From intermodulation components to visual perception and cognition-a review

Measuring attentional selection of object categories using hierarchical frequency tagging

In the present study, we used Hierarchical Frequency Tagging (Gordon et al., 2017) to investigate in electroencephalography how different levels of the neural processing hierarchy interact with category-selective attention during visual object recognition. We constructed stimulus sequences of cyclic wavelet scrambled face and house stimuli at two different frequencies (f1 = 0.8 Hz and f2 = 1 Hz). For each trial, two stimulus sequences of different frequencies were superimposed and additionally augmented by a sinusoidal contrast modulation with f3 = 12.5 Hz. This allowed us to simultaneously assess higher level processing using semantic wavelet-induced frequency-tagging (SWIFT) and processing in earlier visual levels using steady-state visually evoked potentials (SSVEPs), along with their intermodulation (IM) components. To investigate the category specificity of the SWIFT signal, we manipulated the category congruence between target and distractor by superimposing two sequences containing stimuli from the same or different object categories. Participants attended to one stimulus (target) and ignored the other (distractor). Our results showed successful tagging of different levels of the cortical hierarchy. Using linear mixed-effects modeling, we detected different attentional modulation effects on lower versus higher processing levels. SWIFT and IM components were substantially increased for target versus distractor stimuli, reflecting attentional selection of the target stimuli. In addition, distractor stimuli from the same category as targets elicited stronger SWIFT signals than distractor stimuli from a different category indicating category-selective attention. In contrast, for IM components, this category-selective attention effect was largely absent, indicating that IM components probably reflect more stimulus-specific processing.

Adaptation of Ocular Opponency Neurons Mediates Attention-Induced Ocular Dominance Plasticity

Previous research has shown that ocular dominance can be biased by prolonged attention to one eye. The ocular-opponency-neuron model of binocular rivalry has been proposed as a candidate account for this phenomenon. Yet direct neural evidence is still lacking. By manipulating the contrast of dichoptic testing gratings, here we measured the steady-state visually evoked potentials (SSVEPs) at the intermodulation frequencies to selectively track the activities of ocular-opponency-neurons before and after the "dichoptic-backward-movie" adaptation. One hour of adaptation caused a shift of perceptual and neural ocular dominance towards the unattended eye. More importantly, we found a decrease in the intermodulation SSVEP response after adaptation, which was significantly greater when high-contrast gratings were presented to the attended eye than when they were presented to the unattended eye. These results strongly support the view that the adaptation of ocular-opponency-neurons contributes to the ocular dominance plasticity induced by prolonged eye-based attention.

Bi-sinusoidal light stimulation reveals an enhanced response power and reduced phase coherence at the visual cortex in migraine

Introduction

Migraine is associated with enhanced visual sensitivity during and outside attacks. Processing of visual information is a highly non-linear process involving complex interactions across (sub)cortical networks. In this exploratory study, we combined electroencephalography with bi-sinusoidal light stimulation to assess non-linear features of visual processing in participants with migraine.

Methods

Twenty participants with migraine (10 with aura, 10 without aura) and ten non-headache controls were measured (outside attacks). Participants received bi-sinusoidal 13 + 23 Hz red light visual stimulation. Electroencephalography spectral power and multi-spectral phase coherence were compared between groups at the driving stimulation frequencies together with multiples and combinations of these frequencies (harmonic and intermodulation frequencies) caused by non-linearities.

Results

Only at the driving frequency of 13 Hz higher spectral power was found in migraine with aura participants compared with those with migraine without aura and controls. Differences in phase coherence were present for 2nd, 4th, and 5th-order non-linearities in those with migraine (migraine with and without aura) compared with controls. Bi-sinusoidal light stimulation revealed evident non-linearities in the brain's electroencephalography response up to the 5th order with reduced phase coherence for higher order interactions in interictal participants with migraine.

Discussion

Insight into interictal non-linear visual processing may help understand brain dynamics underlying migraine attack susceptibility. Future research is needed to determine the clinical value of the results.

