Article-Journal

Musculoskeletal Robots. Scalability in Neural Control
Anthropomimetic robots sense, behave, interact, and feel like humans. By this definition, they require human-like physical hardware and …
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A Dataset for Visual Navigation with Neuromorphic Methods
Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we …
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Distributed Circuit Plasticity. New Clues for the Cerebellar Mechanisms of Learning
The cerebellum is involved in learning and memory of sensory motor skills. However, the way this process takes place in local …
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Modeling the Cerebellar Microcircuit. New Strategies for a Long-Standing Issue
The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific …
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Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks
The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and …
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Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model
Deep cerebellar nuclei neurons receive both inhibitory (GABAergic) synaptic currents from Purkinje cells (within the cerebellar cortex) …
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Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms
Goal: In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in …
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Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks
The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into …
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Prediction of Manipulation Actions
This work presents an FPGA implementation of a highly parallel architecture for the motion and disparity estimations of color images. …
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A spiking neural simulator integrating event-driven and time-driven computation schemes using parallel CPU-GPU co-processing: a case study
Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural …
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