The steady-state visual evoked potential in vision research: A review

Low frequency visual stimulation enhances slow wave activity without disrupting the sleep pattern in mice

Non-invasive stimulation technologies are emerging as potential treatment options for a range of neurodegenerative disorders. Experimental evidence suggests that stimuli-evoked changes in slow brain rhythms may mitigate or even prevent neuropathological and behavioral impairments. Slow wave activity is prevalent during sleep and can be triggered non-invasively by sensory stimulation targeting the visual system or directly via activation of neurons locally using optogenetics. Here, we developed new tools for delivering visual stimulation using light-emitting diodes in freely moving mice while awake and during sleep. We compared these tools to traditional optogenetic approaches used for local stimulation of neurons in the cerebral cortex. We then used these tools to compare the effects of low-frequency visual versus optogenetic stimulations on the slow wave activity and sleep pattern in mice. Visual stimulation effectively enhanced slow wave activity without disrupting the sleep pattern. Optogenetic stimulation of cortical GABAergic neurons increased NREM sleep. These results suggest that visual stimulation can be effective at boosting slow wave activity without having adverse effects on sleep and thus holds great potential as a non-invasive stimulation treatment strategy.

FB-EEGNet: A fusion neural network across multi-stimulus for SSVEP target detection

BACKGROUND

Steady-state visual evoked potential (SSVEP) is a prevalent paradigm of brain-computer interface (BCI). Recently, deep neural networks (DNNs) have been employed for SSVEP target recognition. However, current DNN models can not fully extract information from SSVEP harmonic components, and ignore the influence of non-target stimuli.

NEW METHOD

To employ information of multiple sub-bands and non-target stimulus data, we propose a DNN model for SSVEP target detection, i.e., FB-EEGNet, which fuses features of multiple neural networks. Additionally, we design a multi-label for each sample and optimize the parameters of FB-EEGNet across multi-stimulus to incorporate the information from non-target stimuli.

RESULTS

Under the subject-specific condition, FB-EEGNet achieves the average classification accuracies (information transfer rate (ITR)) of 76.75 % (50.70 bits/min) and 89.14 % (70.45 bits/min) in a time widow of 0.7 s under the public 12-target dataset and our experimental 9-target dataset, respectively. Under the cross-subject condition, FB-EEGNet achieved mean accuracies (ITRs) of 81.72 % (67.99 bits/min) and 92.15 % (76.12 bits/min) on the public and experimental datasets in a time window of 1 s, respectively.

COMPARISON WITH EXISTING METHODS

FB-EEGNet shows superior performance than CCNN, EEGNet, CCA and FBCCA both for subject-dependent and subject-independent SSVEP target recognition.

CONCLUSION

FB-EEGNet can effectively extract information from multiple sub-bands and cross-stimulus targets, providing a promising way for extracting deep features in SSVEP using neural networks.

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.

Inferring the nature of linguistic computations in the brain

Sentences contain structure that determines their meaning beyond that of individual words. An influential study by Ding and colleagues (2016) used frequency tagging of phrases and sentences to show that the human brain is sensitive to structure by finding peaks of neural power at the rate at which structures were presented. Since then, there has been a rich debate on how to best explain this pattern of results with profound impact on the language sciences. Models that use hierarchical structure building, as well as models based on associative sequence processing, can predict the neural response, creating an inferential impasse as to which class of models explains the nature of the linguistic computations reflected in the neural readout. In the current manuscript, we discuss pitfalls and common fallacies seen in the conclusions drawn in the literature illustrated by various simulations. We conclude that inferring the neural operations of sentence processing based on these neural data, and any like it, alone, is insufficient. We discuss how to best evaluate models and how to approach the modeling of neural readouts to sentence processing in a manner that remains faithful to cognitive, neural, and linguistic principles.

Deficits in auditory and visual steady-state responses in adolescents with bipolar disorder

BACKGROUND

Many aspects of steady-state responses of the brain remain unclear in bipolar disorder (BD) due to the small number of auditory steady-state response (ASSR) studies and the lack of steady-state visual evoked potential (SSVEP) studies on this complex disorder. Therefore, we assessed the patterns of SSVEP and ASSR in adolescents with BD during an active task to detect possible deficits in these important brain responses compared to normal subjects.

METHODS

27 adolescents with BD and 30 healthy adolescents were assessed in this study. The blinking background of the monitor presented at 15 Hz and the tone signal stimulation at 40 Hz evoked SSVEPs and ASSRs, respectively. The phase and amplitude of the steady-state responses were calculated in the auditory and visual conditions.

RESULTS

Patients exhibited a substantially worse performance in the motor control inhibition task during both auditory and visual modalities. Patients showed increased SSVEP amplitude and phase in the frontal region compared to control adolescents. Also, patients exhibited decreased ASSR amplitude in the prefrontal and increased ASSR amplitude in the right-frontal and centro-parietal areas compared to healthy adolescents.

CONCLUSIONS

impairments in the production and preservation of SSVEP and ASSR are evident in BD, implicating abnormalities in visual and auditory pathways. Neurophysiological deficits and worse performance in BD adolescents may imply that visual and auditory pathways cannot well transfer the pertinent information from arriving sensory data to the visual and auditory cortices, and the frontal cortex cannot well integrate incoming signals into a unified and coherent perceptual action.

Modelling neural entrainment and its persistence: influence of frequency of stimulation and phase at the stimulus offset

Neural entrainment, the synchronization of brain oscillations to the frequency of an external stimuli, is a key mechanism that shapes perceptual and cognitive processes.Objective.Using simulations, we investigated the dynamics of neural entrainment, particularly the period following the end of the stimulation, since the persistence (reverberation) of neural entrainment may condition future sensory representations based on predictions about stimulus rhythmicity.Methods.Neural entrainment was assessed using a modified Jansen-Rit neural mass model (NMM) of coupled cortical columns, in which the spectral features of the output resembled that of the electroencephalogram (EEG). We evaluated spectro-temporal features of entrainment as a function of the stimulation frequency, the resonant frequency of the neural populations comprising the NMM, and the coupling strength between cortical columns. Furthermore, we tested if the entrainment persistence depended on the phase of the EEG-like oscillation at the time the stimulus ended.Main Results.The entrainment of the column that received the stimulation was maximum when the frequency of the entrainer was within a narrow range around the resonant frequency of the column. When this occurred, entrainment persisted for several cycles after the stimulus terminated, and the propagation of the entrainment to other columns was facilitated. Propagation also depended on the resonant frequency of the second column, and the coupling strength between columns. The duration of the persistence of the entrainment depended on the phase of the neural oscillation at the time the entrainer terminated, such that falling phases (fromπ/2 to 3π/2 in a sine function) led to longer persistence than rising phases (from 0 toπ/2 and 3π/2 to 2π).Significance.The study bridges between models of neural oscillations and empirical electrophysiology, providing insights to the mechanisms underlying neural entrainment and the use of rhythmic sensory stimulation for neuroenhancement.

