Figure 1.

Block diagram illustrating the role of different fly brain neuropils involved in motor control. Our model assumes that the parameter adaptation for the modulation of the ongoing behavior is performed by the MBs that receive reinforcement signals in form of dopaminargic/octopaminergic neuron activity and elaborate the learning process using a spiking neural network (SNN). The robot performs a visually guided navigation that acts on the Central Pattern Generator (CPG) structure to control locomotion. A reinforcement signal is generated for the MBs whereas a Random Function Generator (RFG) is used to include fluctuations in the set of control parameters for the CPG. The SNN function is used to memorize the temporal evolution of the modulated parameters if this improves the final motor behavior during learning.