MEG frequency tagging reveals a grid-like code during attentional movements

Grid-cells firing fields tile the environment with a 6-fold periodicity during both locomotion and visual exploration. Here, we tested, in humans, whether movements of covert attention elicit grid-like coding using frequency tagging. Participants observed visual trajectories presented sequentially at fixed rate, allowing different spatial periodicities (e.g., 4-, 6-, and 8-fold) to have corresponding temporal periodicities (e.g., 1, 1.5, and 2 Hz), thus resulting in distinct spectral responses. We found a higher response for the (grid-like) 6-fold periodicity and localized this effect in medial-temporal sources. In a control experiment featuring the same temporal periodicity but lacking spatial structure, the 6-fold effect did not emerge, suggesting its dependency on spatial movements of attention. We report evidence that grid-like signals in the human medial-temporal lobe can be elicited by covert attentional movements and suggest that attentional coding may provide a suitable mechanism to support the activation of cognitive maps during conceptual navigation.

EEG measurement for the effect of perceptual eye position and eye position training on comitant strabismus

One of the clinical features of comitant strabismus is that the deviation angles in the first and second eye positions are equal. However, there has been no report of consistency in the electroencephalography (EEG) signals between the 2 positions. In order to address this issue, we developed a new paradigm based on perceptual eye position. We collected steady-state visual evoked potentials (SSVEPs) signals and resting-state EEG data before and after the eye position training. We found that SSVEP signals could characterize the suppression effect and eye position effect of comitant strabismus, that is, the SSVEP response of the dominant eye was stronger than that of the strabismus eye in the first eye position but not in the second eye position. Perceptual eye position training could modulate the frequency band activities in the occipital and surrounding areas. The changes in the visual function of comitant strabismus after training could also be characterized by SSVEP. There was a correlation between intermodulation frequency, power of parietal electrodes, and perceptual eye position, indicating that EEG might be a potential indicator for evaluating strabismus visual function.

Intermodulation responses show integration of interacting bodies in a new whole

People are often seen among other people, relating to and interacting with one another. Recent studies suggest that socially relevant spatial relations between bodies, such as the face-to-face positioning, or facingness, change the visual representation of those bodies, relative to when the same items appear unrelated (e.g., back-to-back) or in isolation. The current study addresses the hypothesis that face-to-face bodies give rise to a new whole, an integrated representation of individual bodies in a new perceptual unit. Using frequency-tagging EEG, we targeted, as a measure of integration, an EEG correlate of the non-linear combination of the neural responses to each of two individual bodies presented either face-to-face as if interacting, or back-to-back. During EEG recording, participants (N = 32) viewed two bodies, either face-to-face or back-to-back, flickering at two different frequencies (F1 and F2), yielding two distinctive responses in the EEG signal. Spectral analysis examined the responses at the intermodulation frequencies (nF1±mF2), signaling integration of individual responses. An anterior intermodulation response was observed for face-to-face bodies, but not for back-to-back bodies, nor for face-to-face chairs and machines. These results show that interacting bodies are integrated into a representation that is more than the sum of its parts. This effect, specific to body dyads, may mark an early step in the transformation towards an integrated representation of a social event, from the visual representation of individual participants in that event.

Effects of altered-reality training on interocular disinhibition in amblyopia

Training of viewing an altered-reality environment dichoptically has been found to reactivate human adult ocular dominance plasticity, allowing improvement of vision for amblyopia. One suspected mechanism for this training effect is ocular dominance rebalancing through interocular disinhibition. Here, we investigated whether the training modulated the neural responses reflecting interocular inhibition. Thirteen patients with amblyopia and 11 healthy controls participated in this study. Before and after six daily altered-reality training sessions, participants watched flickering video stimuli with their steady-state visually evoked potential (SSVEP) signals recorded simultaneously. We assessed the amplitude of SSVEP response at intermodulation frequencies, which was a potential neural indicator of interocular suppression. The results showed that training weakened the intermodulation response only in the amblyopic group, which was in agreement with the hypothesis that the training reduced interocular suppression specific to amblyopia. Moreover, even one month after the training ended, we could still observe this neural training effect. These findings provide preliminary neural evidence in support of the disinhibition account for treating amblyopia. We also explain these results with the ocular opponency model, which, to our knowledge, is the first time for this binocular rivalry model to be used in explaining long-term ocular dominance plasticity.