Ballistocardiogram suppression in concurrent EEG-MRI by dynamic modeling of heartbeats

The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called "dynamic modeling of heartbeats" (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside-MRI), echo-planar imaging (EPI-EEG), or fast MRI acquisition using simultaneous multi-slice and inverse imaging methods (SMS-InI-EEG). In a steady-state visual evoked response (SSVEP) paradigm, the 15-Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside-MRI, SMS-InI-EEG, and EPI-EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high-field MRI systems for neuroscientific and clinical applications.

Optimising the classification of feature-based attention in frequency-tagged electroencephalography data

Brain-computer interfaces (BCIs) are a rapidly expanding field of study and require accurate and reliable real-time decoding of patterns of neural activity. These protocols often exploit selective attention, a neural mechanism that prioritises the sensory processing of task-relevant stimulus features (feature-based attention) or task-relevant spatial locations (spatial attention). Within the visual modality, attentional modulation of neural responses to different inputs is well indexed by steady-state visual evoked potentials (SSVEPs). These signals are reliably present in single-trial electroencephalography (EEG) data, are largely resilient to common EEG artifacts, and allow separation of neural responses to numerous concurrently presented visual stimuli. To date, efforts to use single-trial SSVEPs to classify visual attention for BCI control have largely focused on spatial attention rather than feature-based attention. Here, we present a dataset that allows for the development and benchmarking of algorithms to classify feature-based attention using single-trial EEG data. The dataset includes EEG and behavioural responses from 30 healthy human participants who performed a feature-based motion discrimination task on frequency tagged visual stimuli.

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.

Cortical mechanisms of visual hypersensitivity in women at risk for chronic pelvic pain

ABSTRACT

Increased sensory sensitivity across non-nociceptive modalities is a common symptom of chronic pain conditions and is associated with chronic pain development. Providing a better understanding of the brain-behavior relationships that underlie multimodal hypersensitivity (MMH) may clarify the role of MMH in the development of chronic pain. We studied sensory hypersensitivity in a cohort of women (n = 147) who had diary confirmation of menstrual status and were enriched with risk factors for chronic pelvic pain, such as dysmenorrhea and increased bladder sensitivity. We administered 2 experimental tasks to evaluate the cross-modal relationship between visual and visceral sensitivity. Visual sensitivity was probed by presenting participants with a periodic pattern-reversal checkerboard stimulus presented across 5 brightness intensities during electroencephalography recording. Self-reported visual unpleasantness ratings for each brightness intensity were simultaneously assessed. Visceral sensitivity was evaluated with an experimental bladder-filling task associated with early clinical symptoms of chronic pelvic pain. Visually evoked cortical activity increased with brightness intensity across the entire scalp, especially at occipital electrode sites. Visual stimulation-induced unpleasantness was associated with provoked bladder pain and evoked primary visual cortex activity. However, the relationship between unpleasantness and cortical activity was moderated by provoked bladder pain. These results demonstrate that activity in the primary visual cortex is not greater in individuals with greater visceral sensitivity. We hypothesize that downstream interpretation or integration of this signal is amplified in individuals with visceral hypersensitivity. Future studies aimed at reducing MMH in chronic pain conditions should prioritize targeting of cortical mechanisms responsible for aberrant downstream sensory integration.

Forgotten rhythms? Revisiting the first evidence for rhythms in cognition

Practically every neuroscientist knows that human brain rhythms were first recorded in the 1920s by Hans Berger, who coined the term 'alpha waves' for the regular activity of around 10 cycles per second that was clearly visible in many of his recordings. Almost 100 years later, alpha rhythms are still the subject of active investigation and continue to intrigue researchers. What we have perhaps forgotten though, is the clever experimentation that was carried out during the first decades of electroencephalogram (EEG) research, often using sophisticated, custom-made analysis and stimulation devices. Here, I review selected findings from the early EEG literature regarding the character, origin, and meaning of human brain rhythms, beginning with Berger's publications and then focusing on the use of regular visual stimulation as a tool to understand intrinsic brain rhythms. It is clear that many of these findings are still relevant to open questions about the role of rhythmic brain activity. In addition, they also contain some general lessons for contemporary neuroscientists, meaning that there is great value in looking back at these forgotten publications.

eldBETA: A Large Eldercare-oriented Benchmark Database of SSVEP-BCI for the Aging Population

Global population aging poses an unprecedented challenge and calls for a rising effort in eldercare and healthcare. Steady-state visual evoked potential based brain-computer interface (SSVEP-BCI) boasts its high transfer rate and shows great promise in real-world applications to support aging. Public database is critically important for designing the SSVEP-BCI systems. However, the SSVEP-BCI database tailored for the elder is scarce in existing studies. Therefore, in this study, we present a large eldercare-oriented BEnchmark database of SSVEP-BCI for The Aging population (eldBETA). The eldBETA database consisted of the 64-channel electroencephalogram (EEG) from 100 elder participants, each of whom performed seven blocks of 9-target SSVEP-BCI task. The quality and characteristics of the eldBETA database were validated by a series of analyses followed by a classification analysis of thirteen frequency recognition methods. We expect that the eldBETA database would provide a substrate for the design and optimization of the BCI systems intended for the elders. The eldBETA database is open-access for research and can be downloaded from the website 10.6084/m9.figshare.18032669.

