Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation

Steady-state Visual Evoked Potentials Reveal Dynamic (Re)allocation of Spatial Attention during Maintenance and Utilization of Visual Working Memory

Visual working memory (VWM) allows storing goal-relevant information to guide future behavior. Prior work suggests that VWM is spatially organized and relies on spatial attention directed toward locations at which memory items were encoded, even if location is task-irrelevant. Importantly, attention often needs to be dynamically redistributed between locations, for example, in preparation for an upcoming probe. Very little is known about how attentional resources are distributed between multiple locations during a VWM task and even less about the dynamic changes governing such attentional shifts over time. This is largely due to the inability to use behavioral outcomes to reveal fast dynamic changes within trials. We here demonstrated that EEG steady-state visual evoked potentials (SSVEPs) successfully track the dynamic allocation of spatial attention during a VWM task. Participants were presented with to-be-memorized gratings and distractors at two distinct locations, tagged with flickering discs. This allowed us to dynamically track attention allocated to memory and distractor items via their coupling with space by quantifying the amplitude and coherence of SSVEP responses in the EEG signal to flickering stimuli at the former memory and distractor locations. SSVEP responses did not differ between memory and distractor locations during early maintenance. However, shortly before probe comparison, we observed a decrease in SSVEP coherence over distractor locations indicative of a reallocation of spatial attentional resources. RTs were shorter when preceded by stronger decreases in SSVEP coherence at distractor locations, likely reflecting attentional shifts from the distractor to the probe or memory location. We demonstrate that SSVEPs can inform about dynamic processes in VWM, even if location does not have to be reported by participants. This finding not only supports the notion of a spatially organized VWM but also reveals that SSVEPs betray a dynamic prioritization process of working memory items and locations over time that is directly predictive of memory performance.

Effect of Stimulus Bandwidth on the Auditory Steady-State Response in Scalp- and Ear-EEG

OBJECTIVES

The auditory steady-state response (ASSR) enables hearing threshold estimation based on electroencephalography (EEG) recordings. The choice of stimulus type has an impact on both the detectability and the frequency specificity of the ASSR. Amplitude modulated pure tones provide the most frequency-specific ASSR, but responses to pure tones are weak. The ASSR can be enhanced by increasing the bandwidth of the stimulus, but this comes at the cost of a decrease in the frequency specificity of the measured response. The objective of the present study is to investigate the relationship between stimulus bandwidth and ASSR amplitude.

DESIGN

The amplitude of ASSR was measured for five types of stimuli: 1 kHz pure tone and band-pass noise with 1/3, 1/2, 1, and 2 octave bandwidths centered at 1 kHz. All stimuli were amplitude modulated with a 40 Hz sinusoid. Responses to all stimulus types were measured at 30, 40, and 50 dB SL. ASSRs were measured concurrently using both conventional scalp-EEG and ear-EEG.

RESULTS

Stimulus bandwidth and sound intensity were both found to have a significant effect on the ASSR amplitude for scalp- and ear-EEG recordings. In scalp-EEG ASSRs to all bandwidth stimuli were found to be significantly larger than ASSRs to pure tone at low sound intensity. At higher sound intensities, however, significantly larger responses were only obtained for 1- and 2-octave bandwidth stimuli. In ear-EEG, only the ASSR to 2 octave bandwidth stimulus was significantly larger than the ASSR to amplitude modulated pure tones.

CONCLUSIONS

At low presentation levels, even small increases in stimulus bandwidth (1/3 and 1/2 octave) improve the detectability of ASSR in scalp-EEG with little or no impact on the frequency specificity. In comparison, a larger increase in stimulus bandwidth was needed to improve the ASSR detectability in the ear-EEG recordings.

