Vision in clutter

Decision letter: Neural markers of predictive coding under perceptual uncertainty revealed with Hierarchical Frequency Tagging

Visual evoked potential (VEP)-related EEG signals have attracted widespread attention in the construction of brain-computer interface (BCI) systems. However, long-term use of the BCI system is prone to fatigue. Effectively coping with fatigue is the key to expanding BCI application scenarios. In this brief, we conduct two VEP experiments and propose a novel, concise and practical convolutional neural network (CNN) model to study and solve this problem. In detail, firstly, in terms of the stimulus frequencies in VEP experiments, we intercept the spectrum sequences of the fundamental waves and two harmonics. All these spectrum sequences are then paralleled input into the proposed multi-harmonic linkage CNN (MHLCNN) model, through three branches. Finally, the linkage characteristics of multiple harmonics are combined for VEP signal classification. The experimental results demonstrate that the proposed model shows good scalability, and can respectively improve the average classification accuracy by 23.17% and 15.85% when applied to steady-state VEP (SSVEP) signals in fatigue state and steady-state motion VEP (SSMVEP) signals, compared with the benchmark methods. All these provide a feasible and high-quality solution for reducing the impact of fatigue on the performance of VEP-based BCI systems.

In this paper, to develop a hybrid brain-computer interface based on Steady State Visual Evoked Potential(SSVEP) and P300, we validate a SSVEP brain-computer interface (BCI) with the hybrid stimuli of SSVEP and P300, and analyze the effect of P300 visual stimuli on the classification accuracy of the SSVEP BCI. The hybrid stimuli include the SSVEP stimuli, which consist of twochessboardimagespresented on a LCD screen and flashing at particular frequencies, respectively, and the P300 stimuli, which include nine characters and locate between the SSVEP stimuli. We extract the fundamental frequencies and second harmonics of the frequencies of the SSVEP stimulifrom EEG data as features, andapply a Fisher's linear discriminant analysis to build the classifier. The experimental results from three subjects show that the SSVEP potentials can be elicited well under the hybrid stimuli of SSVEP and P300, and the P300 stimuli under the hybrid condition have no significant effect on the SSVEP BCI. This work laysa foundationfor developing a hybrid BCIbased on SSVEP and P300.

We propose a system for estimating driver attention levels using Visually evoked potentials (VEP), computed from the EEG signals of the visual cortex. We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus, generating a Steady State VEP (SSVEP). Occasionally, a random stimulus is flashed on the screen, and the subsequent POVEP is also analyzed. It is seen that the SSVEP is related to the attention levels of the subjects. The sudden stimulus also generates local maxima/minima values for the POVEP, at the P2 and N2 components. Entropy measures of the frequency response of both the responses could also be used to characterize the occurrence of stimuli. We also propose a system architecture for a driver alertness system, which fuses the above process and a vision based traffic analysis system, to alert the driver well in advance of any decrease in attention.

Binocular summation in strabismic amblyopia is typically reported as being absent or greatly reduced in behavioral studies and is thought to be because of a preferential loss of excitatory interactions between the eyes. Here, we studied how excitatory and suppressive interactions contribute to binocular contrast interactions along the visual cortical hierarchy of humans with strabismic and anisometropic amblyopia in both sexes, using source-imaged steady-state visual evoked potentials (SSVEP) over a wide range of relative contrast between the two eyes. Dichoptic parallel grating stimuli modulated at unique temporal frequencies in each eye allowed us to quantify spectral response components associated with monocular inputs (self-terms) and the response components because of interaction of the inputs of the two eyes [intermodulation (IM) terms]. Although anisometropic amblyopes revealed a similar pattern of responses to normal-vision observers, strabismic amblyopes exhibited substantially reduced IM responses across cortical regions of interest (V1, V3a, hV4, hMT+ and lateral occipital cortex), indicating reduced interocular interactions in visual cortex. A contrast gain control model that simultaneously fits self- and IM-term responses within each cortical area revealed different patterns of binocular interactions between individuals with normal and disrupted binocularity. Our model fits show that in strabismic amblyopia, the excitatory contribution to binocular interactions is significantly reduced in both V1 and extra-striate cortex, whereas suppressive contributions remain intact. Our results provide robust electrophysiological evidence supporting the view that disruption of binocular interactions in strabismus or amblyopia is because of preferential loss of excitatory interactions between the eyes.SIGNIFICANCE STATEMENT We studied how excitatory and suppressive interactions contribute to binocular contrast interactions along the visual cortical hierarchy of humans with normal and amblyopic vision, using source-imaged SSVEP and frequency-domain analysis of dichoptic stimuli over a wide range of relative contrast between the two eyes. A dichoptic contrast gain control model was used to characterize these interactions in amblyopia and provided a quantitative comparison to normal vision. Our model fits revealed different patterns of binocular interactions between normal and amblyopic vision. Strabismic amblyopia significantly reduced excitatory contributions to binocular interactions, whereas suppressive contributions remained intact. Our results provide robust evidence supporting the view that the preferential loss of excitatory interactions disrupts binocular interactions in strabismic amblyopia.

