AIMC Topic: Neurons

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The robustness-fidelity trade-off in Grow When Required neural networks performing continuous novelty detection.

Neural networks : the official journal of the International Neural Network Society Oct 28, 2019
Novelty detection allows robots to recognise unexpected data in their sensory field and can thus be utilised in applications such as reconnaissance, surveillance, self-monitoring, etc. We assess the suitability of Grow When Required Neural Networks (...
Neural Networks, Computer Machine Learning Neurons Computer Simulation
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Multistability and attraction basins of discrete-time neural networks with nonmonotonic piecewise linear activation functions.

Neural networks : the official journal of the International Neural Network Society Oct 21, 2019
This paper is concerned with multistability and attraction basins of discrete-time neural networks with nonmonotonic piecewise linear activation functions. Under some reasonable conditions, the addressed networks have (2m+1) equilibrium points. (m+1)...
Computer Simulation Neurons Neural Networks, Computer Algorithms
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Realistic spiking neural network: Non-synaptic mechanisms improve convergence in cell assembly.

Neural networks : the official journal of the International Neural Network Society Oct 16, 2019
Learning in neural networks inspired by brain tissue has been studied for machine learning applications. However, existing works primarily focused on the concept of synaptic weight modulation, and other aspects of neuronal interactions, such as non-s...
Action Potentials Neurons Machine Learning Brain Models, Neurological Neural Networks, Computer
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Reinforcement Learning in Spiking Neural Networks with Stochastic and Deterministic Synapses.

Neural computation Oct 15, 2019
Though succeeding in solving various learning tasks, most existing reinforcement learning (RL) models have failed to take into account the complexity of synaptic plasticity in the neural system. Models implementing reinforcement learning with spiking...
Models, Neurological Action Potentials Neurons Computer Simulation Neuronal Plasticity Reinforcement, Psychology Synapses Synaptic Transmission Neural Networks, Computer
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A review of learning in biologically plausible spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Oct 11, 2019
Artificial neural networks have been used as a powerful processing tool in various areas such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has encouraged researchers to improve artificial neural networks by ...
Learning Humans Neural Networks, Computer Neuronal Plasticity Algorithms Models, Neurological Brain Action Potentials Neurons
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Study on miR-384-5p activates TGF-β signaling pathway to promote neuronal damage in abutment nucleus of rats based on deep learning.

Artificial intelligence in medicine Oct 10, 2019
BACKGROUND: Any ailment in our organs can be visualized by using different modality signals and images. Hospitals are encountering a massive influx of large multimodality patient data to be analysed accurately and with context understanding. The deep...
Rats Signal Transduction Transforming Growth Factor beta Neurons MicroRNAs Animals Deep Learning Basal Ganglia
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Molecular expression profiles of morphologically defined hippocampal neuron types: Empirical evidence and relational inferences.

Hippocampus Oct 9, 2019
Gene and protein expressions are key determinants of cellular function. Neurons are the building blocks of brain circuits, yet the relationship between their molecular identity and the spatial distribution of their dendritic inputs and axonal outputs...
Data Mining Humans Hippocampus Transcriptome Empirical Research Neurons Knowledge Bases
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DeepBranch: Deep Neural Networks for Branch Point Detection in Biomedical Images.

IEEE transactions on medical imaging Oct 7, 2019
Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blood vessels, and bronchi, is of fundamental interest for biomedical research. 3D branch points play an important role in many reconstruction applicatio...
Humans Neural Networks, Computer Neurons Image Processing, Computer-Assisted Bronchi Algorithms Diagnostic Imaging Retinal Vessels Animals
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Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights.

Nanotechnology Oct 2, 2019
Neuromorphic systems consisting of artificial neurons and memristive synapses could provide a much better performance and a significantly more energy-efficient approach to the implementation of different types of neural network algorithms than tradit...
Computers Neurons Nanocomposites Neural Networks, Computer Algorithms
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Stable memory with unstable synapses.

Nature communications Sep 30, 2019
What is the physiological basis of long-term memory? The prevailing view in Neuroscience attributes changes in synaptic efficacy to memory acquisition, implying that stable memories correspond to stable connectivity patterns. However, an increasing b...
Nerve Net Memory Learning Synapses Memory, Long-Term Neurons Algorithms Homeostasis Neural Networks, Computer Neuronal Plasticity Nonlinear Dynamics Computer Simulation Models, Neurological Software
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