[The supernumerary robotic limbs of brain-computer interface based on asynchronous steady-state visual evoked potential].

Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) have attracted much attention in the field of intelligent robotics. Traditional SSVEP-based BCI systems mostly use synchronized triggers without identifying whether the user is in the control or non-control state, resulting in a system that lacks autonomous control capability. Therefore, this paper proposed a SSVEP asynchronous state recognition method, which constructs an asynchronous state recognition model by fusing multiple time-frequency domain features of electroencephalographic (EEG) signals and combining with a linear discriminant analysis (LDA) to improve the accuracy of SSVEP asynchronous state recognition. Furthermore, addressing the control needs of disabled individuals in multitasking scenarios, a brain-machine fusion system based on SSVEP-BCI asynchronous cooperative control was developed. This system enabled the collaborative control of wearable manipulator and robotic arm, where the robotic arm acts as a "third hand", offering significant advantages in complex environments. The experimental results showed that using the SSVEP asynchronous control algorithm and brain-computer fusion system proposed in this paper could assist users to complete multitasking cooperative operations. The average accuracy of user intent recognition in online control experiments was 93.0%, which provides a theoretical and practical basis for the practical application of the asynchronous SSVEP-BCI system.

[Visual object detection system based on augmented reality and steady-state visual evoked potential].

This study investigates a brain-computer interface (BCI) system based on an augmented reality (AR) environment and steady-state visual evoked potentials (SSVEP). The system is designed to facilitate the selection of real-world objects through visual gaze in real-life scenarios. By integrating object detection technology and AR technology, the system augmented real objects with visual enhancements, providing users with visual stimuli that induced corresponding brain signals. SSVEP technology was then utilized to interpret these brain signals and identify the objects that users focused on. Additionally, an adaptive dynamic time-window-based filter bank canonical correlation analysis was employed to rapidly parse the subjects' brain signals. Experimental results indicated that the system could effectively recognize SSVEP signals, achieving an average accuracy rate of 90.6% in visual target identification. This system extends the application of SSVEP signals to real-life scenarios, demonstrating feasibility and efficacy in assisting individuals with mobility impairments and physical disabilities in object selection tasks.

Motion onset VEPs can see through the blur.

Motion-onset visual evoked potentials (MO VEPs) are robust to dioptric blur when low contrast and low spatial frequency patterns are used for stimulation. To reveal mechanisms of MO VEPs robustness, we studied whether the resistance to defocus persists even when using a high-contrast checkerboard using digital defocus in the emmetropic eyes of 13 subjects (males 20-60 years). We compared the dominant components of MO VEPs to pattern-reversal VEPs (PR VEP), which are sensitive to the blur. For stimulation, we used checkerboard patterns with 15´ and 60´ checks. To defocus the checkerboard, we rendered it with a second-order Zernike polynomial ( Z 2 0 ) with an equivalent defocus of 0, 2, or 4 D. For PR VEP, the checkerboards were reversed in terms of their contrast. To evoke MO VEP, the checkerboard of 60´ checks moved for 200 ms with a speed of 5 or 10 deg/s in the cardinal directions. The MO VEP did not change in peak time (P ≥ 0.0747) or interpeak amplitude (P > 0.0772) with digital blur. In contrast, for PR VEP, the results showed a decrease in interpeak amplitude (P ≤ 6.65ˑ10-4) and an increase in peak time (P ≤ 0.0385). Thus, we demonstrated that MO VEPs evoked by checkerboard, structure containing high spatial content, can be robust to defocus.

Binocularly incongruent, multifrequency-coded SSVEP in VR: feasibility and characteristics.

