AIMC Topic: Action Potentials

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SNN-BERT: Training-efficient Spiking Neural Networks for energy-efficient BERT.

Neural networks : the official journal of the International Neural Network Society Aug 20, 2024
Spiking Neural Networks (SNNs) are naturally suited to process sequence tasks such as NLP with low power, due to its brain-inspired spatio-temporal dynamics and spike-driven nature. Current SNNs employ "repeat coding" that re-enter all input tokens a...
Algorithms Deep Learning Models, Neurological Humans Neural Networks, Computer Action Potentials Neurons
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Artificial intelligence-driven electrocardiography: Innovations in hypertrophic cardiomyopathy management.

Trends in cardiovascular medicine Aug 13, 2024
Hypertrophic Cardiomyopathy (HCM) presents a complex diagnostic and prognostic challenge due to its heterogeneous phenotype and clinical course. Artificial Intelligence (AI) and Machine Learning (ML) techniques hold promise in transforming the role o...
Artificial Intelligence Prognosis Clinical Decision-Making Risk Factors Humans Electrocardiography Signal Processing, Computer-Assisted Action Potentials Heart Rate Risk Assessment Predictive Value of Tests Cardiomyopathy, Hypertrophic Death, Sudden, Cardiac Diagnosis, Computer-Assisted Deep Learning
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Multi-focus image fusion with parameter adaptive dual channel dynamic threshold neural P systems.

Neural networks : the official journal of the International Neural Network Society Aug 8, 2024
Multi-focus image fusion (MFIF) is an important technique that aims to combine the focused regions of multiple source images into a fully clear image. Decision-map methods are widely used in MFIF to maximize the preservation of information from the s...
Action Potentials Neurons Animals Image Processing, Computer-Assisted Models, Neurological Neural Networks, Computer Algorithms Humans
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Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models.

Neural networks : the official journal of the International Neural Network Society Aug 5, 2024
Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological syste...
Humans Animals Models, Neurological Action Potentials Neurons Neural Networks, Computer Cells, Cultured Computer Simulation
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Multitask learning of a biophysically-detailed neuron model.

PLoS computational biology Jul 31, 2024
The human brain operates at multiple levels, from molecules to circuits, and understanding these complex processes requires integrated research efforts. Simulating biophysically-detailed neuron models is a computationally expensive but effective meth...
Models, Neurological Brain Action Potentials Humans Electroencephalography Computer Simulation Neurons Neural Networks, Computer Computational Biology Magnetoencephalography Machine Learning Membrane Potentials
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Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Journal of neural engineering Jul 29, 2024
Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupli...
Neural Networks, Computer Female Male Aged Deep Brain Stimulation Humans Action Potentials Middle Aged Microelectrodes Parkinson Disease Models, Neurological Neurons
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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.
Catheter Ablation Female Atrial Fibrillation Atrial Function, Left Heart Atria Reproducibility of Results Electrocardiography Humans Heart Rate Male Aged Action Potentials Algorithms Predictive Value of Tests Middle Aged Retrospective Studies Deep Learning Signal Processing, Computer-Assisted
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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...
Models, Neurological Action Potentials Neurons Neural Networks, Computer Algorithms Cluster Analysis Humans
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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...
Electric Impedance Animals Deep Learning Action Potentials Electrochemical Techniques Neurons Microscopy
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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 ...
Neural Networks, Computer Algorithms Brain Neurons Humans Models, Neurological Action Potentials
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