SSVEP Responses Research Articles

Electrophysiological correlates of temporal numerosity adaptation.

Much research has revealed the human visual system is capable to estimate numerical quantities, rapidly and reliably, in both the spatial and the temporal domain. This ability is highly susceptible to short-term plastic phenomena related to previous exposure to visual numerical information (i.e., adaptation). However, while determinants of spatial numerosity adaptation have been widely investigated, little is known about the neural underpinnings of short-term plastic phenomena related to the encoding of temporal numerical information. In the present study we investigated the electrophysiological correlates of temporal numerosity adaptation. Participants were asked to estimate the numerosity of a test sequence of flashes after being exposed to either a high or low numerous adapting sequence. Behavioral results confirmed the expected underestimation of test stimulus when this was preceded by a high numerous sequence as compared to when preceded by a low numerous sequence. Electrophysiological data revealed that this behavior was tightly linked to the amplitude of the steady-state visual evoked (ssVEP) response elicited by the test stimulus. When preceded by a high numerous sequence, the test stimulus elicited larger ssVEP responses as compared to when preceded by a low numerous sequence with this pattern being robustly correlated with behavior. Finally, topographical maps showed that this difference was mostly evident across two antero-posterior distributed clusters of electrodes and correlated with changes in functional connectivity. Taken together, our results suggest that visual plastic phenomena related to the encoding of temporal numerosity information reflect changes in rhythmic evoked activity that are likely related to long range communications between distinct brain regions.

No Evidence of Cross-Orientation Suppression Differences in Migraine with Aura Compared to Healthy Controls.

It has been suggested that there may be an imbalance of excitation and inhibitory processes in the visual areas of the brain in people with migraine aura (MA). One idea is thalamocortical dysrhythmia, characterized by disordered oscillations, and thus disordered communication between the lateral geniculate nucleus and the cortex. Cross-orientation suppression is a visual task thought to rely on inhibitory processing, possibly originating in the lateral geniculate nucleus. We measured both resting-state oscillations and cross-orientation suppression using EEG over occipital areas in people with MA and healthy volunteers. We found evidence of cross-orientation suppression in the SSVEP responses, but no evidence of any group difference. Therefore, inhibitory processes related to cross-orientation suppression do not appear to be impaired in MA.

Poster Session I: Binocular contrast integration: Cortical and behavioral signals reflect different computations.

Although binocular contrast perception under dichoptic viewing conditions has been extensively characterized behaviorally, little is known about how the signals from each eye are combined in cortex. Here we compared simultaneously-collected behavioral and EEG measures of dichoptic contrast perception. Observers (n=16) dichoptically viewed a 2-cpd grating flickering at 7.5 Hz and rotating slowly (1º/s). The contrast of the grating shown to each eye modulated sinusoidally over time at independent rates (1/6 and 1/8 Hz). We recorded EEG activity while observers positioned a joystick lever to report perceived contrast as it changed over time. A multiband filter was used to isolate the SSVEP responses to 7.5 Hz signals from electrode Oz (occipital pole), and the standard deviation of this signal provided a measure of neural response amplitude as a function of contrast. A simple model was fit to VEP and behavioral responses, [(L^m+R^m)/2]^(1/m)], which essentially characterized whether responses were better fit by a mean (m≈1) or a max (m>1) model. VEP responses (m = 1.0; MSE = 0.013) were well fit by a mean model, suggesting the EEG signal may have been driven by the input layers of V1. In contrast, behavioral responses (m = 8.8; MSE = 0.011) were well fit by a model that was heavily shifted towards a max model, suggesting a significant non-linear transformation of the contrast signal between the input layers of V1 and conscious perception.

Effect of temporal frequency on habituation in migraine.