Measurement(s)	Steady-state visual evoked potential (SSVEP)
Technology Type(s)	Electroencephalography (EEG)
Factor Type(s)	Elder population
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	Electromagnetic shielding room

Applicability of a Novel Attunement Instrument and Its Relationship to Parental Sensitivity in Infants With and Without Visual Impairments

This study investigated the applicability of a novel instrument to assess parent–child attunement in free play interactions, in dyads with an infant with and without visual impairments (VI). We here report the findings on the reliability and applicability of the newly developed Attune & Stimulate Mother–Infant 56-items Instrument (A&S M-I) in two separate samples: one with infants with VI (N = 20) and one with typically sighted infants (N = 24). In addition, we assessed the contribution of parental sensitivity to attunement in dyadic interactions. The A&S M-I is an observational comprehensive instrument of behaviors that captures different body parts and their motility (i.e., finger movements, arm waving, and foot kicking), and different senses (i.e., audio, tactile, and visual). The appropriate responding of a parent to the child’s signal (i.e., matching and containing) reflects the ability to attune in the dyad as well as parent’s ability to stimulate the child to become engaged in the contact or activity. Consistency assessments revealed good reliability for maternal and infant behaviors, acceptable internal consistency and good test–retest reliability. Furthermore, both samples scored significantly above chance level on attunement, suggesting that the instrument captures parent–infant behavioral coordination, and VI was not related to parent–infant attunement. Lastly, a relation between parental sensitivity and attunement was found only in the TS sample. Altogether, these findings provide promising initial evidence of the applicability of the A&S M-I instrument for assessing dyadic attunement across different populations and ages. Having assessed the applicability of this observational instrument, future work should corroborate these findings in larger samples.

EEG Measurement for Suppression in Refractive Amblyopia and Push-pull Perception Efficacy

In order to evaluate refractive amblyopia suppression and understand the neural mechanism of amblyopia suppression and push-pull perception training, we recorded the EEG of refractive amblyopia children before, during, and after push-pull perception training. We compared the brain activity in different states through the steady-state visual evoked potentials (SSVEPs) response and power topography and compared them with normal children. We found that amblyopic and fellow eyes have different performances in fundamental and harmonic frequency responses. They also show different characteristics when be masked. Push-pull perception training improved the SSVEP performance of amblyopia children by reducing the SSVEP response difference between eyes and improving the intermodulation frequency response. The result of topography showed that push-pull perception reduced the alpha power of occipital and temporal lobes, which was conducive to improving binocular function. The changes of intermodulation response and occipital alpha power were significantly correlated with the clinical indicator. Thus, EEG is a potential method to measure amblyopia suppression and the efficacy of push-pull perception.

High-Density Electroencephalography-Informed Multiband Functional Magnetic Resonance Imaging Reveals Rhythm-Specific Activations Within the Trigeminal Nociceptive Network

The interest in exploring trigeminal pain processing has grown in recent years, mainly due to various pathologies (such as migraine) related to this system. However, research efforts have mainly focused on understanding molecular mechanisms or studying pathological states. On the contrary, non-invasive imaging studies are limited by either spatial or temporal resolution depending on the modality used. This can be overcome by using multimodal imaging techniques such as simultaneous functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Although this technique has already been applied to neuroscientific research areas and consequently gained insights into diverse sensory systems and pathologies, only a few studies have applied EEG-fMRI in the field of pain processing and none in the trigeminal system. Focusing on trigeminal nociception, we used a trigeminal pain paradigm, which has been well-studied in either modality. For validation, we first acquired stand-alone measures with each imaging modality before fusing them in a simultaneous session. Furthermore, we introduced a new, yet simple, non-parametric correlation technique, which exploits trial-to-trial variance of both measurement techniques with Spearman’s correlations, to consolidate the results gained by the two modalities. This new technique does not presume a linear relationship and needs a few repetitions per subject. We also showed cross-validation by analyzing visual stimulations. Using these techniques, we showed that EEG power changes in the theta-band induced by trigeminal pain correlate with fMRI activation within the brainstem, whereas those of gamma-band oscillations correlate with BOLD signals in higher cortical areas.

Novel Invisible Spectral Flicker Induces 40 Hz Neural Entrainment with Similar Spatial Distribution as 40 Hz Stroboscopic Light

Background: Exposure to 40 Hz stroboscopic light, for one hour a day, has previously been published as a potential treatment option for Alzheimer’s disease in animal models. However, exposure for an hour a day to 40 Hz stroboscopic light can be strenuous and examining other types of 40 Hz inducing stimuli is paramount if chronic treatment is wanted. Objective: A core assumption behind ensuring a therapeutic outcome is that the visual stimuli can induce 40 Hz gamma entrainment. Here, we examine whether a specific visual stimulus, 40 Hz invisible spectral flicker (ISF), can induce gamma entrainment and how it differs from both continuous light (CON) and 40 Hz stroboscopic light (STROBE). Methods: The study included non-simultaneous EEG-fMRI neuroimaging of 13 young healthy volunteers during light exposure. Each light condition (i.e., CON, ISF, or STROBE) was active for 30 seconds followed immediately by the next. Results: Entrainment of 40 Hz neural activity were significantly higher signal-to-noise ratio during exposure to ISF (mean: 3.03, 95% CI 2.07 to 3.99) and STROBE (mean: 12.04, 95% CI 10.18 to 13.87) compared to CON. Additionally STROBE had a higher entrainment than ISF (mean: 9.01, 95% CI 7.16 to 12.14). Conclusion: This study presents a novel method of 40 Hz entrainment using ISF. This enables the possibility of future randomized placebo-controlled clinical trials with acceptable double blinding due to the essentially imperceivable flicker, which is expected to substantially reduce discomfort compared to interventions with stroboscopic flicker.

Local Interactions between Steady-State Visually Evoked Potentials at Nearby Flickering Frequencies

