AIMC Topic: Action Potentials

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Spiking Neural P Systems with Extended Channel Rules.

International journal of neural systems Aug 18, 2020
This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neural P systems with extended channel rules (in short, SNP-ECR systems). SNP-ECR systems are a class of distributed parallel computing models. In SNP-ECR...
Action Potentials Neurons Synapses Neural Networks, Computer Models, Neurological
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Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.

Neural networks : the official journal of the International Neural Network Society Aug 17, 2020
Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Spiking neural networks (SNNs) represent a family of event-driven models...
Humans Algorithms Vision, Ocular Neural Networks, Computer Databases, Factual Recognition, Psychology Machine Learning Action Potentials Neurons
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Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics.

Nature communications Aug 12, 2020
Sensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphe...
Neuronal Plasticity Action Potentials Robotics Signal Processing, Computer-Assisted Transistors, Electronic Logic Nociception Presynaptic Terminals
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SpiFoG: an efficient supervised learning algorithm for the network of spiking neurons.

Scientific reports Aug 4, 2020
There has been a lot of research on supervised learning in spiking neural network (SNN) for a couple of decades to improve computational efficiency. However, evolutionary algorithm based supervised learning for SNN has not been investigated thoroughl...
Action Potentials Supervised Machine Learning Neurons Nerve Net
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Spiking Neural P Systems with Delay on Synapses.

International journal of neural systems Jul 23, 2020
Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapse...
Neural Networks, Computer Action Potentials Animals Neurons Models, Neurological Synapses
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A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation.

Neural computation Jul 20, 2020
Bursting plays an important role in neural communication. At the population level, macroscopic bursting has been identified in populations of neurons that do not express intrinsic bursting mechanisms. For the analysis of phase transitions between bur...
Neurons Nerve Net Synaptic Transmission Humans Neural Networks, Computer Computer Simulation Action Potentials
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Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

Scientific reports Jul 9, 2020
The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied f...
Artificial Intelligence Machine Learning Brain Female Animals Nanotechnology Cerebral Cortex Serotonin Dopamine Parkinson Disease Electric Conductivity Single Molecule Imaging Brain Mapping Neurotransmitter Agents Mice Norepinephrine Electrodes Action Potentials Mice, Inbred C57BL
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Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
BACKGROUND: Advances in ablation for atrial fibrillation (AF) continue to be hindered by ambiguities in mapping, even between experts. We hypothesized that convolutional neural networks (CNN) may enable objective analysis of intracardiac activation i...
Atrial Function, Right Pattern Recognition, Automated Atrial Function, Left Electrophysiologic Techniques, Cardiac Time Factors Support Vector Machine Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Registries Atrial Fibrillation Heart Rate Aged Male Middle Aged Diagnosis, Computer-Assisted Neural Networks, Computer Humans Female Reproducibility of Results
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Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are...
Humans Artificial Intelligence Machine Learning Electrocardiography Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Prognosis Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Electrophysiologic Techniques, Cardiac Heart Conduction System Arrhythmias, Cardiac Heart Rate
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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Heart Rate Male Catheter Ablation Middle Aged Proof of Concept Study Diagnosis, Computer-Assisted Female Risk Assessment Organometallic Compounds Meglumine Treatment Outcome Reproducibility of Results Contrast Media Humans Recurrence Risk Factors Magnetic Resonance Imaging Action Potentials Machine Learning Models, Cardiovascular Aged Patient-Specific Modeling Predictive Value of Tests Pulmonary Veins Atrial Fibrillation Retrospective Studies
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