AIMC Topic: Brain

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Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease.

NeuroImage. Clinical
BACKGROUND: In a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patter...

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Journal of psychiatric research
Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigeneti...

Semi-supervised deep learning of brain tissue segmentation.

Neural networks : the official journal of the International Neural Network Society
Brain image segmentation is of great importance not only for clinical use but also for neuroscience research. Recent developments in deep neural networks (DNNs) have led to the application of DNNs to brain image segmentation, which required extensive...

DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal.

Journal of neuroscience methods
BACKGROUND: Electroencephalography (EEG) monitors brain activity during sleep and is used to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so-called sleep stages, which are assigned by experts to every 30s windo...

Common spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface.

Journal of neuroscience methods
BACKGROUND: Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR)....

Adolescent binge drinking disrupts normal trajectories of brain functional organization and personality maturation.

NeuroImage. Clinical
Adolescent binge drinking has been associated with higher risks for the development of many health problems throughout the lifespan. Adolescents undergo multiple changes that involve the co-development processes of brain, personality and behavior; th...

DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping.

NeuroImage
Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI) phase measurements and has gained broad interest because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium in ...

Information Theoretic Feature Transformation Learning for Brain Interfaces.

IEEE transactions on bio-medical engineering
OBJECTIVE: A variety of pattern analysis techniques for model training in brain interfaces exploit neural feature dimensionality reduction based on feature ranking and selection heuristics. In the light of broad evidence demonstrating the potential s...

Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neural representations span various spatiotemporal scales of brain activity, from the spiking activity of single neurons to field activity measuring large-scale networks. The simultaneous analyses of spikes and fields to uncover causal interactions i...

Multisource Transfer Learning for Cross-Subject EEG Emotion Recognition.

IEEE transactions on cybernetics
Electroencephalogram (EEG) has been widely used in emotion recognition due to its high temporal resolution and reliability. Since the individual differences of EEG are large, the emotion recognition models could not be shared across persons, and we n...