Objective.Steady-state visual evoked potentials (SSVEPs) in response to flickering stimuli are popular in brain-computer interfacing but their implementation in virtual reality (VR) offers new opportunities also for clinical applications. While traditional SSVEP target selection relies on single-frequency stimulation of both eyes simultaneously, further called congruent stimulation, recent studies attempted to improve the information transfer rate by using dual-frequency-coded SSVEP where each eye is presented with a stimulus flickering at a different frequency, further called incongruent stimulation. However, few studies have investigated incongruent multifrequency-coded SSVEP (MultiIncong-SSVEP).Approach.This paper reports on a systematical investigation of incongruent dual-, triple-, and quadruple-frequency-coded SSVEP for use in VR, several of which are entirely novel, and compares their performance with that of congruent dual-frequency-coded SSVEP.Main results.We were able to confirm the presence of a summation effect when comparing monocular- and binocular single-frequency congruent stimulation, and a suppression effect when comparing monocular- and binocular dual-frequency incongruent stimulation, as both tap into the binocular vision capabilities which, when hampered, could signal amblyopia.Significance.In sum, our findings not only evidence the potential of VR-based binocularly incongruent SSVEP but also underscore the importance of paradigm choice and decoder design to optimize system performance and user comfort.

Dual-Alpha: a large EEG study for dual-frequency SSVEP brain-computer interface.

BACKGROUND: The domain of brain-computer interface (BCI) technology has experienced significant expansion in recent years. However, the field continues to face a pivotal challenge due to the dearth of high-quality datasets. This lack of robust datasets serves as a bottleneck, constraining the progression of algorithmic innovations and, by extension, the maturation of the BCI field. FINDINGS: This study details the acquisition and compilation of electroencephalogram data across 3 distinct dual-frequency steady-state visual evoked potential (SSVEP) paradigms, encompassing over 100 participants. Each experimental condition featured 40 individual targets with 5 repetitions per target, culminating in a comprehensive dataset consisting of 21,000 trials of dual-frequency SSVEP recordings. We performed an exhaustive validation of the dataset through signal-to-noise ratio analyses and task-related component analysis, thereby substantiating its reliability and effectiveness for classification tasks. CONCLUSIONS: The extensive dataset presented is set to be a catalyst for the accelerated development of BCI technologies. Its significance extends beyond the BCI sphere and holds considerable promise for propelling research in psychology and neuroscience. The dataset is particularly invaluable for discerning the complex dynamics of binocular visual resource distribution.

Pattern-reversal visual evoked potentials in prosthetic vision and simulated visual reduction.

OBJECTIVE: To quantitatively evaluate visual evoked potentials (VEPs) in prosthetic vision and simulated visual reduction. METHODS AND ANALYSIS: Four blind patients implanted with the Argus II retinal prosthesis and seven sighted controls participated. VEPs were recorded with pattern-reversal stimuli (2 cycles of a horizontal square wave grating, 0.1 cycle/degree) at 1.07 reversals per second (rps) for Argus II subjects and 3.37 rps for controls. Argus II patients had both eyes patched, viewing the pattern solely through their implant. Controls viewed the pattern monocularly, either with their best-corrected vision or with simulated visual reduction (field restriction, added blur or reduced display contrast). RESULTS: VEPs recorded in Argus II patients displayed a similar shape to normal VEPs when controls viewed the pattern without simulated visual reduction. In sighted controls, adding blur significantly delayed the P100 peak time by 8.7 ms, 95% CI (0.9, 16.6). Reducing stimulus contrast to 32% and 6% of full display contrast significantly decreased P100 amplitude to 55% (37%, 82%) and 20% (13%, 31%), respectively. Restriction on the field of view had no impact on either the amplitude or the peak latency of P100. CONCLUSION: The early visual cortex in retinal prosthesis users remains responsive to retinal input, showing a similar response profile to that of sighted controls. Pattern-reversal VEP offers valuable insights for objectively evaluating artificial vision therapy systems (AVTSs) when selecting, fitting and training implant users, but the uncertainties in the exact timing and location of electrode stimulation must be considered when interpreting the results.

A MultiModal Vigilance (MMV) dataset during RSVP and SSVEP brain-computer interface tasks.

