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Decoding attention control and selection in visual spatial attention.

Human brain mapping
Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by appl...

Can robotic gait rehabilitation plus Virtual Reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient's recovery and autonomy. The aim of our study is to evaluate the effects of robotic neurorehabilitation using Lokom...

Auditory attention tracking states in a cocktail party environment can be decoded by deep convolutional neural networks.

Journal of neural engineering
OBJECTIVE: A deep convolutional neural network (CNN) is a method for deep learning (DL). It has a powerful ability to automatically extract features and is widely used in classification tasks with scalp electroencephalogram (EEG) signals. However, th...

Single-Trial EEG Responses Classified Using Latency Features.

International journal of neural systems
Covert attention has been repeatedly shown to impact on EEG responses after single and repeated practice sessions. Machine learning techniques are increasingly adopted to classify single-trial EEG responses thereby primarily relying on amplitude-base...

Bio-semantic relation extraction with attention-based external knowledge reinforcement.

BMC bioinformatics
BACKGROUND: Semantic resources such as knowledge bases contains high-quality-structured knowledge and therefore require significant effort from domain experts. Using the resources to reinforce the information retrieval from the unstructured text may ...

Extracting drug-drug interactions from texts with BioBERT and multiple entity-aware attentions.

Journal of biomedical informatics
Drug-drug interactions (DDIs) extraction is one of the important tasks in the field of biomedical relation extraction, which plays an important role in the field of pharmacovigilance. Previous neural network based models have achieved good performanc...

Sequential vessel segmentation via deep channel attention network.

Neural networks : the official journal of the International Neural Network Society
Accurately segmenting contrast-filled vessels from X-ray coronary angiography (XCA) image sequence is an essential step for the diagnosis and therapy of coronary artery disease. However, developing automatic vessel segmentation is particularly challe...

Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.

Medical image analysis
In this paper, we present a new Deep Convolutional Neural Networks (CNNs) dedicated to fully automatic segmentation of Glioblastoma brain tumors with high- and low-grade. The proposed CNNs model is inspired by the Occipito-Temporal pathway which has ...

Neural memory plasticity for medical anomaly detection.

Neural networks : the official journal of the International Neural Network Society
In the domain of machine learning, Neural Memory Networks (NMNs) have recently achieved impressive results in a variety of application areas including visual question answering, trajectory prediction, object tracking, and language modelling. However,...

Academic Emotion Classification and Recognition Method for Large-scale Online Learning Environment-Based on A-CNN and LSTM-ATT Deep Learning Pipeline Method.

International journal of environmental research and public health
Subjective well-being is a comprehensive psychological indicator for measuring quality of life. Studies have found that emotional measurement methods and measurement accuracy are important for well-being-related research. Academic emotion is an emoti...