Article Figures & Data
Figures
- Figure 1.
Experiment description and anatomy. A, Experimental setup: a two-photon microscope was used to image 7 dpf head-restrained larvae while flashes of different luminance were projected on a screen below. B, Composite image showing stacks from GCs (red), IONs (in blue), and PCs (green) registered on a reference anatomy with the whole brain of a 7 dpf larva (in gray). In the enlargements, examples of the raw anatomy (in gray) and the segmented ROIs from a two-photon imaging session (in red, blue, and green for GCs, IONs, and PCs, respectively). See Extended Data Figure 1-1 for more details on the behavior elicited.
- Figure 2.
Responses of GCs and IONs to the “luminance steps” protocol. A, Left, Histogram of the average intertrial correlation (average correlation between activity recorded in different trials). The calculated threshold and the relative fraction of active cells are reported on the histogram. Center, Average traces grouped after hierarchical clustering. Cutting the dendrogram at the height marked by the line (on the left) resulted in eight different clusters, whose average activity is shown on the right, overimposed on a shade matching at each timepoint the brightness level displayed. B, Same plot as in A, for IONs. See Extended Data Figure 2-1 for more details.
- Figure 3.
GC and IONs respond to stimulus intensity and derivative. A, Regressor-based analysis was used to calculate the correlation coefficient between each cell’s fluorescence (lines) and a panel of regressors (shades). The plot shows the cells with the highest correlation values for luminance-related (first two rows) and transition-related (second two rows) regressors. B, Histogram of the distribution of best-fitting regressors for GCs (top) and IONs (bottom). Regressors on the left of the dashed line are luminance related, and regressors on the right are transition related. GCs score higher in luminance-related regressors compared with IONs. C, Scatter plot of the best transition-related coefficient and the best luminance-related coefficient for GCs (red) and IONs (blue) and their relative marginal distributions. The GC population has been downsampled randomly to match the number of IONs, while the marginal distributions refer to the entire population. GCs cluster in the bottom right quadrant of the plot (high luminance–regressor correlation, low transition–regressor correlation), while IONs show higher correlation coefficients for transition-related regressors. D, Performance of a nonlinear decoder used to predict luminance values from GCs (left) and IONs (right) activity. Each point in the swarm plot is one frame of the protocol with the corresponding luminance level (horizontal line). For GCs, 20 iterations of the decoding analysis were performed, with the number of GCs downsampled to match that of IONs. The violin plots in the left panel show the average distribution of predictions across all iterations, while the dots correspond to a single representative iteration. See Extended Data Figure 3-1 for more details.
- Figure 4.
Responses of GCs and IONs to the “flashes” protocol. A, Top-left, Intertrial correlation histogram of GCs for the “flashes” protocol. Center, Cells sorted after hierarchical clustering and (right) average activity for each cluster. B, Same plot as in A, for IONs. See Extended Data Figure 4-1 for more details.
- Figure 5.
Granule cell activity is temporally patterned. A, Single traces for early- (green), sustained- (gray), and late-responding (brown) ROIs. The average response (thick line) is superimposed on all single repetitions (thin lines) of stimulus presentation. B, GCs included in any of the luminance-excited clusters were then sorted based on their center of mass (COM) during the longest flash, with earlier-responding neurons on the top and late-responding ones on the bottom (bottom panels). The above traces represent the average response for ROIs binned according to the time at which their COM was reached (green for early-responding neurons, brown for late-responding ones). C, Same plot as in B, for IONs. In this case, traces in the top panels correspond to single ROI responses. D, Probability density function describing the time points at which responses of neurons from the two imaged populations reach their maximal response. E, Scatter plot of predicted versus actual time elapsed stimulus onset. Prediction was performed at each frame from ION activity (blue dots) and activity of a random subset of GCs (red dots). The red line and shaded area show average ± standard deviation of predictions from 200 GCs subsets. See Extended Data Figure 5-1 for more details.
- Figure 6.
PC responses to luminance stimuli. A, Top-left, Histogram of the average intertrial correlation and its relative threshold. Center, Hierarchical clustering of PC responses to the “steps” protocol, and average activity of the clusters selected after cutting the dendrogram at the height marked by the lines. The shade matches at each timepoint the brightness level displayed. B, Same as in A, for the “flash” protocol. See Extended Data Figures 6-1 and 6-2 for more details.
Extended Data
Extended Data
Download Extended Data, ZIP file.
