Emergent spatial goals in an integrative model of the insect central complex
Fig 6
PI and vector memory of a food location.
(A) PI during the outbound journey (black path) and inbound journey (green path). The activity rate of the hΔ neurons is indicated for different location of both journeys; it encodes the home vector as a sine wave with amplitude corresponding to length and phase corresponding to angle. The agent is rewarded (finds food) when it reaches a set distance from the nest (200 l.u.) and triggers the creation of the synaptic long-term memory at the level of the FBt − to − hΔ axonal connections. (B) Retrieval outbound journey. The long-term FBt memory induces the steering circuit to drive the agent towards the location where the memory and PI cancel, i.e., the rewarded location. The distance between the search peak and target is used as a measure of precision in C. (C) Effect of varying the learning parameter βhΔ on the precision of retrieval journey: this modulates the vector length stored in memory. Each point represents one simulation with a fixed βhΔ randomly chosen in the [0 4] range. Note that because we modulated the motivational input to the FBt with a factor IFBt = 0.5, we corrected the value of βhΔ to verify that the best retrieval was achieve with a perfect memory (βhΔxIFBt ≈ 1).