Willed Attentional Selection of Visual Features: An EEG Study

Visual selective attention studies generally tend to apply cuing paradigms to instructively direct observers' attention to certain locations, features or objects. However, in real situations, attention in humans often flows spontaneously without any specific instructions. Recently, a concept named "willed attention" was raised in visuospatial attention, in which participants are free to make volitional attention decisions. Several ERP components during willed attention were found, along with a perspective that ongoing alpha activity may bias the subsequent attentional choice. However, it remains unclear whether similar neural mechanisms exist in feature- or object-based willed attention. Here, we included choice cues and instruct cues in a feature-based selective attention paradigm, allowing participants to freely choose or to be instructed to attend a color for the subsequent target detection task. Pre-cue ongoing alpha oscillations, cue-evoked potentials and target-related steady-state visual evoked potentials (SSVEPs) were simultaneously measured as markers of attentional processing. As expected, SSVEP responses were similarly modulated by attention between choice and instruct cue trials. Similar to the case of spatial attention, a willed-attention component (Willed Attention Component, WAC) was isolated during the cue-related choice period by comparing choice and instruct cues. However, pre-cue ongoing alpha oscillations did not predict the color choice (yellow vs blue), as indicated by the chance level decoding accuracy (50%). Overall, our results revealed both similarities and differences between spatial and feature-based willed attention, and thus extended the understanding toward the neural mechanisms of volitional attention.

Towards ASSR-based hearing assessment using natural sounds

Objective. The auditory steady-state response (ASSR) allows estimation of hearing thresholds. The ASSR can be estimated from electroencephalography (EEG) recordings from electrodes positioned on both the scalp and within the ear (ear-EEG). Ear-EEG can potentially be integrated into hearing aids, which would enable automatic fitting of the hearing device in daily life. The conventional stimuli for ASSR-based hearing assessment, such as pure tones and chirps, are monotonous and tiresome, making them inconvenient for repeated use in everyday situations. In this study we investigate the use of natural speech sounds for ASSR estimation.Approach.EEG was recorded from 22 normal hearing subjects from both scalp and ear electrodes. Subjects were stimulated monaurally with 180 min of speech stimulus modified by applying a 40 Hz amplitude modulation (AM) to an octave frequency sub-band centered at 1 kHz. Each 50 ms sub-interval in the AM sub-band was scaled to match one of 10 pre-defined levels (0-45 dB sensation level, 5 dB steps). The apparent latency for the ASSR was estimated as the maximum average cross-correlation between the envelope of the AM sub-band and the recorded EEG and was used to align the EEG signal with the audio signal. The EEG was then split up into sub-epochs of 50 ms length and sorted according to the stimulation level. ASSR was estimated for each level for both scalp- and ear-EEG.Main results. Significant ASSRs with increasing amplitude as a function of presentation level were recorded from both scalp and ear electrode configurations.Significance. Utilizing natural sounds in ASSR estimation offers the potential for electrophysiological hearing assessment that are more comfortable and less fatiguing compared to existing ASSR methods. Combined with ear-EEG, this approach may allow convenient hearing threshold estimation in everyday life, utilizing ambient sounds. Additionally, it may facilitate both initial fitting and subsequent adjustments of hearing aids outside of clinical settings.

Attentional Modulation in Early Visual Cortex: A Focused Reanalysis of Steady-state Visual Evoked Potential Studies

Steady-state visual evoked potentials (SSVEPs) are a powerful tool for investigating selective attention. Here, we conducted a combined reanalysis of multiple studies employing this technique in a variety of attentional experiments to, first, establish benchmark effect sizes of attention on amplitude and phase of SSVEPs and, second, harness the power of a large data set to test more specific hypotheses. Data of eight published SSVEP studies were combined, in which human participants (n = 135 in total) attended to flickering random dot stimuli based on their defining features (e.g., location, color, luminance, or orientation) or feature conjunctions. The reanalysis established that, in all the studies, attention reliably enhanced amplitudes, with color-based attention providing the strongest effect. In addition, the latency of SSVEPs elicited by attended stimuli was reduced by ∼4 msec. Next, we investigated the modulation of SSVEP amplitudes in a subset of studies where two different features were attended concurrently. Although most models assume that attentional effects of multiple features are combined additively, our results suggest that neuronal enhancement provided by concurrent attention is better described by multiplicative integration. Finally, we used the combined data set to demonstrate that the increase in trial-averaged SSVEP amplitudes with attention cannot be explained by increased synchronization of single-trial phases. Contrary to the prediction of the phase-locking account, the variance across trials of complex Fourier coefficients increases with attention, which is more consistent with boosting of a largely phase-locked signal embedded in non-phase-locked noise.

