AIMC Topic: Dendrites

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Dendritic normalisation improves learning in sparsely connected artificial neural networks.

PLoS computational biology Aug 9, 2021
Artificial neural networks, taking inspiration from biological neurons, have become an invaluable tool for machine learning applications. Recent studies have developed techniques to effectively tune the connectivity of sparsely-connected artificial n...
Stochastic Processes Dendrites Neurons Nerve Net Animals Deep Learning Models, Neurological Action Potentials Computational Biology Neural Networks, Computer Machine Learning Humans
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Parallel and Recurrent Cascade Models as a Unifying Force for Understanding Subcellular Computation.

Neuroscience Aug 3, 2021
Neurons are very complicated computational devices, incorporating numerous non-linear processes, particularly in their dendrites. Biophysical models capture these processes directly by explicitly modelling physiological variables, such as ion channel...
Neural Networks, Computer Neurons Dendrites Biophysics Artificial Intelligence Models, Neurological
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Drawing inspiration from biological dendrites to empower artificial neural networks.

Current opinion in neurobiology Jun 1, 2021
This article highlights specific features of biological neurons and their dendritic trees, whose adoption may help advance artificial neural networks used in various machine learning applications. Advancements could take the form of increased computa...
Machine Learning Models, Neurological Neurons Neural Networks, Computer Dendrites
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Small universal spiking neural P systems with dendritic/axonal delays and dendritic trunk/feedback.

Neural networks : the official journal of the International Neural Network Society Feb 16, 2021
In spiking neural P (SN P) systems, neurons are interconnected by means of synapses, and they use spikes to communicate with each other. However, in biology, the complex structure of dendritic tree is also an important part in the communication schem...
Neural Networks, Computer Feedback Humans Dendrites Models, Neurological Action Potentials Axons Synapses Reaction Time
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Smooth dendrite morphological neurons.

Neural networks : the official journal of the International Neural Network Society Dec 29, 2020
A typical feature of hyperbox-based dendrite morphological neurons (DMN) is the generation of sharp and rough decision boundaries that inaccurately track the distribution shape of classes of patterns. This feature is because the minimum and maximum a...
Humans Neurons Dendrites Algorithms Support Vector Machine Neural Networks, Computer Machine Learning
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Dendrite P Systems Toolbox: Representation, Algorithms and Simulators.

International journal of neural systems Nov 16, 2020
Dendrite P systems (DeP systems) are a recently introduced neural-like model of computation. They provide an alternative to the more classical spiking neural (SN) P systems. In this paper, we present the first software simulator for DeP systems, and ...
Algorithms Computer Simulation Dendrites Neurons Neural Networks, Computer
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Passive Nonlinear Dendritic Interactions as a Computational Resource in Spiking Neural Networks.

Neural computation Oct 20, 2020
Nonlinear interactions in the dendritic tree play a key role in neural computation. Nevertheless, modeling frameworks aimed at the construction of large-scale, functional spiking neural networks, such as the Neural Engineering Framework, tend to assu...
Nonlinear Dynamics Dendrites Models, Neurological Action Potentials Humans Neural Networks, Computer
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Sparse coding with a somato-dendritic rule.

Neural networks : the official journal of the International Neural Network Society Jun 26, 2020
Cortical neurons are silent most of the time: sparse activity enables low-energy computation in the brain, and promises to do the same in neuromorphic hardware. Beyond power efficiency, sparse codes have favourable properties for associative learning...
Neuronal Plasticity Dendrites Machine Learning Feedback Humans Association Learning Neural Networks, Computer
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NeuroConstruct-based implementation of structured-light stimulated retinal circuitry.

BMC neuroscience Jun 24, 2020
BACKGROUND: Retinal circuitry provides a fundamental window to neural networks, featuring widely investigated visual phenomena ranging from direction selectivity to fast detection of approaching motion. As the divide between experimental and theoreti...
Motion Perception Visual Pathways Amacrine Cells Computer Simulation Neural Inhibition Dendrites Animals Synapses Models, Neurological Retinal Ganglion Cells Neural Networks, Computer
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Dendrite P systems.

Neural networks : the official journal of the International Neural Network Society Apr 18, 2020
It was recently found that dendrites are not just a passive channel. They can perform mixed computation of analog and digital signals, and therefore can be abstracted as information processors. Moreover, dendrites possess a feedback mechanism. Motiva...
Neurons Synapses Models, Neurological Dendrites Humans Action Potentials Neural Networks, Computer
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