AIMC Topic: Brain Mapping
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Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps.
The Journal of comparative neurology
Jan 17, 2018
The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature table...
Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.
Human brain mapping
Jan 16, 2018
Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI pe...
Random ensemble learning for EEG classification.
Artificial intelligence in medicine
Jan 3, 2018
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rap...
Wavelet Analysis
Brain Waves
Cloud Computing
Electrocorticography
Brain
Signal Processing, Computer-Assisted
Humans
Reproducibility of Results
Neural Networks, Computer
Automation
Time Factors
False Negative Reactions
Support Vector Machine
Brain Mapping
False Positive Reactions
Predictive Value of Tests
Electroencephalography
Seizures
Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.
International journal of neural systems
Dec 28, 2017
The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the ...
Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.
Computational and mathematical methods in medicine
Dec 14, 2017
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional me...
Learning non-linear patch embeddings with neural networks for label fusion.
Medical image analysis
Dec 2, 2017
In brain structural segmentation, multi-atlas strategies are increasingly being used over single-atlas strategies because of their ability to fit a wider anatomical variability. Patch-based label fusion (PBLF) is a type of such multi-atlas approaches...
Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Nov 23, 2017
Computerized healthcare has undergone rapid development thanks to the advances in medical imaging and machine learning technologies. Especially, recent progress on deep learning opens a new era for multimedia based clinical decision support. In this ...
Whole brain white matter connectivity analysis using machine learning: An application to autism.
NeuroImage
Oct 25, 2017
In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusio...
From provocation to aggression: the neural network.
BMC neuroscience
Oct 17, 2017
BACKGROUND: In-vivo observations of neural processes during human aggressive behavior are difficult to obtain, limiting the number of studies in this area. To address this gap, the present study implemented a social reactive aggression paradigm in 29...
Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.
Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
Oct 2, 2017
OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flo...
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