Fig. 2. Overview of the key goals and analysis steps.

Goal 1 investigated how neurons reorganize with learning and determine whether numerosity training preserves the integrity of spontaneous number neurons (SPONs). Goal 2 examined how learning changes the properties of individual neurons along the information processing hierarchy from V1, V2, and V3 to IPS. We examined several neuronal properties, including neuronal tuning, stability, selectivity, and distance effects at a single unit level, how they change with numerosity training, and how they correspond to neuronal recordings in primate IPS. Goal 3 investigated how distributed population-level representations change with learning. Goal 4 examined latent structure of distributed population-level neural representations, the coding properties that emerge from these representations, and how these coding properties relate to number sense. Goal 5 identified neuronal tuning and distributed population-level representational features that predict network accuracy. In each goal we examined neural reorganization in each nDNN layer along the information processing hierarchy from V1, V2, V3 to IPS. We also performed control analyses using alternate training methods to check the robustness of the findings.