Individuals with migraine tend to experience discomfort when viewing flickering stimuli. It has been suggested that one of the characteristics of migraine is a lack of habituation to repetitive visual stimuli, although findings can be mixed. Previous work has typically used similar visual stimuli (chequerboard) and only one temporal frequency. This study systematically varied the spatial and temporal characteristics of the visual stimulus, using steady-state visual evoked potentials to assess the differences in amplitude between migraine and control group over consecutive blocks of stimulation. Twenty individuals with migraine and 18 control observers were asked to rate their visual discomfort after viewing sequences of flickering Gabor patches with a frequency of either 3 or 9 Hz across three different spatial frequencies (low 0.5 cpd; mid-range 3 cpd; high 12 cpd). Compared to the control group, the migraine group showed a reduction in SSVEP responses with increased exposure, suggesting habituation processes are intact at 3-Hz stimulation. However, at 9-Hz stimulation, there was evidence of increased responses with increasing exposure in the migraine group in particular, which might suggest a build-up of the response over repetitive presentations. Visual discomfort varied with spatial frequency, for both 3- and 9-Hz stimuli, the highest spatial frequencies were the least uncomfortable compared to the low- and mid-range spatial frequencies in both groups. This difference in SSVEP response behaviour, dependent on temporal frequency, is important to consider when researching the effects of repetitive visual stimulation in migraine and could give some indication of build-up of effects leading to aversion to visual stimuli.

Bichromatic visual stimulus with subharmonic response to achieve a high-accuracy SSVEP BCI system with low eye irritation

ObjectiveWhile various Steady State Visual Evoked Potential Brain-Computer Interfaces (SSVEP BCI) with very high performance have already been developed, eye irritation is a significant burden in their practical use. Generally, there is a tradeoff between eye irritation and BCI accuracy. However, this study proposes a bichromatic visual stimulus with low eye irritation while providing accurately detectable electroencephalogram responses. MethodsThe proposed visual stimulus, which is high-frequency in terms of luminance but with a subharmonic color component, was compared to the conventional high-frequency SSVEP on 16 subjects. Canonical Correlation Analysis, Least Absolute Shrinkage and Selection Operator, Multivariate Synchronization Index (MSI), and Extended MSI were used separately to recognize aimed visual stimuli in a 4-target BCI system. ResultsThe proposed stimulus resulted in significantly (p-value = 0.024) higher accuracy (96 ± 4.1%) compared to the reference (87.1 ± 14.6%) for a processing window of 4.5 s using the Extended MSI algorithm. Eye irritation scores (3.8 ± 1.0 on a 1–9 scale) were also significantly lower (p-value = 0.035) than that of the reference stimulus (4.3 ± 1.1). No cases of illiteracy were observed with the proposed waveform, whereas there were 2 with the reference stimulus. ConclusionThe proposed bichromatic waveform provided significantly higher accuracy, especially for users who do not have strong high-frequency SSVEP responses. Eye irritation was also significantly lower than with conventional reference visual stimulus. The proposed visual stimulus can generate electroencephalogram responses, not only in the high-frequency range but also at half the main frequency. SignificanceThe results are significant for realizing practical, accurate SSVEP BCI systems.

Steady-state visual evoked potentials differentiate between internally and externally directed attention

While attention to external visual stimuli has been extensively studied, attention directed internally towards mental contents (e.g., thoughts, memories) or bodily signals (e.g., breathing, heartbeat) has only recently become a subject of increased interest, due to its relation to interoception, contemplative practices and mental health. The present study aimed at expanding the methodological toolbox for studying internal attention, by examining for the first time whether the steady-state visual evoked potential (ssVEP), a well-established measure of attention, can differentiate between internally and externally directed attention. To this end, we designed a task in which flickering dots were used to generate ssVEPs, and instructed participants to count visual targets (external attention condition) or their heartbeats (internal attention condition). We compared the ssVEP responses between conditions, along with alpha-band activity and the heartbeat evoked potential (HEP) - two electrophysiological measures associated with internally directed attention. Consistent with our hypotheses, we found that both the magnitude and the phase synchronization of the ssVEP decreased when attention was directed internally, suggesting that ssVEP measures are able to differentiate between internal and external attention. Additionally, and in line with previous findings, we found larger suppression of parieto-occipital alpha-band activity and an increase of the HEP amplitude in the internal attention condition. Furthermore, we found a trade-off between changes in ssVEP response and changes in HEP and alpha-band activity: when shifting from internal to external attention, increase in ssVEP response was related to a decrease in parieto-occipital alpha-band activity and HEP amplitudes. These findings suggest that shifting between external and internal directed attention prompts a re-allocation of limited processing resources that are shared between external sensory and interoceptive processing.

