AI Medical Compendium Topic:
Neurons

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Extracting boolean and probabilistic rules from trained neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents two approaches to extracting rules from a trained neural network consisting of linear threshold functions. The first one leads to an algorithm that extracts rules in the form of Boolean functions. Compared with an existing one, th...

Learning in the machine: To share or not to share?

Neural networks : the official journal of the International Neural Network Society
Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sh...

Before and beyond the Wilson-Cowan equations.

Journal of neurophysiology
The Wilson-Cowan equations represent a landmark in the history of computational neuroscience. Along with the insights Wilson and Cowan offered for neuroscience, they crystallized an approach to modeling neural dynamics and brain function. Although th...

Simulating Small Neural Circuits with a Discrete Computational Model.

Biological cybernetics
Simulations of neural activity are commonly based on differential equations. We address the question what can be achieved with a simplified discrete model. The proposed model resembles artificial neural networks enriched with additional biologically ...

Nonlinear Spiking Neural P Systems.

International journal of neural systems
This paper proposes a new variant of spiking neural P systems (in short, SNP systems), nonlinear spiking neural P systems (in short, NSNP systems). In NSNP systems, the state of each neuron is denoted by a real number, and a real configuration vector...

Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation.

Neural networks : the official journal of the International Neural Network Society
Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like Markov random fields. Nevertheless, it remains unclear how probabilis...

Analysis of neurite length of hippocampal neurons cultured into 3D artificial network patterned microfluidic chips.

The International journal of neuroscience
The study aims to lay a foundational probe for the thorough application microfluidic chips in brain function research with microfluidic chips. Neuron slide culture is a common culture method , and the microfluidic chip with the artificial network pa...

Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington's disease mice.

BMC bioinformatics
BACKGROUND: MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional da...

Coding with transient trajectories in recurrent neural networks.

PLoS computational biology
Following a stimulus, the neural response typically strongly varies in time and across neurons before settling to a steady-state. While classical population coding theory disregards the temporal dimension, recent works have argued that trajectories o...