Fig. 4: More informative cues are accorded more weight.
From: Multimodal cue integration and learning in a neural representation of head direction
This figure shows data for 13 flies. a, A bright visual cue and wind cue were tested individually and then combined. One cue was shifted 120° in an alternating sequence every 5 min. In some experiments, the visual cue came first (as shown here) while, in others, the wind came first. b, In the initial single-cue epochs, mean HD encoding accuracy is similar for the two cues (P = 0.76, paired two-sided Wilcoxon test). Thick horizontal lines are mean values. Gray lines are individual flies. c, In the initial single-cue epochs, the difference in HD encoding accuracy for the two cues is correlated with the bump width difference (R2 = −0.68, P = 0.01, Pearson correlation) and the bump amplitude difference (R2 = 0.58, P = 0.04, Pearson correlation). d, Example responses to +120° shifts of the visual cue. In example 1, the bump shifts upward to follow the upward (positive) shift of the cue, whereas, in example 2, it does not. In both cases, the wind does not shift. Extended Data Figure 3a shows these examples in more detail. e, The bump preference index is significantly correlated with relative HD encoding accuracy in the two single-cue environments (P = 0.03, Pearson correlation). Each gray line at a single encoding accuracy connects the data for one fly (four wind shifts in orange and four visual shifts in blue). An index of −1 means that the bump follows the visual cue, whereas +1 means that the bump follows the wind. This index is close to −1 for example 1 and close to +1 for example 2 (blue numerals). f,g, Same as c (f) and e (g) but for model networks with two populations of ER neurons. In different simulation runs, we varied the amplitude of sensory activity of one ER population while holding the amplitude constant in the other population.
