AIMC Topic: Brain

Clear Filters Showing 2431 to 2440 of 4413 articles

Finding Distributed Needles in Neural Haystacks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The human cortex encodes information in complex networks that can be anatomically dispersed and variable in their microstructure across individuals. Using simulations with neural network models, we show that contemporary statistical methods for funct...

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...

Brain Contrast-Enhanced Ultrasound Evaluation of a Pediatric Swine Model.

Ultrasound quarterly
Brain injury remains a leading cause of morbidity and mortality in children. We evaluated the feasibility of using a pediatric swine model to develop contrast-enhanced ultrasound (CEUS)-based measures of brain perfusion for clinical application in va...

Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments.

Neuron
Humans possess an exceptional aptitude to efficiently make decisions from high-dimensional sensory observations. However, it is unknown how the brain compactly represents the current state of the environment to guide this process. The deep Q-network ...

DIKA-Nets: Domain-invariant knowledge-guided attention networks for brain skull stripping of early developing macaques.

NeuroImage
As non-human primates, macaques have a close phylogenetic relationship to human beings and have been proven to be a valuable and widely used animal model in human neuroscience research. Accurate skull stripping (aka. brain extraction) of brain magnet...

Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact.

Journal of neurotrauma
Head injury models are notoriously time consuming and resource demanding in simulations, which prevents routine application. Here, we extend a convolutional neural network (CNN) to instantly estimate element-wise distribution of peak maximum principa...

Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network.

Neurobiology of aging
Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learni...

Quantitative analysis of brain herniation from non-contrast CT images using deep learning.

Journal of neuroscience methods
BACKGROUND: Brain herniation is one of the fatal outcomes of increased intracranial pressure (ICP). It is caused due to the presence of hematoma or tumor mass in the brain. Ideal midline (iML) divides the healthy brain into two (right and left) nearl...

Deep multi-kernel auto-encoder network for clustering brain functional connectivity data.

Neural networks : the official journal of the International Neural Network Society
In this study, we propose a deep-learning network model called the deep multi-kernel auto-encoder clustering network (DMACN) for clustering functional connectivity data for brain diseases. This model is an end-to-end clustering algorithm that can lea...

Estimating myelin-water content from anatomical and diffusion images using spatially undersampled myelin-water imaging through machine learning.

NeuroImage
Myelin is vital for healthy neuronal development, and can therefore provide valuable information regarding neuronal maturation. Anatomical and diffusion weighted images (DWI) possess information related to the myelin content and the current study inv...