Application of a reconstruction technique in detection of dominant SSVEP frequency

Steady-state visual evoked potentials (SSVEPs) are widely used in cognitive neuroscience and brain–computer interfaces (BCIs), but the visual discomfort induced by repetitive luminance flicker limits their usability, particularly in multi-target settings due to strong peripheral distraction. Textured flicker composed of Gabor patches has been proposed as a more comfortable alternative, but its suitability for SSVEP paradigms and its frequency-dependent impact on neural entrainment remain unclear. Here, we directly compared textured Gabor-based flicker and classical luminance flicker using a frequency sweep followed by a multi-class SSVEP BCI task. In Session 1 (N=24), we measured SSVEP signal-to-noise ratio (SNR), inter-trial coherence (ITC), and subjective comfort across 13 stimulation frequencies (3–18Hz). Gabor-based textures elicited higher SNR and ITC than plain flicker at low frequencies (3–9Hz), whereas plain flicker produced stronger and more phase-consistent responses at higher frequencies (12–18Hz), revealing a robust crossover in entrainment. Across almost all frequencies, Gabor stimuli were rated as more comfortable. Based on these results, we defined a low-frequency Gabor-optimized band (5–7Hz) and a higher plain-optimized band (14–16Hz). In Session 2 (N=18), these bands were used in a five-class offline SSVEP BCI. Classification accuracy was highest (Gabor: 95.7% at 5–7Hz; plain: 98.1% at 14–16Hz) when each stimulus type was used in its optimal band and decreased markedly when stimulus type and frequency band were mismatched. Gabor stimuli were consistently rated as more comfortable and nearly imperceptible in peripheral vision. Together, these findings establish textured Gabor flicker as a comfortable and effective alternative to luminance flicker for low-frequency SSVEP paradigms.

543 P120 component of foveal visual evoked potentials encodes luminance contrast in humans

A portable system capable of measuring steady-state visual-evoked potentials (SSVEP) was developed to provide an objective, quantifiable method of electroencephalogram (EEG) testing following a traumatic event. In this study, the portable system was used on 65 healthy rugby players throughout a season to determine whether SSVEP are a reliable electrophysiological biomarker for concussion. Preceding the competition season, all players underwent a baseline SSVEP assessment. During the season, players were re-tested within 72 h of a match for either test-retest reliability or post-injury assessment. In the case of a medically diagnosed concussion, players were reassessed again once deemed recovered by a physician. The SSVEP system consisted of a smartphone housed in a VR-frame delivering a 15 Hz flicker stimulus, while a wireless EEG headset recorded occipital activity. Players were instructed to stare at the screen's fixation point while remaining seated and quiet. Electrodes were arranged according to the 10-20 EEG-positioning nomenclature, with O1-O2 being the recording channels while P1-P2 the references and bias, respectively. All EEG data was processed using a Butterworth bandpass filter, Fourier transformation, and normalization to convert data for frequency analysis. Players SSVEP responses were quantified into a signal-to-noise ratio (SNR), with 15 Hz being the desired signal, and summarized into respective study groups for comparison. Concussed players were seen to have a significantly lower SNR compared to their baseline; however, post-recovery, their SNR was not significantly different from the baseline. Test-retest indicated high device reliability for the portable system. An improved portable SSVEP system was also validated against an established EEG amplifier to ensure the investigative design is capable of obtaining research quality EEG measurements. This is the first study to identify differences in SSVEP responses in amateur athletes following a concussion and indicates the potential for SSVEP as an aid in concussion assessment and management.

