AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Nerve Net

Showing 421 to 430 of 508 articles

Clear Filters

Supervised dictionary learning for inferring concurrent brain networks.

IEEE transactions on medical imaging
Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, G...

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

IEEE transactions on neural networks and learning systems
Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, ...

Regulation of Local Ambient GABA Levels via Transporter-Mediated GABA Import and Export for Subliminal Learning.

Neural computation
Perception of supraliminal stimuli might in general be reflected in bursts of action potentials (spikes), and their memory traces could be formed through spike-timing-dependent plasticity (STDP). Memory traces for subliminal stimuli might be formed i...

Surrogate population models for large-scale neural simulations.

Neural computation
Because different parts of the brain have rich interconnections, it is not possible to model small parts realistically in isolation. However, it is also impractical to simulate large neural systems in detail. This article outlines a new approach to m...

Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.

Nano letters
Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow ...

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

Journal of computational neuroscience
In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks w...

Spontaneous motion on two-dimensional continuous attractors.

Neural computation
Attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons. The firing rate profile, or the neuronal activity, is thought to carry information. Continuous attractor neural networks (CANNs) descri...

A closer look at the apparent correlation of structural and functional connectivity in excitable neural networks.

Scientific reports
The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is a central focus in brain network science. It is an open question, however, how strongly the SC-FC relationship depends on specific topolog...

Deep and shallow architecture of multilayer neural networks.

IEEE transactions on neural networks and learning systems
This paper focuses on the deep and shallow architecture of multilayer neural networks (MNNs). The demonstration of whether or not an MNN can be replaced by another MNN with fewer layers is equivalent to studying the topological conjugacy of its hidde...

On the role of astroglial syncytia in self-repairing spiking neural networks.

IEEE transactions on neural networks and learning systems
It has been shown that brain-like self-repair can arise from the interactions between neurons and astrocytes where endocannabinoids are synthesized and released from active neurons. This retrograde messenger feeds back to local synapses directly and ...