AIMC Topic: Connectome

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Reporting details of neuroimaging studies on individual traits prediction: A literature survey.

NeuroImage May 2, 2022
Using machine-learning tools to predict individual phenotypes from neuroimaging data is one of the most promising and hence dynamic fields in systems neuroscience. Here, we perform a literature survey of the rapidly work on phenotype prediction in he...
Connectome Phenotype Attention Machine Learning Algorithms Humans
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Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI.

IEEE transactions on medical imaging May 2, 2022
Susceptibility induced distortion is a major artifact that affects the diffusion MRI (dMRI) data analysis. In the Human Connectome Project (HCP), the state-of-the-art method adopted to correct this kind of distortion is to exploit the displacement fi...
Humans Brain Artifacts Deep Learning Image Processing, Computer-Assisted Connectome Diffusion Magnetic Resonance Imaging
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Predicting brain structural network using functional connectivity.

Medical image analysis Apr 22, 2022
Uncovering the non-trivial brain structure-function relationship is fundamentally important for revealing organizational principles of human brain. However, it is challenging to infer a reliable relationship between individual brain structure and fun...
Humans Neural Networks, Computer Brain Connectome Genetic Diseases, X-Linked Eye Diseases, Hereditary Magnetic Resonance Imaging Neuroimaging
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FOD-Net: A deep learning method for fiber orientation distribution angular super resolution.

Medical image analysis Apr 6, 2022
Mapping the human connectome using fiber-tracking permits the study of brain connectivity and yields new insights into neuroscience. However, reliable connectome reconstruction using diffusion magnetic resonance imaging (dMRI) data acquired by widely...
Deep Learning Connectome Humans Image Processing, Computer-Assisted Diffusion Magnetic Resonance Imaging Brain
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Brain Decoding Using fMRI Images for Multiple Subjects through Deep Learning.

Computational and mathematical methods in medicine Mar 1, 2022
Substantial information related to human cerebral conditions can be decoded through various noninvasive evaluating techniques like fMRI. Exploration of the neuronal activity of the human brain can divulge the thoughts of a person like what the subjec...
Deep Learning Functional Neuroimaging Computational Biology Magnetic Resonance Imaging Imaging, Three-Dimensional Databases, Factual Humans Brain Mapping Brain Neural Networks, Computer Connectome
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Introducing and applying Newtonian blurring: an augmented dataset of 126,000 human connectomes at braingraph.org.

Scientific reports Feb 23, 2022
Gaussian blurring is a well-established method for image data augmentation: it may generate a large set of images from a small set of pictures for training and testing purposes for Artificial Intelligence (AI) applications. When we apply AI for non-i...
Electronic Data Processing Connectome Artificial Intelligence Image Processing, Computer-Assisted Internet Datasets as Topic Diagnostic Imaging Humans
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Predicting individual traits from unperformed tasks.

NeuroImage Jan 18, 2022
Relating individual differences in cognitive traits to brain functional organization is a long-lasting challenge for the neuroscience community. Individual intelligence scores were previously predicted from whole-brain connectivity patterns, extracte...
Adult Humans Magnetic Resonance Imaging Machine Learning Task Performance and Analysis Individuality Brain Connectome
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A comparative study of machine learning methods for predicting the evolution of brain connectivity from a baseline timepoint.

Journal of neuroscience methods Jan 4, 2022
BACKGROUND: Predicting the evolution of the brain network, also called connectome, by foreseeing changes in the connectivity weights linking pairs of anatomical regions makes it possible to spot connectivity-related neurological disorders in earlier ...
Connectome Machine Learning Brain
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Robotically-induced hallucination triggers subtle changes in brain network transitions.

NeuroImage Dec 28, 2021
The perception that someone is nearby, although nobody can be seen or heard, is called presence hallucination (PH). Being a frequent hallucination in patients with Parkinson's disease, it has been argued to be indicative of a more severe and rapidly ...
Adolescent Magnetic Resonance Imaging Adult Humans Connectome Robotics Male Female Hallucinations
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Predicting individual task contrasts from resting-state functional connectivity using a surface-based convolutional network.

NeuroImage Dec 26, 2021
Task-based and resting-state represent the two most common experimental paradigms of functional neuroimaging. While resting-state offers a flexible and scalable approach for characterizing brain function, task-based techniques provide superior locali...
Reproducibility of Results Datasets as Topic Humans Rest Magnetic Resonance Imaging Connectome Emotions Neural Networks, Computer Brain Mapping
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