All experiments were performed with approval from and in accordance with the University of Queensland Animal Welfare Unit (approval SBMS/378/16). Adult zebrafish (Danio rerio) were housed in a commercial RAS aquarium (Tecniplast S.p.A., Varese, Italy), in 28°C water (pH 7.5 ± 0.26, conductivity 992 ± 35 μS/cm², Ammonia 0–0.25 ppm, GH 83 ± 25 ppm, Ca2+ 76 ± 26 ppm) on a 14:10 h light:dark photoperiod, with 310,000 μJs/cm² UV disinfection. Fish were fed twice daily with a mixed commercial diet of O.range Wean and NRD at a 1:1 ratio, with a dusting of Spirulina powder (100g/kg; INVE Aquaculture Thailand) at a rate of approximately 5% body mass per day. Fish were housed at a stocking density of 10 fish per liter. Larval fish were reared in a 3 per-ml rotifer polyculture, based on the method described in Best et al. (2010), before being weaned to an exclusive dry food diet by 30 dpf. Adult zebrafish were mated as previously described to generate larvae for experiments (Westerfield, 2000). All experiments were performed in animals homozygous for the nacre mutation of the Tupfel long fin (TLN) strain (Lister et al., 1999).

The ChR2(ET/TC)-mCherry plasmid (Berndt et al., 2011) was provided by K. Deisseroth (Stanford University). All subcloning for transgenesis was performed using the Gateway Tol2 transgenesis system (Kwan et al., 2007). pME-MCS (construct 237, Tol2kit v1.2) was altered to include additional cloning sites with the forward primer CCCGGGACCGGTAGATCTTGATCAGGATCC and the reverse primer GGATCCTGATCAAGATCTACCGGTCCCGGG, creating the plasmid pME-MCS_linker. ChR2(ET/TC)-mCherry was cloned into the middle entry vector pME-MCS_linker using a blunt ApaI and XbaI sites, creating PME_ChR2(ET/TC)-mCherry. This was combined with a 10.5X UAS 5′ entry vector (construct 327, Tol2kit v1.2), a 3′ polyA containing vector (construct 302, Tol2kit v1.2) and a pDestTol2pA2 destination vector (construct 394, Tol2kit v1.2) using LR Clonase II Plus (Life Technologies) in a multi-site Gateway reaction. This generated the plasmid pDest_10.5XUAS:ChR2(ET/TC)-mCherry, which was confirmed by sequencing (AGRF, The University of Queensland, St. Lucia, QLD, Australia).

For transgenesis, plasmids were injected into single cell embryos within 40 min of fertilization, with an injection mix containing 75 ng/μL Tol2 transposase RNA and 100 ng/μL plasmid DNA. Injections were carried out in embryos obtained from crosses where a Gal4^s1168t;UAS:Kaede (Scott and Baier, 2009) animal was mated to an animal homozygous for the nacre mutation (Lister et al., 1999). Injected embryos were screened for transient expression of the protein at 48 h post fertilization, and were then raised to adulthood. Founders with offspring containing the desired transgene were identified using fluorescence microscopy, and were then outcrossed to TLN animals to create stable transgenic lines.

Animals expressing UAS:Kaede under the control of the Gal4^s1113t transgene (Scott et al., 2007) were fixed, stained with the tERK antibody (Cell Signaling, ID 4696), and imaged as previously described (Randlett et al., 2015). Multiple tiles were stitched using the Pairwise Stitching ImageJ plugin (Preibisch et al., 2009). Image registration of Kaede expression was performed against a model of anti-tERK expression in the nervous system of larval zebrafish. This was performed with CMTK¹ using the command string -awr 010203 -T 8 -X 52 -C 8 -G 80 -R 3 -A “--accuracy 0.4” -W “--accuracy 1.6”. Multiple (n = 9) registered animals were combined to create an average model of Kaede expression in Gal4^s1113t;UAS:Kaede animals, which was incorporated into a local version of the Z-Brain atlas. Analysis of the location of expression of a given transgenic line was performed using the Z-Brain toolbox (Randlett et al., 2015).