Vigilance represents an ability to sustain prolonged attention and plays a crucial role in ensuring the reliability and optimal performance of various tasks. In this report, we describe a MultiModal Vigilance (MMV) dataset comprising seven physiological signals acquired during two Brain-Computer Interface (BCI) tasks. The BCI tasks encompass a rapid serial visual presentation (RSVP)-based target image retrieval task and a steady-state visual evoked potential (SSVEP)-based cursor-control task. The MMV dataset includes four sessions of seven physiological signals for 18 subjects, which encompasses electroencephalogram(EEG), electrooculogram (EOG), electrocardiogram (ECG), photoplethysmogram (PPG), electrodermal activity (EDA), electromyogram (EMG), and eye movement. The MMV dataset provides data from four stages: 1) raw data, 2) pre-processed data, 3) trial data, and 4) feature data that can be directly used for vigilance estimation. We believe this dataset will achieve flexible reuse and meet the various needs of researchers. And this dataset will greatly contribute to advancing research on physiological signal-based vigilance research and estimation.

Neuro-ophthalmic and Neuro-otologic Evaluation in Individuals with Motion Sickness Susceptibility.

Since the physiological background of motion sickness is not entirely clear, it was aimed to examine the physiological differences in groups consisting of individuals susceptible and non-susceptible to motion sickness. Sixty subjects [motion sickness (MS) group: 33 female, 3 male; 28.8 ± 8.1 years; control group: 19 female, 5 male; 24.5 ± 4.3 years] were included in the study. Near visual acuity test on the treadmill in the presence of visual stimulation, pattern visual-evoked potentials, oculomotor tests, and computerized dynamic posturography were applied. Receiver operating characteristic analysis was performed to determine the parameter that provides the excellent discrimination between the groups. The most effective parameter in differentiating the study groups was determined as dynamic visual acuity with 77.8% sensitivity and 95.8% specificity. Significant differences were found in the vestibular (mean ± standard deviation: 0.63 ± 0.17), visual (0.77 ± 0.18), and composite scores (73.11 ± 11.89) of the patients (P=.000) in posturographic evaluation. In the visual-evoked potential examination, a significant decrease was found in the amplitude values between the P100-N145 waves in the binocular (5.0 ± 2.8, P=.002), right eye (7.6 ± 3.2, P=.009) and left eye (7.9 ± 2.9, P=.016) in the symptomatic patients. In binocular oculomotor evaluation, directional asymmetric findings were obtained. It has been shown that the most effective test parameter that distinguishes the MS susceptible and non-susceptible individuals is the dynamic visual acuity value. Based on the results of neuro-physiological tests, it was suggested that a possible visual-vestibular integration disorder in individuals susceptible to motion sickness may affect visual and vestibular performance.

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling.

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

Blockade of GluN2B-Containing NMDA Receptors Prevents Potentiation and Depression of Responses during Ocular Dominance Plasticity.

Monocular deprivation (MD) causes an initial decrease in synaptic responses to the deprived eye in juvenile mouse primary visual cortex (V1) through Hebbian long-term depression (LTD). This is followed by a homeostatic increase, which has been attributed either to synaptic scaling or to a slide threshold for Hebbian long-term potentiation (LTP) rather than scaling. We therefore asked in mice of all sexes whether the homeostatic increase during MD requires GluN2B-containing NMDA receptor activity, which is required to slide the plasticity threshold but not for synaptic scaling. Selective GluN2B blockade from 2-6 d after monocular lid suture prevented the homeostatic increase in miniature excitatory postsynaptic current (mEPSC) amplitude in monocular V1 of acute slices and prevented the increase in visually evoked responses in binocular V1 in vivo. The decrease in mEPSC amplitude and visually evoked responses during the first 2 d of MD also required GluN2B activity. Together, these results support the idea that GluN2B-containing NMDA receptors first play a role in LTD immediately following eye closure and then promote homeostasis during prolonged MD by sliding the plasticity threshold in favor of LTP.

