AIMC Topic: Electroencephalography
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Mapping dynamical properties of cortical microcircuits using robotized TMS and EEG: Towards functional cytoarchitectonics.
NeuroImage
May 3, 2016
Brain dynamics at rest depend on the large-scale interactions between oscillating cortical microcircuits arranged into macrocolumns. Cytoarchitectonic studies have shown that the structure of those microcircuits differs between cortical regions, but ...
Extensions to a manifold learning framework for time-series analysis on dynamic manifolds in bioelectric signals.
Physical review. E
Apr 29, 2016
This paper addresses the challenge of extracting meaningful information from measured bioelectric signals generated by complex, large scale physiological systems such as the brain or the heart. We focus on a combination of the well-known Laplacian ei...
Using ELM-based weighted probabilistic model in the classification of synchronous EEG BCI.
Medical & biological engineering & computing
Apr 21, 2016
Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing interest from various research fields recently. A new method that combines ELM with probabilistic model ...
Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 12, 2016
OBJECTIVES: This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier...
Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.
International journal of neural systems
Apr 11, 2016
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification a...
An EEG-Based Fuzzy Probability Model for Early Diagnosis of Alzheimer's Disease.
Journal of medical systems
Apr 8, 2016
Alzheimer's disease is a degenerative brain disease that results in cardinal memory deterioration and significant cognitive impairments. The early treatment of Alzheimer's disease can significantly reduce deterioration. Early diagnosis is difficult, ...
Pattern recognition for electroencephalographic signals based on continuous neural networks.
Neural networks : the official journal of the International Neural Network Society
Apr 6, 2016
This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method fo...
Optimal training dataset composition for SVM-based, age-independent, automated epileptic seizure detection.
Medical & biological engineering & computing
Mar 31, 2016
Automated seizure detection is a valuable asset to health professionals, which makes adequate treatment possible in order to minimize brain damage. Most research focuses on two separate aspects of automated seizure detection: EEG feature computation ...
Classifying Response Correctness across Different Task Sets: A Machine Learning Approach.
PloS one
Mar 31, 2016
Erroneous behavior usually elicits a distinct pattern in neural waveforms. In particular, inspection of the concurrent recorded electroencephalograms (EEG) typically reveals a negative potential at fronto-central electrodes shortly following a respon...
Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 18, 2016
Electroencephalography (EEG) headsets are the most commonly used sensing devices for brain-computer interface. In real-world applications, there are advantages to extrapolating data from one user session to another. However, these advantages are limi...
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