Laplacian reference is optimal for steady-state visual-evoked potentials

Steady-state visual-evoked potentials (SSVEPs) are widely used in human neuroscience studies and applications such as brain-computer interfaces (BCIs). Surprisingly, no previous study has systematically evaluated different reference methods for SSVEP analysis, despite that signal reference is crucial for the proper assessment of neural activities. In the present study, using four datasets from our previous SSVEP studies (Chen J, Valsecchi M, Gegenfurtner KR. J Neurophysiol 118: 749-754, 2017; Chen J, Valsecchi M, Gegenfurtner KR. Neuropsychologia 102: 206-216, 2017; Chen J, McManus M, Valsecchi M, Harris LR, Gegenfurtner KR. J Vis 19: 8, 2019) and three public datasets from other studies (Baker DH, Vilidaite G, Wade AR. PLoS Comput Biol 17: e1009507, 2021; Lygo FA, Richard B, Wade AR, Morland AB, Baker DH. NeuroImage 230: 117780, 2021; Vilidaite G, Norcia AM, West RJH, Elliott CJH, Pei F, Wade AR, Baker DH. Proc R Soc B 285: 20182255, 2018), we compared four reference methods: monopolar reference, common average reference, averaged-mastoids reference, and Laplacian reference. The quality of the resulting SSVEP signals was compared in terms of both signal-to-noise ratios (SNRs) and reliability. The results showed that Laplacian reference, which uses signals at the maximally activated electrode after subtracting the average of the nearby electrodes to reduce common noise, gave rise to the highest SNRs. Furthermore, the Laplacian reference resulted in SSVEP signals that were highly reliable across recording sessions or trials. These results suggest that Laplacian reference is optimal for SSVEP studies and applications. Laplacian reference is especially advantageous for SSVEP experiments where short preparation time is preferred as it requires only data from the maximally activated electrode and a few surrounding electrodes.NEW & NOTEWORTHY The present study provides a comprehensive evaluation of the use of different reference methods for steady-state visual-evoked potentials (SSVEPs) and has found that Laplacian reference increases signal-to-noise ratios (SNRs) and enhances reliabilities of SSVEP signals. Thus, the results suggest that Laplacian reference is optimal for SSVEP analysis.

Neural entrainment underpins sensorimotor synchronization to dynamic rhythmic stimuli

Neural entrainment, defined as unidirectional synchronization of neural oscillations to an external rhythmic stimulus, is a topic of major interest in the field of neuroscience. Despite broad scientific consensus on its existence, on its pivotal role in sensory and motor processes, and on its fundamental definition, empirical research struggles in quantifying it with non-invasive electrophysiology. To this date, broadly adopted state-of-the-art methods still fail to capture the dynamic underlying the phenomenon. Here, we present event-related frequency adjustment (ERFA) as a methodological framework to induce and to measure neural entrainment in human participants, optimized for multivariate EEG datasets. By applying dynamic phase and tempo perturbations to isochronous auditory metronomes during a finger-tapping task, we analyzed adaptive changes in instantaneous frequency of entrained oscillatory components during error correction. Spatial filter design allowed us to untangle, from the multivariate EEG signal, perceptual and sensorimotor oscillatory components attuned to the stimulation frequency. Both components dynamically adjusted their frequency in response to perturbations, tracking the stimulus dynamics by slowing down and speeding up the oscillation over time. Source separation revealed that sensorimotor processing enhanced the entrained response, supporting the notion that the active engagement of the motor system plays a critical role in processing rhythmic stimuli. In the case of phase shift, motor engagement was a necessary condition to observe any response, whereas sustained tempo changes induced frequency adjustment even in the perceptual oscillatory component. Although the magnitude of the perturbations was controlled across positive and negative direction, we observed a general bias in the frequency adjustments towards positive changes, which points at the effect of intrinsic dynamics constraining neural entrainment. We conclude that our findings provide compelling evidence for neural entrainment as mechanism underlying overt sensorimotor synchronization, and highlight that our methodology offers a paradigm and a measure for quantifying its oscillatory dynamics by means of non-invasive electrophysiology, rigorously informed by the fundamental definition of entrainment.

