AIMC Topic: Brain

Clear Filters Showing 2311 to 2320 of 4413 articles

Intranasal vasopressin modulates resting state brain activity across multiple neural systems: Evidence from a brain imaging machine learning study.

Neuropharmacology
Arginine vasopressin (AVP), a neuropeptide with widespread receptors in brain regions important for socioemotional processing, is critical in regulating various mammalian social behavior and emotion. Although a growing body of task-based brain imagin...

Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data.

Scientific reports
A key challenge to gaining insight into complex systems is inferring nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only s...

A deep learning approach to identifying immunogold particles in electron microscopy images.

Scientific reports
Electron microscopy (EM) enables high-resolution visualization of protein distributions in biological tissues. For detection, gold nanoparticles are typically used as an electron-dense marker for immunohistochemically labeled proteins. Manual annotat...

Deep learning for robust detection of interictal epileptiform discharges.

Journal of neural engineering
Automatic detection of interictal epileptiform discharges (IEDs, short as 'spikes') from an epileptic brain can help predict seizure recurrence and support the diagnosis of epilepsy. Developing fast, reliable and robust detection methods for IEDs bas...

Volume Reduction Techniques for the Classification of Independent Components of rs-fMRI Data: a Study with Convolutional Neural Networks.

Neuroinformatics
In the last decade, neurosciences have had an increasing interest in resting state functional magnetic resonance imaging (rs-fMRI) as a result of its advantages, such as high spatial resolution, compared to other brain exploration techniques. To impr...

Machine learning-based decision tree classifier for the diagnosis of progressive supranuclear palsy and corticobasal degeneration.

Neuropathology and applied neurobiology
AIMS: This study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning-based decision tree classifier.

Analysis of the human connectome data supports the notion of a "Common Model of Cognition" for human and human-like intelligence across domains.

NeuroImage
The Common Model of Cognition (CMC) is a recently proposed, consensus architecture intended to capture decades of progress in cognitive science on modeling human and human-like intelligence. Because of the broad agreement around it and preliminary ma...

Clinical validation of a commercially available deep learning software for synthetic CT generation for brain.

Radiation oncology (London, England)
BACKGROUND: Most studies on synthetic computed tomography (sCT) generation for brain rely on in-house developed methods. They often focus on performance rather than clinical feasibility. Therefore, the aim of this work was to validate sCT images gene...

Deep learning-enhanced T mapping with spatial-temporal and physical constraint.

Magnetic resonance in medicine
PURPOSE: To propose a reconstruction framework to generate accurate T maps for a fast MR T mapping sequence.