AIMC Topic: Neuronal Plasticity

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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 ...
Humans Biomimetics Information Storage and Retrieval Nerve Net Action Potentials Signal Processing, Computer-Assisted Learning Neural Networks, Computer Neurons Neuronal Plasticity Machine Learning Models, Neurological Computer Simulation
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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...
Humans Neural Networks, Computer Learning Synapses Memory Animals Neuronal Plasticity Models, Neurological
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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...
Neural Networks, Computer Microscopy, Electron, Transmission Optical Imaging Electrical Equipment and Supplies Time Equipment Design Excitatory Postsynaptic Potentials Neuronal Plasticity Action Potentials Synapses Oxides Biomimetic Materials
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Behavioral plasticity through the modulation of switch neurons.

Neural networks : the official journal of the International Neural Network Society Nov 12, 2015
A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural ...
Behavior Reinforcement, Psychology Neurosciences Neuronal Plasticity Signal Processing, Computer-Assisted Neurons Synapses Machine Learning Maze Learning Neural Networks, Computer Algorithms Problem Solving Artificial Intelligence Computer Simulation
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Novel plasticity rule can explain the development of sensorimotor intelligence.

Proceedings of the National Academy of Sciences of the United States of America Oct 26, 2015
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, ...
Exploratory Behavior Humans Nervous System Physiological Phenomena Computer Simulation Robotics Neuronal Plasticity Creativity Motivation Models, Neurological Behavior
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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 ...
Neural Networks, Computer Learning Neuronal Plasticity Action Potentials 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...
Animals Neuronal Plasticity Models, Neurological Humans Stochastic Processes Neural Networks, Computer Action Potentials Neurons Cerebral Cortex
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Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.

IEEE transactions on bio-medical engineering Oct 1, 2015
GOAL: In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction.
Computer Simulation Neuronal Plasticity Models, Neurological Action Potentials Humans Cerebellum Blinking Neural Networks, Computer Algorithms
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Spinal plasticity in robot-mediated therapy for the lower limbs.

Journal of neuroengineering and rehabilitation Sep 17, 2015
Robot-mediated therapy can help improve walking ability in patients following injuries to the central nervous system. However, the efficacy of this treatment varies between patients, and evidence for the mechanisms underlying functional improvements ...
Spinal Cord Injuries Lower Extremity Humans Brain Injuries Robotics Neuronal Plasticity
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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...
Models, Neurological Neural Networks, Computer Action Potentials Neuronal Plasticity Nonlinear Dynamics Neurons
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