Random Tactile Noise Stimulation Reveals Beta-Rhythmic Impulse Response Function of the Somatosensory System

Both passive tactile stimulation and motor actions result in dynamic changes in beta band (15-30 Hz Hz) oscillations over somatosensory cortex. Similar to alpha band (8-12 Hz) power decrease in the visual system, beta band power also decreases following stimulation of the somatosensory system. This relative suppression of α and β oscillations is generally interpreted as an increase in cortical excitability. Here, next to traditional single-pulse stimuli, we used a random intensity continuous right index finger tactile stimulation (white noise), which enabled us to uncover an impulse response function of the somatosensory system. Contrary to previous findings, we demonstrate a burst-like initial increase rather than decrease of beta activity following white noise stimulation (human participants, N = 18, 8 female). These β bursts, on average, lasted for 3 cycles, and their frequency was correlated with resonant frequency of somatosensory cortex, as measured by a multifrequency steady-state somatosensory evoked potential paradigm. Furthermore, beta band bursts shared spectro-temporal characteristics with evoked and resting-state β oscillations. Together, our findings not only reveal a novel oscillatory signature of somatosensory processing that mimics the previously reported visual impulse response functions, but also point to a common oscillatory generator underlying spontaneous β bursts in the absence of tactile stimulation and phase-locked β bursts following stimulation, the frequency of which is determined by the resonance properties of the somatosensory system.SIGNIFICANCE STATEMENT The investigation of the transient nature of oscillations has gained great popularity in recent years. The findings of bursting activity, rather than sustained oscillations in the beta band, have provided important insights into its role in movement planning, working memory, inhibition, and reactivation of neural ensembles. In this study, we show that also in response to tactile stimulation the somatosensory system responds with ∼3 cycle oscillatory beta band bursts, whose spectro-temporal characteristics are shared with evoked and resting-state beta band oscillatory signatures of the somatosensory system. As similar bursts have been observed in the visual domain, these oscillatory signatures might reflect an important supramodal mechanism in sensory processing.

Disrupted auditory N1, theta power and coherence suppression to willed speech in people with schizophrenia

The phenomenon of sensory self-suppression - also known as sensory attenuation - occurs when a person generates a perceptible stimulus (such as a sound) by performing an action (such as speaking). The sensorimotor control system is thought to actively predict and then suppress the vocal sound in the course of speaking, resulting in lowered cortical responsiveness when speaking than when passively listening to an identical sound. It has been hypothesized that auditory hallucinations in schizophrenia result from a reduction in self-suppression due to a disruption of predictive mechanisms required to anticipate and suppress a specific, self-generated sound. It has further been hypothesized that this suppression is evident primarily in theta band activity. Fifty-one people, half of whom had a diagnosis of schizophrenia, were asked to repeatedly utter a single syllable, which was played back to them concurrently over headphones while EEG was continuously recorded. In other conditions, recordings of the same spoken syllables were played back to participants while they passively listened, or were played back with their onsets preceded by a visual cue. All participants experienced these conditions with their voice artificially shifted in pitch and also with their unaltered voice. Suppression was measured using event-related potentials (N1 component), theta phase coherence and power. We found that suppression was generally reduced on all metrics in the patient sample, and when voice alteration was applied. We additionally observed reduced theta coherence and power in the patient sample across all conditions. Visual cueing affected theta coherence only. In aggregate, the results suggest that sensory self-suppression of theta power and coherence is disrupted in schizophrenia.

Neural Underpinnings of Proactive and Preemptive Adjustments of Action Control

This study aimed to trace the neural basis of proactive and preemptive adjustments of executive control and their effects on online processing of response conflict. In two EEG experiments, participants performed the flanker task with predictive cueing of conflict. The following questions were addressed: "Does conflict cueing improve performance?" We observed improved behavioral performance in the predictive condition, suggesting that participants proactively utilized the cues to prepare for the upcoming demands. "How is conflict processing affected by predictive cueing?" Conflict-related modulations of midfrontal N2 and theta power were smaller in the predictive than in the neutral condition. This suggests that proactive control suppressed the impact of incongruent flankers so that the conflict was reduced, and so was the involvement of online control. "Is proactive control implemented through preactivation of online control?" Conflict cueing increased midfrontal theta power also before target onset, suggesting preactivation of the control processes beforehand. "Do proactive and reactive control depend on common or unique processes?" Unlike the online control, the proactive control triggered a burst of theta power in the right hemisphere's dorsal and ventral lateral prefrontal cortices, connected with the midfrontal area via theta phase coherence. This indicates that the two control modes involve partially unique but coordinated neural processes. "Is preemptive control implemented through modulations of visual processing?" Predictive cueing modulated both the pretarget preparatory alpha desynchronization and the target selection-related posterior contralateral negativity (N2pc and sustained posterior contralateral negativity), in line with the hypothesis of preemptive tuning of sensory selection aimed at reducing the impact of conflicting stimuli.

