AIMC Topic: Neurons

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Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours?

PLoS computational biology Oct 10, 2017
All organisms wishing to survive and reproduce must be able to respond adaptively to a complex, changing world. Yet the computational power available is constrained by biology and evolution, favouring mechanisms that are parsimonious yet robust. Here...
Neural Networks, Computer Behavior, Animal Drosophila melanogaster Pattern Recognition, Visual Visual Cortex Animals Models, Neurological Neurons
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Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay.

Biological cybernetics Oct 9, 2017
Contrary to forward biomechanical functions, which are deterministic, inverse biomechanical functions are generally not. Calculating an inverse biomechanical function is an ill-posed problem, which has no unique solution for a manipulator with severa...
Biomechanical Phenomena Humans Fuzzy Logic Neurons Online Systems Computer Simulation Models, Neurological Cerebellum Learning Efferent Pathways Movement
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Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience Oct 6, 2017
Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed...
Learning Female Animals Machine Learning Algorithms Computer Simulation Cluster Analysis Models, Neurological Neurons Macaca mulatta Male Prefrontal Cortex Cognition Neural Networks, Computer
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SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

Neural networks : the official journal of the International Neural Network Society Oct 5, 2017
Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in ...
Nonlinear Dynamics Synapses Computational Biology Cluster Analysis Neurons Neural Networks, Computer Machine Learning Algorithms
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Stimulus-induced transitions between spike-wave discharges and spindles with the modulation of thalamic reticular nucleus.

Journal of computational neuroscience Sep 22, 2017
It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical mechanisms of spatiotemporal evolutions between these two types of activity, however, are not well ...
Models, Neurological Neural Networks, Computer Action Potentials Nonlinear Dynamics Computer Simulation Neurons Neural Inhibition Animals Nerve Net Intralaminar Thalamic Nuclei Humans Electric Stimulation
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Lifelong learning of human actions with deep neural network self-organization.

Neural networks : the official journal of the International Neural Network Society Sep 20, 2017
Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather l...
Machine Learning Robotics Neurons Humans Pattern Recognition, Visual Neural Networks, Computer
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Synchrony measure for a neuron driven by excitatory and inhibitory inputs and its adaptation to experimentally-recorded data.

Bio Systems Sep 15, 2017
The aim of the current work is twofold: firstly to adapt an existing method measuring the input synchrony of a neuron driven only by excitatory inputs in such a way so as to account for inhibitory inputs as well and secondly to further appropriately ...
Action Potentials Neurons Auditory Cortex Neural Inhibition Guinea Pigs Computer Simulation Animals Models, Neurological Neural Networks, Computer
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Robust spike-train learning in spike-event based weight update.

Neural networks : the official journal of the International Neural Network Society Sep 12, 2017
Supervised learning algorithms in a spiking neural network either learn a spike-train pattern for a single neuron receiving input spike-train from multiple input synapses or learn to output the first spike time in a feedforward network setting. In th...
Neurons Synapses Algorithms Models, Neurological Humans Action Potentials Supervised Machine Learning Neural Networks, Computer
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Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

Journal of computational neuroscience Sep 12, 2017
Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of ...
Nerve Net Normal Distribution Synaptic Transmission Humans Action Potentials Computer Simulation Neural Networks, Computer Neurons Animals Synapses Models, Neurological
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Nano-topography Enhances Communication in Neural Cells Networks.

Scientific reports Aug 29, 2017
Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can dir...
Nerve Net Microscopy, Fluorescence Female Cell Communication Neural Networks, Computer Calcium Animals Neurons Cells, Cultured Mice Molecular Imaging Pregnancy Microscopy, Atomic Force
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