AIMC Topic: Neurons

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Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

Neural computation Oct 23, 2015
Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we ...
Learning Neuronal Plasticity Action Potentials Neural Networks, Computer Supervised Machine Learning Neurons
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Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

International journal of neural systems Oct 9, 2015
Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recen...
Stochastic Processes Neuronal Plasticity Models, Neurological Neurons Cerebral Cortex Action Potentials Neural Networks, Computer Animals Humans
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The transfer and transformation of collective network information in gene-matched networks.

Scientific reports Oct 9, 2015
Networks, such as the human society network, social and professional networks, and biological system networks, contain vast amounts of information. Information signals in networks are distributed over nodes and transmitted through intricately wired l...
Humans Neural Networks, Computer Algorithms Neurons Nerve Net Signal Transduction Models, Neurological Gene Regulatory Networks Models, Genetic
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A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.

Scientific reports Oct 8, 2015
In this paper we present a unified framework for extreme learning machines and reservoir computing (echo state networks), which can be physically implemented using a single nonlinear neuron subject to delayed feedback. The reservoir is built within t...
Neural Networks, Computer User-Computer Interface Machine Learning Neurons Humans Nonlinear Dynamics Software Computers
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New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays.

ISA transactions Oct 3, 2015
In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is cha...
Computer Simulation Neurons Uncertainty Neural Networks, Computer Algorithms
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Impact of sub and supra-threshold adaptation currents in networks of spiking neurons.

Journal of computational neuroscience Sep 24, 2015
Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulatio...
Potassium Channels, Voltage-Gated Humans Computer Simulation Animals Neural Networks, Computer Synapses Calcium Channels Nerve Tissue Proteins Nerve Net Neurons Cerebral Cortex Adaptation, Physiological Nonlinear Dynamics Models, Neurological Action Potentials
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Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus.

eLife Sep 24, 2015
Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron proper...
Rodentia Hippocampus Information Storage and Retrieval Animals Neurons Knowledge Bases
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Rich spectrum of neural field dynamics in the presence of short-term synaptic depression.

Physical review. E, Statistical, nonlinear, and soft matter physics Sep 14, 2015
In continuous attractor neural networks (CANNs), spatially continuous information such as orientation, head direction, and spatial location is represented by Gaussian-like tuning curves that can be displaced continuously in the space of the preferred...
Neurons Neural Networks, Computer Models, Neurological Nonlinear Dynamics Neuronal Plasticity Action Potentials
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Asymptotic Stability of a Class of Neutral Delay Neuron System in a Critical Case.

IEEE transactions on neural networks and learning systems Aug 28, 2015
In this brief, the asymptotic stability properties of a neutral delay neuron system are studied mainly in a critical case when the exponential stability is not possible. If a critical value of the coefficient in the neutral delay neuron system is con...
Nonlinear Dynamics Models, Neurological Neurons Humans Computer Simulation Neural Networks, Computer Algorithms Time Factors
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Investigation on Amari's dynamical neural field with global constant inhibition.

Neural networks : the official journal of the International Neural Network Society Aug 28, 2015
In this paper, the properties of Amari's dynamical neural field with global constant inhibition induced by its kernel are investigated. Amari's dynamical neural field illustrates many neurophysiological phenomena successfully and has been applied to ...
Cluster Analysis Neural Networks, Computer Neurons Algorithms
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