Figure 2. Agreement between Readout Units Requires a Large Piriform.

(A) Response of a readout unit versus the response of a second readout connected to an independent set of piriform neurons, either before training (top) or after training to a single odor (bottom), for a panel of odors with 70%, with 30%, or at chance levels of overlap with the trained odor, color coded as in Figure 1. Gray boxes denote the regions in which the readouts do not agree for θ = 0.5 and f = 0.7.

(B) Scaling with N_y of readout agreement (with f = 0) versus other measures of readout performance: readout agreement with a threshold of θ = 0.5 (brown) or θ = 0.9 (orange), readout correlation (black), SNR (gray), and accuracy (magenta). All quantities except SNR are defined from 0 to 1 (Max[SNR] = 3.4). We normalize SNR such that the minimum value is 0 and the maximum value is 1 to enable comparison to other quantities.

(C) Comparison with experimental data from the Drosophila mushroom body. The correlation between two model MBONs as a function of the number of inputs they receive (black). Published data (Hige et al., 2015b) showing the correlation across odors in three conjugate pairs of MBONs versus the number of KCs that innervate each MBON (gray; mean ± SEM).

(D) Readout agreement is smaller than readout correlation (top), while readout accuracy is greater than normalized readout SNR (bottom).

(E) Intuition for why readout agreement is smaller than readout correlation. As the correlation between two readouts grows, their joint probability distribution becomes elongated (gray), but even when this distribution is very elongated, an appreciable portion remains in the off-diagonal quadrants (orange).