Animals expressing the desired fluorescent proteins, under the control of the Gal4^s1113t were mated and raised as outlined above. All Kaede photoconversion experiments were carried out in 6 dpf animals, which were screened for desired fluorescence at 2 dpf and raised in the dark to avoid unwanted photoconversion. At 6 dpf, animals were mounted dorsal side down in 2% low melt agarose (Progen Biosciences, Murrarie, QLD, Australia) in 50 mm glass bottom dishes (MatTek Corporation, Ashland, MA, USA), which were then filled with E3 media.

Photoconversions were performed on an Olympus BX61 upright confocal microscope, using 405 nm light focused into a 10 μm region of interest (ROI), which was scanned across the cell bodies of neurons expressing UAS:Kaede. After conversions, animals were left for 1 h at 28.5°C in the dark, to allow photoconverted Kaede to diffuse from converted somae into axons. Fish were then imaged on an inverted Yokogawa 3i spinning disc confocal, using a 488 nm laser to image unconverted (green) Kaede, and a 561 nm laser to image converted (red) Kaede. Z-stacks were taken at 40× magnification, with a 0.2 μm slice interval.

Other fluorescent microscopy of the Gal4^s1113t line was performed on a Zeiss-LSM 710 inverted confocal microscope, using a 561 nm laser to image red fluorescence, and a 488 nm laser to image green fluorescence, and using either 10× or 20× objectives.

Deconvolution of images acquired using the spinning disc confocal was performed with Huygens Professional Plus Deconvolution (Scientific Volume Imaging, Hilversum, Netherlands). A theoretical point spread function (PSF) was used, calculated from the parameters used for image acquisition. The signal to noise ratio (SNR) was calculated separately for each channel for each image by comparing the fluorescence intensity of a ROI to the fluorescence intensity of the background. Deconvolution was performed with a total image change threshold of 0.01, with single block processing on and a maximum iteration value of 60.

Spatial analysis of neuropil laminae was performed using Imaris v8.1 (Bitplane, Zurich, Switzerland). Surfaces of both the red and green channels in the neuropil were created using the “surface creation” plugin, where the neuropil was highlighted as a ROI. To remove any out-of-focus light remaining after deconvolution, a background subtraction of 0.2 μm was used. Thresholding of the image was performed so that only axons in the neuropil were included in the surface reconstruction. Once surfaces were completed, clipping planes were used to section out a 20 μm slice through the medial region of the rostral-caudal axis. To calculate the average intensity of the red and green channels, measurements of the fluorescence intensity was taken in three evenly spaced points, which were averaged to get the mean fluorescent intensity over the depth of the neuropil.

Animals used for optogenetic experiments were generated by crossing animals carrying Gal4^s1113t to animals carrying Gal4^s1168t;UAS:ChR2-mCherry, HuC:H2B-GCaMP6s, creating larvae with the genotype Gal4^s1113t;UAS:ChR2-mCherry, HuC:H2B-GCaMP6s. Animals were screened for the desired fluorescent pattern at 2 dpf, and were raised until 6 dpf as described above. Animals were mounted dorsal side up in 2% low melt agarose and immobilized using 100 μM tubocurarine (tubocurarine hydrochloride pentahydrate, Sigma-Aldrich). Larvae were mounted in a custom built glass sided imaging chamber and were allowed to acclimate for 30 min prior to imaging on a house-built selective planar illumination microscope (SPIM; Thompson et al., 2016). Optogenetic experiments were performed by splitting a 488 nm laser between a spatial light modulator (SLM; HOLOEYE Photonics, Germany) and the illumination tube of the SPIM. To avoid off target optogenetic activation of ChR2, a 0.975 neutral density filter was added to the SPIM path upstream of the beam expander.

