Introducing chaotic codes for the modulation of code modulated visual evoked potentials (c-VEP) in normal adults for visual fatigue reduction

Abstract

Code modulated Visual Evoked Potentials (c-VEP) based BCI studies usually employ m-sequences as a modulating codes for their broadband spectrum and correlation property. However, subjective fatigue of the presented codes has been a problem. In this study, we introduce chaotic codes containing broadband spectrum and similar correlation property. We examined whether the introduced chaotic codes could be decoded from EEG signals and also compared the subjective fatigue level with m-sequence codes in normal subjects. We generated chaotic code from one-dimensional logistic map and used it with conventional 31-bit m-sequence code. In a c-VEP based study in normal subjects (n = 44, 21 females) we presented these codes visually and recorded EEG signals from the corresponding codes for their four lagged versions. Canonical correlation analysis (CCA) and spatiotemporal beamforming (STB) methods were used for target identification and comparison of responses. Additionally, we compared the subjective self-declared fatigue using VAS caused by presented m-sequence and chaotic codes. The introduced chaotic code was decoded from EEG responses with CCA and STB methods. The maximum total accuracy values of 93.6 ± 11.9% and 94 ± 14.4% were achieved with STB method for chaotic and m-sequence codes for all subjects respectively. The achieved accuracies in all subjects were not significantly different in m-sequence and chaotic codes. There was significant reduction in subjective fatigue caused by chaotic codes compared to the m-sequence codes. Both m-sequence and chaotic codes were similar in their accuracies as evaluated by CCA and STB methods. The chaotic codes significantly reduced subjective fatigue compared to the m-sequence codes.

Introducing Rhythmic Sinusoidal Amplitude-Modulated Auditory Stimuli with Multiple Message Frequency Coding for Fatigue Reduction in Normal Subjects: An EEG Study

“…This is in agreement with the findings of our previous study on the comparison between the fatigue levels that simple and rhythmic single-message sinusoidal AM stimuli can cause (Shamsi et al, 2017). It is also in accordance with the results of previous studies on rhythmic (Keihani et al, 2018b;Keihani et al, 2018a) and chaotic (Shirzhiyan et al, 2019) visual stimuli that reduced the subjective fatigue, and confirms our second hypothesis. In addition, the insignificant and infinitesimal correlation between the fatigue and the psychological state can ensure us that the subjects truly reported the fatigue that was mainly caused by listening to the stimuli, regardless of their psychological status.…”

“…Moreover, rhythmic stimulation modulates the intrinsic neural oscillatory characteristics (Treder et al, 2014;Herrmann et al, 2016) and facilitates keeping focus (Sato et al, 2019). Interestingly, it was revealed that rhythmic (Keihani et al, 2018b;Keihani et al, 2018a) and chaotic (Shirzhiyan et al, 2019) visual alongside auditory stimuli (Shamsi et al, 2017) brought about both enough distinguishable EEGs and less subjects' fatigue, compared to simple stimuli. Thus, rhythmic stimuli are one of the promising options for being used in aBCI.…”

Asynchronous c-VEP communication tools—efficiency comparison of low-target, multi-target and dictionary-assisted BCI spellers

“…In general, only a few participants rated the flickering sensation during the spelling tasks as exhausting (16% and 5% for the 4-target and 32-target speller) or annoying (14% and 5%). Still, the flickering sensation can be reduced by employing more subtle stimulus patterns 41 , 42 or higher flickering rates 43 , 44 . However, a decrease in performance may be expected as a consequence.…”

Toward New Modalities in VEP-Based BCI Applications Using Dynamical Stimuli: Introducing Quasi-Periodic and Chaotic VEP-Based BCI

“…Frequency-based BCIs may use visual stimuli that are modulated in time according to a sine wave with different temporal frequencies, which also evoke EEG responses at the same frequencies and their harmonics ( Middendorf et al, 2000 ; Müller-Putz et al, 2005 ; Wang et al, 2006 ). Orthogonal visual stimuli in code-based BCIs are generated by random codes such as m -sequences, whereby different shifts of a modulating code have been used to evoke code-modulated VEPs (c-VEPs) ( Nakanishi et al, 2014 ; Riechmann et al, 2016 ; Wei et al, 2016 , 2018 ; Spüler, 2017 ; Liu et al, 2018 ; Shirzhiyan et al, 2019 ).…”

“…Utilization of visual stimuli with quasi-periodic and chaotic patterns that are closer to natural scenes in BCI applications requires further research. In our previous study, we used chaotic and pseudo-random m -sequence binary codes and found that chaotic codes lead to comparatively less fatigue ( Shirzhiyan et al, 2019 ). In this study, we introduce a new kind of visual stimuli with quasi-periodic and chaotic characteristics to evoke distinct visual potentials in normal subjects for their possible application in VEP-based BCIs.…”