AIMC Topic: Memory

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Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks.

PloS one Nov 16, 2017
A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when lear...
Algorithms Humans Learning Neural Networks, Computer Memory
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False memory for orthographically versus semantically similar words in adolescents with dyslexia: a fuzzy-trace theory perspective.

Annals of dyslexia Nov 13, 2017
The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces-assumed in the fuzzy-trace theory. The participants were 71 high school students (33 wi...
Cognition Semantics Memory Dyslexia Humans Young Adult Mental Recall Word Association Tests Female Male Adolescent Adolescent Behavior Fuzzy Logic
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Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study.

PloS one Oct 27, 2017
The Hopfield model is a pioneering neural network model with associative memory retrieval. The analytical solution of the model in mean field limit revealed that memories can be retrieved without any error up to a finite storage capacity of O(N), whe...
Neural Networks, Computer Models, Theoretical Nerve Net Memory
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Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatiotemporal Scales RNN Model.

Neural computation Oct 24, 2017
This letter proposes a novel predictive coding type neural network model, the predictive multiple spatiotemporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN learns to predict visually perceived human whole-body cyclic movement patterns b...
Neural Networks, Computer Algorithms Learning Humans Movement Visual Perception Visual Pathways Predictive Value of Tests Nonlinear Dynamics Memory
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Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Nature communications Sep 29, 2017
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures ...
Long-Term Potentiation Electronics Synapses Memory Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer Algorithms Learning
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Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

Brain and language Sep 9, 2017
Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks ...
Middle Aged Semantics Comprehension Adult Male Memory Diffusion Tensor Imaging Temporal Lobe Connectome Epilepsy, Temporal Lobe Nerve Net Humans Machine Learning Retrospective Studies Language Female
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Memory States and Transitions between Them in Attractor Neural Networks.

Neural computation Aug 4, 2017
Human memory is capable of retrieving similar memories to a just retrieved one. This associative ability is at the base of our everyday processing of information. Current models of memory have not been able to underpin the mechanism that the brain co...
Memory Association Humans Neural Networks, Computer Brain Models, Neurological Neurons
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An online supervised learning method based on gradient descent for spiking neurons.

Neural networks : the official journal of the International Neural Network Society Apr 27, 2017
The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified...
Nerve Net Memory Models, Neurological Algorithms Action Potentials Learning Neurons Supervised Machine Learning Synapses
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Avoiding Catastrophic Forgetting.

Trends in cognitive sciences Apr 23, 2017
Humans regularly perform new learning without losing memory for previous information, but neural network models suffer from the phenomenon of catastrophic forgetting in which new learning impairs prior function. A recent article presents an algorithm...
Neural Networks, Computer Humans Synapses Algorithms Memory Learning Retention, Psychology
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Autoassociative Memory and Pattern Recognition in Micromechanical Oscillator Network.

Scientific reports Mar 24, 2017
Towards practical realization of brain-inspired computing in a scalable physical system, we investigate a network of coupled micromechanical oscillators. We numerically simulate this array of all-to-all coupled nonlinear oscillators in the presence o...
Pattern Recognition, Automated Memory Oscillometry Physical Phenomena Neural Networks, Computer Models, Theoretical Computer Simulation Nonlinear Dynamics
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