Steady-state visually evoked potentials (SSVEPs) are widely used to index top-down cognitive processing in human electroencephalogram (EEG) studies. Typically, two stimuli flickering at different temporal frequencies (TFs) are presented, each producing a distinct response in the EEG at its flicker frequency. However, how SSVEP responses in EEGs are modulated in the presence of a competing flickering stimulus just because of sensory interactions is not well understood. We have previously shown in local field potentials (LFPs) recorded from awake monkeys that when two overlapping full-screen gratings are counterphased at different TFs, there is an asymmetric SSVEP response suppression, with greater suppression from lower TFs, which further depends on the relative orientations of the gratings (stronger suppression and asymmetry for parallel compared with orthogonal gratings). Here, we first confirmed these effects in both male and female human EEG recordings. Then, we mapped the response suppression of one stimulus (target) by a competing stimulus (mask) over a much wider range than the previous study. Surprisingly, we found that the suppression was not stronger at low frequencies in general, but systematically varied depending on the target TF, indicating local interactions between the two competing stimuli. These results were confirmed in both human EEG and monkey LFP and electrocorticogram (ECoG) data. Our results show that sensory interactions between multiple SSVEPs are more complex than shown previously and are influenced by both local and global factors, underscoring the need to cautiously interpret the results of studies involving SSVEP paradigms.SIGNIFICANCE STATEMENT Steady-state visually evoked potentials (SSVEPs) are extensively used in human cognitive studies and brain-computer interfacing applications where multiple stimuli flickering at distinct frequencies are concurrently presented in the visual field. We recently characterized interactions between competing flickering stimuli in animal recordings and found that stimuli flickering slowly produce larger suppression. Here, we confirmed these in human EEGs, and further characterized the interactions by using a much wider range of target and competing (mask) frequencies in both human EEGs and invasive animal recordings. These revealed a new "local" component, whereby the suppression increased when competing stimuli flickered at nearby frequencies. Our results highlight the complexity of sensory interactions among multiple SSVEPs and underscore the need to cautiously interpret studies involving SSVEP paradigms.

Visual cortex responds to sound onset and offset during passive listening

Sounds enhance our ability to detect, localize, and respond to co-occurring visual targets. Research suggests that sounds improve visual processing by resetting the phase of ongoing oscillations in visual cortex. However, it remains unclear what information is relayed from the auditory system to visual areas and if sounds modulate visual activity even in the absence of visual stimuli (e.g., during passive listening). Using intracranial electroencephalography (iEEG) in humans, we examined the sensitivity of visual cortex to three forms of auditory information during a passive listening task: auditory onset responses, auditory offset responses, and rhythmic entrainment to sounds. Because some auditory neurons respond to both sound onsets and offsets, visual timing and duration processing may benefit from each. Additionally, if auditory entrainment information is relayed to visual cortex, it could support the processing of complex stimulus dynamics that are aligned between auditory and visual stimuli. Results demonstrate that in visual cortex, amplitude-modulated sounds elicited transient onset and offset responses in multiple areas, but no entrainment to sound modulation frequencies. These findings suggest that activity in visual cortex (as measured with iEEG in response to auditory stimuli) may not be affected by temporally fine-grained auditory stimulus dynamics during passive listening (though it remains possible that this signal may be observable with simultaneous auditory-visual stimuli). Moreover, auditory responses were maximal in low-level visual cortex, potentially implicating a direct pathway for rapid interactions between auditory and visual cortices. This mechanism may facilitate perception by time-locking visual computations to environmental events marked by auditory discontinuities.

Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series

Since its beginnings in the early 20th century, the psychophysiological study of human brain function has included research into the spectral properties of electrical and magnetic brain signals. Now, dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods, with a focus on foundational aspects of frequency domain and time-frequency analyses. It also provides publication guidelines, which aim to (1) foster replication and scientific rigor, (2) assist new researchers who wish to enter the field of brain oscillations, and (3) facilitate communication among authors, reviewers, and editors.

EEG frequency tagging evidence of social interaction recognition

Previous neuroscience studies have provided important insights into the neural processing of third-party social interaction recognition. Unfortunately, however, the methods they used are limited by a high susceptibility to noise. Electroencephalogram (EEG) frequency tagging is a promising technique to overcome this limitation, as it is known for its high signal-to-noise ratio. So far, EEG frequency tagging has mainly been used with simplistic stimuli (e.g. faces), but more complex stimuli are needed to study social interaction recognition. It therefore remains unknown whether this technique could be exploited to study third-party social interaction recognition. To address this question, we first created and validated a wide variety of stimuli that depict social scenes with and without social interaction, after which we used these stimuli in an EEG frequency tagging experiment. As hypothesized, we found enhanced neural responses to social scenes with social interaction compared to social scenes without social interaction. This effect appeared laterally at occipitoparietal electrodes and strongest over the right hemisphere. Hence, we find that EEG frequency tagging can measure the process of inferring social interaction from varying contextual information. EEG frequency tagging is particularly valuable for research into populations that require a high signal-to-noise ratio like infants, young children and clinical populations.

Naturalistic viewing conditions can increase task engagement and aesthetic preference but have only minimal impact on EEG quality

Free gaze and moving images are typically avoided in EEG experiments due to the expected generation of artifacts and noise. Yet for a growing number of research questions, loosening these rigorous restrictions would be beneficial. Among these is research on visual aesthetic experiences, which often involve open-ended exploration of highly variable stimuli. Here we systematically compare the effect of conservative vs. more liberal experimental settings on various measures of behavior, brain activity and physiology in an aesthetic rating task. Our primary aim was to assess EEG signal quality. 43 participants either maintained fixation or were allowed to gaze freely, and viewed either static images or dynamic (video) stimuli consisting of dance performances or nature scenes. A passive auditory background task (auditory steady-state response; ASSR) was added as a proxy measure for overall EEG recording quality. We recorded EEG, ECG and eyetracking data, and participants rated their aesthetic preference and state of boredom on each trial. Whereas both behavioral ratings and gaze behavior were affected by task and stimulus manipulations, EEG SNR was barely affected and generally robust across all conditions, despite only minimal preprocessing and no trial rejection. In particular, we show that using video stimuli does not necessarily result in lower EEG quality and can, on the contrary, significantly reduce eye movements while increasing both the participants' aesthetic response and general task engagement. We see these as encouraging results indicating that - at least in the lab - more liberal experimental conditions can be adopted without significant loss of signal quality.

Dual Passive Reactive Brain-Computer Interface: A Novel Approach to Human-Machine Symbiosis

The present study proposes a novel concept of neuroadaptive technology, namely a dual passive-reactive Brain-Computer Interface (BCI), that enables bi-directional interaction between humans and machines. We have implemented such a system in a realistic flight simulator using the NextMind classification algorithms and framework to decode pilots' intention (reactive BCI) and to infer their level of attention (passive BCI). Twelve pilots used the reactive BCI to perform checklists along with an anti-collision radar monitoring task that was supervised by the passive BCI. The latter simulated an automatic avoidance maneuver when it detected that pilots missed an incoming collision. The reactive BCI reached 100% classification accuracy with a mean reaction time of 1.6 s when exclusively performing the checklist task. Accuracy was up to 98.5% with a mean reaction time of 2.5 s when pilots also had to fly the aircraft and monitor the anti-collision radar. The passive BCI achieved a F1-score of 0.94. This first demonstration shows the potential of a dual BCI to improve human-machine teaming which could be applied to a variety of applications.

