AIMC Topic: Action Potentials

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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 Neural Networks, Computer Models, Neurological Action Potentials Neurons 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...
Neural Networks, Computer Brain Models, Neurological Humans Action Potentials Neurons Attention
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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 Animals Deep Learning Electrophysiological Phenomena Myocytes, Cardiac Electrophysiology Microelectrodes Action Potentials 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...
Neural Networks, Computer Computer Simulation Animals Humans Neurons Nerve Net Memory Models, Neurological Action Potentials Astrocytes
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CS-QCFS: Bridging the performance gap in ultra-low latency spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Jan 1, 2025
Spiking Neural Networks (SNNs) are at the forefront of computational neuroscience, emulating the nuanced dynamics of biological systems. In the realm of SNN training methods, the conversion from ANNs to SNNs has generated significant interest due to ...
Humans Neurons Neural Networks, Computer Algorithms Models, Neurological Action Potentials
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Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Dec 31, 2024
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell...
Ion Channels Patch-Clamp Techniques Humans Neurons Deep Learning Alzheimer Disease Action Potentials Kinetics
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A robust Parkinson's disease detection model based on time-varying synaptic efficacy function in spiking neural network.

BMC neurology Dec 30, 2024
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high e...
Humans Action Potentials Neural Networks, Computer Parkinson Disease Algorithms Neurons Models, Neurological
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Free-space optical spiking neural network.

PloS one Dec 30, 2024
Neuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal dissipation. As an...
Action Potentials Algorithms Brain Humans Models, Neurological Neural Networks, Computer
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Exploring the Versatility of Spiking Neural Networks: Applications Across Diverse Scenarios.

International journal of neural systems Dec 23, 2024
In the last few decades, Artificial Neural Networks have become more and more important, evolving into a powerful tool to implement learning algorithms. Spiking neural networks represent the third generation of Artificial Neural Networks; they have e...
Action Potentials Epilepsy Neurons Neural Networks, Computer Algorithms Humans
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Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.

Journal of cardiovascular electrophysiology Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Reproducibility of Results Risk Factors Aged Male Middle Aged Decision Support Techniques Phenotype Female Predictive Value of Tests Treatment Outcome Catheter Ablation Risk Assessment Humans Atrial Fibrillation Cluster Analysis Recurrence Machine Learning Time Factors Heart Rate Action Potentials
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