signal-to-noise ratios for cells imaged under the same conditions. Mean±SEM: water/CG: 0.72 ± 0.02, air/CG: 0.87 ± 0.02, air/prism: 1.05 ± 0.02, p < 0.001 for all comparisons, Kolmogorov-Smirnov test, n = 142, 131, and 113 cells, respectively. d, Distribution of orientation selectivity indexes for cells imaged under the same conditions. Mean±SEM: water/CG: 0.38 ± 0.02, air/CG: 0.34 ± 0.02, air/prism: 0.34 ± 0.02, p > 0.05 for all comparisons, Kolmogorov-Smirnov test, n = 142, 131, and 113 cells, respectively.

Supplementary Figure 2 Comparison of methods for extracting fluorescent time-series.

a, Example field of view showing GCaMP6f-expressing neurons imaged via two-photon microscopy. Scale bar is 20 µm b, Distribution of neurons (regions of interest, ROIs) identified following rigid motion correction with manual selection (left) or non-rigid motion correction with automated selection (right). Color-matched cells are shown in (a). c, Relationship between correlations of single neuron time series versus correlations of CCNs, for the two different methods of ROI selection, for 176 matched cells in 1 mouse. d, Relationship between t-SNE 1 and t-SNE 2 values for all CCNs, illustrating that maps identified following either manual or automated ROI selection are similarly distributed, for 238 cells identified manually and 244 cells identified by Suite2p in 1 mouse. Colors are as in (b).

Supplementary Figure 3 Analysis of tissue damage beneath an implanted microprism.

a, Example coronal section of mouse brain, stained for Hsp70/72, a marker for cell damage. The prism was implanted over the right hemisphere (dashed box). Scale bar is 0.5 mm. b, Population data showing no change in Hsp70/72 expression relative to the control hemisphere for four animals.

Supplementary Figure 4 Comparison of parcellation methods with sensory-evoked activity.

Three example mice are shown, with activity evoked by whisker deflection (red) or auditory stimulation (blue) illustrated. Parcellations highlighted in white are for either the Allen CCFv3 atlas (upper images) or functional parcellation derived from spontaneous activity in the same animal (lower images). Scale bar is 2 mm.

Supplementary Figure 5 Additional examples of functional neuronal connectivity with cortical networks.

a, Illustration of the functional parcellation with regions labelled based on correspondence with the anatomical parcellation. Color code as in Fig. 3e. b, Activity index calculated from all significance maps for a single animal using the functional parcellation. c, Averages from the 3 clusters in (b). d, Schematized two-photon field-of-view with individual cells colored by cluster membership. Scale bar is 20 μm. e-h, Same as (a-d), but for a different mouse.

Supplementary Figure 6 Example outlier cell-centered networks for the clusters in Fig. 3.

Example CCNs displayed with the activity index of functionally-defined parcels from the same mouse shown in Fig. 3. The clusters to which these cells belong are indicated to the top left of each CCN. CCNs are roughly grouped based on which anatomical regions are most active, indicated to the left.

Supplementary Figure 7 Comparison of methods for calculating cortex-wide network membership.

a, Schematic of the spike-triggered average map (STM) procedure16, adapted for two-photon data. A spike-triggered average is calculated for all frames in a 2 second window around each ‘spike.’ For our analysis, we threshold each cell’s spike probability at four standard deviations above 0 (or a minimum of 0.2) to derive spike times. The STM is the maximum value for each pixel within the 2 second spike-triggered average. Permutation testing is performed by calculating a null distribution of STMs using 1000 random shuffles of spike times. Non-significant (p>0.05) pixels are transparent. b, Schematic of the spike-triggered average map (SpAM) procedure15, adapted for two-photon data. SpAMs are calculated by taking the partial correlation of cell ΔF/F and each mesoscopic pixel ΔF/F with respect to mean ΔF/F for all pixels across cortex. P values for each correlation are Benjamini-Hochberg corrected for multiple comparisons (5% false positive rate). Non-significant (p>0.05) pixels are transparent. c, CCN for the same cell (cell 3 from Fig. 3) as in (a, b). Non-significant (p > 0.05) pixels are transparent. d, Correlation between CCNs, SpAMs, and STMs for all analyzed cells (same as in Fig. 3) across 3 mice. Box-and-whisker plots of cell correlations show median, interquartile, and 5th-95th percentile values.

Supplementary Figure 8 Viral or transgenic expression of GCaMP6 does not disrupt cortical or hippocampal physiology.

a, Mean firing rate of regular spiking, putative pyramidal neurons in the visual cortex for the three cohorts of mice (wild-type mean±SEM: 1.1±0.2, n=3 mice, AAV9-hSyn-GCaMP6s mean±SEM: 1.2±0.2, n=3 mice, Slc17a7-Cre;CaMKIIa-tTa;TITL-GCaMP6f mean±SEM: 1.6±0.3, n=3 mice). b, Example local field potential (LFP) recordings from the three cohorts. c, Normalized LFP power spectra for the three cohorts, measured in visual cortex (upper traces) or hippocampus (lower traces). Shaded areas indicate SEM. N = 3 mice for each group. d, Overlaid power spectra from (c).

Supplementary Figure 9 Additional examples of CCNs varying by neuronal class and sensitivity to arousal.

a, Activity index calculated from all significance maps for all cells recorded in a single animal. Cells are clustered into six groups. Columns to the right indicate cell type (red indicates VIP-IN, black indicates pyramidal cell) and whether cells are correlated with whisking (colors as in Fig. 5d). b, Averages of the six clusters in (a) with parcels colored by their activity index. c, Fractional distribution of cells into each cluster, separated by type or modulation by whisking. d-f, g-i, Same as (a-c) for two additional mice.

Supplementary Figure 10 Two broad motifs for cortical network organization.

Schematic illustration showing the general patterns of long-range connectivity for cells in the primary somatosensory cortex as determined by simultaneous two-photon and mesoscopic imaging. Individual neurons tend to belong to either a fronto-lateral or postero-medial network, with both categories also involving retrosplenial areas.

Supplementary Figure 11 CCNs for VIP-INs and pyramidal cells are stable across days.

a, Schematized two-photon field-of-view of cells imaged over multiple days. Red indicates VIP-INs and black indicates pyramidal cells. Lighter shades indicate cells that were active in only one imaging session. Scale bar is 20 μm. b, CCNs for pyramidal cells and VIP-IN indicated by arrows in (a) over two days. c, Pearson’s correlation of CCNs calculated for individual pyramidal cells and VIP-INs from data collected over two days.

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Barson, D., Hamodi, A.S., Shen, X. et al. Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits. Nat Methods 17, 107–113 (2020). https://doi.org/10.1038/s41592-019-0625-2

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