Spatial and temporal (non)binding of audiovisual rhythms in sensorimotor synchronisation

Human movement synchronisation with moving objects strongly relies on visual input. However, auditory information also plays an important role, since real environments are intrinsically multimodal. We used electroencephalography (EEG) frequency tagging to investigate the selective neural processing and integration of visual and auditory information during motor tracking and tested the effects of spatial and temporal congruency between audiovisual modalities. EEG was recorded while participants tracked with their index finger a red flickering (rate f_V = 15 Hz) dot oscillating horizontally on a screen. The simultaneous auditory stimulus was modulated in pitch (rate f_A = 32 Hz) and lateralised between left and right audio channels to induce perception of a periodic displacement of the sound source. Audiovisual congruency was manipulated in terms of space in Experiment 1 (no motion, same direction or opposite direction), and timing in Experiment 2 (no delay, medium delay or large delay). For both experiments, significant EEG responses were elicited at f_V and f_A tagging frequencies. It was also hypothesised that intermodulation products corresponding to the nonlinear integration of visual and auditory stimuli at frequencies f_V ± f_A would be elicited, due to audiovisual integration, especially in Congruent conditions_. However, these components were not observed. Moreover, synchronisation and EEG results were not influenced by congruency manipulations, which invites further exploration of the conditions which may modulate audiovisual processing and the motor tracking of moving objects.

Decoding semantics from intermodulation responses in frequency-tagged stereotactic EEG

BACKGROUND

Humans perform object recognition using holistic processing, which is different from computers. Intermodulation responses in the steady-state visual evoked potential (SSVEP) of scalp electroencephalography (EEG) have recently been used as an objective label for holistic processing.

NEW METHOD

Using stereotactic EEG (sEEG) to record SSVEP directly from inside of the brain, we aimed to decode Chinese characters from non-characters with activation from multiple brain areas including occipital, parietal, temporal, and frontal cortices.

RESULTS

Semantic categories could be decoded from responses at the intermodulation frequency with high accuracy (80%-90%), but not the base frequency. Moreover, semantic categories could be decoded with activation from multiple areas including temporal, parietal, and frontal areas.

COMPARISON WITH EXISTING METHOD(S)

Previous studies investigated holistic processing in faces and words with frequency-tagged scalp EEGs. The current study extended the results to stereotactic EEG signals directly recorded from the brain.

CONCLUSIONS

The human brain applies holistic processing in recognizing objects like Chinese characters. Our findings could be extended to an add-on feature in the existing SSVEP BCI speller.

Intermodulation from Unisensory to Multisensory Perception: A Review

Previous intermodulation (IM) studies have employed two (or more) temporal modulations of a stimulus, with different local elements of the stimulus being modulated by different frequencies. Brain activities of IM obtained mainly from electroencephalograms (EEG) have been analyzed in the frequency domain. As a powerful tool, IM, which can provide a direct and objective physiological measure of neural interaction, has emerged as a promising method to decipher neural interactions in visual perception, and reveal the underlying different perceptual processing levels. In this review, we summarize the recent applications of IM in visual perception, detail the protocols and types of IM, and extend its utility and potential applications to the multisensory domain. We propose that using IM could prevail in partially revealing the potential hierarchical processing of multisensory information and contribute to a deeper understanding of the underlying brain dynamics.

