AIMC Topic: Brain Mapping
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Multivariate classification of drug-naive obsessive-compulsive disorder patients and healthy controls by applying an SVM to resting-state functional MRI data.
BMC psychiatry
Jul 5, 2019
BACKGROUND: Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed intrinsic regional activity alterations in obsessive-compulsive disorder (OCD), but those results were based on group analyses, which limits thei...
Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.
Magnetic resonance in medicine
Jul 4, 2019
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
Gray Matter
White Matter
Cerebrovascular Circulation
Normal Distribution
Least-Squares Analysis
Positron-Emission Tomography
Healthy Volunteers
Adult
Male
Neural Networks, Computer
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Humans
Brain
Brain Mapping
Computer Simulation
Oxygen
Female
Oxygen Consumption
Bypassing the volume conduction effect by multilayer neural network for effective connectivity estimation.
Medical & biological engineering & computing
Jul 4, 2019
Differentiation of real interactions between different brain regions from spurious ones has been a challenge in neuroimaging researches. While using electroencephalographic data, those spurious interactions are mostly caused by the volume conduction ...
Brain Tumour Segmentation Using Convolutional Neural Network with Tensor Flow.
Asian Pacific journal of cancer prevention : APJCP
Jul 1, 2019
Introduction: The determination of tumour extent is a major challenging task in brain tumour planning and quantitative evaluation. Magnetic Resonance Imaging (MRI) is one of the non-invasive technique has emanated as a front- line diagnostic tool for...
Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain.
Journal of visualized experiments : JoVE
Jul 1, 2019
Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries unique challenges in children. Similarly, transcranial direct current stimulation (tDCS) can improve...
A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.
Human brain mapping
Jun 22, 2019
Imaging studies have characterized functional and structural brain abnormalities in adults after premature birth, but these investigations have mostly used univariate methods that do not account for hypothesized interdependencies between brain region...
Real-time estimation of electric fields induced by transcranial magnetic stimulation with deep neural networks.
Brain stimulation
Jun 17, 2019
BACKGROUND: Transcranial magnetic stimulation (TMS) plays an important role in treatment of mental and neurological illnesses, and neurosurgery. However, it is difficult to target specific brain regions accurately because the complex anatomy of the b...
The Ventral Visual Pathway Represents Animal Appearance over Animacy, Unlike Human Behavior and Deep Neural Networks.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jun 13, 2019
Recent studies showed agreement between how the human brain and neural networks represent objects, suggesting that we might start to understand the underlying computations. However, we know that the human brain is prone to biases at many perceptual a...
Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks.
Neuroscience
Jun 8, 2019
Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, inte...
Machine learning in resting-state fMRI analysis.
Magnetic resonance imaging
Jun 5, 2019
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. W...
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