AIMC Topic: Action Potentials

Clear Filters Showing 171 to 180 of 521 articles

Synaptic Learning With Augmented Spikes.

IEEE transactions on neural networks and learning systems Feb 28, 2022
Traditional neuron models use analog values for information representation and computation, while all-or-nothing spikes are employed in the spiking ones. With a more brain-like processing paradigm, spiking neurons are more promising for improvements ...
Action Potentials Neurons Recognition, Psychology Neural Networks, Computer Learning
View on PubMed DOI

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Circulation. Arrhythmia and electrophysiology Jan 28, 2022
BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while ...
Risk Assessment Time Factors Treatment Outcome Machine Learning Risk Factors Electrocardiography, Ambulatory Fibrosis Atrial Fibrillation Magnetic Resonance Imaging Action Potentials Humans Patient-Specific Modeling Atrial Remodeling Recurrence Atrial Function, Left Models, Cardiovascular Heart Rate Catheter Ablation
View on PubMed DOI

The effects of temperature on the dynamics of the biological neural network.

Journal of biological physics Jan 21, 2022
The nerve cells are responsible for transmitting messages through the action potential, which generates electrical stimulation. One of the methods and tools of electrical stimulation is infrared neural stimulation (INS). Since the mechanism of INS is...
Action Potentials Neurons Temperature Models, Neurological Neural Networks, Computer
View on PubMed DOI

Memristive Behaviors Dominated by Reversible Nucleation Dynamics of Phase-Change Nanoclusters.

Small (Weinheim an der Bergstrasse, Germany) Jan 20, 2022
One of the important steps for realizing artificial intelligence is identifying elementary units that are beneficial for neural network construction. A type of memristive behavior in which phase-change nanoclusters nucleate adaptively in two adjacent...
Neural Networks, Computer Artificial Intelligence Action Potentials Neurons
View on PubMed DOI

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BMC cardiovascular disorders Oct 13, 2021
BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar electrocardiographic (ECG) patterns, characterized by ST-segment elevation in the right precordial leads, and risk of Sudden Cardiac Death (SCD). Furthe...
Heart Rate Brugada Syndrome Action Potentials Predictive Value of Tests Humans Signal Processing, Computer-Assisted Machine Learning Transcriptome Italy Reproducibility of Results Prognosis Research Design Diagnosis, Computer-Assisted Workflow Gene Expression Profiling Retrospective Studies Prospective Studies Electrocardiography
View on PubMed DOI

Synaptic Weight Evolution and Charge Trapping Mechanisms in a Synaptic Pass-Transistor Operation With a Direct Potential Output.

IEEE transactions on neural networks and learning systems Oct 5, 2021
We present an intensive study on the weight modulation and charge trapping mechanisms of the synaptic transistor based on a pass-transistor concept for the direct voltage output. In this article, the pass-transistor concept for a metal-oxide-semicond...
Databases, Factual Action Potentials Synapses Electrons Humans Neural Networks, Computer Artificial Intelligence
View on PubMed DOI

Extreme neural machines.

Neural networks : the official journal of the International Neural Network Society Oct 1, 2021
Recurrent neural networks can solve a variety of computational tasks and produce patterns of activity that capture key properties of brain circuits. However, learning rules designed to train these models are time-consuming and prone to inaccuracies w...
Action Potentials Neurons Neural Networks, Computer Learning Models, Neurological
View on PubMed DOI

Visual explanations from spiking neural networks using inter-spike intervals.

Scientific reports Sep 24, 2021
By emulating biological features in brain, Spiking Neural Networks (SNNs) offer an energy-efficient alternative to conventional deep learning. To make SNNs ubiquitous, a 'visual explanation' technique for analysing and explaining the internal spike b...
Neural Networks, Computer Machine Learning Brain Neurons Visual Perception Models, Neurological Humans Action Potentials
View on PubMed DOI

Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses.

Computational intelligence and neuroscience Aug 25, 2021
The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron's firing. In this work, in order to improve computi...
Action Potentials Neural Networks, Computer Neurons Models, Neurological Synapses
View on PubMed DOI

Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 19, 2021
Biological neurons have adaptive nature and perform complex computations involving the filtering of redundant information. However, most common neural cell models, including biologically plausible, such as Hodgkin-Huxley or Izhikevich, do not possess...
Neurons Neural Networks, Computer Algorithms Models, Neurological Action Potentials Neuronal Plasticity
View on PubMed DOI
Popular Topics
Recent Journals