Brain-Switches for Asynchronous Brain−Computer Interfaces: A Systematic Review

A brain–computer interface (BCI) has been extensively studied to develop a novel communication system for disabled people using their brain activities. An asynchronous BCI system is more realistic and practical than a synchronous BCI system, in that, BCI commands can be generated whenever the user wants. However, the relatively low performance of an asynchronous BCI system is problematic because redundant BCI commands are required to correct false-positive operations. To significantly reduce the number of false-positive operations of an asynchronous BCI system, a two-step approach has been proposed using a brain-switch that first determines whether the user wants to use an asynchronous BCI system before the operation of the asynchronous BCI system. This study presents a systematic review of the state-of-the-art brain-switch techniques and future research directions. To this end, we reviewed brain-switch research articles published from 2000 to 2019 in terms of their (a) neuroimaging modality, (b) paradigm, (c) operation algorithm, and (d) performance

On the stimulus duty cycle in steady state visual evoked potential

Brain-computer interfaces (BCI) are useful devices that allow direct control of external devices using thoughts, i.e. brain's electrical activity. There are several BCI paradigms, of which steady state visual evoked potential (SSVEP) is the most commonly used due to its quick response and accuracy. SSVEP stimuli are typically generated by varying the luminance of a target for a set number of frames or display events. Conventionally, SSVEP based BCI paradigms use magnitude (amplitude) information from frequency domain but recently, SSVEP based BCI paradigms have begun to utilize phase information to discriminate between similar frequency targets. This paper will demonstrate that using a single frame to modulate a stimulus may lead to a bi-modal distribution of SSVEP as a consequence of a user attending both transition edges. This incoherence, while of less importance in traditional magnitude domain SSVEP BCIs becomes critical when phase is taken into account. An alternative modulation technique incorporating a 50% duty cycle is also a popular method for generating SSVEP stimuli but has a unimodal distribution due to user's forced attention to a single transition edge. This paper demonstrates that utilizing the second method results in significantly enhanced performance in information transfer rate in a phase discrimination SSVEP based BCI

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery

BCI-Based Navigation in Virtual and Real Environments

A Brain-Computer Interface (BCI) is a system that enables people to control an external device with their brain activity, without the need of any muscular activity. Researchers in the BCI field aim to develop applications to improve the quality of life of severely disabled patients, for whom a BCI can be a useful channel for interaction with their environment. Some of these systems are intended to control a mobile device (e. g. a wheelchair). Virtual Reality is a powerful tool that can provide the subjects with an opportunity to train and to test different applications in a safe environment. This technical review will focus on systems aimed at navigation, both in virtual and real environments.This work was partially supported by the Innovation, Science and Enterprise Council of the Junta de Andalucía (Spain), project P07-TIC-03310, the Spanish Ministry of Science and Innovation, project TEC 2011-26395 and by the European fund ERDF