AIMC Topic: Connectome

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A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.

IEEE journal of biomedical and health informatics Sep 13, 2019
OBJECTIVE: We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network classification only very recently...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Electroencephalography Signal Processing, Computer-Assisted Schizophrenia Connectome Deep Learning Adolescent Child
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Decoding Brain States From fMRI Signals by Using Unsupervised Domain Adaptation.

IEEE journal of biomedical and health informatics Sep 11, 2019
With the development of deep learning in medical image analysis, decoding brain states from functional magnetic resonance imaging (fMRI) signals has made significant progress. Previous studies often utilized deep neural networks to automatically clas...
Humans Adult Brain Magnetic Resonance Imaging Task Performance and Analysis Young Adult Unsupervised Machine Learning Connectome Signal Processing, Computer-Assisted
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PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Psychophysiology Sep 10, 2019
Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although ...
Machine Learning Female Reproducibility of Results Adult Humans Cerebral Cortex Connectome Dissociative Disorders Depersonalization Male Middle Aged Stress Disorders, Post-Traumatic Magnetic Resonance Imaging
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A null model of the mouse whole-neocortex micro-connectome.

Nature communications Aug 29, 2019
In connectomics, the study of the network structure of connected neurons, great advances are being made on two different scales: that of macro- and meso-scale connectomics, studying the connectivity between populations of neurons, and that of micro-s...
Connectome Nerve Net Neocortex Mice Neural Networks, Computer Models, Statistical Brain Neurons Animals Models, Animal
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Connectomic Profiling Identifies Responders to Vagus Nerve Stimulation.

Annals of neurology Aug 27, 2019
OBJECTIVE: Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using struc...
Drug Resistant Epilepsy Magnetoencephalography Vagus Nerve Stimulation Patient Selection Humans Image Interpretation, Computer-Assisted Connectome Female Child Diffusion Tensor Imaging Male Treatment Outcome Adolescent Support Vector Machine Child, Preschool
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Characterizing functional regional homogeneity (ReHo) as a B-SNIP psychosis biomarker using traditional and machine learning approaches.

Schizophrenia research Aug 19, 2019
BACKGROUND: Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived using brain-based cognitive and electrophysiological markers. Here, we characterized a local functional-connectivity measure, regional homogeneity (ReH...
Adult Male Middle Aged Bipolar Disorder Support Vector Machine Magnetic Resonance Imaging Schizophrenia Humans Biomarkers Psychotic Disorders Brain Female Connectome
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Moving in time: Simulating how neural circuits enable rhythmic enactment of planned sequences.

Neural networks : the official journal of the International Neural Network Society Aug 19, 2019
Many complex actions are mentally pre-composed as plans that specify orderings of simpler actions. To be executed accurately, planned orderings must become active in working memory, and then enacted one-by-one until the sequence is complete. Examples...
Nerve Net Music Periodicity Humans Time Perception Magnetic Resonance Imaging Neural Networks, Computer Models, Neurological Brain Connectome
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Multi-view learning-based data proliferator for boosting classification using highly imbalanced classes.

Journal of neuroscience methods Aug 14, 2019
BACKGROUND: Multi-view data representation learning explores the relationship between the views and provides rich complementary information that can improve computer-aided diagnosis. Specifically, existing machine learning methods devised to automate...
Image Interpretation, Computer-Assisted Neuroimaging Connectome Machine Learning Autism Spectrum Disorder Humans Brain Magnetic Resonance Imaging
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MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.

Magnetic resonance in medicine Aug 2, 2019
PURPOSE: To develop a machine learning approach using convolutional neural network for reducing MRI Gibbs-ringing artifact.
Signal Processing, Computer-Assisted Diffusion Artifacts Neuroimaging Brain Brain Neoplasms Image Processing, Computer-Assisted Diffusion Magnetic Resonance Imaging Signal-To-Noise Ratio Connectome Phantoms, Imaging Knee Humans Neural Networks, Computer Machine Learning Algorithms
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A difference degree test for comparing brain networks.

Human brain mapping Jul 26, 2019
Recently, there has been a proliferation of methods investigating functional connectivity as a biomarker for mental disorders. Typical approaches include massive univariate testing at each edge or comparisons of network metrics to identify differing ...
Depressive Disorder, Major Nerve Net Humans Female Magnetic Resonance Imaging Neural Networks, Computer Connectome Adult Computer Simulation Male Middle Aged
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