Investigation of the Effect of Spatial Filtering for Detecting Auditory Steady-State Responses Recorded from Ear-EEG

Auditory steady-state responses (ASSRs) enable hearing threshold estimation based on electrophysiological measurements and are widely used in clinical practice. Traditionally, ASSRs are recorded from a few electroencephalography (EEG) electrodes placed on the scalp. Ear-EEG is a method in which the EEG is recorded from electrodes placed within or around the ear and is thus more suitable for use in everyday life. Ear-EEG is typically recorded from multiple electrodes in order to enhance redundancy and robustness, but a pair of electrodes (so-called "best pair") is usually chosen for the further analysis. Spatial filtering uses an optimized weighted combination of the electrodes, and is thus in general a better method for analysis of multichannel EEG. In this study we propose a new spatial filtering method based on solving a constrained optimization problem. Empirical evaluation based on ear-EEG recorded from nine subjects shows that the proposed spatial filtering method provides a significant increase in ASSR SNR as compared to the conventional "best pair" method. Clinical Relevance - ASSR can be estimated from ear-EEG recordings. Integrating ear-EEG into hearing aids would allow hearing aids to characterize hearing loss and thereby adjust the audio processing accordingly.

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.

Mutual beta power modulation in dyadic entrainment

Across a broad spectrum of interactions, humans exhibit a prominent tendency to synchronize their movements with one another. Traditionally, this phenomenon has been explained from the perspectives of predictive coding or dynamical systems theory. While these theories diverge with respect to whether individuals hold internal models of each other, they both assume a predictive or anticipatory mechanism enabling rhythmic interactions. However, the neural bases underpinning interpersonal synchronization are still a subject under active investigation. Here we provide evidence that the brain relies on a common oscillatory mechanism to pace self-generated rhythmic movements and to track the movements produced by a partner. By performing dual-electroencephalography recordings during a joint finger-tapping task, we identified an oscillatory component in the beta range (∼ 20 Hz), which was significantly modulated by both self-generated and other-generated movement. In conditions where the partners perceived each other, we observed periodic fluctuations of beta power as a function of the reciprocal movement cycles. Crucially, this modulation occurred both in visually and in auditorily coupled conditions, and was accompanied by recurrent periods of dyadic synchronized behavior. Our results show that periodic beta power modulations may be a critical mechanism underlying interpersonal synchronization, possibly enabling mutual predictions between coupled individuals, leading to co-regulation of timing and overt mutual adaptation. Our findings thus provide a potential bridge between influential theories attempting to explain interpersonal coordination, and a concrete connection to its neurophysiological bases.

Improving user experience of SSVEP BCI through low amplitude depth and high frequency stimuli design

Steady-States Visually Evoked Potentials (SSVEP) refer to the sustained rhythmic activity observed in surface electroencephalography (EEG) in response to the presentation of repetitive visual stimuli (RVS). Due to their robustness and rapid onset, SSVEP have been widely used in Brain Computer Interfaces (BCI). However, typical SSVEP stimuli are straining to the eyes and present risks of triggering epileptic seizures. Reducing visual stimuli contrast or extending their frequency range both appear as relevant solutions to address these issues. It however remains sparsely documented how BCI performance is impacted by these features and to which extent user experience can be improved. We conducted two studies to systematically characterize the effects of frequency and amplitude depth reduction on SSVEP response. The results revealed that although high frequency stimuli improve visual comfort, their classification performance were not competitive enough to design a reliable/responsive BCI. Importantly, we found that the amplitude depth reduction of low frequency RVS is an effective solution to improve user experience while maintaining high classification performance. These findings were further validated by an online T9 SSVEP-BCI in which stimuli with 40% amplitude depth reduction achieved comparable results (>90% accuracy) to full amplitude stimuli while significantly improving user experience.

