AIMC Topic: Neurons

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Synchronization in STDP-driven memristive neural networks with time-varying topology.

Journal of biological physics Sep 1, 2023
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by s...
Synapses Neurons Brain Neural Networks, Computer Models, Neurological Neuronal Plasticity
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HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks.

IEEE transactions on neural networks and learning systems Sep 1, 2023
Spiking neural networks (SNNs), inspired by the neuronal network in the brain, provide biologically relevant and low-power consuming models for information processing. Existing studies either mimic the learning mechanism of brain neural networks as c...
Neural Networks, Computer Brain Neurons Algorithms Machine Learning
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DEBI-NN: Distance-encoding biomorphic-informational neural networks for minimizing the number of trainable parameters.

Neural networks : the official journal of the International Neural Network Society Aug 25, 2023
Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts of data to train, given, that the number of their trainable parameters has a polynomial relati...
Diagnostic Imaging Algorithms Neural Networks, Computer Neurons Artificial Intelligence
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Bio-inspired, task-free continual learning through activity regularization.

Biological cybernetics Aug 17, 2023
The ability to sequentially learn multiple tasks without forgetting is a key skill of biological brains, whereas it represents a major challenge to the field of deep learning. To avoid catastrophic forgetting, various continual learning (CL) approach...
Brain Feedback Neurons Algorithms Neural Networks, Computer
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SWsnn: A Novel Simulator for Spiking Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology Aug 16, 2023
Spiking neural network (SNN) simulators play an important role in neural system modeling and brain function research. They can help scientists reproduce and explore neuronal activities in brain regions, neuroscience, brain-like computing, and other f...
Computer Simulation Brain Neural Networks, Computer Neurons Artificial Intelligence
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Spiking neural P systems with lateral inhibition.

Neural networks : the official journal of the International Neural Network Society Aug 12, 2023
As a member of the third generation of artificial neural network models, spiking neural P systems (SN P systems) have gained a hot research spot in recent years. This work introduces the phenomenon of lateral inhibition in biological nervous systems ...
Action Potentials Neurons Models, Neurological Neural Networks, Computer
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DLATA: Deep Learning-Assisted transformation alignment of 2D brain slice histology.

Neuroscience letters Aug 9, 2023
Accurate alignment of brain slices is crucial for the classification of neuron populations by brain region, and for quantitative analysis in in vitro brain studies. Current semi-automated alignment workflows require labor intensive labeling of featur...
Brain Neurons Mice Deep Learning Image Processing, Computer-Assisted Animals
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Distribution Patterns of Subgroups of Inhibitory Neurons Divided by Calbindin 1.

Molecular neurobiology Aug 7, 2023
The inhibitory neurons in the brain play an essential role in neural network firing patterns by releasing γ-aminobutyric acid (GABA) as the neurotransmitter. In the mouse brain, based on the protein molecular markers, inhibitory neurons are usually t...
Mice, Transgenic Parvalbumins Neurons Calbindin 1 Brain Neural Networks, Computer Mice Animals
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Experimental validation of the free-energy principle with in vitro neural networks.

Nature communications Aug 7, 2023
Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, w...
Models, Neurological Neurons Rats Animals Neural Networks, Computer
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Improving the Classification Performance of Dendrite Morphological Neurons.

IEEE transactions on neural networks and learning systems Aug 4, 2023
Dendrite morphological neurons (DMNs) are neural models for pattern classification, where dendrites are represented by a geometric shape enclosing patterns of the same class. This study evaluates the impact of three dendrite geometries-namely, box, e...
Algorithms Support Vector Machine Neural Networks, Computer Neurons Cluster Analysis Dendrites
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