The power of rhythms: how steady-state evoked responses reveal early neurocognitive development

Electroencephalography (EEG) is a non-invasive and painless recording of cerebral activity, particularly well-suited for studying young infants, allowing the inspection of cerebral responses in a constellation of different ways. Of particular interest for developmental cognitive neuroscientists is the use of rhythmic stimulation, and the analysis of steady-state evoked potentials (SS-EPs) - an approach also known as frequency tagging. In this paper we rely on the existing SS-EP early developmental literature to illustrate the important advantages of SS-EPs for studying the developing brain. We argue that (1) the technique is both objective and predictive: the response is expected at the stimulation frequency (and/or higher harmonics), (2) its high spectral specificity makes the computed responses particularly robust to artifacts, and (3) the technique allows for short and efficient recordings, compatible with infants' limited attentional spans. We additionally provide an overview of some recent inspiring use of the SS-EP technique in adult research, in order to argue that (4) the SS-EP approach can be implemented creatively to target a wide range of cognitive and neural processes. For all these reasons, we expect SS-EPs to play an increasing role in the understanding of early cognitive processes. Finally, we provide practical guidelines for implementing and analyzing SS-EP studies.

Ensemble size perception: Its neural signature and the role of global interaction over individual items

To efficiently process complex visual scenes, the visual system often summarizes statistical information across individual items and represents them as an ensemble. However, due to the lack of techniques to disentangle the representation of the ensemble from that of the individual items constituting the ensemble, whether there exists a specialized neural mechanism for ensemble processing and how ensemble perception is computed in the brain remain unknown. To address these issues, we used a frequency-tagging EEG approach to track brain responses to periodically updated ensemble sizes. Neural responses tracking the ensemble size were detected in parieto-occipital electrodes, revealing a global and specialized neural mechanism of ensemble size perception. We then used the temporal response function to isolate neural responses to the individual sizes and their interactions. Notably, while the individual sizes and their local and global interactions were encoded in the EEG signals, only the global interaction contributed directly to the ensemble size perception. Finally, distributed attention to the global stimulus pattern enhanced the neural signature of the ensemble size, mainly by modulating the neural representation of the global interaction between all individual sizes. These findings advocate a specialized, global neural mechanism of ensemble size perception and suggest that global interaction between individual items contributes to ensemble perception.

A Novel Hybrid Brain-Computer Interface Combining Motor Imagery and Intermodulation Steady-State Visual Evoked Potential

The hybrid brain-computer interface (hBCI) combining motor imagery (MI) and steady-state visual evoked potential (SSVEP) has been proven to have better performance than a pure MI- or SSVEP-based brain-computer interface (BCI). In most studies on hBCIs, subjects have been required to focus their attention on flickering light-emitting diodes (LEDs) or blocks while imagining body movements. However, these two classical tasks performed concurrently have a poor correlation. Therefore, it is necessary to reduce the task complexity of such a system and improve its user-friendliness. Aiming to achieve this goal, this study proposes a novel hybrid BCI that combines MI and intermodulation SSVEPs. In the proposed system, images of both hands flicker at the same frequency (i.e., 30 Hz) but at different grasp frequencies (i.e., 1 Hz for the left hand, and 1.5 Hz for the right hand), resulting in different intermodulation frequencies for encoding targets. Additionally, movement observation for subjects can help to perform the MI task better. In this study, two types of brain signals are classified independently and then fused by a scoring mechanism based on the probability distribution of relevant parameters. The online verification results showed that the average accuracies of 12 healthy subjects and 11 stroke patients were 92.40 ± 7.45% and 73.07 ± 9.07%, respectively. The average accuracies of 10 healthy subjects in the MI, SSVEP, and hybrid tasks were 84.00 ± 12.81%, 80.75 ± 8.08%, and 89.00 ± 9.94%, respectively. The high recognition accuracy verifies the feasibility and robustness of the proposed system. This study provides a novel and natural paradigm for a hybrid BCI based on MI and SSVEP.

