AIMC Topic:
Neurons

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Adopting improved Adam optimizer to train dendritic neuron model for water quality prediction.

Mathematical biosciences and engineering : MBE Mar 20, 2023
As one of continuous concern all over the world, the problem of water quality may cause diseases and poisoning and even endanger people's lives. Therefore, the prediction of water quality is of great significance to the efficient management of water ...
Humans Computer Simulation Neurons Algorithms Neural Networks, Computer Water Quality
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Stochastic photonic spiking neuron for Bayesian inference with unsupervised learning.

Optics letters Mar 15, 2023
Stochasticity is an inherent feature of biological neural activities. We propose a noise-injection scheme to implement a GHz-rate stochastic photonic spiking neuron (S-PSN). The firing-probability encoding is experimentally demonstrated and exploited...
Neurons Unsupervised Machine Learning Bayes Theorem Action Potentials Neural Networks, Computer
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NeuroAI: If grid cells are the answer, is path integration the question?

Current biology : CB Mar 13, 2023
Spatially modulated neurons known as grid cells are thought to play an important role in spatial cognition. A new study has found that units with grid-cell-like properties can emerge within artificial neural networks trained to path integrate, and de...
Cognition Models, Neurological Learning Space Perception Entorhinal Cortex Neurons Action Potentials Neural Networks, Computer
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Macroscopic dynamics of neural networks with heterogeneous spiking thresholds.

Physical review. E Feb 1, 2023
Mean-field theory links the physiological properties of individual neurons to the emergent dynamics of neural population activity. These models provide an essential tool for studying brain function at different scales; however, for their application ...
Adaptation, Physiological Neurons Models, Neurological Action Potentials Neural Networks, Computer
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Artificial intelligence gives neuron reconstruction a performance boost.

Nature methods Feb 1, 2023
Neurons Algorithms Artificial Intelligence Neural Networks, Computer
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Explaining the Neuroevolution of Fighting Creatures Through Virtual fMRI.

Artificial life Jan 2, 2023
While interest in artificial neural networks (ANNs) has been renewed by the ubiquitous use of deep learning to solve high-dimensional problems, we are still far from general artificial intelligence. In this article, we address the problem of emergent...
Artificial Intelligence Neural Networks, Computer Neurons Magnetic Resonance Imaging
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Spiking Neural Networks and Mathematical Models.

Advances in experimental medicine and biology Jan 1, 2023
Neural networks are applied in various scientific fields such as medicine, engineering, pharmacology, etc. Investigating operations of neural networks refers to estimating the relationship among single neurons and their contributions to the network a...
Brain Neural Networks, Computer Action Potentials Models, Neurological Neurons
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Neuron tracing from light microscopy images: automation, deep learning and bench testing.

Bioinformatics (Oxford, England) Dec 13, 2022
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...
Automation Animals Microscopy Deep Learning Algorithms Imaging, Three-Dimensional Mammals Neurons
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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...
Computer Simulation Neurons Algorithms Neural Networks, Computer Synapses
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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...
Synapses Models, Neurological Synaptic Transmission Artificial Intelligence Neurons
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