Smell what you hardly see: Odors assist visual categorization in the human brain

Visual categorization is the brain ability to rapidly and automatically respond to a certain category of inputs. Whether category-selective neural responses are purely visual or can be influenced by other sensory modalities remains unclear. Here, we test whether odors modulate visual categorization, expecting that odors facilitate the neural categorization of congruent visual objects, especially when the visual category is ambiguous. Scalp electroencephalogram (EEG) was recorded while natural images depicting various objects were displayed in rapid 12-Hz streams (i.e., 12 images / second) and variable exemplars of a target category (either human faces, cars, or facelike objects in dedicated sequences) were interleaved every 9^th stimulus to tag category-selective responses at 12/9 = 1.33 Hz in the EEG frequency spectrum. During visual stimulation, participants (N = 26) were implicitly exposed to odor contexts (either body, gasoline or baseline odors) and performed an orthogonal cross-detection task. We identify clear category-selective responses to every category over the occipito-temporal cortex, with the largest response for human faces and the lowest for facelike objects. Critically, body odor boosts the response to the ambiguous facelike objects (i.e., either perceived as nonface objects or faces) over the right hemisphere, especially for participants reporting their presence post-stimulation. By contrast, odors do not significantly modulate other category-selective responses, nor the general visual response recorded at 12 Hz, revealing a specific influence on the categorization of congruent ambiguous stimuli. Overall, these findings support the view that the brain actively uses cues from the different senses to readily categorize visual inputs, and that olfaction, which has long been considered as poorly functional in humans, is well placed to disambiguate visual information.

Evoked responses to rhythmic visual stimulation vary across sources of intrinsic alpha activity in humans

Rhythmic flickering visual stimulation produces steady-state visually evoked potentials (SSVEPs) in electroencephalogram (EEG) recordings. Based on electrode-level analyses, two dichotomous models of the underpinning mechanisms leading to SSVEP generation have been proposed: entrainment or superposition, i.e., phase-alignment or independence of endogenous brain oscillations from flicker-induced oscillations, respectively. Electrode-level analyses, however, represent an averaged view of underlying 'source-level' activity, at which variability in SSVEPs may lie, possibly suggesting the co-existence of multiple mechanisms. To probe this idea, we investigated the variability of SSVEPs derived from the sources underpinning scalp EEG responses during presentation of a flickering radial checkerboard. Flicker was presented between 6 and 12 Hz in 1 Hz steps, and at individual alpha frequency (IAF i.e., the dominant frequency of endogenous alpha oscillatory activity). We tested whether sources of endogenous alpha activity could be dissociated according to evoked responses to different flicker frequencies relative to IAF. Occipitoparietal sources were identified by temporal independent component analysis, maximal resting-state alpha power at IAF and source localisation. The pattern of SSVEPs to rhythmic flicker relative to IAF was estimated by correlation coefficients, describing the correlation between the peak-to-peak amplitude of the SSVEP and the absolute distance of the flicker frequency from IAF across flicker conditions. We observed extreme variability in correlation coefficients across sources, ranging from -0.84 to 0.93, with sources showing largely different coefficients co-existing within subjects. This result demonstrates variation in evoked responses to flicker across sources of endogenous alpha oscillatory activity. Data support the idea of multiple SSVEP mechanisms.

Oscillatory entrainment to our early social or physical environment and the emergence of volitional control

An individual's early interactions with their environment are thought to be largely passive; through the early years, the capacity for volitional control develops. Here, we consider: how is the emergence of volitional control characterised by changes in the entrainment observed between internal activity (behaviour, physiology and brain activity) and the sights and sounds in our everyday environment (physical and social)? We differentiate between contingent responsiveness (entrainment driven by evoked responses to external events) and oscillatory entrainment (driven by internal oscillators becoming temporally aligned with external oscillators). We conclude that ample evidence suggests that children show behavioural, physiological and neural entrainment to their physical and social environment, irrespective of volitional attention control; however, evidence for oscillatory entrainment beyond contingent responsiveness is currently lacking. Evidence for how oscillatory entrainment changes over developmental time is also lacking. Finally, we suggest a mechanism through which periodic environmental rhythms might facilitate both sensory processing and the development of volitional control even in the absence of oscillatory entrainment.

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.

The Influence of the Modulation Index on Frequency-Modulated Steady-State Visual Evoked Potentials

Based on increased user experience during stimulation, frequency-modulated steady-state visual evoked potentials (FM-SSVEPs) have been suggested as an improved stimulation method for brain-computer interfaces. Adapting such a novel stimulation paradigm requires in-depth analyses of all different stimulation parameters and their influence on brain responses as well as the user experience during the stimulation. In the current manuscript, we assess the influence of different values for the modulation index, which determine the spectral distribution in the stimulation signal on FM-SSVEPs. We visually stimulated 14 participants at different target frequencies with four different values for the modulation index. Our results reveal that changing the modulation index in a way that elevates the stimulation power in the targeted sideband leads to increased FM-SSVEP responses. There is, however, a tradeoff with user experience as increased modulation indices also lead to increased perceived flicker intensity as well as decreased stimulation comfort in our participants. Our results can guide the choice of parameters in future FM-SSVEP implementations.

The Relationship Between Stage of Leber's Hereditary Optic Neuropathy and Pattern Electroretinogram Latency

Purpose

The purpose of this study was to compare the baseline steady-state pattern electroretinogram (SS-PERG) of patients with G11778A Leber hereditary optic neuropathy (LHON) with different stages of visual acuity (VA) loss before allotopic gene therapy (GT).

Methods

Patients (n = 28) were enrolled into groups (GT I: chronic bilateral VA ≤35 Early Treatment Diabetic Retinopathy Study [ETDRS]; GT II: acute bilateral VA ≤35 ETDRS; GT III: acute unilateral, VA ≤35 ETDRS, and better eye VA ≥70 ETDRS) and tested with SS-PERG together with 210 age-matched normal controls (NCs). SS-PERG amplitude (nV) and latency (ms) of each eye were averaged for groups GT I, GT II, and NC. Symptomatic eyes (GT III-S) and asymptomatic eyes (GT III-A) of group GT III were included separately and accounted for by using generalized estimating equation (GEE) methods.