An SSPVEP Brain-Computer Interface Using a Small Amount of Flicker Stimuli

Brain-computer interface based on steady-state visual evoked potential (SSVEP-BCI) has been widely concerned because of its highest SNR of EEG signals. This kind of BCIs needs to modulate the control instructions with visual stimuli. However, a large number of visual stimuli will induce strong visual fatigue, and occupy a large area of screen space. As a result of the above disadvantages, the further application of this kind of BCIs can not be accepted by most users. It has been verified that 40 control instructions can be encoded with 20 flicker stimuli. The visual fatigue caused by SSVEP-BCIs can be alleviated by reducing the number of flicker stimuli. However, whether it is possible to encode the same number of control instructions with fewer flicker stimuli or not still remains unknown. This study will show the performance of the SSPVEP-BCIs after further removing some redundant flicker stimuli. We divide the proposed BCI system into four subsystems, and the performance of each subsystem will be shown in this paper. 12 flickering disks were used as visual stimuli to stimulate the brain to produce SSVEP responses. 12 targets were set on the flickering disks, and 28 targets were set alternately between the flicker stimuli, ensuring that always exist 1 to 2 flicker stimuli near each target. Manhattan distance based task-related component analysis (MTRCA) was used to process and decode the EEG signals in this paper. The performance within each of the subsystems was investigated and compared. When the sampling time was set to 4.6 s, the average accuracy of all subjects reaches 77.12%. This result shows that the 40-target BCI system based on proposed stimulation paradigm is available to the vast majority of users. Meanwhile, the accuracy of three subsystems is greater than 80% when the sampling time is 4.6 s. This result shows that the performance of SSPVEP stimulation paradigm is accepted in the application scenarios which only require a small number of instructions. In this paper, the research of SSPVEP paradigm is improved. It is revealed that using less flicker stimuli can still stimulate the brain to produce classifiable SSVEP responses. The conclusion of this study can guide the following study and application of SSPVEP-BCIs.

Steady-state visual evoked potential responses predict visual discomfort judgements.

It has been suggested that aesthetically pleasing stimuli are processed efficiently by the visual system, whereas uncomfortable stimuli are processed inefficiently. This study consists of a series of three experiments investigating this idea using a range of images of abstract artworks, photographs of natural scenes, and computer-generated stimuli previously shown to be uncomfortable. Subjective judgements and neural correlates were measured using electroencephalogram (EEG) (steady-state visual evoked potentials, SSVEPs). In addition, global image statistics (contrast, Fourier amplitude spectral slope and fractal dimension) were taken into account. When effects of physical image contrast were controlled, fractal dimension predicted discomfort judgements, suggesting the SSVEP response is more likely to be influenced by distribution of edges than the spectral slope. Importantly, when effects of physical contrast and fractal dimension were accounted for using linear mixed effects modelling, SSVEP responses predicted subjective judgements of images. Specifically, when stimuli were not matched for perceived contrast, there was a positive relationship between SSVEP responses and how pleasing a stimulus was judged to be, and conversely a negative relationship between discomfort and SSVEP response. This is significant as it shows that the neural responses in early visual areas contribute to the subjective (un)pleasantness of images, although the results of this study do not provide clear support for the theory of efficient coding as the cause of perceived pleasantness or discomfort of images, and so other explanations need to be considered.

Efficient Artifact Removal from Low-Density Wearable EEG using Artifacts Subspace Reconstruction.

