Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Feb 3, 2020
We argue that natural language can be usefully described as quasi-compositional and we suggest that deep learning-based neural language models bear long-term promise to capture how language conveys meaning. We also note that a successful account of h...
Decision-making plays an essential role in the interpersonal interactions and cognitive processing of individuals. There has been increasing interest in being able to predict an individual's decision-making response (i.e., acceptance or rejection). W...
IEEE transactions on bio-medical engineering
Feb 1, 2020
OBJECTIVE: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, ...
Association between electroencephalography (EEG) and individually personal information is being explored by the scientific community. Though person identification using EEG is an attraction among researchers, the complexity of sensing limits using su...
Linear machine learning models "learn" a data transformation by being exposed to examples of input with the desired output, forming the basis for a variety of powerful techniques for analyzing neuroimaging data. However, their ability to learn the de...
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...
We introduce two Convolutional Neural Network (CNN) classifiers optimized for inferring brain states from magnetoencephalographic (MEG) measurements. Network design follows a generative model of the electromagnetic (EEG and MEG) brain signals allowin...
Syntactic and semantic information processing can interact selectively during language comprehension. However, the nature and extent of the interactions, in particular of semantic effects on syntax, remain to some extent elusive. We revisit an influe...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
This paper presents the design of a machine learning-based classifier for the differentiation between Schizophrenia patients and healthy controls using features extracted from electroencephalograph(EEG) signals based on event related potential(ERP). ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Deep learning techniques have recently been successful in the classification of brain evoked responses for multiple applications, including brain-machine interface. Single-trial detection in the electroencephalogram (EEG) of brain evoked responses, l...