AIMC Topic: Synapses

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Adaptive synapse-based neuron model with heterogeneous multistability and riddled basins.

Chaos (Woodbury, N.Y.) Dec 1, 2022
Biological neurons can exhibit complex coexisting multiple firing patterns dependent on initial conditions. To this end, this paper presents a novel adaptive synapse-based neuron (ASN) model with sine activation function. The ASN model has time-varyi...
Neural Networks, Computer Neurons Synapses Algorithms Computer Simulation
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Neural Information Processing and Computations of Two-Input Synapses.

Neural computation Sep 12, 2022
Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological n...
Synaptic Transmission Synapses Artificial Intelligence Models, Neurological Neurons
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Scalability of Large Neural Network Simulations via Activity Tracking With Time Asynchrony and Procedural Connectivity.

Neural computation Aug 16, 2022
We present a new algorithm to efficiently simulate random models of large neural networks satisfying the property of time asynchrony. The model parameters (average firing rate, number of neurons, synaptic connection probability, and postsynaptic dura...
Computer Simulation Animals Humans Neural Networks, Computer Synapses Action Potentials Mammals Models, Neurological
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Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports Aug 2, 2022
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...
Microscopy, Electron Fear Synapses Deep Learning Mice Neuronal Plasticity Mitochondria Animals
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Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America Sep 28, 2021
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...
Neural Networks, Computer Electrons Artificial Intelligence Algorithms Synapses Insulator Elements Models, Neurological Neuronal Plasticity Animals Aplysia Nickel
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Molecular memristors offer a path to ultra-efficient computing.

Nature Sep 1, 2021
Synapses Neural Networks, Computer
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Training Spiking Neural Networks in the Strong Coupling Regime.

Neural computation Apr 13, 2021
Recurrent neural networks trained to perform complex tasks can provide insight into the dynamic mechanism that underlies computations performed by cortical circuits. However, due to a large number of unconstrained synaptic connections, the recurrent ...
Models, Neurological Neural Networks, Computer Learning Synapses
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Transition to synchronization in heterogeneous inhibitory neural networks with structured synapses.

Chaos (Woodbury, N.Y.) Mar 1, 2021
Inhibitory neurons form an extensive network involved in the development of different rhythms in the cerebral cortex. A transition from an incoherent state, where all inhibitory neurons fire unrelated to each other, to a synchronized or locked state,...
Models, Neurological Nerve Net Action Potentials Neural Networks, Computer Neurons Synapses
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3D Integrable W/SiN/n-Si/p-Si 1D1R Unipolar Resistive Random Access Memory Synapse for Suppressing Reverse Leakage in Spiking Neural Network.

Journal of nanoscience and nanotechnology Aug 1, 2020
In this paper, we pose reverse leakage current issue which occurs when resistive random access memory (RRAM) is used as synapse for spiking neural networks (SNNs). To prevent this problem, 1 diode-1 RRAM (1D1R) synapse is suggested and simulated to e...
Neural Networks, Computer Synapses
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Dynamics and bifurcations in multistable 3-cell neural networks.

Chaos (Woodbury, N.Y.) Jul 1, 2020
We disclose the generality of the intrinsic mechanisms underlying multistability in reciprocally inhibitory 3-cell circuits composed of simplified, low-dimensional models of oscillatory neurons, as opposed to those of a detailed Hodgkin-Huxley type [...
Neurons Neural Networks, Computer Synapses Humans Models, Neurological
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