IEEE transactions on neural networks and learning systems
Jul 21, 2014
An extreme learning machine (ELM) is a feedforward neural network (FNN) like learning system whose connections with output neurons are adjustable, while the connections with and within hidden neurons are randomly fixed. Numerous applications have dem...
Neural networks : the official journal of the International Neural Network Society
Jun 9, 2014
Although it is very important to scrutinize recurrent structures of neural networks for elucidating brain functions, conventional methods often have difficulty in characterizing global loops within a network systematically. Here we applied the Hodge-...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Synaptic increase is a common phenomenon in the brain of autism spectrum disorder (ASD). However, the impact of increased synapses on the neurophysiological activity of ASD remains unclear. To address this, we propose a large-scale cortical network m...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
A single neuron receives an extensive array of synaptic inputs through its dendrites, raising the fundamental question of how these inputs undergo integration and summation, culminating in the initiation of spikes in the soma. Experimental and comput...
International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Jul 1, 2025
Poor sleep quality has been found to be associated with functional abnormalities in a few regions of the human brain. However, the brain is a dynamic network cooperation system, and it is necessary to study the relationship between sleep quality and ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Artificial neural networks (ANNs) were originally modeled after their biological counterparts, but have since conceptually diverged in many ways. The resulting network architectures are not well understood, and furthermore, we lack the quantitative t...
Tension-type headache (TTH) is a primary headache with the highest prevalence. Previous studies have revealed the local brain abnormalities of TTH patients. However, little is known about its brain connectivity disruption. Based on rs-fMRI data from ...
Neural networks are responsible for processing sensory stimuli and driving the synaptic activity required for brain function and behavior. This computational capacity is expensive and requires a steady supply of energy and building blocks to operate....
A mean field method for pulse-coupled oscillators with delays used a self-connected oscillator to represent a synchronous cluster of - 1 oscillators and a single oscillator assumed to be perturbed from the cluster. A periodic train of biexponential ...
IEEE journal of biomedical and health informatics
Jun 1, 2025
Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neurodegenerative disorders, such as Alzheimer's disease. In this study, we developed a Fully Hyperbolic...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.