AIMC Topic:
Neurons

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STDP Forms Associations between Memory Traces in Networks of Spiking Neurons.

Cerebral cortex (New York, N.Y. : 1991) Mar 14, 2020
Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. Ho...
Humans Neural Networks, Computer Learning Action Potentials Neurons Memory Neuronal Plasticity Models, Neurological
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Reply to: One neuron versus deep learning in aftershock prediction.

Nature Oct 1, 2019
Deep Learning Neurons Neural Networks, Computer Algorithms
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An Effective Encoder-Decoder Network for Neural Cell Bodies and Cell Nucleus Segmentation of EM Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Neural systems are complicated networks connected by a large number of neurons through gap junctions and synapse. At present, for electron microscopy connectomics research, neuron structure recognition algorithms mostly focus on synapses, dendrites, ...
Humans Cell Nucleus Microscopy, Electron Cell Body Image Processing, Computer-Assisted Neural Networks, Computer Neurons Algorithms
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Neuron segmentation with deep learning.

Nature methods Jun 1, 2019
Neural Networks, Computer Neurons Calcium Machine Learning Deep Learning
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Gradient and Hamiltonian coupled systems on undirected networks.

Mathematical biosciences and engineering : MBE May 23, 2019
Many real world applications are modelled by coupled systems on undirected networks. Two striking classes of such systems are the gradient and the Hamiltonian systems. In fact, within these two classes, coupled systems are admissible only by the undi...
Synapses Neurons Brain Neural Networks, Computer Nonlinear Dynamics Models, Biological Algorithms Humans
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Neural population control via deep image synthesis.

Science (New York, N.Y.) May 3, 2019
Particular deep artificial neural networks (ANNs) are today's most accurate models of the primate brain's ventral visual stream. Using an ANN-driven image synthesis method, we found that luminous power patterns (i.e., images) can be applied to primat...
Visual Cortex Macaca Visual Fields Nerve Net Neural Networks, Computer Models, Neurological Neurons Animals
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Using deep learning to probe the neural code for images in primary visual cortex.

Journal of vision Apr 1, 2019
Primary visual cortex (V1) is the first stage of cortical image processing, and major effort in systems neuroscience is devoted to understanding how it encodes information about visual stimuli. Within V1, many neurons respond selectively to edges of ...
Orientation, Spatial Visual Cortex Neural Networks, Computer Macaca Orientation Neurons Animals Visual Perception Deep Learning
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Automated Neuron Detection in High-Content Fluorescence Microscopy Images Using Machine Learning.

Neuroinformatics Apr 1, 2019
The study of neuronal morphology in relation to function, and the development of effective medicines to positively impact this relationship in patients suffering from neurodegenerative diseases, increasingly involves image-based high-content screenin...
Humans Microscopy, Fluorescence Neurons Animals Machine Learning Image Processing, Computer-Assisted Rats Algorithms
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Stability properties of neural networks with non-instantaneous impulses.

Mathematical biosciences and engineering : MBE Feb 18, 2019
In this paper, we consider neural networks in the case when the neurons are subject to a certain impulsive state displacement at fixed moments and the duration of this displacement is not negligible small (these are known as non-instantaneous impulse...
Pattern Recognition, Automated Nerve Net Computer Simulation Models, Biological Time Factors Algorithms Neurons Humans Brain Neural Networks, Computer Nonlinear Dynamics
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Emerging techniques in statistical analysis of neural data.

Journal of computational neuroscience Feb 1, 2019
Humans Neural Networks, Computer Neurons Brain Statistics as Topic Data Analysis Models, Neurological
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