AIMC Topic: Synapses

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Low-power artificial neuron networks with enhanced synaptic functionality using dual transistor and dual memristor.

PloS one Jan 27, 2025
Artificial neurons with bio-inspired firing patterns have the potential to significantly improve the performance of neural network computing. The most significant component of an artificial neuron circuit is a large amount of energy consumption. Rece...
Synapses Models, Neurological Transistors, Electronic Action Potentials Neural Networks, Computer Neurons
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Random noise promotes slow heterogeneous synaptic dynamics important for robust working memory computation.

Proceedings of the National Academy of Sciences of the United States of America Jan 16, 2025
Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neural circuits perform cognitive tasks. Training such networks to perform tasks that require information main...
Models, Neurological Memory, Short-Term Neurons Prefrontal Cortex Cognition Nerve Net Neural Networks, Computer Humans Animals Synapses
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Dynamic Control of Weight-Update Linearity in Magneto-Ionic Synapses.

Nano letters Jan 13, 2025
Multifunctional hardware technologies for neuromorphic computing are essential for replicating the complexity of biological neural systems, thereby improving the performance of artificial synapses and neurons. Integrating ionic and spintronic technol...
Neurons Synapses Magnetic Fields Neural Networks, Computer
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Two-Terminal Neuromorphic Devices for Spiking Neural Networks: Neurons, Synapses, and Array Integration.

ACS nano Dec 12, 2024
The ever-increasing volume of complex data poses significant challenges to conventional sequential global processing methods, highlighting their inherent limitations. This computational burden has catalyzed interest in neuromorphic computing, particu...
Action Potentials Neurons Biomimetics Humans Neural Networks, Computer Synapses
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Spike-VisNet: A novel framework for visual recognition with FocusLayer-STDP learning.

Neural networks : the official journal of the International Neural Network Society Nov 26, 2024
Current vision-inspired spiking neural networks (SNNs) face key challenges due to their model structures typically focusing on single mechanisms and neglecting the integration of multiple biological features. These limitations, coupled with limited s...
Pattern Recognition, Visual Neurons Synapses Visual Perception Action Potentials Retina Humans Neural Networks, Computer Neuronal Plasticity Models, Neurological Learning
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Self-Lateral Propagation Elevates Synaptic Modifications in Spiking Neural Networks for the Efficient Spatial and Temporal Classification.

IEEE transactions on neural networks and learning systems Oct 29, 2024
The brain's mystery for efficient and intelligent computation hides in the neuronal encoding, functional circuits, and plasticity principles in natural neural networks. However, many plasticity principles have not been fully incorporated into artific...
Neurons Synapses Nerve Net Models, Neurological Action Potentials Humans Algorithms Neuronal Plasticity Neural Networks, Computer
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A Self-Driven GaO Memristor Synapse for Humanoid Robot Learning.

Small methods Sep 30, 2024
In recent years, the rapid development of brain-inspired neuromorphic systems has created an imperative demand for artificial photonic synapses that operate with low power consumption. In this study, a self-driven memristor synapse based on gallium o...
Synapses Nanowires Gallium Learning Humans Robotics Artificial Intelligence
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Deep brain stimulation and lag synchronization in a memristive two-neuron network.

Neural networks : the official journal of the International Neural Network Society Sep 10, 2024
In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of h...
Deep Brain Stimulation Nonlinear Dynamics Synapses Action Potentials Neurons Humans Computer Simulation Neuronal Plasticity Neural Networks, Computer Models, Neurological
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A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture.

Neural networks : the official journal of the International Neural Network Society Sep 10, 2024
Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple tasks. Deploying the constructed model in a distributed neuromorphic system, however, remains time-consuming and challenging due to considerations such ...
Humans Neural Networks, Computer Databases, Factual Brain Action Potentials Artificial Intelligence Computer Simulation Neurons Models, Neurological Synapses
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Neuromorphic learning and recognition in WOthin film-based forming-free flexible electronic synapses.

Nanotechnology Aug 23, 2024
In pursuing advanced neuromorphic applications, this study introduces the successful engineering of a flexible electronic synapse based on WO, structured as W/WO/Pt/Muscovite-Mica. This artificial synapse is designed to emulate crucial learning behav...
Synapses Electrical Synapses Tungsten Neural Networks, Computer Neuronal Plasticity Oxides Learning Titanium
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