AIMC Topic: Action Potentials

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Heterogeneous quantization regularizes spiking neural network activity.

Scientific reports Apr 23, 2025
The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains, on the other hand, are adept at learning stable sensory representations given noisy observations, a ...
Models, Neurological Action Potentials Neurons Humans Neural Networks, Computer Animals Nerve Net
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders Apr 7, 2025
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...
Arrhythmias, Cardiac Heart Rate Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Reproducibility of Results Diagnosis, Computer-Assisted Humans Electrocardiography Machine Learning Algorithms
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Finger Vein Recognition Based on Unsupervised Spiking Convolutional Neural Network with Adaptive Firing Threshold.

Sensors (Basel, Switzerland) Apr 3, 2025
Currently, finger vein recognition (FVR) stands as a pioneering biometric technology, with convolutional neural networks (CNNs) and Transformers, among other advanced deep neural networks (DNNs), consistently pushing the boundaries of recognition acc...
Algorithms Deep Learning Convolutional Neural Networks Humans Neural Networks, Computer Neurons Fingers Veins Support Vector Machine Action Potentials
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RRAM-Based Spiking Neural Network With Target-Modulated Spike-Timing-Dependent Plasticity.

IEEE transactions on biomedical circuits and systems Apr 2, 2025
The spiking neural network (SNN) training with spike timing-dependent plasticity (STDP) for image classification usually requires a lot of neurons to extract representative features and(or) needs an external classifier. Conventional bio-inspired lear...
Humans Models, Neurological Action Potentials Neural Networks, Computer Neurons Algorithms Neuronal Plasticity
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GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity.

Pharmaceutical research Mar 26, 2025
PURPOSE: The human Ether-a-go-go Related-Gene (hERG) encodes rectifying potassium channels that play a significant role during action potential repolarization of cardiomyocytes. Blockade of the hERG channel by off-target drugs can lead to long QT syn...
Deep Learning Action Potentials Cardiotoxicity Humans Algorithms Graph Neural Networks Ether-A-Go-Go Potassium Channels Neural Networks, Computer Computer Simulation Machine Learning Potassium Channel Blockers ERG1 Potassium Channel
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Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks.

Nature neuroscience Mar 24, 2025
The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials...
Epilepsy Memory, Short-Term Neurons Adult Nerve Net Recurrent Neural Networks Humans Male Female Temporal Lobe Neural Networks, Computer Theta Rhythm Action Potentials Young Adult
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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 ...
Electroencephalography Cerebral Cortex Brain Waves Nerve Net Computer Simulation Humans Thalamus Neural Networks, Computer Epilepsies, Partial Models, Neurological Action Potentials
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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 ...
Silicon Models, Neurological Action Potentials Neurons Humans Neural Networks, Computer
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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 ...
Action Potentials Machine Learning 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...
Humans Neural Networks, Computer Action Potentials Electroencephalography Seizures
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