Central to our understanding of how visual-evoked potentials (VEPs) contribute to visual processing is the question of where their anatomical sources are. Three well-established measures of low-level visual cortical activity are widely used: the first component ("C1") of the transient and multifocal VEP, and the steady-state VEP (SSVEP). Although primary visual cortex (V1) activity has often been implicated in the generation of all three signals, their dominant sources remain uncertain due to the limited resolution and methodological heterogeneity of source modelling. Here, we provide the first characterisation of all three signals in one analytic framework centred on the "cruciform model", which describes how scalp topographies of V1 activity vary with stimulus location due to the retinotopy and unique folding pattern of V1. We measured the transient C1, multifocal C1, and SSVEPs driven by an 18.75 Hz and 7.5 Hz flicker, and regressed them against forward models of areas V1, V2, and V3 generated from the Benson-2014 retinotopy atlas. The topographic variations of all four VEP signals across the visual field were better captured by V1 models, explaining between 2 and 6 times more variance than V2/V3. Models with all three visual areas improved fit further, but complementary analyses of temporal dynamics across all three signals indicated that the bulk of extrastriate contributions occur considerably later than V1. Overall, our data support the use of peak C1 amplitude and SSVEPs to probe V1 activity, although the SSVEP contains stronger extrastriate contributions. Moreover, we provide elaborated heuristics to distinguish visual areas in VEP data based on signal lateralisation as well as polarity inversion.

Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40–60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz) and beta (15–30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline after approx. 500 ms. During the steady-state response, we observed alpha band desynchronization over occipital sites and after 500 ms also over frontal sites, while neighboring areas synchronized. The power in beta band over occipital sites increased during the stimulation period, possibly caused by increase in power at sub-harmonic frequencies of stimulation. Gamma power was also enhanced by the stimulation. Significance. These findings have direct implications on the use of RVS and SSVEPs for neural process investigation through steady-state topography, controlled entrainment of brain oscillations and BCIs. A deep understanding of SSVEP propagation in time and space and the link with ongoing brain rhythms is crucial for optimizing the typical SSVEP applications for studying, assisting, or augmenting human cognitive and sensorimotor function.

Spectrum-Enhanced TRCA (SE-TRCA): A novel approach for direction detection in SSVEP-based BCI

Through experience, humans can learn to suppress locations that frequently contain distracting stimuli. However, the neural mechanism underlying learned suppression remains largely unknown. In this study, we combined steady-state visually evoked potentials (SSVEPs) with event-related potentials (ERPs) to investigate the mechanism behind statistically learned spatial suppression. Twenty-four male and female human participants performed a version of the additional singleton search task in which one location contained a distractor stimulus frequently. The search stimuli constantly flickered on-and-off the screen, resulting in steady-state entrainment. Prior to search onset, no differences in the SSVEP response were found, though a post hoc analysis did reveal proactive alpha lateralization. Following search onset, clear evoked differences in both the SSVEP and ERP signals emerged at the suppressed location relative to all other locations. Crucially, the early timing of these evoked modulations suggests that learned distractor suppression occurs at the initial stages of visual processing.

Electrophysiological evidence for an early attentional mechanism in visual processing in humans

A variety of assessment tools are currently available to help clinicians assess Sports Related Concussion (SRC). Currently, the most widely available tools are neither objective nor portable, and are therefore not ideal for assessment at the site and time of a suspected injury. A portable system was developed to deliver a measurement of the steady-state visual-evoked potential (SSVEP). This system involved a smartphone housed in a Google Cardboard frame, which delivered a 15-Hz flicker visual stimulus while an electroencephalography (EEG) headset recorded EEG signals. Sixty-five rugby union players were tested during their regular season and were stratified into healthy, concussed, and recovered groups based on clinical examination. Their SSVEP response was quantified into a signal-to-noise ratio (SNR). The SNRs of players in each study group were summarized. Additionally, the SNRs of individual players who had baseline, post-injury, and post-recovery readings were analyzed. Sixty-five participants completed a baseline evaluation to measure their SSVEP. Twelve of these participants sustained a medically diagnosed concussion and completed SSVEP re-testing within 72 h. Eight concussed players received follow-up SSVEP testing after recovery. Concussed participants had a lower SNR [2.20 (2.04–2.38)] when compared to their baseline [4.54 (3.79–5.10)]. When clinically recovered, participant SNR was not significantly different to their baseline [4.82 (4.13–5.18)]. The baseline SNRs of the players who experienced a concussion during the season were not different to those of players who did not experience a concussion [4.80 (4.07–5.68)]. This is the first study to identify differences in SSVEP responses in male amateur rugby union players with and without concussion. It is also the first SSVEP demonstration for concussion evaluation at point-of-care. SSVEPs are significantly attenuated in the presence of concussion in these male athletes. Individuals returned to their baseline SSVEP following clinical recovery from the concussive injury. The use of SSVEPs has the potential to be a supplemental aid for the assessment and management of concussion.