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» Phenomenological models of synaptic plasticity based on spik...
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NIPS
2004
13 years 9 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
JCNS
2008
78views more  JCNS 2008»
13 years 6 months ago
A computational study of synaptic mechanisms of partial memory transfer in cerebellar vestibulo-ocular-reflex learning
There is a debate regarding whether motor memory is stored in the cerebellar cortex, or the cerebellar nuclei, or both. Memory may be acquired in the cortex and then be transferred...
Naoki Masuda, Shun-ichi Amari
IJCNN
2008
IEEE
14 years 1 months ago
Adaptation of barn owl localization system with spike timing dependent plasticity
— To localize a seen object, the superior colliculus of the barn owl integrates the visual and auditory localization cues which are accessed from the sensory system of the brain....
Juan Huo, Alan F. Murray, Leslie Smith, Zhijun Yan...
ICONIP
2008
13 years 9 months ago
Noise-Tolerant Analog Circuits for Sensory Segmentation Based on Symmetric STDP Learning
Abstract. We previously proposed a neural segmentation model suitable for implementation with complementary metal-oxide-semiconductor (CMOS) circuits. The model consists of neural ...
Gessyca Maria Tovar, Tetsuya Asai, Yoshihito Amemi...
EVOW
2001
Springer
14 years 1 days ago
Evolution of Spiking Neural Controllers for Autonomous Vision-Based Robots
Abstract. We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on phy...
Dario Floreano, Claudio Mattiussi