AIMC Topic: Neurons

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Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Journal of neural engineering Jul 29, 2024
Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupli...
Neural Networks, Computer Female Male Middle Aged Microelectrodes Parkinson Disease Aged Neurons Humans Deep Brain Stimulation Models, Neurological Action Potentials
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Photonic deep residual time-delay reservoir computing.

Neural networks : the official journal of the International Neural Network Society Jul 27, 2024
Time-delay reservoir computing (TDRC) represents a simplified variant of recurrent neural networks, employing a nonlinear node with a feedback mechanism to construct virtual nodes. The capabilities of TDRC can be enhanced by transitioning to a deep a...
Neural Networks, Computer Artificial Intelligence Deep Learning Nonlinear Dynamics Time Factors Photons Neurons Algorithms Feedback
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Morphological classification of neurons based on Sugeno fuzzy integration and multi-classifier fusion.

Scientific reports Jul 11, 2024
In order to extract more important morphological features of neuron images and achieve accurate classification of the neuron type, a method is proposed that uses Sugeno fuzzy integral integration of three optimized deep learning models, namely AlexNe...
Neurons Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Fuzzy Logic Deep Learning Humans
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Improved switching condition for reachable set estimation of discrete-time switched delayed neural networks.

Neural networks : the official journal of the International Neural Network Society Jul 10, 2024
This research delves into the reachable set estimation (RSE) problem for general switched delayed neural networks (SDNNs) in the discrete-time context. Note that existing relevant research on SDNNs predominantly relies on either time-dependent or sta...
Humans Neural Networks, Computer Algorithms Neurons Computer Simulation Time Factors
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Antiferromagnetic artificial neuron modeling of the withdrawal reflex.

Journal of computational neuroscience Jul 10, 2024
Replicating neural responses observed in biological systems using artificial neural networks holds significant promise in the fields of medicine and engineering. In this study, we employ ultra-fast artificial neurons based on antiferromagnetic (AFM) ...
Neural Networks, Computer Computer Simulation Animals Humans Reflex Models, Neurological Neurons
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Flexible multitask computation in recurrent networks utilizes shared dynamical motifs.

Nature neuroscience Jul 9, 2024
Flexible computation is a hallmark of intelligent behavior. However, little is known about how neural networks contextually reconfigure for different computations. In the present work, we identified an algorithmic neural substrate for modular computa...
Neural Networks, Computer Algorithms Nerve Net Models, Neurological Learning Neurons Animals
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A Delayed Spiking Neural Membrane System for Adaptive Nearest Neighbor-Based Density Peak Clustering.

International journal of neural systems Jul 6, 2024
Although the density peak clustering (DPC) algorithm can effectively distribute samples and quickly identify noise points, it lacks adaptability and cannot consider the local data structure. In addition, clustering algorithms generally suffer from hi...
Neurons Humans Models, Neurological Action Potentials Algorithms Cluster Analysis Neural Networks, Computer
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Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Analytical chemistry Jul 2, 2024
Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recentl...
Animals Neurons Deep Learning Action Potentials Microscopy Electrochemical Techniques Electric Impedance
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Directly training temporal Spiking Neural Network with sparse surrogate gradient.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024
Brain-inspired Spiking Neural Networks (SNNs) have attracted much attention due to their event-based computing and energy-efficient features. However, the spiking all-or-none nature has prevented direct training of SNNs for various applications. The ...
Neurons Models, Neurological Action Potentials Humans Algorithms Neural Networks, Computer Brain
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Leveraging spiking neural networks for topic modeling.

Neural networks : the official journal of the International Neural Network Society Jun 27, 2024
This article investigates the application of spiking neural networks (SNNs) to the problem of topic modeling (TM): the identification of significant groups of words that represent human-understandable topics in large sets of documents. Our research i...
Action Potentials Neuronal Plasticity Natural Language Processing Models, Neurological Neurons Humans Neural Networks, Computer
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