AIMC Topic: Neuronal Plasticity

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Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 7, 2018
Biological neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifelong learning. The interplay of these elements leads to the emergence of biological intelligence. Inspired by such intricate ...
Humans Neural Networks, Computer Machine Learning Models, Neurological Neurons Nerve Net Forecasting Computer Simulation Neuronal Plasticity
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An open-source tool for analysis and automatic identification of dendritic spines using machine learning.

PloS one Jul 5, 2018
Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuron...
Neurons Software Machine Learning Image Processing, Computer-Assisted Microscopy Algorithms Mice Dendritic Spines Animals Neuronal Plasticity
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Effect of inhibitory spike-timing-dependent plasticity on fast sparsely synchronized rhythms in a small-world neuronal network.

Neural networks : the official journal of the International Neural Network Society Jul 2, 2018
We consider the Watts-Strogatz small-world network (SWN) consisting of inhibitory fast spiking Izhikevich interneurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plas...
Interneurons Neural Inhibition Long-Term Potentiation Action Potentials Humans Neurons Synapses Neural Networks, Computer Animals Neuronal Plasticity
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A self-organizing short-term dynamical memory network.

Neural networks : the official journal of the International Neural Network Society Jun 20, 2018
Working memory requires information about external stimuli to be represented in the brain even after those stimuli go away. This information is encoded in the activities of neurons, and neural activities change over timescales of tens of milliseconds...
Synapses Nerve Net Neural Networks, Computer Brain Neuronal Plasticity Models, Neurological Memory, Short-Term Neurons Humans
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A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus.

Scientific reports Jun 19, 2018
Memristive systems have gained considerable attention in the field of neuromorphic engineering, because they allow the emulation of synaptic functionality in solid state nano-physical systems. In this study, we show that memristive behavior provides ...
Humans Neural Networks, Computer Models, Theoretical Neuronal Plasticity Synapses Hippocampus
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Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron Jun 14, 2018
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...
Neural Networks, Computer Learning Animals Temporal Lobe Association Learning Neuronal Plasticity Memory
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A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

eNeuro Apr 24, 2018
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...
Connectome Nerve Net Reward Synapses Humans Neural Networks, Computer Computer Simulation Animals Models, Theoretical Neuronal Plasticity
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Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society Jan 12, 2018
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...
Action Potentials Unsupervised Machine Learning Neurons Heart Rate Wearable Electronic Devices Humans Probability Electrocardiography Algorithms Neuronal Plasticity
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A new approach to detect the coding rule of the cortical spiking model in the information transmission.

Neural networks : the official journal of the International Neural Network Society Jan 3, 2018
Investigation of the role of the local field potential (LFP) fluctuations in encoding the received sensory information by the nervous system remains largely unknown. On the other hand, transmission of these translation rules in information transmissi...
Humans Neural Networks, Computer Action Potentials Neuronal Plasticity Neurons Models, Neurological Synapses
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STDP-based spiking deep convolutional neural networks for object recognition.

Neural networks : the official journal of the International Neural Network Society Dec 23, 2017
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively sha...
Pattern Recognition, Visual Humans Computer Simulation Neural Networks, Computer Neurons Learning Photic Stimulation Animals Visual Perception Neuronal Plasticity Models, Neurological Action Potentials
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