AIMC Topic: Brain Mapping
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Graph-theory based degree centrality combined with machine learning algorithms can predict response to treatment with antiepileptic medications in children with epilepsy.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jul 26, 2021
BACKGROUND AND PURPOSE: The purpose of the current study is to detect changes of graph-theory-based degree centrality (DC) and their relationship with the clinical treatment effects of anti-epileptic drugs (AEDs) for patients with childhood absence e...
Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning.
Zeitschrift fur medizinische Physik
Jul 24, 2021
INTRODUCTION: Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM) region only. Reducing the spatial coverage to the DGM vicinity can sub...
Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction.
NeuroImage
Jul 16, 2021
Quantitative susceptibility mapping (QSM) and R2* mapping are MRI post-processing methods that quantify tissue magnetic susceptibility and transverse relaxation rate distributions. However, QSM and R2* acquisitions are relatively slow, even with para...
The neural representation of abstract words may arise through grounding word meaning in language itself.
Human brain mapping
Jul 15, 2021
In order to describe how humans represent meaning in the brain, one must be able to account for not just concrete words but, critically, also abstract words, which lack a physical referent. Hebbian formalism and optimization are basic principles of b...
Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine.
Brain and behavior
Jul 15, 2021
OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core...
MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.
NeuroImage
Jul 8, 2021
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility dis...
Lesion probability mapping in MS patients using a regression network on MR fingerprinting.
BMC medical imaging
Jul 8, 2021
BACKGROUND: To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula: see text], [Formula: see text], NAWM, and GM- proba...
Untangling the Animacy Organization of Occipitotemporal Cortex.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 6, 2021
Some of the most impressive functional specializations in the human brain are found in the occipitotemporal cortex (OTC), where several areas exhibit selectivity for a small number of visual categories, such as faces and bodies, and spatially cluster...
Convolutional neural networks for cytoarchitectonic brain mapping at large scale.
NeuroImage
Jul 2, 2021
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the microstructural organization of the brain, as regional di...
Behavioral correlates of cortical semantic representations modeled by word vectors.
PLoS computational biology
Jun 23, 2021
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...
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