This project can be divided in three main tasks: 1) experimentation in mice to study the NCCs contribution to the generation of movement sequences, 2) development of new and more advanced cerebellar computational models based on recurrent networks, and 3) development of biologically inspired control systems based on cerebellar models for robot control.
Regarding the experimentation in mice, we designed and performed three different experiments to study how the cerebellum, and more concretely the NCCs, could contribute to the generation of movement sequences. We used a modified version of the eye blink conditioning (EBC) experiment for this study. In the original version, the mouse had to correlate a conditional stimulus (CS), a bright light, with an unconditional stimulus (US), an air puff in the eye, which is generated after the CS. After several training sessions, the cerebellum in the mouse learns to correlate both events, generating a conditional response (CR) that closes the eyelid after the CS and just before the US. In this project we modified this original experimental protocol, introducing another puff in the other eye (US2) after the first puff (US1). Thus, the mouse should generate a sequence of movements after the CS, closing both eyes (CR1 and CR2) in a coordinated way just before the US1 and US2 respectively.
Analyzing the brain anatomy, the CR1 could propagate between both sides of the cerebellum following different pathways: a) NCCs, b) red nuclei, and c) red and facial nuclei. We firstly performed optogenetics experiments in several genetically modified mice, implanting an optical fiber in the cerebellum to disable the generation of the CR1 and checking the effect in the CR2. The experimental results demonstrated that the first cerebellum used the CS to generate the CR1, while the second one just used the CR1 and US1, but not the CS, to generate CR2.Thus we demonstrated the capacity of both sides of the cerebellum to generate and coordinate movement sequences.
After the optogenetics study, we performed two additional pharmacological experiments to respectively inhibit the red and facial nuclei, “disabling the propagation” of the CR1 and checking the effect in CR2. In both cases, the suppression of the CR1 also produced the suppression of the CR2 (the same results that we observed in the optogenetics experiment).
Regarding the cerebellar modeling, we developed and published several advanced recurrent cerebellar models, using recurrent NOCs, to modulate the activity in the Inferior Olive (one of the cerebellar inputs) during simulated Vestibulo-Ocular Reflex (VOR) experiments. We have also implemented a full recurrent cerebellar model implementing both NCCs and NOCs, able to reproduce and explain the experimental results obtained during the first task.
Finally, for the neurorobotic experimentation, we have integrated the full recurrent cerebellar model in the sensorimotor system of a robot. Thanks to the new NCCs, this cerebellar model was able to inplicitely identify and model the manipulated object by the robot, adjusting the motor commands to perform the desired task with whatever object. This learning process is non-destructive in the new cerebellar topology, solving one of the main issues of feed-forward cerebellar models.
