AIMC Topic: Neuronal Plasticity

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Intrinsic Plasticity for Natural Competition in Koniocortex-Like Neural Networks.

International journal of neural systems May 16, 2016
In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a compl...
Machine Learning Software Algorithms Computer Simulation Humans Neural Networks, Computer Cerebral Cortex Neural Pathways Thalamus Neural Inhibition Neuronal Plasticity Models, Neurological Bayes Theorem Neurons
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Is cortical connectivity optimized for storing information?

Nature neuroscience Apr 11, 2016
Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamic...
Neural Networks, Computer Memory Neuronal Plasticity Models, Neurological Cerebral Cortex
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A Computational Framework for Realistic Retina Modeling.

International journal of neural systems Apr 7, 2016
Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different v...
Computer Simulation Animals Neuronal Plasticity Models, Neurological Neural Networks, Computer Software Algorithms Feedback, Physiological Membrane Potentials Macaca Pattern Recognition, Automated Vision, Ocular Neural Pathways Adaptation, Physiological Retina Nonlinear Dynamics Linear Models
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Mechanisms of memory storage in a model perirhinal network.

Brain structure & function Mar 12, 2016
The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked ...
Neuronal Plasticity Models, Neurological Action Potentials Neurons Memory Interneurons Perirhinal Cortex Humans Neural Networks, Computer Animals
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Feature-Linking Model for Image Enhancement.

Neural computation Mar 4, 2016
Inspired by gamma-band oscillations and other neurobiological discoveries, neural networks research shifts the emphasis toward temporal coding, which uses explicit times at which spikes occur as an essential dimension in neural representations. We pr...
Models, Neurological Image Enhancement Nerve Net Gamma Rhythm Humans Neural Networks, Computer Neuronal Plasticity
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Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity.

PloS one Jan 25, 2016
At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. H...
Laryngeal Muscles Motor Neurons Lip Jaw Models, Neurological Reward Dopamine Nerve Net Phonetics Computer Simulation Humans Motor Cortex Neural Networks, Computer Language Development Feedback Machine Learning Auditory Perception Infant Neuronal Plasticity
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Neuroplasticity in dynamic neural networks comprised of neurons attached to adaptive base plate.

Neural networks : the official journal of the International Neural Network Society Dec 9, 2015
In this paper, a learning algorithm is developed for Dynamic Plastic Continuous Neural Networks (DPCNNs) to improve their learning of highly nonlinear time dependent problems. A DPCNN is comprised of a base medium, which is nonlinear and plastic, and...
Adaptation, Physiological Humans Computer Simulation Neural Networks, Computer Neuronal Plasticity Algorithms Neurons Brain Nonlinear Dynamics
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Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PLoS computational biology Dec 3, 2015
The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be ...
Models, Neurological Action Potentials Signal Processing, Computer-Assisted Neurons Machine Learning Humans Biomimetics Computer Simulation Neural Networks, Computer Information Storage and Retrieval Learning Nerve Net Neuronal Plasticity
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Efficient Associative Computation with Discrete Synapses.

Neural computation Nov 24, 2015
Neural associative networks are a promising computational paradigm for both modeling neural circuits of the brain and implementing associative memory and Hebbian cell assemblies in parallel VLSI or nanoscale hardware. Previous work has extensively in...
Memory Animals Humans Neuronal Plasticity Neural Networks, Computer Models, Neurological Learning Synapses
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Synaptic Metaplasticity Realized in Oxide Memristive Devices.

Advanced materials (Deerfield Beach, Fla.) Nov 17, 2015
Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-t...
Electrical Equipment and Supplies Neural Networks, Computer Biomimetic Materials Time Action Potentials Microscopy, Electron, Transmission Neuronal Plasticity Oxides Optical Imaging Excitatory Postsynaptic Potentials Equipment Design Synapses
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