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.

A multidimensional evaluation of the benefits of an ecologically realistic training based on pretend play for preschoolers' cognitive control and self-regulation: From behavior to the underlying theta neuro-oscillatory activity

To what extent can cognitive control, self-regulation, and the underlying midfrontal theta oscillatory activity of preschool children be modified by an ecologically realistic training based on pretend play? To answer this question, 70 children aged 4-6 years (37 boys) were assigned to a training group or a control group using a pairing randomization procedure. Children were administered 20 play sessions over 10 weeks. Benefits were evaluated with a pre-post design. The intervention helped children to engage more in self-regulation within the training activities. However, the intervention did not promote self-regulation outside of the training context, nor did it influence cognitive control and theta activity. These results provide a better understanding of the limitations of an ecologically realistic approach to cognitive control training.

A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiology

The goal of this paper is to present a theoretical and practical introduction to generalized eigendecomposition (GED), which is a robust and flexible framework used for dimension reduction and source separation in multichannel signal processing. In cognitive electrophysiology, GED is used to create spatial filters that maximize a researcher-specified contrast. For example, one may wish to exploit an assumption that different sources have different frequency content, or that sources vary in magnitude across experimental conditions. GED is fast and easy to compute, performs well in simulated and real data, and is easily adaptable to a variety of specific research goals. This paper introduces GED in a way that ties together myriad individual publications and applications of GED in electrophysiology, and provides sample MATLAB and Python code that can be tested and adapted. Practical considerations and issues that often arise in applications are discussed.

Effect of sustained selective attention on steady-state visual evoked potentials

Visual-spatial selective attention enhances the processing of task-relevant visual events while suppressing the processing of irrelevant ones. In this study, we employed a frequency-tagging paradigm to investigate how sustained visual-spatial attention modulates the first harmonic and second harmonic steady-state visual evoked potentials (SSVEPs). Unlike previous studies, that investigated stimulation durations of 10 s or less, we tested a 30-s period. SSVEPs were elicited by simultaneously presenting to the right and left visual hemifields two pattern reversal checkerboard stimuli modulating at 7.14 Hz and 11.11 Hz. Participants were cued to selectively attend to one visual hemifield while ignoring the other. Behavioral results indicated that participants selectively attended to the cued visual hemifield. When participants attended to the visual stimuli, there were larger second harmonic SSVEPs but no attentional modulation of first harmonics. The results are consistent with the proposal that neural populations underlying first, and second harmonics have distinct functional roles, i.e., first harmonics' mechanisms preserve stimulus properties and are resistant to attentional gain, whereas second harmonics mediate attentional modulation. This interpretation is supported by a gain control theory of selective attention.

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.

Neural Entrainment Meets Behavior: The Stability Index as a Neural Outcome Measure of Auditory-Motor Coupling

Understanding rhythmic behavior in the context of coupled auditory and motor systems has been of interest to neurological rehabilitation, in particular, to facilitate walking. Recent work based on behavioral measures revealed an entrainment effect of auditory rhythms on motor rhythms. In this study, we propose a method to compute the neural component of such a process from an electroencephalographic (EEG) signal. A simple auditory-motor synchronization paradigm was used, where 28 healthy participants were instructed to synchronize their finger-tapping with a metronome. The computation of the neural outcome measure was carried out in two blocks. In the first block, we used Generalized Eigendecomposition (GED) to reduce the data dimensionality to the component which maximally entrained to the metronome frequency. The scalp topography pointed at brain activity over contralateral sensorimotor regions. In the second block, we computed instantaneous frequency from the analytic signal of the extracted component. This returned a time-varying measure of frequency fluctuations, whose standard deviation provided our "stability index" as a neural outcome measure of auditory-motor coupling. Finally, the proposed neural measure was validated by conducting a correlation analysis with a set of behavioral outcomes from the synchronization task: resultant vector length, relative phase angle, mean asynchrony, and tempo matching. Significant moderate negative correlations were found with the first three measures, suggesting that the stability index provided a quantifiable neural outcome measure of entrainment, with selectivity towards phase-correction mechanisms. We address further adoption of the proposed approach, especially with populations where sensorimotor abilities are compromised by an underlying pathological condition. The impact of using stability index can potentially be used as an outcome measure to assess rehabilitation protocols, and possibly provide further insight into neuropathological models of auditory-motor coupling.