Neural correlates of integration processes during dynamic face perception

Integrating the spatiotemporal information acquired from the highly dynamic world around us is essential to navigate, reason, and decide properly. Although this is particularly important in a face-to-face conversation, very little research to date has specifically examined the neural correlates of temporal integration in dynamic face perception. Here we present statistically robust observations regarding the brain activations measured via electroencephalography (EEG) that are specific to the temporal integration. To that end, we generate videos of neutral faces of individuals and non-face objects, modulate the contrast of the even and odd frames at two specific frequencies (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f_1$$\end{document}f1 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f_2$$\end{document}f2) in an interlaced manner, and measure the steady-state visual evoked potential as participants view the videos. Then, we analyze the intermodulation components (IMs: (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$nf_1\pm mf_2$$\end{document}nf1±mf2), a linear combination of the fundamentals with integer multipliers) that consequently reflect the nonlinear processing and indicate temporal integration by design. We show that electrodes around the medial temporal, inferior, and medial frontal areas respond strongly and selectively when viewing dynamic faces, which manifests the essential processes underlying our ability to perceive and understand our social world. The generation of IMs is only possible if even and odd frames are processed in succession and integrated temporally, therefore, the strong IMs in our frequency spectrum analysis show that the time between frames (1/60 s) is sufficient for temporal integration.

Steady state evoked potentials indicate changes in nonlinear neural mechanisms of vision in sight recovery individuals

Humans with a transient phase of congenital pattern vision deprivation have been observed to feature prevailing deficits, particularly in higher order visual functions. However, the neural correlates of these prevalent visual impairments remain unclear. To probe different visual processing stages, we measured steady state visual evoked potentials (SSVEPs) generated by luminance flicker stimuli at 6.1 Hz, with superimposed horizontal periodic motion at 2.1 Hz or 2.4 Hz. SSVEP responses at the fundamental and second harmonic of luminance flicker frequency, and at their intermodulation frequencies with motion information, were analyzed. Three groups were tested: (1) 15 individuals who had suffered a lack of pattern vision from birth due to the presence of bilateral total congenital cataracts (CC group), which were surgically removed between 4 months and 22 years of age, (2) 13 individuals with reversed developmental i.e., later developing cataracts (DC group), and (3) normally sighted control participants (SC group; n = 13) matched in age and sex to the CC individuals. SSVEPs at the second harmonic frequency (i.e., 12.2 Hz) and at the intermodulation frequencies (8.2 Hz, and 8.5 Hz) were attenuated in the CC group. In contrast, fundamental frequency responses (i.e., at 6.1 Hz) were not significantly altered in the CC group compared to the control groups (SC and DC groups). Based on previous evidence on the role of striate vs. extrastriate generators of fundamental vs. second harmonics of SSVEPs, these results provide evidence for a stronger experience dependence of extrastriate than striate cortical processing, and furthermore, suggest a sensitive period for the development of putative nonlinear neural mechanisms hypothesized to mediate visual feature binding.

A Deep Neural Network for SSVEP-based Brain-Computer Interfaces

OBJECTIVE

Target identification in brain-computer interface (BCI) spellers refers to the electroencephalogram (EEG) classification for predicting the target character that the subject intends to spell. When the visual stimulus of each character is tagged with a distinct frequency, the EEG records steady-state visually evoked potentials (SSVEP) whose spectrum is dominated by the harmonics of the target frequency. In this setting, we address the target identification and propose a novel deep neural network (DNN) architecture.

METHOD

The proposed DNN processes the multi-channel SSVEP with convolutions across the sub-bands of harmonics, channels, time, and classifies at the fully connected layer. We test with two publicly available large scale (the benchmark and BETA) datasets consisting of in total 105 subjects with 40 characters. Our first stage training learns a global model by exploiting the statistical commonalities among all subjects, and the second stage fine tunes to each subject separately by exploiting the individualities.

RESULTS

Our DNN achieves impressive information transfer rates (ITRs) on both datasets, 265.23 bits/min and 196.59 bits/min, respectively, with only 0.4 seconds of stimulation. The code is available for reproducibility at https://github.com/osmanberke/Deep-SSVEP-BCI.

CONCLUSION

The presented DNN strongly outperforms the state-of-the-art techniques as our accuracy and ITR rates are the highest ever reported performance results on these datasets.

SIGNIFICANCE

Due to its unprecedentedly high speller ITRs and flawless applicability to general SSVEP systems, our technique has great potential in various biomedical engineering settings of BCIs such as communication, rehabilitation and control.

