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CEREBSENSING SIGNED

Cerebellar Distributed Plasticity Towards Active Sensing and Motor Control

Total Cost €

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EC-Contrib. €

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Partnership

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Project "CEREBSENSING" data sheet

The following table provides information about the project.

Coordinator
UNIVERSIDAD DE GRANADA 

Organization address
address: CUESTA DEL HOSPICIO SN
city: GRANADA
postcode: 18071
website: www.ugr.es

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website https://www.ugr.es/
 Total cost 158˙121 €
 EC max contribution 158˙121 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2015
 Duration (year-month-day) from 2015-11-01   to  2018-01-22

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSIDAD DE GRANADA ES (GRANADA) coordinator 158˙121.00

Map

 Project objective

The ability to perceive and understand the state of the surrounding environment and the own state is critical for next generation robotic systems. To that aim, the human brain is still far beyond current artificial systems performance due to its capability of processing huge amounts of heterogeneous sensorial data. Interestingly, the cerebellum has been shown to play a crucial role in the generation of dexterous movements as evidenced from cerebellar ataxic patients. Behavioural studies suggest that the cerebellum actively improves sensorial discrimination and proprioception thanks to the prediction of the sensorial consequences of actions. In the last decade, several forms of long-term synaptic plasticity have been observed within the cerebellum, suggesting that distributed plasticity could support the predictive action. However the way in which those mechanisms cooperate in order to improve the function of the whole cerebellar network is not completely understood. In this project, the candidate will develop a novel theory of sensorial information representation and processing based on the cerebellar architecture. The proposed model will make use of long-term synaptic plasticity mechanisms distributed along connections existing in the cerebellar input layer (granular layer) to iteratively create sparse representations of the information, allowing fast and effective learning in successive layers. The predictions extracted from this model will be useful to design new experimental protocols to unveil the cerebellar role in acting and sensing. By providing multiple relevant contributions across the spectrum of the H2020 objectives in terms of its potential to advance robotic manufacturing, brain processing understanding, and novel computing paradigms, this project will enable the candidate to enhance his position at the forefront of advances in this field.

 Publications

year authors and title journal last update
List of publications.
2016 Jesús A. Garrido, Niceto R. Luque, Silvia Tolu, Egidio D’Angelo
Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks
published pages: , ISSN: 0129-0657, DOI:
International Journal of Neural Systems 2019-06-07
2017 Francisco Naveros, Jesus A. Garrido, Richard R. Carrillo, Eduardo Ros, Niceto R. Luque
Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks
published pages: , ISSN: 1662-5196, DOI:
Frontiers in Neuroinformatics 2019-06-07
2016 Niceto R. Luque, Jesús A. Garrido, Francisco Naveros, Richard R. Carrillo, Egidio D’Angelo, Eduardo Ros
Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model
published pages: , ISSN: 1662-5188, DOI:
Frontiers in Computational Neuroscience 2019-06-07
2016 Christoph Richter, Sören Jentzsch, Rafael Hostettler, Jesús A. Garrido, Eduardo Ros, Alois Knoll, Florian Röhrbein, Patrick van der Smagt, Jörg Conradt.
Musculoskeletal Robots: Scalability in Neural Control
published pages: , ISSN: 1070-9932, DOI:
IEEE Robotics and Automation Magazine 2019-06-07

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The information about "CEREBSENSING" are provided by the European Opendata Portal: CORDIS opendata.

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