Imaging was performed at 5 Hz, for 70 s (350 time points), at a depth of 50 μm under the skin of the animal, with imaging focused on the tectum. The activation of the hypothalamic nuclei was performed at time points 50, 150 and 250, and with pulses lasting for either 100 ms for “short” experiments, or 5000 ms for “long” experiments. The hologram displayed on the SLM was iteratively calculated using the Gerchberg-Saxton algorithm (Gerchberg and Saxton, 1972; Whyte and Courtial, 2005), resulting in a 2D illumination source at a chosen depth. In relatively low-scattering medium we theorized that a 10 μm disc would be very thin (Lutz et al., 2008), however by scanning the 10 μm disc at the depth of the hypothalamus (125 μm below the skin), we determined that the light spread in the z-plane was approximately 15 μm above and below the focal point (Favre-Bulle et al., 2015). Sibling controls not expressing ChR2 were subjected to identical experimental conditions to control for illumination.

For movies taken during optogenetic experiments, we first deleted all frames in which the SLM was active; this resulted in movies containing frames 1–50, 77–150, 177–250 and 277–350 for long SLM experiments and frames 1–50, 53–150, 153–250 and 253–350 for short SLM experiments. This was done to avoid artifacts produced by the reflected SLM light. Images were then registered to eliminate drift in the X- and Y-axes using the “Align_slices_in_stack” ImageJ plugin². To create an individual ROI for each cell in the PVL and neuropil, an average Z-projection of the image sequence was generated and then cropped to the border of the PVL and neuropil. A mask of this image was created using the Morphological Segmentation Plugin in ImageJ with a watershed function tolerance of 18 (Meyer and Beucher, 1990; Legland et al., 2016). Oversegmenting was tolerated, as the merging of erroneously split cells was performed during subsequent MATLAB analysis of these data.

Analysis of all data was performed using a custom written MATLAB code. Data were imported as a 16 BIT .tiff series, which were then transformed into a 2-dimensional data matrix, containing the gray values of every pixel in the 350-frame time series. Using the mask created above, the mean values of all pixels within each ROI were calculated for each time point. To measure the activity of individual neurons, the baseline fluorescence for each ROI was calculated by averaging the first ten time points for each individual ROI (F0). The raw gray value of every time point (FI) minus the baseline, was then divided by the baseline giving us the fluorescent change over time, which was then multiplied by 100 to give us percentage change over time: ΔF/F = ((FI−F0)/F0)*100

After the ∆F/F of each ROI was calculated, ROIs with a correlation coefficient of above 0.97 were removed from the data using the corrcoeff MATLAB function. After duplicates had been removed, for each ROI at each SLM event, neural activity resulting from the SLM was identified by calculating the correlation of four time points before the SLM, and six time points after the SLM to three model profiles of GCaMP events. These were calculated by averaging 50 individual GCaMP signals over five separate movies (10 per movie) where cells were qualitatively excited or inhibited by the SLM illumination. For an ROI to be deemed either excited or inhibited, the minimum Pearson’s correlation coefficient of all three SLM events to a model GCaMP profile had to be greater than 0.6, and the maximum probability value was required to be below 0.001. Every ROI that passed the above criteria was included as either an excited or an inhibited ROI, depending on which model spike it was correlated to. ROIs that did not meet these criteria were not included in the analysis. This analysis was performed on all experimental and control data. To compare the number of active cells between groups, an unpaired Student’s t-test was performed (significance < 0.05), as data were normally distributed (one sample t-test).