Results

Compared to NC, SS-PERG amplitudes were reduced similarly by approximately 50% (P < 0.001) among all GT groups (NC > GT I, GT II, GT III-S, and GT III-A). SS-PERG latencies were shorter by ≥3.5 ms in all LHON groups and differed by disease stage (G III-A < NC, P = 0.002; GT III-S < GT III-A, P = 0.01; GT II < GT III-S, P = 0.03; GT I < NC, P < 0.001, but not different from other GT groups, all P > 0.1).

Conclusions

Although SS-PERG amplitude reduction did not distinguish between disease stages, SS-PERG latency shortening occurred in asymptomatic eyes and symptomatic eyes and distinguished between disease stages.

Translational Relevance

SS-PERG latency shortening is consistent with primary damage of smaller/slower axons and sparing of larger/faster axons and may provide an objective staging of LHON, which may be helpful to determine efficacy in LHON trials.

Perception is associated with the brain's metabolic response to sensory stimulation

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here we show in human primary visual cortex (V1) that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level dependent functional MRI (BOLD-fMRI) have markedly different neurometabolic responses as measured by functional MRS. In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate-aspartate shuttle, occurred in V1 only when the flickering was perceived, without any relation with behavioral or physiological variables. Whereas the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering, indicating increased output from V1. These results demonstrate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD fMRI.

Supramodality of neural entrainment: Rhythmic visual stimulation causally enhances auditory working memory performance

The frontoparietal network is involved in multiple tasks, such as visual mental rotation, working memory, or arithmetic. Whether those different cognitive processes are supported by the same supramodal network or distinct, but overlapping, functional systems is unresolved. We investigate whether frontoparietal activity can be selectively entrained by rhythmic sensory stimulations (visual rotation) and whether this entrainment can causally modulate task performance in another modality (auditory working memory). We show that rhythmic visual presentations of rotating shapes, known to activate the dorsal pathway, increase frontoparietal connectivity at stimulation frequency as measured with MEG/EEG. We then show that frontoparietal theta oscillations predict auditory working memory performance. Last, we demonstrate that theta rhythmic visual stimulation applied during auditory memory causally enhances performance, and both the rotating properties of the stimulus and its flickering frequency drive the effect. This study provides causal evidence of the supramodal role of the frontoparietal network in human cognition.

Nonlinearity in bone-conducted amplitude-modulated cervical vestibular evoked myogenic potentials: Harmonic distortion products

Otolith organs of the balance system, the saccule and utricle, encode linear acceleration. Integrity of the saccule is commonly assessed using cervical vestibular evoked myogenic potentials (cVEMPs) arising from an inhibitory reflex along the vestibulospinal pathway. Conventional approaches to eliciting these responses use brief, transient sounds to elicit onset responses. Here we used long-duration amplitude-modulated (AM) tones to elicit cVEMPs (AMcVEMPs) and analyzed their spectral content for evidence of nonlinear processing consistent with known characteristics of vestibular hair cells. Twelve young adults (ages 21-25) with no hearing or vestibular pathologies participated in this study. AMcVEMPs were elicited by bone-conducted AM tones with a 500 Hz carrier frequency. Eighteen modulation frequencies were used between 7 and 403 Hz. All participants had robust distortion products at harmonics of the modulation frequency. Total harmonic distortion ranged from approximately 10 to 80%. AMcVEMPs contain harmonic distortion products consistent with vestibular hair cell nonlinearities, and this new approach to studying the otolith organs may provide a non-invasive, in vivo method to study nonlinearity of vestibular hair cells in humans.

Monitoring the effect of oxytocin on the neural sensitivity to emotional faces via frequency-tagging EEG: A double-blind, cross-over study

The neuropeptide oxytocin (OXT) is suggested to exert an important role in human social behaviors by modulating the salience of social cues. To date, however, there is mixed evidence whether a single dose of OXT can improve the behavioral and neural sensitivity for emotional face processing. To overcome difficulties encountered with classic event-related potential studies assessing stimulus-saliency, we applied frequency-tagging EEG to implicitly assess the effect of a single dose of OXT (24 IU) on the neural sensitivity for positive and negative facial emotions. Neutral faces with different identities were presented at 6 Hz, periodically interleaved with an expressive face (angry, fearful, and happy, in separate sequences) every fifth image (i.e., 1.2 Hz oddball frequency). These distinctive frequency tags for neutral and expressive stimuli allowed direct and objective quantification of the neural expression-categorization responses. The study involved a double-blind, placebo-controlled, cross-over trial with 31 healthy adult men. Contrary to our expectations, we did not find an effect of OXT on facial emotion processing, neither at the neural, nor at the behavioral level. A single dose of OXT did not evoke social enhancement in general, nor did it affect social approach-avoidance tendencies. Possibly ceiling performances in facial emotion processing might have hampered further improvement.

Hyperintensities of middle frontal gyrus in patients with diabetic optic neuropathy: a dynamic amplitude of low-frequency fluctuation study

Diabetic optic neuropathy (DON) is a diverse complication of diabetes and its pathogenesis has not been fully elucidated. The purpose of this study was to explore dynamic cerebral activity changes in DON patients using dynamic amplitude of low-frequency fluctuation (dALFF). In total, 22 DON patients and 22 healthy controls were enrolled. The dALFF approach was used in all participants to investigate dynamic intrinsic brain activity differences between the two groups. Compared with HCs, DON patients exhibited significantly increased dALFF variability in the right middle frontal gyrus (P < 0.01). Conversely, DON patients exhibited obviously decreased dALFF variability in the right precuneus (P < 0.01). We also found that there were significant negative correlations between HADS scores and dALFF values of the right middle frontal gyrus in the DON patients (r = -0.6404, P <0.01 for anxiety and r = -0.6346, P <0.01 for depression; HADS, Hospital Anxiety and Depression Scale). Abnormal variability of dALFF was observed in specific areas of the cerebrum in DON patients, which may contribute to distinguishing patients with DON from HCs and a better understanding of DON, hyperintensities of right middle frontal gyrus may be potential diagnostic marker for DON.