Light-weight, minimally-obtrusive mobile EEG systems with a small number of electrodes (i.e., low-density) allow for convenient monitoring of the brain activity in out-of-the-lab conditions. However, they pose a higher risk for signal contamination with non-stereotypical artifacts due to hardware limitations and the challenging environment where signals are collected. A promising solution is Artifacts Subspace Reconstruction (ASR), a component-based approach that can automatically remove non-stationary transient-like artifacts in EEG data. Since ASR has only been validated with high-density systems, it is unclear whether it is equally efficient on low-density portable EEG. This paper presents a complete analysis of ASR performance based on clean and contaminated datasets acquired with BioWolf, an Ultra-Low-Power system featuring only eight channels, during SSVEP sessions recorded from six adults. Empirical results show that even with such few channels, ASR efficiently corrects artifacts, enabling an overall enhancement of up to 40% in SSVEP response. Furthermore, by choosing the optimal ASR parameters on a single-subject basis, SSVEP response can be further increased to more than 45%. These results suggest that ASR is a viable and robust method for online automatic artifact correction with low-density BCI systems in real-life scenarios.

The brain as a network cable: Transmission of a modulated optical signal between two computers via the human brain

Abstract The SSVEP response is used to transmit information in a unidirectional through-brain non-cognitive (entirely passive) communication channel. This, in effect, is connecting two otherwise disconnected computers through the brain, allowing us to consider the bandwidth of SSVEP encoding. The system uses green LEDs driven by a square wave to stimulate SSVEPs with EEG measurements being recorded by an EMOTIV EPOC. The stimulation and detection of SSVEPs is at the base of the channel - upon which a communication stack is implemented, allowing for character strings to be transmitted between an independent sender and receiver. The system was tested on four subjects, the best BER performance being achieved when using a PSDA detector on the O1 electrode with a 7,4 Hamming code being used as the FEC. A practical ITR of 25.6 bits/min was achieved. A prefix based transmission protocol was developed which allows the receiver to determine when a message is being sent and also allows the receiver to synchronise with the sender without the need for a secondary connection. The developed protocol correctly determined that a message was being sent across the channel 90% of the time with an average absolute synchronisation error of 0.397 s between sender and receiver.

SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

Steady-state visual evoked potentials-based brain-computer interfaces (SSVEP-BCI) has the advantage of high information transfer rate (ITR) and little user training, and it has a high application value in the field of disability assistance and human-computer interaction. Generally SSVEP-BCI requires a personal computer screen (PC) to display several repetitive visual stimuli for inducing the SSVEP response, which reduces its portability and flexibility. Using augmented reality (AR) glasses worn on the head to display the repetitive visual stimuli could solve the above drawbacks, but whether it could achieve the same accuracy as PC screen in the case of reduced brightness and increased interference is unknown. In current study, we firstly designed 4 stimulus layouts and displayed them with Microsoft HoloLens (AR-SSVEP) glasses, comparison analysis showed that the classification accuracies are influenced by the stimulus layout when the stimulus duration is less than 3s. When the stimulus duration exceeds 3s, there is no significant accuracy difference between the 4 layouts. Then we designed a similar experimental paradigm on PC screen (PC-SSVEP) based on the best layout of AR. Classification results showed that AR-SSVEP achieved similar accuracy with PC-SSVEP when the stimulus duration is more than 3s, but when the stimulus duration is less than 2s, the accuracy of AR-SSVEP is lower than PC-SSVEP. Brain topological analysis indicated that the spatial distribution of SSVEP responses is similar, both of which are strongest in the occipital region. Current study indicated that stimulus layout is a key factor when building SSVEP-BCI with AR glasses, especially when the stimulation time is short.

