The article considers modern technologies for reading signals from the human brain and nervous system selects optimal technology to improve efficiency of adult learning with help a neurocomputer interface. Existing brain-computer interfaces (BCI) can be divided into invasive non-invasive. first, BCIs, are neuroimplants in certain parts that work on basis electrocorticography (ECOG) or intracran...

We develop and test three deep-learning recurrent convolutional architectures for learning to recognize single trial EEG event related potentials for P300 brain-computer interfaces (BCI)s. One advantage of the neural network solution is that it provides a natural way to share a lower-level feature space between subjects while adapting the classifier that works on that feature space. We compare ...

The application of brain-computer interfaces (BCI) shows promising results in stroke rehabilitation, but the underlying neural substrates and processes of successful BCI-based neurorehabilitation remain unclear. The goal of our present work was to identify the brain areas associated with successful visuomotor integration and motor learning (VMIL), and investigate their connection with successfu...

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive revie...

Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive techni...

Brain-Computer Interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by the brain. Since the characteristics of such direct brain-to-computer interaction are limited in several aspects, one major challenge in BCI research is intelligent front-end design. Here we present the mental text entry application ...

Brain–Computer Interfaces (BCIs) provide a nonmuscular channel to communicate with the outside world by means of brain activity. A crucial step for efficient BCI operation is brain signal processing methods. Most BCI systems for humans use scalp recorded electroencephalographic activity, whereas Electrocorticography (ECoG) is a minimally-invasive alternative to electroencephalogram (EEG), provi...

As an emerging technology, brain-computer interfaces (BCIs) bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM) algorithm for brain-computer interface (BCI) systems, aiming at reducing the time-consuming training process. In this algor...

Accessibility, adaptability, and transparency of Brain-Computer Interface (BCI) tools the data they collect will likely impact how we collectively navigate a new digital age. This discussion reviews some diverse transdisciplinary applications BCI technology draws speculative inferences about ways in which tools, combined with machine learning (ML) algorithms may shape future. BCIs come substant...

Brain Computer Interfaces are specialized systems that allows users to control computer applications using their brain waves. Initially, BCI were mostly used in medical field. But after some research and thanks consumer-grade electroencephalography (EEG) devices, many opportunities opened outside of the One particular area is gaining more evidence due arrival devices games, as it user-friendly ...