The FreqTag toolbox: A principled approach to analyzing electrophysiological time series in frequency tagging paradigms

Steady-state visual evoked potential (ssVEP) frequency tagging is an increasingly used method in electrophysiological studies of visual attention and perception. Frequency tagging is suitable for studies examining a wide range of populations, including infants and children. Frequency tagging involves the presentation of different elements of a visual array at different temporal rates, thus using stimulus timing to “tag” the brain response to a given element by means of a unique time signature. Leveraging the strength of the ssVEP frequency tagging method to isolate brain responses to concurrently presented and spatially overlapping visual objects requires specific signal processing methods. Here, we introduce the FreqTag suite of functions, an open source MATLAB toolbox. The purpose of the FreqTag toolbox is three-fold. First, it will equip users with a set of transparent and reproducible analytical tools for the analysis of ssVEP data. Second, the toolbox is designed to illustrate fundamental features of frequency domain and time-frequency domain approaches. Finally, decision criteria for the application of different functions and analyses are described. To promote reproducibility, raw algorithms are provided in a modular fashion, without additional hidden functions or transformations. This approach is intended to facilitate a fundamental understanding of the transformations and algorithmic steps in FreqTag, and to allow users to visualize and test each step in the toolbox.

Intracerebral electrical stimulation of the right anterior fusiform gyrus impairs human face identity recognition

Brain regions located between the right fusiform face area (FFA) in the middle fusiform gyrus and the temporal pole may play a critical role in human face identity recognition but their investigation is limited by a large signal drop-out in functional magnetic resonance imaging (fMRI). Here we report an original case who is suddenly unable to recognize the identity of faces when electrically stimulated on a focal location inside this intermediate region of the right anterior fusiform gyrus. The reliable transient identity recognition deficit occurs without any change of percept, even during nonverbal face tasks (i.e., pointing out the famous face picture among three options; matching pictures of unfamiliar or familiar faces for their identities), and without difficulty at recognizing visual objects or famous written names. The effective contact is associated with the largest frequency-tagged electrophysiological signals of face-selectivity and of familiar and unfamiliar face identity recognition. This extensive multimodal investigation points to the right anterior fusiform gyrus as a critical hub of the human cortical face network, between posterior ventral occipito-temporal face-selective regions directly connected to low-level visual cortex, the medial temporal lobe involved in generic memory encoding, and ventral anterior temporal lobe regions holding semantic associations to people's identity.

Nociceptive Intra-epidermal Electric Stimulation Evokes Steady-State Responses in the Secondary Somatosensory Cortex

Recent studies have established the presence of nociceptive steady-state evoked potentials (SSEPs), generated in response to thermal or intra-epidermal electric stimuli. This study explores cortical sources and generation mechanisms of nociceptive SSEPs in response to intra-epidermal electric stimuli. Our method was to stimulate healthy volunteers (n = 22, all men) with 100 intra-epidermal pulse sequences. Each sequence had a duration of 8.5 s, and consisted of pulses with a pulse rate between 20 and 200 Hz, which was frequency modulated with a multisine waveform of 3, 7 and 13 Hz (n = 10, 1 excluded) or 3 and 7 Hz (n = 12, 1 excluded). As a result, evoked potentials in response to stimulation onset and contralateral SSEPs at 3 and 7 Hz were observed. The SSEPs at 3 and 7 Hz had an average time delay of 137 ms and 143 ms respectively. The evoked potential in response to stimulation onset had a contralateral minimum (N1) at 115 ms and a central maximum (P2) at 300 ms. Sources for the multisine SSEP at 3 and 7 Hz were found through beamforming near the primary and secondary somatosensory cortex. Sources for the N1 were found near the primary and secondary somatosensory cortex. Sources for the N2-P2 were found near the supplementary motor area. Harmonic and intermodulation frequencies in the SSEP power spectrum remained below a detectable level and no evidence for nonlinearity of nociceptive processing, i.e. processing of peripheral firing rate into cortical evoked potentials, was found.

Does Oblique Effect Affect SSVEP-Based Visual Acuity Assessment?

This study aimed to explore whether there was an effect on steady-state visual evoked potential (SSVEP) visual acuity assessment from the oblique effect or the stimulus orientation. SSVEPs were induced by seven visual stimuli, e.g., the reversal sinusoidal gratings with horizontal, two oblique, and vertical orientations, reversal checkerboards with vertical and oblique orientations, and oscillating expansion-contraction concentric-rings, at six spatial frequency steps. Ten subjects participated in the experiment. Subsequently, a threshold estimation criterion was used to determine the objective SSVEP visual acuity corresponding to each visual stimulus. Taking the SSVEP amplitude and signal-to-noise-ratio (SNR) of the fundamental reversal frequency as signal characteristics, both the SSVEP amplitude and SNR induced by the reversal sinusoidal gratings at 3.0 cpd among four stimulus orientations had no significant difference, and the same finding was also shown in the checkerboards between vertical and oblique orientation. In addition, the SSVEP visual acuity obtained by the threshold estimation criterion for all seven visual stimuli showed no significant difference. This study demonstrated that the SSVEPs induced by all these seven visual stimuli had a similarly good performance in evaluating visual acuity, and the oblique effect or the stimulus orientation had little effect on SSVEP response as well as the SSVEP visual acuity.

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.

Assessing the Effect of the Refresh Rate of a Device on Various Motion Stimulation Frequencies Based on Steady-State Motion Visual Evoked Potentials

The refresh rate is one of the important parameters of visual presentation devices, and assessing the effect of the refresh rate of a device on motion perception has always been an important direction in the field of visual research. This study examined the effect of the refresh rate of a device on the motion perception response at different stimulation frequencies and provided an objective visual electrophysiological assessment method for the correct selection of display parameters in a visual perception experiment. In this study, a flicker-free steady-state motion visual stimulation with continuous scanning frequency and different forms (sinusoidal or triangular) was presented on a low-latency LCD monitor at different refresh rates. Seventeen participants were asked to observe the visual stimulation without head movement or eye movement, and the effect of the refresh rate was assessed by analyzing the changes in the intensity of their visual evoked potentials. The results demonstrated that an increased refresh rate significantly improved the intensity of motion visual evoked potentials at stimulation frequency ranges of 7-28 Hz, and there was a significant interaction between the refresh rate and motion frequency. Furthermore, the increased refresh rate also had the potential to enhance the ability to perceive similar motion. Therefore, we recommended using a refresh rate of at least 120 Hz in motion visual perception experiments to ensure a better stimulation effect. If the motion frequency or velocity is high, a refresh rate of≥240 Hz is also recommended.

