Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains.

Complex-Valued Neural Networks: Advances and Applications

Background 
Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has become one of the most promising modalities for a practical noninvasive BCI system. Owing to both the limitation of refresh rate of liquid crystal display (LCD) or cathode ray tube (CRT) monitor, and the specific physiological response property that only a very small number of stimuli at certain frequencies could evoke strong SSVEPs, the available frequencies for SSVEP stimuli are limited. Therefore, it may not be enough to code multiple targets with the traditional frequencies coding protocols, which poses a big challenge for the design of a practical SSVEP-based BCI. This study aimed to provide an innovative coding method to tackle this problem.


Methodology/Principal Findings 
In this study, we present a novel protocol termed multiple frequencies sequential coding (MFSC) for SSVEP-based BCI. In MFSC, multiple frequencies are sequentially used in each cycle to code the targets. To fulfill the sequential coding, each cycle is divided into several coding epochs, and during each epoch, certain frequency is used. Obviously, different frequencies or the same frequency can be presented in the coding epochs, and the different epoch sequence corresponds to the different targets. To show the feasibility of MFSC, we used two frequencies to realize four targets and carried on an offline experiment. The current study shows that: 1) MFSC is feasible and efficient; 2) the performance of SSVEP-based BCI based on MFSC can be comparable to some existed systems.


Conclusions/Significance 
The proposed protocol could potentially implement much more targets with the limited available frequencies compared with the traditional frequencies coding protocol. The efficiency of the new protocol was confirmed by real data experiment. We propose that the SSVEP-based BCI under MFSC might be a promising choice in the future.

/pdf/multiple-frequencies-sequential-coding-for-ssvep-based-brain-rjmg7b80m9.pdf

Multiple Frequencies Sequential Coding for SSVEP-Based Brain-Computer Interface

Gamma Entrainment: Impact on Neurocircuits, Glia, and Therapeutic Opportunities

Brain-computer interfaces (BCIs) promise to provide a novel access channel for assistive technologies, including augmentative and alternative communication (AAC) systems, to people with severe speech and physical impairments (SSPI). Research on the subject has been accelerating significantly in the last decade and the research community took great strides toward making BCI-AAC a practical reality to individuals with SSPI. Nevertheless, the end goal has still not been reached and there is much work to be done to produce real-world-worthy systems that can be comfortably, conveniently, and reliably used by individuals with SSPI with help from their families and care givers who will need to maintain, setup, and debug the systems at home. This paper reviews reports in the BCI field that aim at AAC as the application domain with a consideration on both technical and clinical aspects.

/pdf/noninvasive-brain-computer-interfaces-for-augmentative-and-3np9ok8bxp.pdf

Noninvasive Brain–Computer Interfaces for Augmentative and Alternative Communication

An amplitude-modulated visual stimulation for reducing eye fatigue in SSVEP-based brain-computer interfaces.

Steady state visual evoked potential (SSVEP) is the brain's natural electrical potential response for visual stimuli at specific frequencies. Using a visual stimulus flashing at some given frequency will entrain the SSVEP at the same frequency, thereby allowing determination of the subject's visual focus. The faster an SSVEP is identified, the higher information transmission rate the system achieves. Thus, an effective stimulus, defined as one with high success rate of eliciting SSVEP and high signal-noise ratio, is desired. Also, researchers observed that harmonic frequencies often appear in the SSVEP at a reduced magnitude. Are the harmonics in the SSVEP elicited by the fundamental stimulating frequency or by the artifacts of the stimuli? In this paper, we compare the SSVEP responses of three periodic stimuli: square wave (with different duty cycles), triangle wave, and sine wave to find an effective stimulus. We also demonstrate the connection between the strength of the harmonics in SSVEP and the type of stimulus.

/pdf/square-or-sine-finding-a-waveform-with-high-success-rate-of-57s5zpri72.pdf

Square or sine: finding a waveform with high success rate of eliciting SSVEP

The sum of sine waves was used to evoke Steady State Visual Evoked Potentials (SSVEP). The SSVEP responses were elicited by visual stimuli in the form of a flickering light emitting diode (LED). We recorded EEG responses to these stimuli and analyzed the observed spectral differences due to square waves, triangle waves and sine waves. We showed that the resolution of the dual stimuli, which is defined as the difference between two frequencies, is essential to SSVEP experiments. Reliable dual SSVEP spikes from EEG signals can only be acquired if the dual stimuli are at least 4Hz apart. We also tested tri-stimuli and showed that consistent EEG responses are not achievable, even though the stimuli were 4Hz apart. The essence of these experiments is to demonstrate the resolutions under which dual sine waves can generate consistent SSVEP responses.

Aik Min Choong

Papers

Square or sine: finding a waveform with high success rate of eliciting SSVEP

Steady state visual evoked potentials by dual sine waves