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Whole-brain activity mapping onto a zebrafish brain atlas

Abstract

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.

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Figure 1: Analysis pipeline: creating the zebrafish reference brain atlas (Z-Brain) and whole-brain activity maps (MAP-maps).
Figure 2: pERK is a neural-activity marker in zebrafish neurons.
Figure 3: Neural activity underlying the OMR.
Figure 4: Activity induced by aversive stimuli and by hunting and feeding.
Figure 5: Spatial ICA across fish as a method for localizing functional brain networks.

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Acknowledgements

We are grateful to M. Wullimann (Ludwig Maximilian University) for his critical and detailed input regarding the identification of regions for the Z-Brain segmentation, Y. Yoshihara (RIKEN Brain Science Institute) and T. Okuyama (University of Tokyo) for pointing us to the pERK antibody, G. Jefferis (MRC Laboratory of Molecular Biology) for help with brain registrations, M. Nikitchenko (Harvard) for help with computational and web resources, A. Douglass (University of Utah) and J. Wortzman (Harvard) for creation of the Tg(UAS:GCaMP5G) line, D. Prober (Caltech) for sharing the Tg(hcrt:mRFP) and Tg(qrfp:GFP) lines before publication, M. Hasemeyer (Harvard) for many helpful discussions, and the many members of the zebrafish community who shared their transgenic fish lines. Funding was provided by an HFSP Long-Term fellowship (LT000772/2012-L to O.R.); the Agency for Science, Technology and Research, Singapore (C.L.W.); a Marie Curie Fellowship (E.A.N.); the Swartz Foundation (J.E.F.); the Simons Foundation (SCGB award 325207 to F.E.); and NIH grants R01 HL109525, U01 MH105960 (both to A.F.S.), R24 NS086601, U01 NS090449 and DP1 NS082121-02 (to F.E.).

Author information

Authors and Affiliations

Authors

Contributions

O.R., F.E. and A.F.S. conceived of the project. O.R. performed most experiments and data analysis. C.L.W., E.A.N., D.S. and A.M.B.L. also performed experiments. E.A.N., J.E.F. and R.P. also analyzed data. D.S. and C.R. created new transgenic fish strains. O.N. built the website. O.R., F.E. and A.F.S. wrote the paper, with input from all other authors. F.E. and A.F.S. supervised the project.

Corresponding authors

Correspondence to Owen Randlett or Florian Engert.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Qualitative analyses of Z-Brain registration accuracy.

(a) Images of the post-registration positioning of Hcrt and Qrfp expressing cells in the hypothalamus from 15 different Tg(Hcrt:RFP);Tg(Qrfp:GFP)48 double transgenic fish, and the mean-signal across all fish, highlighting the tight overlap of cell-occupied territories across fish and the differential territories of these adjacent cell types. Images are maximum intensity z-projections over the 21 slices (42um) (b) Examples of the staining patterns of 14 different labels in the tectal neuropil, revealing clear and distinct banding patterns. Images are all from the same x-plane in the Z-Brain. (c) Convergence of multiple markers labeling Mauthner cell (MC) circuitry in the Z-Brain. Reticulospinal backfills and Tg(S1181t:Gal4; uas:Kaede)51 label the Mautner cell soma and axon. Tg(-6.7FRHcrtR:Gal4);Tg(uasKaede)37 and anti-Znp1 label the MC axon cap (AxC), and anti-Glycine receptor labels the surface of the MC. Images are all from the same z-plane in the Z-Brain. Scale bars, 50 μm.

Supplementary Figure 2 Examples of the successful registration of brains imaged pre-fixation and post-fixation.

Tg(Elavl3:GCaMP5G)2 fish were imaged live by 2-photon microscopy to record calcium activity. Fish were then fixed, and immunostained for pERK and tERK (not shown), and the Tg(Elavl3:GCaMP5G) transgene was re-imaged by confocal microscopy. The post-fixation image data was then registered into the anatomical stack acquired during live imaging using CMTK, and the imaging slice was re-identified using 3D cross correlation analysis. This resulted in cellular resolution overlap between the pre-and post fixation data. Shown are examples from two different fish. Scale bars, 50 μm.

Supplementary Figure 3 Discriminability and cell-type promiscuity of the pERK indicator.

(a) The Reciever Operator Characteristic plots for 4 different fish, comparing the ability of pERK to discriminate between true and false positives, where a ROI with >30 s of detected Ca2+ activity is considered to be a true positive and an active cell. Strong leftward deviation from the diagonal line indicates good discriminability in all four fish analyzed. (b) The area under the ROC curve (AUC) yields a number between 0 and 1, representing the probability that the pERK will be higher in a randomly chosen active neuron than in a randomly chosen silent neuron. By plotting the AUC as a function of the threshold of required activity observed during Ca2+ imaging to classify a cell as ‘active’, we see that the AUC increases as we increase this stringency on activity. We observe values of nearly chance (0.5) for very low activity thresholds (<1 s), while after 10 and 30 s thresholds we see values of ~0.7 and ~0.8, and we observe perfect discrimination in Fish 2 at the 41-s threshold. This indicates that the discriminability of the pERK indicator increases with increasing levels of activity. (c) Examples of Tg(Vglut2a:GFP)64 positive (arrows) and negative (arrowheads) cells exhibiting high pERK levels in the Habenula (Hab) and Telencephalon (Tel). (d) Examples of a Tg(Glyt2:GFP)53 positive (arrow) and negative (arrowhead) cell exhibiting high pERK levels in the hindbrain.

Supplementary Figure 4 Z-Brain analyses of OMR-induced activity patterns showing the activation of anterior-hindbrain GABAergic neurons.