The dynamics of reading complex words: evidence from steady-state visual evoked potentials

The present study used steady-state visual evoked potentials (SSVEPs) to examine the spatio-temporal dynamics of reading morphologically complex words and test the neurophysiological activation pattern elicited by stems and suffixes. Three different types of target words were presented to proficient readers in a delayed naming task: truly suffixed words (e.g., farmer), pseudo-suffixed words (e.g., corner), and non-suffixed words (e.g., cashew). Embedded stems and affixes were flickered at two different frequencies (18.75 Hz and 12.50 Hz, respectively). The stem data revealed an earlier SSVEP peak in the truly suffixed and pseudo-suffixed conditions compared to the non-suffixed condition, thus providing evidence for the form-based activation of embedded stems during reading. The suffix data also showed a dissociation in the SSVEP response between suffixes and non-suffixes with an additional activation boost for truly suffixed words. The observed differences are discussed in the context of current models of complex word recognition.

Steady state evoked potential (SSEP) responses in the primary and secondary somatosensory cortices of anesthetized cats: Nonlinearity characterized by harmonic and intermodulation frequencies

When presented with an oscillatory sensory input at a particular frequency, F [Hz], neural systems respond with the corresponding frequency, f [Hz], and its multiples. When the input includes two frequencies (F1 and F2) and they are nonlinearly integrated in the system, responses at intermodulation frequencies (i.e., n1*f1+n2*f2 [Hz], where n1 and n2 are non-zero integers) emerge. Utilizing these properties, the steady state evoked potential (SSEP) paradigm allows us to characterize linear and nonlinear neural computation performed in cortical neurocircuitry. Here, we analyzed the steady state evoked local field potentials (LFPs) recorded from the primary (S1) and secondary (S2) somatosensory cortex of anesthetized cats (maintained with alfaxalone) while we presented slow (F1 = 23Hz) and fast (F2 = 200Hz) somatosensory vibration to the contralateral paw pads and digits. Over 9 experimental sessions, we recorded LFPs from N = 1620 and N = 1008 bipolar-referenced sites in S1 and S2 using electrode arrays. Power spectral analyses revealed strong responses at 1) the fundamental (f1, f2), 2) its harmonic, 3) the intermodulation frequencies, and 4) broadband frequencies (50-150Hz). To compare the computational architecture in S1 and S2, we employed simple computational modeling. Our modeling results necessitate nonlinear computation to explain SSEP in S2 more than S1. Combined with our current analysis of LFPs, our paradigm offers a rare opportunity to constrain the computational architecture of hierarchical organization of S1 and S2 and to reveal how a large-scale SSEP can emerge from local neural population activities.

Holistic Integration in the Processing of Chinese Characters as Revealed by Electroencephalography Frequency Tagging

It is debated whether perceptual expertise of nonface objects, such as visual words, is indicated by holistic processing, which is regarded as a marker of perceptual expertise of faces. We address this question by frequency-tagged electroencephalography. Different parts of real or pseudo Chinese characters are presented at distinctive frequencies (6 or 7.2 Hz), which induce frequency-tagged steady-state visual-evoked potentials at occipital brain areas. The intermodulation response (e.g., 6 + 7.2 = 13.2 Hz) would emerge when holistic integration takes place. Our results suggest that the intermodulation response to the real characters is left lateralized, which is contralateral to previous findings with faces. Furthermore, at the left occipital area, the intermodulation response to real characters is more prominent than pseudo characters, suggesting that holistic integration is enhanced for real characters than for pseudo ones. Taken together, our findings suggest that holistic integration is potentially a general expertise marker for both faces and non-face objects.

