AIMC Topic: Action Potentials

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Memory-Dependent Computation and Learning in Spiking Neural Networks Through Hebbian Plasticity.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Spiking neural networks (SNNs) are the basis for many energy-efficient neuromorphic hardware systems. While there has been substantial progress in SNN research, artificial SNNs still lack many capabilities of their biological counterparts. In biologi...
Neural Networks, Computer Action Potentials Machine Learning Neurons Computer Simulation Memory Learning Neuronal Plasticity Models, Neurological Humans
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Bio-plausible reconfigurable spiking neuron for neuromorphic computing.

Science advances Feb 5, 2025
Biological neurons use diverse temporal expressions of spikes to achieve efficient communication and modulation of neural activities. Nonetheless, existing neuromorphic computing systems mainly use simplified neuron models with limited spiking behavi...
Models, Neurological Humans Action Potentials Neural Networks, Computer Neurons
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A multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.

Journal of neural engineering Feb 5, 2025
The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosing and locating the epileptogenic region. The traditional seizure detection methods lack spike features and have low sample richness. This paper propos...
Nerve Net Humans Neural Networks, Computer Action Potentials Electroencephalography Epilepsy Seizures
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Spatio-temporal transformers for decoding neural movement control.

Journal of neural engineering Feb 4, 2025
. Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to...
Spatio-Temporal Analysis Models, Neurological Action Potentials Neural Networks, Computer Animals Male Movement Motor Cortex Macaca mulatta Neurons Psychomotor Performance
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Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience Feb 1, 2025
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...
Conditioning, Classical Time Perception Humans Neurons Discrimination, Psychological Neural Networks, Computer Nerve Net Animals Time Factors Models, Neurological Action Potentials
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Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation.

Neuroinformatics Feb 1, 2025
The bidirectional interactions between brain and heart through autonomic nervous system is the prime focus of neuro-cardiology community. The computer models designed to analyze brain and heart signals are either complex in terms of molecular and cel...
Heart Rate Myocytes, Cardiac Autonomic Nervous System Action Potentials Heart Humans Neural Networks, Computer Brain Computer Simulation Animals
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Low-power artificial neuron networks with enhanced synaptic functionality using dual transistor and dual memristor.

PloS one Jan 27, 2025
Artificial neurons with bio-inspired firing patterns have the potential to significantly improve the performance of neural network computing. The most significant component of an artificial neuron circuit is a large amount of energy consumption. Rece...
Transistors, Electronic Action Potentials Neural Networks, Computer Neurons Models, Neurological Synapses
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Towards parameter-free attentional spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Jan 16, 2025
Brain-inspired spiking neural networks (SNNs) are increasingly explored for their potential in spatiotemporal information modeling and energy efficiency on emerging neuromorphic hardware. Recent works incorporate attentional modules into SNNs, greatl...
Attention Humans Action Potentials Neural Networks, Computer Neurons Brain Models, Neurological
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Intelligent in-cell electrophysiology: Reconstructing intracellular action potentials using a physics-informed deep learning model trained on nanoelectrode array recordings.

Nature communications Jan 14, 2025
Intracellular electrophysiology is essential in neuroscience, cardiology, and pharmacology for studying cells' electrical properties. Traditional methods like patch-clamp are precise but low-throughput and invasive. Nanoelectrode Arrays (NEAs) offer ...
Humans Electrophysiological Phenomena Animals Myocytes, Cardiac Deep Learning Electrophysiology Action Potentials Microelectrodes Nanotechnology
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Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network.

IEEE transactions on neural networks and learning systems Jan 7, 2025
Mammalian brains operate in very special surroundings: to survive they have to react quickly and effectively to the pool of stimuli patterns previously recognized as danger. Many learning tasks often encountered by living organisms involve a specific...
Models, Neurological Action Potentials Astrocytes Neurons Nerve Net Memory Neural Networks, Computer Computer Simulation Animals Humans
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