AIMC Topic: Neurons

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Qualitative Analysis and Bifurcation in a Neuron System With Memristor Characteristics and Time Delay.

IEEE transactions on neural networks and learning systems May 3, 2021
This article focuses on the hybrid effects of memristor characteristics, time delay, and biochemical parameters on neural networks. First, we propose a novel neuron system with memristor and time delays in which the memristor is characterized by a sm...
Computer Simulation Models, Neurological Neurons Neural Networks, Computer Algorithms
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Multistability and associative memory of neural networks with Morita-like activation functions.

Neural networks : the official journal of the International Neural Network Society Apr 30, 2021
This paper presents the multistability analysis and associative memory of neural networks (NNs) with Morita-like activation functions. In order to seek larger memory capacity, this paper proposes Morita-like activation functions. In a weakened condit...
Computer Simulation Neural Networks, Computer Neurons Algorithms
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Leveraging deep learning to control neural oscillators.

Biological cybernetics Apr 28, 2021
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization,...
Neurons Humans Models, Neurological Parkinson Disease Neural Networks, Computer Deep Learning
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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...
Humans Algorithms Computer Simulation Neural Networks, Computer Nonlinear Dynamics Action Potentials Photons Animals Neurons Models, Neurological
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Predictive Visual Motion Extrapolation Emerges Spontaneously and without Supervision at Each Layer of a Hierarchical Neural Network with Spike-Timing-Dependent Plasticity.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 22, 2021
The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localization of a moving object. One way this problem might be solved is extrapolation: using an object's past t...
Neurons Motion Perception Neuronal Plasticity Models, Neurological Neural Networks, Computer Brain Humans
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Hybrid memristor-CMOS neurons for in-situ learning in fully hardware memristive spiking neural networks.

Science bulletin Apr 17, 2021
Spiking neural network, inspired by the human brain, consisting of spiking neurons and plastic synapses, is a promising solution for highly efficient data processing in neuromorphic computing. Recently, memristor-based neurons and synapses are becomi...
Learning Computers Humans Brain Neural Networks, Computer Neurons
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Adaptive SNN for Anthropomorphic Finger Control.

Sensors (Basel, Switzerland) Apr 13, 2021
Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adaptability is among the characteristics of such control units, which provides the anthropomorphic hand w...
Humans Neural Networks, Computer Computers Fingers Neurons Learning
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Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data.

Scientific reports Apr 9, 2021
A key challenge to gaining insight into complex systems is inferring nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only s...
Magnetic Resonance Imaging Causality Computer Simulation Computational Biology Neurons Nerve Net Models, Neurological Models, Statistical Humans Machine Learning Software Brain
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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...
Neural Networks, Computer Neurons Myocytes, Cardiac Single-Cell Analysis Machine Learning Ion Channel Gating Ion Channels Action Potentials Computer Simulation Cardiac Electrophysiology
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Artificial Neuron and Synapse Devices Based on 2D Materials.

Small (Weinheim an der Bergstrasse, Germany) Apr 4, 2021
Neuromorphic systems, which emulate neural functionalities of a human brain, are considered to be an attractive next-generation computing approach, with advantages of high energy efficiency and fast computing speed. After these neuromorphic systems a...
Neurons Synapses Neural Networks, Computer Neuronal Plasticity
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