The SSVEP tracks attention, not consciousness, during perceptual filling-in

Research on the neural basis of conscious perception has almost exclusively shown that becoming aware of a stimulus leads to increased neural responses. By designing a novel form of perceptual filling-in (PFI) overlaid with a dynamic texture display, we frequency-tagged multiple disappearing targets as well as their surroundings. We show that in a PFI paradigm, the disappearance of a stimulus and subjective invisibility is associated with increases in neural activity, as measured with steady-state visually evoked potentials (SSVEPs), in electroencephalography (EEG). We also find that this increase correlates with alpha-band activity, a well-established neural measure of attention. These findings cast doubt on the direct relationship previously reported between the strength of neural activity and conscious perception, at least when measured with current tools, such as the SSVEP. Instead, we conclude that SSVEP strength more closely measures changes in attention.

The Validity of Steady-State Visual Evoked Potentials as Attention Tags and Input Signals: A Critical Perspective of Frequency Allocation and Number of Stimuli

Steady-state visual evoked potential (SSVEP) is a periodic response to a repetitive visual stimulus at a specific frequency. Currently, SSVEP is widely treated as an attention tag in cognitive activities and is used as an input signal for brain-computer interfaces (BCIs). However, whether SSVEP can be used as a reliable indicator has been a controversial issue. We focused on the independence of SSVEP from frequency allocation and number of stimuli. First, a cue-target paradigm was adopted to examine the interaction between SSVEPs evoked by two stimuli with different frequency allocations under different attention conditions. Second, we explored whether signal strength and the performance of SSVEP-based BCIs were affected by the number of stimuli. The results revealed that no significant interaction of SSVEP responses appeared between attended and unattended stimuli under various frequency allocations, regardless of their appearance in the fundamental or second-order harmonic. The amplitude of SSVEP suffered no significant gain or loss under different numbers of stimuli, but the performance of SSVEP-based BCIs varied along with duration of stimuli; that is, the recognition rate was not affected by the number of stimuli when the duration of stimuli was long enough, while the information transfer rate (ITR) presented the opposite trend. It can be concluded that SSVEP is a reliable tool for marking and monitoring multiple stimuli simultaneously in cognitive studies, but much caution should be taken when choosing a suitable duration and the number of stimuli, in order to achieve optimal utility of BCIs in the future.

Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain

Functional neuroimaging experiments that employ naturalistic stimuli (natural scenes, films, spoken narratives) provide insights into cognitive function "in the wild". Natural stimuli typically possess crowded, spectrally dense, dynamic, and multimodal properties within a rich multiscale structure. However, when using natural stimuli, various challenges exist for creating parametric manipulations with tight experimental control. Here, we revisit the typical spectral composition and statistical dependences of natural scenes, which distinguish them from abstract stimuli. We then demonstrate how to selectively degrade subtle statistical dependences within specific spatial scales using the wavelet transform. Such manipulations leave basic features of the stimuli, such as luminance and contrast, intact. Using functional neuroimaging of human participants viewing degraded natural images, we demonstrate that cortical responses at different levels of the visual hierarchy are differentially sensitive to subtle statistical dependences in natural images. This demonstration supports the notion that perceptual systems in the brain are optimally tuned to the complex statistical properties of the natural world. The code to undertake these stimulus manipulations, and their natural extension to dynamic natural scenes (films), is freely available.

Electrophysiological correlates of gist perception: a steady-state visually evoked potentials study

Gist perception refers to perceiving the substance or general meaning of a scene. To investigate its neuronal mechanisms, we used the steady-state visually evoked potential (SSVEP) method—an evoked oscillatory cortical response at the same frequency as a visual stimulus flickered at this frequency. Two neighboring stimuli were flickered at different frequencies f₁ and f₂, for example, a drawing of a sun on the left side of the screen flickering at 8.6 Hz and the drawing of a parasol on the right side of the screen flickering at 12 Hz. SSVEPs enabled us to separate the responses to the two distinct stimuli by extracting oscillatory brain responses at f₁ and f₂. Additionally, it allowed to investigate intermodulation frequencies, that is, the brain’s response at a linear combination of f₁ and f₂ (here at f₁ + f₂ = 20.6 Hz) as an indicator of processing shared aspects of the input, that is, gist perception (here: a beach scene). We recorded high-density EEG of 18 participants. Results revealed clear and separable neuronal oscillations at f₁ and f₂. Additionally, occipital electrodes showed increased amplitudes at the intermodulation frequency in related as compared to unrelated pairs. The increase in intermodulation frequency was associated with bilateral temporal and parietal lobe activation, probably reflecting the interaction of local object representations as a basis for activating the gist network. The study demonstrates that SSVEPs are an excellent method to unravel mechanisms underlying the processing within multi-stimulus displays in the context of gist perception.

