AIMC Topic: Brain

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Spine dynamics in the brain, mental disorders and artificial neural networks.

Nature reviews. Neuroscience
In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability ...

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets.

PLoS computational biology
Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular popul...

Geometric deep learning on brain shape predicts sex and age.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about t...

Deep unregistered multi-contrast MRI reconstruction.

Magnetic resonance imaging
Multiple magnetic resonance images of different contrasts are normally acquired for clinical diagnosis. Recently, research has shown that the previously acquired multi-contrast (MC) images of the same patient can be used as anatomical prior to accele...

Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast.

NeuroImage
Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently have contrast constraints as well-typically requiring T1-weighted images ...

Representational Content of Oscillatory Brain Activity during Object Recognition: Contrasting Cortical and Deep Neural Network Hierarchies.

eNeuro
Numerous theories propose a key role for brain oscillations in visual perception. Most of these theories postulate that sensory information is encoded in specific oscillatory components (e.g., power or phase) of specific frequency bands. These theori...

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Nature communications
Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here,...

Delayed brain development of Rolandic epilepsy profiled by deep learning-based neuroanatomic imaging.

European radiology
OBJECTIVES: Although Rolandic epilepsy (RE) has been regarded as a brain developmental disorder, neuroimaging studies have not yet ascertained whether RE has brain developmental delay. This study employed deep learning-based neuroanatomic biomarker t...

Integrative learning for population of dynamic networks with covariates.

NeuroImage
Although there is a rapidly growing literature on dynamic connectivity methods, the primary focus has been on separate network estimation for each individual, which fails to leverage common patterns of information. We propose novel graph-theoretic ap...

High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network.

PloS one
Magnetic resonance electrical properties tomography (MREPT) aims to visualize the internal high-frequency conductivity distribution at Larmor frequency using the B1 transceive phase data. From the magnetic field perturbation by the electrical field a...