Through preliminary screening of an existing collection of Gal4 enhancer trap lines (Scott et al., 2007; Scott and Baier, 2009), we identified the transgenic line Gal4^s1113t as containing apparent projections into the tectal neuropil in 6 dpf larvae. An initial assessment of the anatomy of the line was performed using the transgenic line UAS:Kaede (Scott et al., 2007). Animals with the genotype Gal4^s1113t;UAS:Kaede were used to create a model of the average expression pattern of the Gal4^s1113t transgenic line, which was then registered against the annotated Z-Brain atlas of the zebrafish brain (Randlett et al., 2015), and also compared with the the Atlas of Early Zebrafish Development (Mueller and Wullimann, 2005). Assessment against the Zebrafish Brain Atlas suggested expression within a small number of neurons in the vicinity of the rostral hypothalamus (RH), with sparse labeling of neurons in the rhombencephalon and telencephalon (Figure 1). Neurites originating from the labeled neurons in the vicinity of the RH were seen in the midbrain and hindbrain (Figure 1H). The most notable concentration of neurites was found in the tectal neuropil, where Kaede was concentrated toward the medial (and therefore, deep) laminae. Outside of the vicinity of the RH, we observed labeled neurites in the valvula cerebellum (Figure 1F), within neuropil regions of the hindbrain caudal to the cerebellum, and also in a region medial to the torus semicircularis (Figure 1H). Observations of Kaede expression in individual Gal4^s1113t; UAS:Kaede animals supported these conclusions (Figure 2).

Overall, this analysis suggests that the majority of cell bodies labeled within Gal4^s1113t are located within the vicinity of the RH, with additional sparse labeling in the forebrain and hindbrain (Figures 2A,B). This, in turn, implies that the neurites visualized in these animals likely belong to these RH neurons. To confirm that the neurites observed in the tectal neuropil are sending synapses to the neuropil, we created Gal4^s1113t; UAS:synaptophysin-GFP larvae (Heap et al., 2013; Hines et al., 2015), in which the presynaptic terminals of Gal4-positive neurons are labeled. Following photoconversion of Kaede in the whole animal, we observed dense GFP labeling of presynaptic terminals throughout the deep laminae of the tectal neuropil (Figure 2C), suggesting that these neurites are axons, and that they are forming synapses in, rather than simply passing through, the tectal neuropil.

The above data establish that neurons expressing Gal4 under the control of Gal4^s1113t transgene project axons into the tectal neuropil, but they do not conclusively demonstrate that the Gal4-positive RH neurons are the source of those axons. To address this, we performed targeted photoconversion of Kaede in the RH of Atoh7:Gal4; Gal4^s1113t, UAS:Kaede larvae, which express Kaede both in RGCs and throughout the Gal4^s1113t expression pattern (arrow, Figure 3A). Following targeted photoconversion of RH neurons, red Kaede diffused down the axons of these neurons, arriving in the deep sublaminae of the tectal neuropil (Figure 3B). Kaede in RGC axons remained unconverted, assuring that off-target photoconversion was negligible (Figures 3B,C). Combined with the previous data, this confirms that the Gal4-positive neurons in the RH are the source of the observed presynaptic terminals in the tectal neuropil.

In light of this, and since functionally distinct laminae are an important part of tectal visual processing, we next undertook a detailed analysis of the neuropil laminae into which the RH axons project. The tectal neuropils of Atoh7:Gal4; Gal4^s1113t, UAS:Kaede larvae with targeted RH photoconversion contain both the axons of RGCs (green, labeling the SO, SFGS, SGC, and SAC/SPV), and the axons of RH projection neurons (containing photoconverted red Kaede). This provides a scaffold in green that allows us to register our RH afferents against the retinorecipient laminae of the neuropil. The strongest signal from RH projection neurons was in the deepest neuropil lamina: the SAC/SPV (arrows, Figures 3C–F). Other RH projections were present in the SFGS (arrowhead, Figures 3C,D,F), and a non-retinorecipient sublamina located between the SGC and SAC/SPV (asterisks, Figures 3E,F). This shows that RH projection neurons target multiple discrete depths of the tectal neuropil, including both retinorecipient and non-retinorecipient laminae (Figure 3G).

In order to gauge the functional relevance of these RH projections, we next observed the calcium responses that tectal neurons have to optogenetic RH stimulation. To do this, we used larvae with the genotype Gal4^s1113t;UAS:Channelrhodopsin2(ET/TC)-mCherry, HuC:H2B-GCaMP6s (Chen et al., 2013; Vladimirov et al., 2014). It is worth noting that in these experiments, the imaging plane was significantly more dorsal than the ChR2-expressing neurons in the RH. The result is that the illumination plane, although it is at 488 nm, does not lead to any observable activation of ChR2-expressing neurons on the RH.