EEG based dynamic RDS recognition with frequency domain selection and bispectrum feature optimization

BACKGROUND

Stereopsis plays a vital role in many aspects of human daily life. Random-dot stereogram (RDS) is often used to detect stereoacuity and perform research on visual cognition. Electroencephalogram (EEG) is one of the commonly adopted visual cognition techniques due to its noninvasive collection.

NEW METHOD

In this study, a methodology named WPT-BED based on wavelet packet transform (WPT) and bispectral eigenvalues of differential signals (BED) is proposed, which can classify the three-pattern EEG signals evoked by dynamic RDS (DRDS). Specifically, the signals are decomposed into different frequency bands by WPT. The appropriate sub-bands are selected for reconstruction. Finally, the optimized bispectrum features are extracted for classification to achieve higher accuracy.

RESULTS

The classification performance of the proposed method in different periods of signal processing are investigated. The method WPT-BED has the highest classification accuracy 84.38%, and the average classification accuracy is 73.98%. The active channels with higher accuracy are focused on the visual pathway in the human cerebral cortex.

COMPARISON WITH EXISTING METHODS

Comparison with other methods for EEG signals classification is performed to identify the effectiveness of the proposed methodology.

CONCLUSIONS

The proposed methodology can effectively distinguish the EEG signals evoked by DRDS. It demonstrates the feasibility of DRDS recognition based on EEG.

40-Hz Binaural beats enhance training to mitigate the attentional blink

This study investigated whether binaural beat stimulation could accelerate the training outcome in an attentional blink (AB) task. The AB refers to the lapse in detecting a target T2 in rapid serial visual presentation (RSVP) after the identification of a preceding target T1. Binaural beats (BB) are assumed to entrain neural oscillations and support cognitive function. Participants were assigned into two groups and presented with BB sounds while performing the AB task on three subsequent days in a cross-over design. Group A was presented with 40-Hz BB during the first day and 16 Hz during the second day, while the order of beat frequencies was reversed in Group B. No sound was presented on the third day. MEG recordings confirmed a strong entrainment of gamma oscillations during 40-Hz BB stimulation and smaller gamma entrainment with 16-Hz BB. The rhythm of the visual stimulation elicited 10-Hz oscillations in occipital MEG sensors which were of similar magnitude for both BB frequencies. The AB performance did not increase within a session. However, participants improved between sessions, with overall improvement equal in both groups. Group A improved more after the first day than the second day. In contrast, group B gained more from the 40 Hz stimulation on the second day than from 16-Hz stimulation on the first day. Taken together, 40-Hz BB stimulation during training accelerates the training outcome. The improvement becomes evident not immediately, but after consolidation during sleep. Therefore, auditory beats stimulation is a promising method of non-invasive brain stimulation for enhancing training and learning which is well-suited to rehabilitation training.

Effects of Monocular Perceptual Learning on Binocular Visual Processing in Adolescent and Adult Amblyopia

Re-establishing normal binocular visual processing is the key to amblyopia recovery beyond the critical period of visual development. Here, by combining perceptual learning, behavioral testing, and steady-state visually evoked potentials (SSVEPs), we examined how monocular perceptual learning in the amblyopic eye could change binocular visual processing in the adolescent and adult amblyopic visual system. We found that training reduced the interocular difference between amblyopic and fellow eyes and increased the amplitude of a binocular SSVEP component, with a significant negative correlation between the two measures. Our results demonstrate that training in the amblyopic eye primarily improves binocular rather than monocular visual processing in the amblyopic visual system, suggesting that behavioral training could potentially address key neural deficits in adolescent and adult amblyopia.