AIMC Topic: Brain Mapping

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Decoding and mapping task states of the human brain via deep learning.

Human brain mapping Dec 9, 2019
Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requir...
Memory, Short-Term Psychomotor Performance Connectome Transfer, Psychology Image Processing, Computer-Assisted Humans Support Vector Machine Databases, Factual Magnetic Resonance Imaging Adult Brain Mapping Male Deep Learning Brain Reproducibility of Results Gambling
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Robot-assisted versus manual navigated stereoelectroencephalography in adult medically-refractory epilepsy patients.

Epilepsy research Dec 9, 2019
OBJECTIVE: Stereoelectroencephalography (SEEG) has experienced a recent growth in adoption for epileptogenic zone (EZ) localization. Advances in robotics have the potential to improve the efficiency and safety of this intracranial seizure monitoring ...
Humans Retrospective Studies Female Stereotaxic Techniques Brain Mapping Robotics Drug Resistant Epilepsy Adult Electroencephalography Male Neurosurgical Procedures Middle Aged Treatment Outcome
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Utilizing wavelet deep learning network to classify different states of task-fMRI for verifying activation regions.

The International journal of neuroscience Dec 4, 2019
We propose a convolutional neural network (CNN) based on wavelet for verifying the activation regions decided with statistical analysis. Because the functional magnetic resonance imaging (fMRI) data contains lots of noises, it is difficult to get th...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Mapping Wavelet Analysis Visual Perception Humans Brain Deep Learning
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Integrating functional connectivity and MVPA through a multiple constraint network analysis.

NeuroImage Nov 30, 2019
Traditional general linear model-based brain mapping efforts using functional neuroimaging are complemented by more recent multivariate pattern analyses (MVPA) that apply machine learning techniques to identify the cognitive states associated with re...
Recognition, Psychology Models, Theoretical Young Adult Magnetic Resonance Imaging Adult Perception Brain Mapping Male Concept Formation Humans Semantics Cerebral Cortex Adolescent Imagination Neural Networks, Computer Connectome Female
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Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 27, 2019
We present the application of limited one-time sampling irregularity map (LOTS-IM): a fully automatic unsupervised approach to extract brain tissue irregularities in magnetic resonance images (MRI), for quantitatively assessing white matter hyperinte...
White Matter Unsupervised Machine Learning Sensitivity and Specificity Humans Brain Mapping Disease Progression Multiple Sclerosis Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Magnetic Resonance Imaging
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A robust deep neural network for denoising task-based fMRI data: An application to working memory and episodic memory.

Medical image analysis Nov 26, 2019
In this study, a deep neural network (DNN) is proposed to reduce the noise in task-based fMRI data without explicitly modeling noise. The DNN artificial neural network consists of one temporal convolutional layer, one long short-term memory (LSTM) la...
Humans Neural Networks, Computer Aged Brain Mapping Image Enhancement Task Performance and Analysis Image Processing, Computer-Assisted Memory, Episodic Magnetic Resonance Imaging
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.

Scientific reports Nov 22, 2019
Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to class...
Epilepsy Memory, Short-Term Datasets as Topic Task Performance and Analysis Cognition Unsupervised Machine Learning Brain Mapping Electroencephalography Electrodes, Implanted Electrophysiological Phenomena Evoked Potentials Verbal Behavior Electrocorticography Biomedical Engineering Humans Algorithms Brain Retrospective Studies Sensitivity and Specificity
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QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field.

NeuroImage Nov 21, 2019
Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects th...
Magnetic Resonance Imaging Brain Mapping Artifacts Brain Female Male Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.

Computational and mathematical methods in medicine Nov 4, 2019
In recent years, functional brain network topological features have been widely used as classification features. Previous studies have found that network node scale differences caused by different network parcellation definitions significantly affect...
Nerve Net Adult Cluster Analysis Brain Brain Mapping Diagnosis, Computer-Assisted Male Humans Female Medical Informatics Middle Aged Adolescent Reproducibility of Results Neural Networks, Computer Pattern Recognition, Automated Depressive Disorder, Major Support Vector Machine Young Adult Machine Learning Magnetic Resonance Imaging Algorithms
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Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates.

Molecular psychiatry Oct 29, 2019
In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted "biosignal" approach h...
Humans Machine Learning Female Magnetic Resonance Imaging Young Adult Fear Brain Mapping Adult Amygdala Male Prefrontal Cortex
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