To determine whether projections from the RH are excitatory or inhibitory in the tectum, we performed experiments where neurons expressing ChR2 were excited with a short (100 ms) pulse of blue light. Such stimulation excited a similar number of tectal neurons both in our experimental larvae and in controls not expressing ChR2, suggesting that the responses in these experiments are simply tectal visual responses to the flash of light from the SLM (Figures 4A,C). As a means of probing for inhibitory effects, we extended our light pulse to 5 s in order to produce prolonged inhibition of postsynaptic tectal neurons. If RH inputs are inhibitory, this should result in a decrease in GCaMP signal in the postsynaptic cells (Tian et al., 2009; Akerboom et al., 2012), followed either by a return to baseline, or “rebound firing” in response to the disinhibition of the postsynaptic neurons at the end of hypothalamic stimulation (Bennett, 1966; Aizenman and Linden, 1999; Jay et al., 2015). Based on these expectations, a small but significant proportion of tectal neurons appeared to be inhibited by RH input (Figures 4B,C). These PVL neurons, both as individuals and as a population, showed decreased GCaMP fluorescence following the hypothalamic excitation, and in most cases, rebound firing. Habituation of this rebound firing occurred during the course of our three-trial experiment (Figure 4B).

The tecta of various teleost species, including zebrafish, are known to receive input from the retina, and from a host of regions throughout the brain. Here, we demonstrate that neurons within the RH project to the tectum in larval zebrafish. These findings are similar to those described in numerous fish species including the hagfish and lamprey, where numerous hypothalamic clusters have been observed projecting in an ipsilateral fashion to the optic tectum (Amemiya, 1983; Meek and Nieuwenhuys, 1998; de Arriba and Pombal, 2007). In inspecting these projections in more detail, we also show that they specifically target the tectal neuropil’s deeper retinorecipient laminae, as well as a non-retinorecipient lamina between the SGC and SAC/SPV. This arrangement has several implications for the overall structure of the tectal neuropil. It has previously been shown that the broad laminae delineated by RGC axons each comprise several sublaminae with distinct contributions to visual processing (Xiao and Baier, 2007; Bollmann and Engert, 2009; Xiao et al., 2011; Robles et al., 2013, 2014). The RH projections that we have found in retinorecipient laminae, especially the SFGS, occupy a sharp subset of the lamina, suggesting that they may be restricted to specific sublaminae. This suggests a tight coupling between retinal and nonretinal inputs to these laminae, and potentially specific contributions from the RH to particular types of visual processing. RH afferents also target one lamina, between the SGC and SAC/SPV, that is not innervated by RGCs. Two conclusions can be drawn from this observation. First, it shows that this non-retinorecipient lamina is not exclusively involved with secondary visual processing, since it is also incorporating distinct nonretinal inputs. Second, since RH inputs innervate a sharp subset of the space between the SGC and the SAC/SPV, it appears that these non-retinorecipient laminae, like their retinorecipient counterparts, may contain functionally distinct sublaminae.

Following the anatomical descriptions of these RH projections to the tectum, it was important to determine their functional contributions to tectal circuitry. This involved both short pulses of optogenetic stimulation to the RH (designed to elicit excitatory responses in tectal PVL neurons) and long pulses of RH stimulation (designed to identify inhibited PVL neurons). Short pulses of excitation in the RH led to tectal activity, but this was not significantly higher in ChR expressing animals than in ChR⁻ controls. This result is consistent with an absence of excitatory RH input to the tectum, or with a low level of excitatory input that fell below the sensitivity of our experiment. Long pulses of optogenetic stimulation to the RH drove inhibitory responses in the tectal PVL. The fact that there are apparently no tectal cells excited by RH stimulation suggests that the inhibited PVL neurons are directly post-synaptic to the projection neurons. Inhibition does not appear to result, for example, from the activation of tectal inhibitory neurons.