Virtual colocalization analysis, comparing the OMR-induced activity in the medial anterior hindbrain (m-aHB) and lateral anterior hindbrain (l-aHB) to the Tg(Gad1b:GFP)32 label. The MAP-Map activity patterns are shown as outlines of the activated areas. (b) Comparison of pERK levels in Gad1B-positive cells in the m-aHB and l-aHB of Tg(Gad1B:GFP) fish, presented with gratings moving to the right. Shown are histograms, revealing significantly increased pERK levels on the right side of the brain (p=4.3x10−25, and p=8.2x10−15 for the m-aHB and l-aHB respectively, Mann-Whitney test, n=8 fish). The inset shows the results for non-GFP labeled cells, which do not show such a strong (although still significant) shift in distribution (p=6.9x10−4, and p=3.6x10−3 for the m-aHB and l-aHB, respectively). Scale bar, 50 μm.

Supplementary Figure 5 Virtual colocalization of Z-Brain labels and hunting- and feeding-induced activity.

(a) MAP-Map activity induced by exposure to paramecia (Fig. 4i) is present in the vicinity of the nucleus of the medial longitudinal fascicle (nucMLF), which partially overlaps with the MeL neurons and surrounding neuropil anterior (arrowheads) and posterior (arrows) to the cells. (b) Strong activation of the area postrema, virtually overlapping with the noradrenergic neurons labeled by both Tg(etVmat2:GFP)52 and anti-TH Z-Brain labels. (c) Suppressive signals in the dorsal-caudal hindbrain (dcHB) overlapped with two stripes of neurons labeled by Tg(Glyt2:GFP)53, which are referred to as Stripe 2 and Stripe 3 in the Z-Brain. Scale bars, 50 μm.

Supplementary Figure 6 Independent components retrieved from the analysis of 820 pERK-stained fish.

Shown are the Z and X maximum intensity projections of the z-score values of the 30 independent components, linearly mapped between z-score values of 1 and 4. Green and magenta colors represent positive and negative loadings of the independent component signals, respectively.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Table 1 (PDF 13356 kb)

Anatomical labels in the Z-Brain.

The 29 image stacks in the Z-Brain database are show, scrolling from dorsal to ventral. Stacks are in the same order as in Supplementary Table 1, moving right to left and top to bottom of the montage. (AVI 2718 kb)

Segmented anatomical regions in the Z-Brain.

Three slice views of the Z-Brain are shown in the left panel (blue box = x/y, green = x/z, red =y/z). Shown are the outlines of all the anatomical regions contained in the Z-Brain, overlayed on the Tg(HuC:H2B-RFP) mean stack label. The slice region for each box is shown by the colored tick marks. The right panel displays a rotating 3D reconstruction of the Z-Brain region outlines. Colours are assigned pseudo-randomly, biased such that the major anatomical regions are enriched for the following colours: Telencephalon \xA0 Green, Diencephalon \xA0 Cyan, Mesencephalon \xA0Yellow, Rhombencephalon \x96 Red, Spinal Cord \xA0 Magenta, Ganglia/Other (including eyes and olfactory epithelium) \xA0 Blue.\xA0 (AVI 48535 kb)

MAP-Map: exposure to pentylenetetrazol (PTZ), related to Fig. 2f.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1941 kb)

MAP-Map: exposure to MS-222, related to Fig. 2g.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 2023 kb)

MAP-Map: exposure to MS-222, related to Fig. 2h.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1932 kb)

MAP-Map: the optomotor response, related to Fig. 3c.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 169 kb)

MAP-Map: exposure to mustard oil, related to Fig. 4a.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 2105 kb)

MAP-Map: tap stimuli, related to Fig. 4b.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1992 kb)

MAP-Map: exposure to noxious heat, related to Fig. 4c.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1941 kb)

MAP-Map: electric shock stimuli, related to Fig. 4d.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1986 kb)

Intersection of aversive MAP-Maps, related to Fig. 4e.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 460 kb)

MAP-Map: exposure to paramecia, related to Fig. 4i.

Green and magenta signals represent increased and decreased neural activity (pERK levels) over controls, respectively. Blue, green and red boxed regions show the x/y, x/z and y/z slice views. Tick marks depict the slice view position. (MP4 1938 kb)

Supplementary Data 1

Anatomical analyses of MAP-Maps using the Z-Brain. For each MAP-Map (Fig. 2f-h, 3c, 4a-e,i) there are two table outputs as separate sheets in the .xls file, reflecting green (activation) signals, and magenta (suppressive) signals, relative to controls. In each table, column 1 is the name of the ranked Z-Brain region, column 2 is the mean signal within that region, where 65535 would represent a fully saturated signals with all voxels having greater than or equal to a 0.5 delta median value, and 0 would represent no signal. In columns 3 through 12 we list the top five candidate anatomical labels that overlap with the MAP-Map signal in the region. Odd columns list the label's name, even columns indicate the enrichment for that label, which is calculated as the mean label signal within the pixels that show activity, divided by the mean label signal in the 50 pixels surrounding the region. Therefore, numbers greater than 1 indicate signal enrichment over the surrounding. (XLS 609 kb)

Supplementary Data 2

Quantification and ranking of label signals within Z-Brain regions. For each region the labels are ranked according to either the local signal enrichment calculated as the mean signal within the region, divided by the mean signal in a 50 voxel radius surrounding the region (Brightness Ratio to Surrounding sheet), or the mean signal within the region (Average Brightness sheet). (XLS 592 kb)

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Randlett, O., Wee, C., Naumann, E. et al. Whole-brain activity mapping onto a zebrafish brain atlas. Nat Methods 12, 1039–1046 (2015). https://doi.org/10.1038/nmeth.3581

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