AIMC Topic: Brain Mapping

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Convolutional neural networks for decoding of covert attention focus and saliency maps for EEG feature visualization.

Journal of neural engineering Oct 23, 2019
OBJECTIVE: Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal decoding for brain-computer interfaces (BCI). Arti...
Humans Brain Mapping Electroencephalography Attention Neural Networks, Computer Female Male
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Regression-based machine-learning approaches to predict task activation using resting-state fMRI.

Human brain mapping Oct 22, 2019
Resting-state fMRI has shown the ability to predict task activation on an individual basis by using a general linear model (GLM) to map resting-state network features to activation z-scores. The question remains whether the relatively simplistic GLM ...
Humans Machine Learning Regression Analysis Connectome Brain Nerve Net Brain Mapping Adult Task Performance and Analysis Magnetic Resonance Imaging
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Granger causality analysis in combination with directed network measures for classification of MS patients and healthy controls using task-related fMRI.

Computers in biology and medicine Oct 13, 2019
Several studies have already assessed brain network variations in multiple sclerosis (MS) patients and healthy controls (HCs). The underlying neural system's functioning is apparently too complicated, however. Therefore, the neural time series' analy...
Brain Mapping Multiple Sclerosis Nerve Net Support Vector Machine Magnetic Resonance Imaging Models, Neurological Humans Brain Female Adult Male
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A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime.

Cortex; a journal devoted to the study of the nervous system and behavior Oct 4, 2019
Neurological patients with apraxia of pantomime provide us with a unique opportunity to study the neural correlates of higher-order motor function. Previous studies using lesion-behaviour mapping methods led to inconsistent anatomical results, report...
Stroke Psychomotor Performance Functional Laterality Male Middle Aged Brain Mapping Apraxias Nerve Net Parietal Lobe Imitative Behavior Humans Machine Learning Female Aged Aged, 80 and over Adult
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Transfer learning of deep neural network representations for fMRI decoding.

Journal of neuroscience methods Oct 1, 2019
BACKGROUND: Deep neural networks have revolutionised machine learning, with unparalleled performance in object classification. However, in brain imaging (e.g., fMRI), the direct application of Convolutional Neural Networks (CNN) to decoding subject s...
Visual Perception Transfer, Psychology Humans Image Processing, Computer-Assisted Brain Magnetic Resonance Imaging Adult Brain Mapping Deep Learning
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NeuroSLAM: a brain-inspired SLAM system for 3D environments.

Biological cybernetics Sep 30, 2019
Roboticists have long drawn inspiration from nature to develop navigation and simultaneous localization and mapping (SLAM) systems such as RatSLAM. Animals such as birds and bats possess superlative navigation capabilities, robustly navigating over l...
Models, Neurological Humans Brain Mapping Neural Networks, Computer Spatial Navigation Robotics Brain Computer Simulation Animals
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Post-hoc modification of linear models: Combining machine learning with domain information to make solid inferences from noisy data.

NeuroImage Sep 26, 2019
Linear machine learning models "learn" a data transformation by being exposed to examples of input with the desired output, forming the basis for a variety of powerful techniques for analyzing neuroimaging data. However, their ability to learn the de...
Linear Models Neuroimaging Evoked Potentials Humans Machine Learning Brain Mapping Brain Data Interpretation, Statistical Adult Electroencephalography Models, Theoretical
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Combined tract segmentation and orientation mapping for bundle-specific tractography.

Medical image analysis Sep 12, 2019
While the major white matter tracts are of great interest to numerous studies in neuroscience and medicine, their manual dissection in larger cohorts from diffusion MRI tractograms is time-consuming, requires expert knowledge and is hard to reproduce...
Brain Mapping Datasets as Topic White Matter Neural Pathways Phantoms, Imaging Diffusion Tensor Imaging Humans Machine Learning Image Processing, Computer-Assisted
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Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning.

IEEE transactions on neural networks and learning systems Sep 5, 2019
Accurate segmentation of anatomical brain structures is crucial for many neuroimaging applications, e.g., early brain development studies and the study of imaging biomarkers of neurodegenerative diseases. Although multi-atlas segmentation (MAS) has a...
Image Interpretation, Computer-Assisted Brain Humans Deep Learning Neural Networks, Computer Brain Mapping Databases, Factual
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Removing segmentation inconsistencies with semi-supervised non-adjacency constraint.

Medical image analysis Aug 31, 2019
The advent of deep learning has pushed medical image analysis to new levels, rapidly replacing more traditional machine learning and computer vision pipelines. However segmenting and labelling anatomical regions remains challenging owing to appearanc...
Supervised Machine Learning Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Brain Mapping Deep Learning
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