Prioritization of social information processing: Eye gaze elicits earlier vMMN than arrows.

Numerous research studies have demonstrated that eye gaze and arrows act as cues that automatically guide spatial attention. However, it remains uncertain whether the attention shifts triggered by these two types of stimuli vary in terms of automatic processing mechanisms. In our current investigation, we employed an equal probability paradigm to explore the likenesses and distinctions in the neural mechanisms of automatic processing for eye gaze and arrows in non-attentive conditions, using visual mismatch negative (vMMN) as an indicator of automatic processing. The sample size comprised 17 participants. The results indicated a significant interaction between time duration, stimulus material, and stimulus type. The findings demonstrated that both eye gaze and arrows were processed automatically, triggering an early vMMN, although with temporal variations. The vMMN for eye gaze occurred between 180 and 220 ms, whereas for arrows it ranged from 235 to 275 ms. Moreover, arrow stimuli produced a more pronounced vMMN amplitude. The earlier vMMN response to eye gaze compared with arrows implies the specificity and precedence of social information processing associated with eye gaze over the processing of nonsocial information with arrows. However, arrow could potentially elicit a stronger vMMN because of their heightened salience compared to the background, and the expansion of attention focusing might amplify the vMMN impact. This study offers insights into the similarities and differences in attention processing of social and non-social information under unattended conditions from the perspective of automatic processing.

Retinal Damage and Visual Network Reconfiguration Defines Visual Function Recovery in Optic Neuritis.

BACKGROUND AND OBJECTIVES: Recovery of vision after acute optic neuritis (AON) is critical to improving the quality of life of people with demyelinating diseases. The objective of the study was to prospectively assess the changes in visual acuity, retinal layer thickness, and cortical visual network in patients with AON to identify the predictors of permanent visual disability. METHODS: We studied a prospective cohort of 88 consecutive patients with AON with 6-month follow-up using high and low-contrast (2.5%) visual acuity, color vision, retinal thickness from optical coherence tomography, latencies and amplitudes of multifocal visual evoked potentials, mean deviation of visual fields, and diffusion-based structural (n = 53) and functional (n = 19) brain MRI to analyze the cortical visual network. The primary outcome was 2.5% low-contrast vision, and data were analyzed with mixed-effects and multivariate regression models. RESULTS: We found that after 6 months, low-contrast vision and quality of vision remained moderately impaired. The thickness of the ganglion cell layer at baseline was a predictor of low-contrast vision 6 months later (ß = 0.49 [CI 0.11-0.88], p = 0.012). The structural cortical visual network at baseline predicted low-contrast vision, the best predictors being the betweenness of the right parahippocampal cortex (ß = -036 [CI -0.66 to 0.06], p = 0.021), the node strength of the right V3 (ß = 1.72 [CI 0.29-3.15], p = 0.02), and the clustering coefficient of the left intraparietal sulcus (ß = 57.8 [CI 12.3-103.4], p = 0.015). The functional cortical visual network at baseline also predicted low-contrast vision, the best predictors being the betweenness of the left ventral occipital cortex (ß = 8.6 [CI: 4.03-13.3], p = 0.009), the node strength of the right intraparietal sulcus (ß = -2.79 [CI: -5.1-0.4], p = 0.03), and the clustering coefficient of the left superior parietal lobule (ß = 501.5 [CI 50.8-952.2], p = 0.03). DISCUSSION: The assessment of the visual pathway at baseline predicts permanent vision disability after AON, indicating that damage is produced early after disease onset and that it can be used for defining vision impairment and guiding therapy.

Beyond primary visual cortex: The leading role of lateral occipital complex in early conscious visual processing.

