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Fig. 4 Spectral tuning of cones by HCs. (A to E) Linear model of spectral tuning in an outer retinal network composed of four cone types and three HC types, with maximum connectivity matrix defined as in Fig. 3K (Methods). Cone tunings are initiated on the basis of in vivo data during HC block (Fig. 2B). Different HC combinations include (A) (from left) the following: no HCs, all HCs, and H1 only. In each case, the model computes resultant cone tunings (solid lines) superimposed on in vivo data in the absence of HC block (shadings, from Fig. 1F) (B) and reconstruction quality (C) as loss relative to the peak performance for the full H1 to H3 model (loss = 0) and in the absence of HCs (loss = 1) and normalized weights such that cones contributing to a given HC, and HCs contributing to the full model, each add up to 1 (D). In addition, resultant HC tunings are shown for the full H1 to H3 model (E). (F to J) In vivo voltage imaging of HC somata’s spectral tuning (Methods). (F and G) Example scan (F) [average image (top) and local response correlation (83) and regions of interest (ROIs; bottom)] and responses (G) (mean superimposed on individual repeats shown for the three HC somata in this scan, of which ROIs 1 and 2 responded broadly across all tested wavelength, while ROI 3 exhibited a clear short-wavelength preference). (H to J) Results of clustering of mean responses from n = 86 ROIs (H) (n = 15 fish) with cluster means (I) and extracted tuning functions (J) (means ± SD). (K and L) Mean tunings of in vivo HC clusters [(K), from (J)] and superposition of each modeled [solid lines, from (E)] and measured [shading, from (K)] HCs. Note that raw (G) and averaged (I) HC responses and the summary heatmap (H) are time inverted to facilitate comparison with summary plots (J to L). The grayscale bar in (H) is in z scores.