AIMC Topic: Action Potentials

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An artificial intelligence-enabled electrocardiogram algorithm for the prediction of left atrial low-voltage areas in persistent atrial fibrillation.

Journal of cardiovascular electrophysiology Jul 25, 2024
OBJECTIVES: We aimed to construct an artificial intelligence-enabled electrocardiogram (ECG) algorithm that can accurately predict the presence of left atrial low-voltage areas (LVAs) in patients with persistent atrial fibrillation.
Male Middle Aged Deep Learning Female Reproducibility of Results Aged Signal Processing, Computer-Assisted Atrial Fibrillation Heart Atria Electrocardiography Action Potentials Predictive Value of Tests Humans Algorithms Retrospective Studies Heart Rate Catheter Ablation Atrial Function, Left
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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...
Action Potentials Neurons Algorithms Humans Cluster Analysis Neural Networks, Computer Models, Neurological
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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 Microscopy Electric Impedance Action Potentials Electrochemical Techniques
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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 ...
Brain Humans Neurons Neural Networks, Computer Models, Neurological Algorithms Action Potentials
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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...
Natural Language Processing Neuronal Plasticity Humans Neurons Models, Neurological Neural Networks, Computer Action Potentials
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Towards biologically plausible model-based reinforcement learning in recurrent spiking networks by dreaming new experiences.

Scientific reports Jun 25, 2024
Humans and animals can learn new skills after practicing for a few hours, while current reinforcement learning algorithms require a large amount of data to achieve good performances. Recent model-based approaches show promising results by reducing th...
Computer Simulation Learning Animals Models, Neurological Action Potentials Neurons Humans Neural Networks, Computer Algorithms Nerve Net Reinforcement, Psychology
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Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory.

Neural networks : the official journal of the International Neural Network Society Jun 20, 2024
The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating s...
Memory CA3 Region, Hippocampal Humans Action Potentials Neural Networks, Computer Learning Animals Neurons Computer Simulation Models, Neurological Hippocampus
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BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network.

Nature communications Jun 20, 2024
Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders rem...
Action Potentials Neurons Biomimetics Neural Networks, Computer Humans Animals Nervous System Diseases Models, Neurological Nerve Net
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Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

Journal of neural engineering Jun 20, 2024
. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effecti...
Synapses Nerve Net Neural Inhibition Models, Neurological Action Potentials Neurons Neural Networks, Computer Computer Simulation Humans
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Self-architectural knowledge distillation for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Jun 19, 2024
Spiking neural networks (SNNs) have attracted attention due to their biological plausibility and the potential for low-energy applications on neuromorphic hardware. Two mainstream approaches are commonly used to obtain SNNs, i.e., ANN-to-SNN conversi...
Models, Neurological Action Potentials Humans Knowledge Neural Networks, Computer Machine Learning Algorithms
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