NEAR: An artifact removal pipeline for human newborn EEG data

Electroencephalography (EEG) is arising as a valuable method to investigate neurocognitive functions shortly after birth. However, obtaining high-quality EEG data from human newborn recordings is challenging. Compared to adults and older infants, datasets are typically much shorter due to newborns’ limited attentional span and much noisier due to non-stereotyped artifacts mainly caused by uncontrollable movements. We propose Newborn EEG Artifact Removal (NEAR), a pipeline for EEG artifact removal designed explicitly for human newborns. NEAR is based on two key steps: 1) A novel bad channel detection tool based on the Local Outlier Factor (LOF), a robust outlier detection algorithm; 2) A parameter calibration procedure for adapting to newborn EEG data the algorithm Artifacts Subspace Reconstruction (ASR), developed for artifact removal in mobile adult EEG. Tests on simulated data showed that NEAR outperforms existing methods in removing representative newborn non-stereotypical artifacts. NEAR was validated on two developmental populations (newborns and 9-month-old infants) recorded with two different experimental designs (frequency-tagging and ERP). Results show that NEAR artifact removal successfully reproduces established EEG responses from noisy datasets, with a higher statistical significance than the one obtained by existing artifact removal methods. The EEGLAB-based NEAR pipeline is freely available at https://github.com/vpKumaravel/NEAR.

tACS facilitates flickering driving by boosting steady-state visual evoked potentials

Objective.There has become of increasing interest in transcranial alternating current stimulation (tACS) since its inception nearly a decade ago. tACS in modulating brain state is an active area of research and has been demonstrated effective in various neuropsychological and clinical domains. In the visual domain, much effort has been dedicated to brain rhythms and rhythmic stimulation, i.e. tACS. However, less is known about the interplay between the rhythmic stimulation and visual stimulation.Approach.Here, we used steady-state visual evoked potential (SSVEP), induced by flickering driving as a widely used technique for frequency-tagging, to investigate the aftereffect of tACS in healthy human subjects. Seven blocks of 64-channel electroencephalogram were recorded before and after the administration of 20min 10Hz tACS, while subjects performed several blocks of SSVEP tasks. We characterized the physiological properties of tACS aftereffect by comparing and validating the temporal, spatial, spatiotemporal and signal-to-noise ratio (SNR) patterns between and within blocks in real tACS and sham tACS.Main results.Our result revealed that tACS boosted the 10Hz SSVEP significantly. Besides, the aftereffect on SSVEP was mitigated with time and lasted up to 5 min.Significance.Our results demonstrate the feasibility of facilitating the flickering driving by external rhythmic stimulation and open a new possibility to alter the brain state in a direction by noninvasive transcranial brain stimulation.

Phase-spatial beamforming renders a visual brain computer interface capable of exploiting EEG electrode phase shifts in motion-onset target responses

Brain-computer interfaces (BCIs) provide communication facilities that do not rely on the brains usual pathways. Visual BCIs are based on changes in EEG activity in response to attended flashing or flickering targets. A less taxing way to encode such targets is with briefly moving stimuli, the onset of which elicits a lateralized EEG potential over the parieto-occipital scalp area called the motion-onset visual evoked potential (mVEP). We recruited 21 healthy subjects for an experiment in which motion-onset stimulations translating leftwards (LT) or rightwards (RT) were encoding 9 displayed targets. We propose a novel algorithm that exploits the phase-shift between EEG electrodes to improve target decoding performance. We hereto extend the spatiotemporal beamformer (stBF) with a phase extracting procedure, leading to the phase-spatial beamformer (psBF). We show that psBF performs significantly better than the stBF (p<0.001 for 1 and 2 stimulus repetitions and p<0.01 for 3 to 5 stimulus repetitions), as well as the previously validated linear support-vector machines (p<0.001 for 5 stimulus repetitions and p<0.01 for 1,2 and 6 stimulus repetitions) and stepwise linear discriminant analysis decoders (p<0.001 for all repetitions) when simultaneously addressing timing and translation direction.

A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex

Synchronization of neuronal responses over large distances is hypothesized to be important for many cortical functions. However, no straightforward methods exist to estimate synchrony non-invasively in the living human brain. MEG and EEG measure the whole brain, but the sensors pool over large, overlapping cortical regions, obscuring the underlying neural synchrony. Here, we developed a model from stimulus to cortex to MEG sensors to disentangle neural synchrony from spatial pooling of the instrument. We find that synchrony across cortex has a surprisingly large and systematic effect on predicted MEG spatial topography. We then conducted visual MEG experiments and separated responses into stimulus-locked and broadband components. The stimulus-locked topography was similar to model predictions assuming synchronous neural sources, whereas the broadband topography was similar to model predictions assuming asynchronous sources. We infer that visual stimulation elicits two distinct types of neural responses, one highly synchronous and one largely asynchronous across cortex.

Imaging the effective networks associated with cortical function through intracranial high-frequency stimulation

Direct electrical stimulation (DES) is considered to be the gold standard for mapping cortical function. A careful mapping of the eloquent cortex is key to successful resective or ablative surgeries, with a minimal postoperative deficit, for treatment of drug‐resistant epilepsy. There is accumulating evidence suggesting that not only local, but also remote activations play an equally important role in evoking clinical effects. By introducing a new intracranial stimulation paradigm and signal analysis methodology allowing to disambiguate EEG responses from stimulation artifacts we highlight the spatial extent of the networks associated with clinical effects. Our study includes 26 patients that underwent stereoelectroencephalographic investigations for drug‐resistant epilepsy, having 337 depth electrodes with 4,351 contacts sampling most brain structures. The routine high‐frequency electrical stimulation protocol for eloquent cortex mapping was altered in a subtle way, by alternating the polarity of the biphasic pulses in a train, causing the splitting the spectral lines of the artifactual components, exposing the underlying tissue response. By performing a frequency‐domain analysis of the EEG responses during DES we were able to capture remote activations and highlight the effect's network. By using standard intersubject averaging and a fine granularity HCP‐MMP parcellation, we were able to create local and distant connectivity maps for 614 stimulations evoking specific clinical effects. The clinical value of such maps is not only for a better understanding of the extent of the effects' networks guiding the invasive exploration, but also for understanding the spatial patterns of seizure propagation given the timeline of the seizure semiology.