Selected Publications

(2021). A cerebellar-based solution to the nondeterministic time delay problem in robotic control. Science Robotics.

Journal

(2019). Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLOS Computational Biology.

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(2018). A Metric for Evaluating Neural Input Representation in Supervised Learning Networks. Frontiers in Neuroscience.

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(2008). A real-time spiking cerebellum model for learning robot control. Biosystems.

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(2006). Event-Driven Simulation Scheme for Spiking Neural Networks Using Lookup Tables to Characterize Neuronal Dynamics. Neural Computation.

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Recent Publications

More Publications

(2021). A cerebellar-based solution to the nondeterministic time delay problem in robotic control. Science Robotics.

Journal

(2021). On the Use of a Multimodal Optimizer for Fitting Neuron Models. Application to the Cerebellar Granule Cell. Frontiers in Neuroinformatics.

Journal

(2020). Reconfigurable cyber-physical system for critical infrastructure protection in smart cities via smart video-surveillance. Pattern Recognition Letters.

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(2019). Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLOS Computational Biology.

Journal

(2018). A Metric for Evaluating Neural Input Representation in Supervised Learning Networks. Frontiers in Neuroscience.

Journal

(2017). Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-Processing for Spiking Neural Networks. Frontiers in Neuroinformatics.

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Projects

Reverse-engineering the cerebellum for adaptive robot control

This project aims to deepen the understanding of the cerebellum functioning through the implementation and simulation of a reduced cerebellar model.

Recent Posts

EDLUT is a computer program designed for high-speed simulation of spiking neural networks.

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Contact

  • (+34) 958241776
  • Edificio auxiliar de la ETSIIT (UGR), oficina 1.3 (primera planta), Calle Periodista Juan Osorio Bueno, s/n. 18014 Granada, Spain