The study of the neural substrates that serve conscious vision is one of the unsolved questions of cognitive neuroscience. So far, consciousness literature has endeavoured to disentangle which brain areas and in what order are involved in giving rise to visual awareness, but the problem of consciousness still remains unsolved. Availing of two different but complementary sources of data (i.e., Fast Optical Imaging and EEG), we sought to unravel the neural dynamics responsible for the emergence of a conscious visual experience. Our results revealed that conscious vision is characterized by a significant increase of activation in extra-striate visual areas, specifically in the Lateral Occipital Complex (LOC), and that, more interestingly, such activity occurred in the temporal window of the ERP component commonly thought to represent the electrophysiological signature of visual awareness, i.e., the Visual Awareness Negativity (VAN). Furthermore, Granger causality analysis, performed to further investigate the flow of activity occurring in the investigated areas, unveiled that neural processes relating to conscious perception mainly originated in LOC and subsequently spread towards visual and motor areas. In general, the results of the present study seem to advocate for an early contribution of LOC in conscious vision, thus suggesting that it could represent a reliable neural correlate of visual awareness. Conversely, striate visual areas, showing awareness-related activity only in later stages of stimulus processing, could be part of the cascade of neural events following awareness emergence.

Enhancement of Hybrid BCI System Performance Based on Motor Imagery and SSVEP by Transcranial Alternating Current Stimulation.

The hybrid brain-computer interface (BCI) is verified to reduce disadvantages of conventional BCI systems. Transcranial electrical stimulation (tES) can also improve the performance and applicability of BCI. However, enhancement in BCI performance attained solely from the perspective of users or solely from the angle of BCI system design is limited. In this study, a hybrid BCI system combining MI and SSVEP was proposed. Furthermore, transcranial alternating current stimulation (tACS) was utilized to enhance the performance of the proposed hybrid BCI system. The stimulation interface presented a depiction of grabbing a ball with both of hands, with left-hand and right-hand flickering at frequencies of 34 Hz and 35 Hz. Subjects watched the interface and imagined grabbing a ball with either left hand or right hand to perform SSVEP and MI task. The MI and SSVEP signals were processed separately using filter bank common spatial patterns (FBCSP) and filter bank canonical correlation analysis (FBCCA) algorithms, respectively. A fusion method was proposed to fuse the features extracted from MI and SSVEP. Twenty healthy subjects took part in the online experiment and underwent tACS sequentially. The fusion accuracy post-tACS reached 90.25% ± 11.40%, which was significantly different from pre-tACS. The fusion accuracy also surpassed MI accuracy and SSVEP accuracy respectively. These results indicated the superior performance of the hybrid BCI system and tACS would improve the performance of the hybrid BCI system.

Examining the relative contribution of slow-burning inflammation and chronic demyelination to axonal damage in chronic multiple sclerosis lesions.

BACKGROUND AND OBJECTIVES: Slow-burning inflammation at the edge, and chronic demyelination at the core, of established multiple sclerosis (MS) lesions are potential mediators of disease progression. However, their relative contribution to progressive axonal damage has not been explored. Therefore, in this study, we investigated the comparative contribution of slow-burning inflammation and chronic demyelination to axonal attrition within MS lesions by measuring progressive tissue rarefaction. In addition, we use the visual system as a model to investigate the effect of chronic demyelination on the acceleration of axonal death in a sub-group of patients with unilateral optic neuritis. METHODS: Pre- and post-gadolinium 3D-T1, 3D FLAIR, diffusion tensor images, Optical Coherence tomography and multifocal visual evoked potentials were acquired from 52 relapsing-remitting MS patients who completed at least 5 years follow-up. Lesion expansion was measured using custom software, and the rate of tissue rarefication inside lesion core was assessed by measuring increase of normalized mean diffusivity (nMD). Axonal loss was also examined in eyes with severe optic nerve demyelination. RESULTS: Among the 361 lesions analyzed, 104 were expanding (a minimum of 4 % expansion per year) and 257 were stable. Expanding lesions showed a significantly higher rate of progressive tissue rarefication inside lesion (1.12 % per year) core compared to stable lesions (0.21 % per year, p = 0.01). The magnitude of nMD change was significantly correlated with the rate of lesion expansion (r = 0.4, p < 0.001). Analysis of retinal ganglion cells in eyes with severe optic nerve demyelination (Inter-eye latency delay of >10 ms) revealed a similar rate of axonal loss (0.19 %) to the degree of tissue rarefaction observed in stable lesions (0.21 %). DISCUSSION: The results of the study suggest that the slow-burning inflammation at the lesion's edge (as measured by lesion expansion), is likely to have a greater impact on tissue damage (as measured by nMD change), when compared to stable chronically demyelinated lesions. The similar modest degree of tissue damage was also observed in chronically demyelinated fibers of the optic nerve.

