NEUSEQBOT - NEUro cerebellar recurrent network for motor SEQuence learning in neuroroBOTics

The new generation of compliant robots, designed to safely interact with humans in unstructured environments, require control systems able to naturally deal with their “biological features”. These robots can be efficiently controlled using biologically inspired control systems based on brain regions such as the cerebellum. This nucleus plays a key role in fluent body movements, being essential for adaptive motor control and coordination of body movements.

The cerebellum was traditionally modelled as a feedforward network with two inputs and one output. Nevertheless, recent experimental studies have demonstrated the existence of multiple recurrent connections in the cerebellum: 1) nucleo-cortical connections (NCCs), and 2) nucleo-olivary connections (NOCs). These recurrent connections back-propagate the cerebellar output activity to the cerebellar inputs, thus shifting the feedforward toward a recurrent approach.

NEUSEQBOT project will focus on the NCCs, studying how they contribute to the motor sequence learning capabilities in the cerebellum. This multidisciplinary study will combine neuroscientific experiments in animals, cerebellar modelling and neurorobotic applications. Firstly, we will experimentally study the NCC effect in the cerebellar dynamics during reflexive eyelid movements in optogenetically modified mice. The experimental results will be used to model a recurrent cerebellum. Finally, this cerebellar model will be tested in a neurorobotic object manipulation task using a compliant robotic arm.

Within the objectives of H2020, NEUSEQBOT project aims to advance our understanding of how the cerebellum (as a recurrent network) processes the sensorimotor information to generate the required motor command sequences, applying this knowledge to develop biologically inspired control systems for neurorobotic applications with compliant robots. This work will enable the experienced researcher to enhance his position at the forefront of advances in these fields.

Funding information: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 891774.

Francisco Naveros
Francisco Naveros
Postdoctoral Researcher

Senior postdoc at the Applied Computational Neuroscience Research Group at the University of Granada.