Cerebellum simulation towards embodiment

 Niceto Luque (HPB SP10 Speaker)


Most simulation efforts in computational neuroscience are devoted to characterise neural models and/or neural system aiming at understanding the computational primitives underlying the neurophysiological substrate. To this end, the cause-effect relationship between well-defined input stimulation patterns and the neural output responses is traditionally settled and studied, thereby obviating the need for a body. Nevertheless, brain and body have co-evolved as the computational primitives of the central nervous system (CNS) with the environment. It is therefore reasonable to extend the cause-effect setups to perception-action setups in order to ease the study of the neural sensorimotor primitives that a body generates in closed-loop.

The mammalian cerebellum is pivotal in integrating the sensorial and motor pathways and coordinating the subsequent motor action being the perfect candidate for studying its computational primitives in perception-action setups. Neuroscience proposes well-established experimental setups (behavioural/cognitive tasks) which facilitate the study of the cerebellar role in motor adaptation and its related pathologies. Replicating cerebellar synthetic setups (i. e. Eye blink Classical Conditioning, the Vestibulo-Ocular Reflex… etc.) requires embodying the cerebellar network within a front-end body. Embodying not only needs for a biologically plausible cerebellar network and an actual body but also body-cerebellar efficient interfaces. Cerebellar embodiment constitutes the pinnacle of our lab mission for which during more than a decade, we have developed handcrafted solutions for  neurorobotics where neural interfaces, efficient neural simulators specifically designed for embedded neural systems (such as our neural simulator EDLUT) and robotic agents has been lacking.