Assessment of high-frequency steady-state visual evoked potentials from below-the-hairline areas for a brain-computer interface based on Depth-of-Field

Background and ObjectiveRecently, a promising Brain-Computer Interface based on Steady-State Visual Evoked Potential (SSVEP-BCI) was proposed, which composed of two stimuli presented together in the center of the subject’s field of view, but at different depth planes (Depth-of-Field setup). Thus, users were easily able to select one of them by shifting their eye focus. However, in that work, EEG signals were collected through electrodes placed on occipital and parietal regions (hair-covered areas), which demanded a long preparation time. Also, that work used low-frequency stimuli, which can produce visual fatigue and increase the risk of photosensitive epileptic seizures. In order to improve the practicality and visual comfort, this work proposes a BCI based on Depth-of-Field using the high-frequency SSVEP response measured from below-the-hairline areas (behind-the-ears). MethodsTwo high-frequency stimuli (31 Hz and 32 Hz) were used in a Depth-of-Field setup to study the SSVEP response from behind-the-ears (TP9 and TP10). Multivariate Spectral F-test (MSFT) method was used to verify the elicited response. Afterwards, a BCI was proposed to command a mobile robot in a virtual reality environment. The commands were recognized through Temporally Local Multivariate Synchronization Index (TMSI) method. ResultsThe data analysis reveal that the focused stimuli elicit distinguishable SSVEP response when measured from hairless areas, in spite of the fact that the non-focused stimulus is also present in the field of view. Also, our BCI shows a satisfactory result, reaching average accuracy of 91.6% and Information Transfer Rate (ITR) of 5.3 bits/min. ConclusionThese findings contribute to the development of more safe and practical BCI.

Attention differentially modulates the amplitude of resonance frequencies in the visual cortex

Rhythmic visual stimuli (flicker) elicit rhythmic brain responses at the frequency of the stimulus, and attention generally enhances these oscillatory brain responses (steady state visual evoked potentials, SSVEPs). Although SSVEP responses have been tested for flicker frequencies up to 100 Hz [Herrmann, 2001], effects of attention on SSVEP amplitude have only been reported for lower frequencies (up to ~30 Hz), with no systematic comparison across a wide, finely sampled frequency range. Does attention modulate SSVEP amplitude at higher flicker frequencies (gamma band, 30–80 Hz), and is attentional modulation constant across frequencies? By isolating SSVEP responses from the broadband EEG signal using a multivariate spatiotemporal source separation method, we demonstrate that flicker in the alpha and gamma bands elicit strongest and maximally phase stable brain responses (resonance), on which the effect of attention is opposite: positive for gamma and negative for alpha. Finding subject-specific gamma resonance frequency and a positive attentional modulation of gamma-band SSVEPs points to the untapped potential of flicker as a non-invasive tool for studying the causal effects of interactions between visual gamma-band rhythmic stimuli and endogenous gamma oscillations on perception and attention.

Discrimination of SSVEP responses using a kernel based approach.

Brain Computer Interfaces based on Steady State Visual Evoked Potentials have gained increased attention due to their low training requirements and higher information transfer rates. In this work, a method based on sparse kernel machines is proposed for the discrimination of Steady State Visual Evoked Potentials responses. More specifically, a new kernel based on Partial Least Squares is introduced to describe the similarities between EEG trials, while the estimation of regression weights is performed using the Sparse Bayesian Learning framework. The experimental results obtained on two benchmarking datasets, have shown that the proposed method provides significantly better performance compared to state of the art approaches of the related literature.

F190. Investigation of the Visual Steady-State Response and Cognition in Schizophrenia

Individuals with schizophrenia (SZ) display cognitive deficits in working memory and inhibition tasks. Some healthy people display similar deficits in cognitive performance without exhibiting symptoms of schizophrenia. Electroencephalographic (EEG) studies of the visual steady-state response (ssVEP) probe the oscillatory capacity of the primary visual cortex and indicate differences based on task demands. This study used ssVEP in healthy comparison groups with High (HCC) and Low (LCC) levels of cognitive control and SZ to determine if altered ssVEP responses in preparation for an ocular-motor response task that varied in cognitive demand were associated with cognition or psychopathology.

