AIMC Topic: Action Potentials

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Understanding the Spatio-Temporal Coupling of Spikes and Spindles in Focal Epilepsy Through a Network-Level Computational Model.

International journal of neural systems Mar 15, 2025
The electrophysiological findings have shown that epileptiform spikes triggering sleep spindles within 1[Formula: see text]s across multiple channels are commonly observed during sleep in focal epilepsy (FE). Such spatio-temporal couplings of spikes ...
Neural Networks, Computer Computer Simulation Models, Neurological Humans Brain Waves Nerve Net Thalamus Action Potentials Electroencephalography Cerebral Cortex Epilepsies, Partial
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FPGA implementation of a complete digital spiking silicon neuron for circuit design and network approach.

Scientific reports Mar 12, 2025
When attempting to replicate the same biological spiking neuron model actions of the human brain, the spiking neuron model methodology and hardware realization design for the nervous system of the brain are crucial considerations. This work provides ...
Neurons Humans Neural Networks, Computer Silicon Models, Neurological Action Potentials
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LAST-PAIN: Learning Adaptive Spike Thresholds for Low Back Pain Biosignals Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 7, 2025
Spiking neural networks (SNNs) present the potential for ultra-low-power computation, especially when implemented on dedicated neuromorphic hardware. However, a significant challenge is the efficient conversion of continuous real-world data into the ...
Machine Learning Action Potentials Humans Signal Processing, Computer-Assisted Algorithms Neural Networks, Computer Low Back Pain Databases, Factual
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Predicting EEG seizures using graded spiking neural networks.

Journal of neural engineering Mar 6, 2025
To develop and evaluate a novel, non-patient-specific epileptic seizure prediction system using graded spiking neural networks (GSNNs) implemented on Intel's Loihi 2 neuromorphic processor, addressing the challenges of real-time, energy-efficient pre...
Seizures Humans Neural Networks, Computer Action Potentials Electroencephalography
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Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness.

IEEE transactions on neural networks and learning systems Feb 28, 2025
Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse plasticity rules, synaptic scaling presents indispensable effects on homeostasis maintenance and synaptic strength regulation. In the current mo...
Synapses Learning Animals Neuronal Plasticity Models, Neurological Neural Networks, Computer Action Potentials Algorithms Neurons Computer Simulation Humans
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Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Cardiovascular engineering and technology Feb 26, 2025
Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the heart's function. In the recent decade, various attempts have been made to automate the classification of electrocardiogram signals to detect heartbe...
Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Signal Processing, Computer-Assisted Humans Arrhythmias, Cardiac Databases, Factual Heart Rate Electrocardiography Action Potentials Predictive Value of Tests
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Exploring temporal information dynamics in Spiking Neural Networks: Fast Temporal Efficient Training.

Journal of neuroscience methods Feb 25, 2025
BACKGROUND: Spiking Neural Networks (SNNs) hold significant potential in brain simulation and temporal data processing. While recent research has focused on developing neuron models and leveraging temporal dynamics to enhance performance, there is a ...
Models, Neurological Action Potentials Neurons Brain Humans Time Factors Neural Networks, Computer Algorithms
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An accurate and fast learning approach in the biologically spiking neural network.

Scientific reports Feb 24, 2025
Computations adapted from the interactions of neurons in the nervous system have the potential to be a strong foundation for building computers with cognitive functions including decision-making, generalization, and real-time learning. In this contex...
Nerve Net Pyramidal Cells Algorithms Action Potentials Learning Neurons Humans Models, Neurological Neural Networks, Computer Machine Learning
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Explainable paroxysmal atrial fibrillation diagnosis using an artificial intelligence-enabled electrocardiogram.

The Korean journal of internal medicine Feb 21, 2025
BACKGROUND/AIMS: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent ...
Neural Networks, Computer Artificial Intelligence Female Aged Male Middle Aged Humans Early Diagnosis Action Potentials Deep Learning Predictive Value of Tests Electrocardiography Atrial Fibrillation
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Spiking neural networks on FPGA: A survey of methodologies and recent advancements.

Neural networks : the official journal of the International Neural Network Society Feb 14, 2025
The mimicry of the biological brain's structure in information processing enables spiking neural networks (SNNs) to exhibit significantly reduced power consumption compared to conventional systems. Consequently, these networks have garnered heightene...
Neurons Humans Neural Networks, Computer Brain Animals Action Potentials
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