Extended Data Fig. 2: DMN benchmark of connectomic constraints.

(a-d) How would incomplete knowledge of connectome affect the tuning predictions? We artificially varied DMNs with random parameters, connectome-constrained or task-optimized parameters. Five experiments: Four ‘Synapse-optimized models’, one ‘Fully optimized’. Details in Methods. How would incomplete knowledge of cell types affect the tuning predictions? We artificially assumed some cell types to be indistinguishable, with shared physiological parameters (resting potentials, time constants, and unitary synapse strengths). Two experiments: (1) ‘Full DMN Merge T4, T5’ assumes that T4 and T5 subtypes were indistinguishable, reducing the number of cell types to 58. (2) ‘Full DMN Merge E/I’ assumes that we had three cell types, excitatory (37 cell types), inhibitory (22 cell types) or both (4 cell types), based on our knowledge of synapse signs. Tuning predictions are shown in comparison to the Full DMN and the DMN with random parameters. (a) Task error. (b) Predicted correlations to flash response indices, T4, and T5 motion-tuning curves (10 best models). (c) Predicted correlations to known direction selectivity indices. (d) Distances between known preferred directions and predicted preferred directions for T4 and T5 neurons. (e) Better task-performing models predict motion-tuning neurons better. We correlate predicted tuning metrics from each model to the known tuning properties to understand when better performing models give us better tuning predictions. (orange) When correlating the direction selectivity index of each model to the binary known properties for T4 and T5 and their input cell types, we find that this correlation is higher for better performing models (Pearson correlation, \(r=-0.60\), p \(=2.6\times {10}^{-6}\), \(t=r\sqrt{\frac{\text{df}}{1-{r}^{2}}}\), 95% CI = [−1, −0.42], df =48). (magenta) While the models predicted the known contrast preferences generally well, the correlation of flash response index to the binary known contrast preferences of 31 cell types did not significantly increase with better performing models.