Robotics

INTSENSO - Integración sensorimotora para control adaptativo mediante aprendizaje en cerebelo y centros nerviosos relacionados. Aplicación en robótica
Esta investigación ha sido financiada con cargo a la ayuda MICINN-FEDER-PID2019-109991GB-I00 concedida por el Ministerio de Ciencia e Innovación.
INTSENSO - Integración sensorimotora para control adaptativo mediante aprendizaje en cerebelo y centros nerviosos relacionados. Aplicación en robótica
VOR Adaptation on a Humanoid iCub Robot Using a Spiking Cerebellar Model
We embed a spiking cerebellar model within an adaptive real-time (RT) control loop that is able to operate a real robotic body (iCub) …
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A Metric for Evaluating Neural Input Representation in Supervised Learning Networks
Supervised learning has long been attributed to several feed-forward neural circuits within the brain, with particular attention being …
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Exploring Vestibulo-Ocular Adaptation in a Closed-Loop Neuro-Robotic Experiment Using STDP. A Simulation Study
Studying and understanding the computational primitives of our neural system requires for a diverse and complementary set of …
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Spiking cerebellar model with multiple plasticity sites reproduces eye blinking classical conditioning
Eye blinking classical conditioning is one of the most extensively studied paradigms related to the cerebellum. In this work we have …
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Integrated neural and robotic simulations. Simulation of cerebellar neurobiological substrate for an object-oriented dynamic model abstraction process
Experimental studies of the Central Nervous System (CNS) at multiple organization levels aim at understanding how information is …
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