AIMC Topic: Dendrites

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Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.

Nature communications Jan 22, 2025
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl...
Humans Learning Neural Networks, Computer Deep Learning Algorithms Dendrites
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Multi-compartment neuron and population encoding powered spiking neural network for deep distributional reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Nov 17, 2024
Inspired by the brain's information processing using binary spikes, spiking neural networks (SNNs) offer significant reductions in energy consumption and are more adept at incorporating multi-scale biological characteristics. In SNNs, spiking neurons...
Dendrites Neurons Reinforcement, Psychology Animals Deep Learning Humans Models, Neurological Algorithms Neural Networks, Computer Action Potentials Computer Simulation
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Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays.

IEEE transactions on neural networks and learning systems May 2, 2024
Episodic memory is fundamental to the brain's cognitive function, but how neuronal activity is temporally organized during its encoding and retrieval is still unknown. In this article, combining hippocampus structure with a spiking neural network (SN...
Neuronal Plasticity Models, Neurological Neural Networks, Computer Algorithms Hippocampus Memory, Episodic Dendrites Action Potentials Neurons Humans
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NADOL: Neuromorphic Architecture for Spike-Driven Online Learning by Dendrites.

IEEE transactions on biomedical circuits and systems Jan 26, 2024
Biologically plausible learning with neuronal dendrites is a promising perspective to improve the spike-driven learning capability by introducing dendritic processing as an additional hyperparameter. Neuromorphic computing is an effective and essenti...
Computers Education, Distance Dendrites Neural Networks, Computer Artificial Intelligence
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Learning smooth dendrite morphological neurons by stochastic gradient descent for pattern classification.

Neural networks : the official journal of the International Neural Network Society Sep 25, 2023
This article presents a learning algorithm for dendrite morphological neurons (DMN) based on stochastic gradient descent (SGD). In particular, we focus on a DMN topology that comprises spherical dendrites, smooth maximum activation function nodes, an...
Neurons Dendrites Algorithms Random Forest 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...
Neurons Dendrites Support Vector Machine Cluster Analysis Neural Networks, Computer Algorithms
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Introducing the Dendrify framework for incorporating dendrites to spiking neural networks.

Nature communications Jan 10, 2023
Computational modeling has been indispensable for understanding how subcellular neuronal features influence circuit processing. However, the role of dendritic computations in network-level operations remains largely unexplored. This is partly because...
Neural Networks, Computer Computer Simulation Neurons Dendrites
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Dendrite Net: A White-Box Module for Classification, Regression, and System Identification.

IEEE transactions on cybernetics Nov 18, 2022
The simulation of biological dendrite computations is vital for the development of artificial intelligence (AI). This article presents a basic machine-learning (ML) algorithm, called Dendrite Net or DD, just like the support vector machine (SVM) or m...
Neural Networks, Computer Support Vector Machine Dendrites Artificial Intelligence Algorithms
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Accuracy Versus Simplification in an Approximate Logic Neural Model.

IEEE transactions on neural networks and learning systems Oct 27, 2021
An approximate logic neural model (ALNM) is a novel single-neuron model with plastic dendritic morphology. During the training process, the model can eliminate unnecessary synapses and useless branches of dendrites. It will produce a specific dendrit...
Databases, Factual Reproducibility of Results Neural Networks, Computer Algorithms Logic Humans Dendrites Neuronal Plasticity Synapses
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Single cortical neurons as deep artificial neural networks.

Neuron Aug 10, 2021
Utilizing recent advances in machine learning, we introduce a systematic approach to characterize neurons' input/output (I/O) mapping complexity. Deep neural networks (DNNs) were trained to faithfully replicate the I/O function of various biophysical...
Cerebral Cortex Models, Neurological Dendrites Humans Receptors, N-Methyl-D-Aspartate Pyramidal Cells Deep Learning
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