AIMC Topic: Neurons

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Developmental metaplasticity in neural circuit codes of firing and structure.

Neural networks : the official journal of the International Neural Network Society Sep 30, 2016
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plastici...
Models, Neurological Neurons Synapses Animals Neuronal Plasticity Neural Networks, Computer Brain Humans
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Impaired neurogenesis of the dentate gyrus is associated with pattern separation deficits: A computational study.

Journal of integrative neuroscience Sep 21, 2016
The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the ...
Animals Models, Neurological Neurons Neural Networks, Computer Synaptic Transmission Alzheimer Disease Dentate Gyrus Neurogenesis
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Delay-distribution-dependent H state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

Neural networks : the official journal of the International Neural Network Society Sep 19, 2016
This paper deals with the H state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying sto...
Models, Theoretical Noise Neurons Computer Simulation Time Factors Probability Neural Networks, Computer Algorithms
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Emergence of event cascades in inhomogeneous networks.

Scientific reports Sep 14, 2016
There is a commonality among contagious diseases, tweets, and neuronal firings that past events facilitate the future occurrence of events. The spread of events has been extensively studied such that the systems exhibit catastrophic chain reactions i...
Humans Neural Networks, Computer Neurons Memory Models, Theoretical
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Spiking Neural P Systems with Neuron Division and Dissolution.

PloS one Sep 14, 2016
Spiking neural P systems are a new candidate in spiking neural network models. By using neuron division and budding, such systems can generate/produce exponential working space in linear computational steps, thus provide a way to solve computational ...
Computer Simulation Neurons Humans Action Potentials Neural Networks, Computer
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New results on exponential synchronization of memristor-based neural networks with discontinuous neuron activations.

Neural networks : the official journal of the International Neural Network Society Sep 10, 2016
This paper investigates the exponential synchronization of delayed memristor-based neural networks (MNNs) with discontinuous activation functions. Based on the framework of Filippov solution and differential inclusion theory, using new analytical tec...
Time Factors Neurons Nonlinear Dynamics Humans Feedback Animals Neural Networks, Computer Algorithms
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Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System.

IEEE transactions on biomedical circuits and systems Sep 9, 2016
We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a ge...
Neural Networks, Computer Machine Learning Neurons Neuronal Plasticity Synapses Models, Neurological
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Emergence of low noise frustrated states in E/I balanced neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 8, 2016
We study emerging phenomena in binary neural networks where, with a probability c synaptic intensities are chosen according with a Hebbian prescription, and with probability (1-c) there is an extra random contribution to synaptic weights. This new te...
Neural Networks, Computer Animals Cerebral Cortex Monte Carlo Method Probability Memory Noise Synapses Nerve Net Neurons Random Allocation
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Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks.

Journal of computational neuroscience Sep 2, 2016
A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected p...
Brain Computer Simulation Animals Humans Neural Networks, Computer Neurons Nonlinear Dynamics Synapses Models, Neurological Action Potentials
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Curiosity Search: Producing Generalists by Encouraging Individuals to Continually Explore and Acquire Skills throughout Their Lifetime.

PloS one Sep 2, 2016
Natural animals are renowned for their ability to acquire a diverse and general skill set over the course of their lifetime. However, research in artificial intelligence has yet to produce agents that acquire all or even most of the available skills ...
Exploratory Behavior Neurons Nerve Net Artificial Intelligence Algorithms Humans Learning
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