AIMC Topic: Action Potentials

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Efficient learning with augmented spikes: A case study with image classification.

Neural networks : the official journal of the International Neural Network Society May 12, 2021
Efficient learning of spikes plays a valuable role in training spiking neural networks (SNNs) to have desired responses to input stimuli. However, current learning rules are limited to a binary form of spikes. The seemingly ubiquitous phenomenon of b...
Models, Neurological Action Potentials Neurons Neural Networks, Computer Learning
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ELVISort: encoding latent variables for instant sorting, an artificial intelligence-based end-to-end solution.

Journal of neural engineering Apr 26, 2021
The growing number of recording sites of silicon-based probes means that an increasing amount of neural cell activities can be recorded simultaneously, facilitating the investigation of underlying complex neural dynamics. In order to overcome the cha...
Models, Neurological Action Potentials Signal Processing, Computer-Assisted Artificial Intelligence Algorithms
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Collective and synchronous dynamics of photonic spiking neurons.

Nature communications Apr 23, 2021
Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective sp...
Nonlinear Dynamics Action Potentials Photons Humans Neurons Neural Networks, Computer Algorithms Computer Simulation Animals Models, Neurological
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On Robot Compliance: A Cerebellar Control Approach.

IEEE transactions on cybernetics Apr 15, 2021
The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebe...
Cerebellum Brain-Computer Interfaces Humans Movement Neuronal Plasticity Action Potentials Models, Neurological Robotics Upper Extremity
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Artificial neural network model for predicting changes in ion channel conductance based on cardiac action potential shapes generated via simulation.

Scientific reports Apr 9, 2021
Many studies have revealed changes in specific protein channels due to physiological causes such as mutation and their effects on action potential duration changes. However, no studies have been conducted to predict the type of protein channel abnorm...
Cardiac Electrophysiology Ion Channels Ion Channel Gating Machine Learning Computer Simulation Single-Cell Analysis Action Potentials Neurons Myocytes, Cardiac Neural Networks, Computer
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A biomimetic neural encoder for spiking neural network.

Nature communications Apr 9, 2021
Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-dri...
Humans Neural Networks, Computer Transistors, Electronic Datasets as Topic Biomimetic Materials Algorithms Action Potentials Biomimetics Sensory Receptor Cells Nerve Net Visual Cortex
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Learning precise spatiotemporal sequences via biophysically realistic learning rules in a modular, spiking network.

eLife Mar 18, 2021
Multiple brain regions are able to learn and express temporal sequences, and this functionality is an essential component of learning and memory. We propose a substrate for such representations via a network model that learns and recalls discrete seq...
Action Potentials Neurons Neural Networks, Computer Biophysical Phenomena Learning Spatio-Temporal Analysis Models, Neurological
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Machine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement.

Circulation. Arrhythmia and electrophysiology Mar 9, 2021
Cardiac Pacing, Artificial Heart Rate Transcatheter Aortic Valve Replacement Pacemaker, Artificial Atrioventricular Block Prospective Studies Action Potentials Retrospective Studies Aortic Valve Risk Factors Risk Assessment Predictive Value of Tests Humans Treatment Outcome Machine Learning Decision Support Techniques
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Signal-to-signal neural networks for improved spike estimation from calcium imaging data.

PLoS computational biology Mar 1, 2021
Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result i...
Neural Networks, Computer Models, Neurological Action Potentials Calcium Algorithms Fluorescence
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Dynamics of a Large-Scale Spiking Neural Network with Quadratic Integrate-and-Fire Neurons.

Neural plasticity Feb 23, 2021
Since the high dimension and complexity of the large-scale spiking neural network, it is difficult to research the network dynamics. In recent decades, the mean-field approximation has been a useful method to reduce the dimension of the network. In t...
Synapses Nerve Net Models, Neurological Neural Inhibition Neural Networks, Computer Action Potentials Computer Simulation Neurons
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