AIMC Topic: Brain Mapping

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Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: Machine learning applied to resting-state fMRI.

Cortex; a journal devoted to the study of the nervous system and behavior Nov 8, 2024
Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great poten...
Brain Female Male Child Humans Machine Learning Nerve Net Reading Dyslexia Magnetic Resonance Imaging Brain Mapping Attention Perception
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A simple but tough-to-beat baseline for fMRI time-series classification.

NeuroImage Nov 6, 2024
Current neuroimaging studies frequently use complex machine learning models to classify human fMRI data, distinguishing healthy and disordered brains, often to validate new methods or enhance prediction accuracy. Yet, where prediction accuracy is a c...
Humans Machine Learning Magnetic Resonance Imaging Brain Image Processing, Computer-Assisted Brain Mapping
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Modeling Functional Brain Networks for ADHD via Spatial Preservation-Based Neural Architecture Search.

IEEE journal of biomedical and health informatics Nov 6, 2024
Modeling functional brain networks (FBNs) for attention deficit hyperactivity disorder (ADHD) has sparked significant interest since the abnormal functional connectivity is discovered in certain functional magnetic resonance imaging (fMRI)-based brai...
Algorithms Attention Deficit Disorder with Hyperactivity Brain Male Adolescent Child Magnetic Resonance Imaging Brain Mapping Humans Neural Networks, Computer
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Deep learning-based whole-brain B -mapping at 7T.

Magnetic resonance in medicine Oct 27, 2024
PURPOSE: This study investigates the feasibility of using complex-valued neural networks (NNs) to estimate quantitative transmit magnetic RF field (B ) maps from multi-slice localizer scans with different slice orientations in the human head at 7T, a...
Algorithms Brain Female Image Processing, Computer-Assisted Reproducibility of Results Magnetic Resonance Imaging Brain Mapping Humans Healthy Volunteers Young Adult Neural Networks, Computer Adult Male Deep Learning
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Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning.

Neuroreport Sep 11, 2024
Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dyna...
Humans Machine Learning Brain Female Brain Mapping Middle Aged Young Adult Depressive Disorder, Major Adult Support Vector Machine Male Magnetic Resonance Imaging
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Prediction of anhedonia in patients with first-episode schizophrenia using a Wavelet-ALFF-based Support vector regression model.

Neuroscience Sep 5, 2024
Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely burdensome. Our study applied resting-state functional magnetic resonance imaging (fMRI)-based support vector regression (SVR) to predict anhedonia i...
Anhedonia Wavelet Analysis Schizophrenic Psychology Magnetic Resonance Imaging Brain Mapping Schizophrenia Humans Brain Female Young Adult Adult Male Support Vector Machine
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A Plug-In Graph Neural Network to Boost Temporal Sensitivity in fMRI Analysis.

IEEE journal of biomedical and health informatics Sep 5, 2024
Learning-based methods offer performance leaps over traditional methods in classification analysis of high-dimensional functional MRI (fMRI) data. In this domain, deep-learning models that analyze functional connectivity (FC) features among brain reg...
Brain Mapping Neural Networks, Computer Algorithms Brain Adult Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans
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SAD: semi-supervised automatic detection of BOLD activations in high temporal resolution fMRI data.

Magma (New York, N.Y.) Aug 29, 2024
OBJECTIVE: Despite the prevalent use of the general linear model (GLM) in fMRI data analysis, assuming a pre-defined hemodynamic response function (HRF) for all voxels can lead to reduced reliability and may distort the inferences derived from it. To...
Male Image Processing, Computer-Assisted Humans Hemodynamics Magnetic Resonance Imaging Brain ROC Curve Neural Networks, Computer Brain Mapping Female Algorithms Linear Models Reproducibility of Results Adult
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An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping.

Biomedical physics & engineering express Aug 19, 2024
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A key challenge in the quantitative analysis of dFDG-PET is characteriz...
Positron-Emission Tomography Fluorodeoxyglucose F18 Carotid Artery, Internal Deep Learning Image Processing, Computer-Assisted Brain Mapping Brain Humans Radiopharmaceuticals Female Neural Networks, Computer Male Algorithms
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Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.

Journal of affective disorders Aug 16, 2024
BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotempo...
Female Young Adult Adult Male Brain Mapping Middle Aged Humans Depressive Disorder, Major Machine Learning Case-Control Studies Brain Magnetic Resonance Imaging
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