These experiments do not allow us to discriminate between the effects of direct monosynaptic connections and those resulting from more complex pathways. Therefore, it is possible that RH activity drives responses in an intermediate structure, which in turn inhibits PVL neurons. One candidate for such an intermediate structure would be the precursor to the preglomerular complex, the migrated posterior tubercular area (M2 region), which innervates the tectum (Mueller and Wullimann, 2005; Mueller, 2012). In the Gal4^s1113t line, this structure appears to receive neurites from RH neurons expressing Gal4 (Figure 1I), supporting this possibility. Given the direct anatomical projection from the RH to the tectal neuropil in this line, however, the most parsimonious explanation is that the RH projection neurons are feeding directly into the tectal circuit.

The combined results of our anatomical and functional analyses have implications for the roles that nonretinal inputs may play in tectal processing. Given the diverse roles for the hypothalamus including arousal (Prober et al., 2006; Chiu and Prober, 2013), the detection of prey (Filosa et al., 2016) and feeding (Yokobori et al., 2011, 2012; Nishiguchi et al., 2012) it seems likely that these inhibitory signals may provide some sort of modulatory effect, conceivably influencing approach/escape decisions or other behavioral calculations being carried out by tectal circuits (Barker and Baier, 2015; Bianco and Engert, 2015). Muto et al. (2017) have recently shown that visual prey stimuli trigger hypothalamic activity in larval zebrafish, and that this information is relayed through the pretectum prior to arriving in the hypothalamus. Furthermore, expression of toxins in the hypothalamus reduced prey capture behavior. This raises a possible role for the hypothalamus in gating predatory behavior.

The anatomy of these projections appears to be similar with those described by Kaslin et al. (2004), who show that Orexin expression in the tectal neuropil is confined to the SAC in adult zebrafish. This finding suggests that orexin-expressing neurons within the hypothalamus of zebrafish may project to similar laminae of the optic tectum as the RH projections shown in this study. If our described projections are those described by Kaslin et al. (2004), it suggests that they could potentially be involved in controlling sleep and wakefulness (Kaslin et al., 2004). That the responses in the tectum are sparse and inhibitory further supports the idea that the hypothalamus’ role is to influence or contextualize the sensory signals, rather than to be a major driver of them. Of course, the identity, morphology, and connectivity of the tectal cells inhibited by the RH will be of interest as this circuit is further explored, as would the activity of hypothalamic projection neurons in the contexts of predation, sleep and other behaviors.

More broadly, these results add to the direct evidence for a larval zebrafish tectum that receives more numerous and diverse inputs than had previously been recognized, more in line with what has been described in adult fish and tetrapods. The anatomical and circuit mapping experiments in this study compliment and extend recent work showing that the tectum and the Raphe, a structure known to target of hypothalamus in both larval and adult zebrafish (Lillesaar et al., 2009; Herculano and Maximino, 2014), work together to drive behaviors based on the feeding state of larvae (Filosa et al., 2016), and thus provides grounds to understand how the visual and metabolic systems work together to drive behaviors. Additionally, the results from the optogenetic studies presented here complement previous work describing the neurotransmitter profiles of neurons within the RH, showing in this context that they have inhibitory effects on postsynaptic partners (Kaslin et al., 2004). Combined, the facts that the tectum receives direct afferents from several brain regions (Yokogawa et al., 2012; Heap et al., 2013; Filosa et al., 2016), and responds to multiple sensory modalities (Thompson et al., 2016), paint a picture of a structure that is more completely homologous to its mammalian counterpart, the superior colliculus, than has previously been appreciated. They also suggest that the tectum may be less of a self-contained visual processing center, and more of an integrative locus for diverse information. While RGCs remain, both in anatomical and functional terms, the strongest single input to the tectum in larval zebrafish, it is increasingly clear that tectal function is broader and more nuanced than its traditional role as a visual processing center would suggest.