Figure 1-1
A) Average normalized bout probability for each individual fish across all stimulus presentations (heatmap), and average probability across all fish (blue line). B) Bout probability changes on a 3.5 s window around luminance offsets. Average bout probability across all off transitions is shown for each fish in gray lines, and the average bout probability across all fish is plotted in blue. C) The average bout probability at offset (during the 1.5 s following luminance changes, green line) across all fish, compared to the 1st percentile (red line) of a dataset generated via bootstrapping. D) Difference between the bout probability at offset and the 1st percentile for the bootstrapping analysis performed individually on each fish. Fish labeled in green correspond to animals where the bout probability was smaller than the 1st percentile. Download Figure 1-1, TIF file.
Figure 2-1
A) Schema of the stimulus presented, with the color scheme used for all figures mapped on top of its luminance profile. B) Average fluorescence during the upward luminance steps from minimum luminance (left) and during downward luminance steps from maximum luminance (right) for each GC cluster. C) History dependence of luminance responses for all GC clusters. Average normalized fluorescence during the presentation of the same two intermediate levels of luminance (low intermediate: above, high intermediate: below), compared in epochs when it was reached from a higher (x values) or lower (y values) luminance level. Clusters that deviate from the diagonal are the ones showing the strongest temporal history dependence (color-coded according to Figure 2A). D) Example of GC responses from various clusters, with individual stimulus repetitions (thin lines), average (thick line), and the ROI morphology (on the right). E) Contribution of individual fish to the observed clusters for GCs and IONs. Each color corresponds to one fish. Download Figure 2-1, TIF file.
Figure 3-1
All regressors used in the regression analysis (shades), and the best scoring ROI for each regressor (lines). While for luminance-related regressors the highest correlation values were always from GCs, for transition-related regressors most of the best scoring ROIs were from IONs. Download Figure 3-1, TIF file.
Figure 4-1
A) Schema of the stimulus presented, with the color scheme used for all figures mapped on top of its luminance profile. E) Contribution of individual fish to the observed clusters for GCs and IONs. Each color corresponds to one fish. Download Figure 4-1, TIF file.
Figure 5-1
A) In order to cross-validate our sorting of ROI responses, the COM for each neuron was calculated based on the average response during half of its repetitions, and the other half of the repetitions were used to plot the figures shown in Figure 5. Figure 5-1A shows, for each ROI, the COM calculated on each half of the repetition. B) Histogram of the R2 values between predicted and actual time from stimulus onset, as decoded from 200 subsamples of GCs. The blue line marks the R2 value obtained using the same number of IONs. C) Additional examples for single GC traces exhibiting temporally-patterned responses, from early- to late-responding neurons (color coded from green to brown). Average response (thick lines) is superimposed to single repetitions of stimulus presentation (thin lines). Download Figure 5-1, TIF file.
Figure 6-1
A) Contribution of individual fish to the observed clusters for PCs in the steps protocol. Each color corresponds to one fish. B) Contribution of individual fish to the observed clusters for PCs in the flashes protocol. Download Figure 6-1, TIF file.
Figure 6-2
A) Schema of the modeling approach. (Left) PCs receive inputs from IONs and GCs. Starting from GC and IO response clusters (center) we linearly combined them trying to reconstruct each PC activity (right). B) Histogram of costs (L2) on the test traces from all PCs (green line), compared to a shuffle distribution (brown shade) that was obtained calculating costs after a random regressor-wise reshuffling of the weight matrix (i.e., all values from each individual regressor were kept and reshuffled in new random combinations). A threshold was defined to ensure that only 5% of these random fits could have a lower cost. The green shade indicates the data that were kept after such selection. C) Examples of individual fits. (Left) Average PC response (thick green line) calculated on the individual test repetitions (thin green lines), and reconstructed trace from the model (black line). (Right) Red, trace reconstructed with GC coefficients only; blue: trace reconstructed with IO coefficients only. D) Matrix of weights assigned to each regressor (rows) for all PC ROIs (columns). Vertical gray lines separate PCs clustered together in Figure 6A. E) Correlation between the reliability index and the fit error, including only PCs for which the fit was considered better-than-random. F) Scatter plot showing the relation between the GC/IO weights ratio vs. cell reliability. Each dot represents the two values for a single PC cell, color coded by the GC/IO index. The response of PCs dominated by GC inputs are more reliable compared to cells dominated by IO inputs (Spearman rho: 0.19, p = 5.8*10-4). Download Figure 6-2, TIF file.
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