Assessing Lateral Interaction in the Synesthetic Visual Brain.

In grapheme-color synesthesia, letters and numbers evoke abnormal colored perceptions. Although the underlying mechanisms are not known, it is largely thought that the synesthetic brain is characterized by atypical connectivity throughout various brain regions, including the visual areas. To study the putative impact of synesthesia on the visual brain, we assessed lateral interactions (i.e., local functional connectivity between neighboring neurons in the visual cortex) by recording steady-state visual evoked potentials (ssVEPs) over the occipital region in color-grapheme synesthetes (n = 6) and controls (n = 21) using the windmill/dartboard paradigm. Discrete Fourier Transform analysis was conducted to extract the fundamental frequency and the second harmonics of ssVEP responses from contrast-reversing stimuli presented at 4.27 Hz. Lateral interactions were assessed using two amplitude-based indices: Short-range and long-range lateral interactions. Results indicated that synesthetes had a statistically weaker signal coherence of the fundamental frequency component compared to the controls, but no group differences were observed on lateral interaction indices. However, a significant correlation was found between long-range lateral interactions and the type of synesthesia experience (projector versus associator). We conclude that the occipital activity related to lateral interactions in synesthetes does not substantially differ from that observed in controls. Further investigation is needed to understand the impact of synesthesia on visual processing, specifically in relation to subjective experiences of synesthete individuals.

Tracking feature-based attention

Objective. Feature-based attention (FBA) helps one detect objects with a particular color, motion, or orientation. FBA works globally; the attended feature is enhanced at all positions in the visual field. This global property of FBA lets one use stimuli presented in the peripheral visual field to track attention in a task presented centrally. The present study explores the use of SSVEPs, generated by flicker presented peripherally, to track attention in a visual search task presented centrally. We evaluate whether this use of EEG to track FBA is robust enough to track attention when performing visual search within a dynamic 3D environment presented with a head-mounted display (HMD). Approach. Observers first performed a visual search task presented in the central visual field within a stationary virtual environment. The purpose of this first experiment was to establish whether flicker presented peripherally can produce SSVEPs during HMD use. The second experiment placed observers in a dynamic virtual environment in which observers moved around a racetrack. Peripheral flicker was again used to track attention to the color of the target in the visual search task. Main results. SSVEPs produced by flicker in the peripheral visual field are influenced strongly by attention in observers with stationary or moving viewpoints. Offline classification results show that one can track an observer’s attended color, which suggests that these methods may provide a viable means for tracking FBA in a real-time task. Significance. Current FBA and brain–computer interface (BCI) studies primarily use foveal flicker to produce SSVEP responses. The present study’s finding that one can use peripherally-presented flicker to track attention in dynamic virtual environments promises a more flexible and practical approach to BCIs based on FBA.

An Adaptive SSVEP-Based Brain-Computer Interface to Compensate Fatigue-Induced Decline of Performance in Practical Application.

Brain-computer interfaces based on steady-state visual evoked potentials are promising communication systems for people with speech and motor disabilities. However, reliable SSVEP response requires user's attention, which degrades over time due to significant eye-fatigue when low-frequency visual stimuli (5-15 Hz) are used. Previous studies have shown that eye-fatigue can be reduced using high-frequency flickering stimuli (>25 Hz). Here, it is quantitatively demonstrated that the performance of a high-frequency SSVEP BCI decreases over time, but this amount of decrease can be compensated effectively by using two proposed adaptive algorithms. This leaded to a robust alternative communication system for practical applications. The asynchronous spelling system implemented in this study uses a threshold-based version of LASSO algorithm for frequency recognition. In long online experiments, when participants typed a sentence with the BCI system for 16 times, accuracy of the system was close to its maximum along the experiment. However, regression analysis on typing speed of each sentence demonstrated a significant decrease in all 7 subjects ( ) when thresholds obtained from a calibration test were kept fixed over the experiment. In comparison, no significant change in typing speed was observed when the proposed adaptive algorithms were used. The analysis of variances revealed that the average typing speed of the last four sentences when using adaptive relational algorithm (8.7 char/min) was significantly higher than the tolerance-based algorithm (8.1 char/min) and significantly above 6 char/min when the fixed thresholds were used. Therefore, the relational algorithm proposed in this paper could successfully compensate for the effect of fatigue on performance of the SSVEP BCI system.

Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects.

Background: Recent EEG-SSVEP signal based BCI studies have used high frequency square pulse visual stimuli to reduce subjective fatigue. However, the effect of total harmonic distortion (THD) has not been considered. Compared to CRT and LCD monitors, LED screen displays high-frequency wave with better refresh rate. In this study, we present high frequency sine wave simple and rhythmic patterns with low THD rate by LED to analyze SSVEP responses and evaluate subjective fatigue in normal subjects.Materials and Methods: We used patterns of 3-sequence high-frequency sine waves (25, 30, and 35 Hz) to design our visual stimuli. Nine stimuli patterns, 3 simple (repetition of each of above 3 frequencies e.g., P25-25-25) and 6 rhythmic (all of the frequencies in 6 different sequences e.g., P25-30-35) were chosen. A hardware setup with low THD rate (<0.1%) was designed to present these patterns on LED. Twenty two normal subjects (aged 23–30 (25 ± 2.1) yrs) were enrolled. Visual analog scale (VAS) was used for subjective fatigue evaluation after presentation of each stimulus pattern. PSD, CCA, and LASSO methods were employed to analyze SSVEP responses. The data including SSVEP features and fatigue rate for different visual stimuli patterns were statistically evaluated.Results: All 9 visual stimuli patterns elicited SSVEP responses. Overall, obtained accuracy rates were 88.35% for PSD and > 90% for CCA and LASSO (for TWs > 1 s). High frequency rhythmic patterns group with low THD rate showed higher accuracy rate (99.24%) than simple patterns group (98.48%). Repeated measure ANOVA showed significant difference between rhythmic pattern features (P < 0.0005). Overall, there was no significant difference between the VAS of rhythmic [3.85 ± 2.13] compared to the simple patterns group [3.96 ± 2.21], (P = 0.63). Rhythmic group had lower within group VAS variation (min = P25-30-35 [2.90 ± 2.45], max = P35-25-30 [4.81 ± 2.65]) as well as least individual pattern VAS (P25-30-35).Discussion and Conclusion: Overall, rhythmic and simple pattern groups had higher and similar accuracy rates. Rhythmic stimuli patterns showed insignificantly lower fatigue rate than simple patterns. We conclude that both rhythmic and simple visual high frequency sine wave stimuli require further research for human subject SSVEP-BCI studies.

Present and past selves: a steady-state visual evoked potentials approach to self-face processing

The self-face has a prioritized status in the processing of incoming visual inputs. As the self-face changes over the lifespan, this stimulus seems to be well-suited for investigation of the self across time. Here, steady-state visual evoked potentials (SSVEP, oscillatory responses to periodic stimulation with a frequency that mirrors the frequency of stimulation) were used to investigate this topic. Different types of faces (present self, past self, close-other’s, unknown, scrambled) flickered four times per second in two types of stimulation (‘identical’, with the same image of a given type of face; ‘different’, with different images of the same type of face). Each of the 10 stimulation sessions lasted 90 seconds and was repeated three times. EEG data were recorded and analyzed in 20 participants. In general, faces evoked higher SSVEP than scrambled faces. The impact of identical and different stimulation was similar for faces and scrambled faces: SSVEP to different stimuli (faces, scrambled faces) was enhanced in comparison to identical ones. Present self-faces evoked higher SSVEP responses than past self-faces in the different stimulation condition only. Thus, our results showed that the physical aspects of the present and past selves are differentiated on the neural level in the absence of an overt behavior.