Assessing the visual afferent pathway with the multifocal visual evoked potentials in the radiologically isolated syndrome.

The early identification of individuals with radiologically isolated syndrome (RIS) who are at an elevated risk of progressing to multiple sclerosis (MS) is essential for making informed treatment decisions. This study aimed to evaluate the predictive potential of multifocal Visual Evoked Potentials (mfVEP) measures in individuals with RIS with respect to their conversion to MS. A prospective observational cohort study was conducted, involving 21 individuals with RIS recruited from a MS center. Baseline assessments, including mfVEP, magnetic resonance imaging (MRI), and clinical examinations, were performed, and participants were longitudinally followed for up to 24 months. The primary outcome measures were the conversion to MS. Over a clinical follow-up period of 24 months, five individuals (5/21) with RIS progressed to MS. MfVEP amplitude responses (interocular and monocular probability analysis) demonstrated abnormal cluster visual field defects in 47.6% of RIS eyes at baseline, whereas multifocal VEP latency analysis showed significant delays in 38.4%. A reduction in interocular amplitude [OR = 0.036, (95% CI 0.003-0.503); P = 0.014], monocular amplitude [OR = 0.083, (95% CI 0.007-0.982); P = 0.048], and a prolonged interocular latency [OR = 0.095, (95% CI 0.009-0.972); P = 0.047] were associated with a higher relative risk of clinical conversion at the 2-year follow-up. Multifocal VEP may serve as a novel and independent risk factor for predicting the conversion to MS in individuals with Radiologically Isolated Syndrome.

Processing of visual hapaxes in picture naming task: An event-related potential study.

Object recognition and visual categorization are typically swift and seemingly effortless tasks that involve numerous underlying processes. In our investigation, we utilized a picture naming task to explore the processing of rarely encountered objects (visual hapaxes) in comparison to common objects. Our aim was to determine the stage at which these rare objects are classified as unnamable. Contrary to our expectations and in contrast to some prior research on event-related potentials (ERPs) with novel and atypical objects, no differences between conditions were observed in the late time windows corresponding to the P300 or N400 components. However, distinctive patterns between hapaxes and common objects surfaced in three early time windows, corresponding to the posterior N1 and P2 waves, as well as a widespread N2 wave. According to the ERP data, the differentiation between hapaxes and common objects occurs within the first 380 ms of the processing line, involving only limited and indirect top-down influence.

Human-centred physical neuromorphics with visual brain-computer interfaces.

Steady-state visual evoked potentials (SSVEPs) are widely used for brain-computer interfaces (BCIs) as they provide a stable and efficient means to connect the computer to the brain with a simple flickering light. Previous studies focused on low-density frequency division multiplexing techniques, i.e. typically employing one or two light-modulation frequencies during a single flickering light stimulation. Here we show that it is possible to encode information in SSVEPs excited by high-density frequency division multiplexing, involving hundreds of frequencies. We then demonstrate the ability to transmit entire images from the computer to the brain/EEG read-out in relatively short times. High-density frequency multiplexing also allows to implement a photonic neural network utilizing SSVEPs, that is applied to simple classification tasks and exhibits promising scalability properties by connecting multiple brains in series. Our findings open up new possibilities for the field of neural interfaces, holding potential for various applications, including assistive technologies and cognitive enhancements, to further improve human-machine interactions.