Emotional content overrides spatial attention

Spatial attention is our capacity to attend to or ignore particular regions of our spatial environment. However, some classes of stimuli may be able to override our efforts to ignore them. Here we assessed the relationship between involuntary attentional capture with emotional images and spatial attention at early stages of perceptual processing. Multiple scenes of unpleasant and neutral content were displayed in rapid serial visual presentation (RSVP) streams that elicited the steady-state visual evoked potential (SSVEP), a neural marker of selective attention at early visual areas. In a spatial cueing task, participants were cued to covertly attend to RSVP streams presented at 4 and 6 Hz presentation rates in the left and right visual hemifields. The task was to detect square targets occasionally displayed within the image streams, responding only to those appearing on the cued side. The RSVP streams were always neutral pictures in one visual hemifield but would unpredictably switch from neutral to aversive content in the other visual hemifield. We found that SSVEP amplitude was consistently modulated by a change in emotional valence of image streams, regardless of whether the change in content occurred in the attended or unattended spatial location, reflecting an automatic sensory amplification for affective stimuli. The present data provide further evidence in support that emotional images can attract visual processing resources independently of spatial attention allocation, and are consistent with sustained sensory facilitation of early visual areas through re-entrant feedback projections from higher-order cortical areas involved in the extraction of affective information.

Individual Alpha Frequency Determines the Impact of Bottom-Up Drive on Visual Processing

Endogenous alpha oscillations propagate from higher-order to early visual cortical regions, consistent with the observed modulation of these oscillations by top-down factors. However, bottom-up manipulations also influence alpha oscillations, and little is known about how these top-down and bottom-up processes interact to impact behavior. To address this, participants performed a detection task while viewing a stimulus flickering at multiple alpha band frequencies. Bottom-up drive at a participant's endogenous alpha frequency either impaired or enhanced perception, depending on the frequency, but not amplitude, of their endogenous alpha oscillation. Fast alpha drive impaired perceptual performance in participants with faster endogenous alpha oscillations, while participants with slower oscillations displayed enhanced performance. This interaction was reflected in slower endogenous oscillatory dynamics in participants with fast alpha oscillations and more rapid dynamics in participants with slow endogenous oscillations when receiving high-frequency bottom-up drive. This central tendency may suggest that driving visual circuits at alpha band frequencies that are away from the peak alpha frequency improves perception through dynamical interactions with the endogenous oscillation. As such, studies that causally manipulate neural oscillations via exogenous stimulation should carefully consider interacting effects of bottom-up drive and endogenous oscillations on behavior.

Steady-State Visually Evoked Potentials and Feature-based Attention: Preregistered Null Results and a Focused Review of Methodological Considerations

Feature-based attention is the ability to selectively attend to a particular feature (e.g., attend to red but not green items while looking for the ketchup bottle in your refrigerator), and steady-state visually evoked potentials (SSVEPs) measured from the human EEG signal have been used to track the neural deployment of feature-based attention. Although many published studies suggest that we can use trial-by-trial cues to enhance relevant feature information (i.e., greater SSVEP response to the cued color), there is ongoing debate about whether participants may likewise use trial-by-trial cues to voluntarily ignore a particular feature. Here, we report the results of a preregistered study in which participants either were cued to attend or to ignore a color. Counter to prior work, we found no attention-related modulation of the SSVEP response in either cue condition. However, positive control analyses revealed that participants paid some degree of attention to the cued color (i.e., we observed a greater P300 component to targets in the attended vs. the unattended color). In light of these unexpected null results, we conducted a focused review of methodological considerations for studies of feature-based attention using SSVEPs. In the review, we quantify potentially important stimulus parameters that have been used in the past (e.g., stimulation frequency, trial counts) and we discuss the potential importance of these and other task factors (e.g., feature-based priming) for SSVEP studies.

EEG Decoding of Dynamic Facial Expressions of Emotion: Evidence from SSVEP and Causal Cortical Network Dynamics

The neural cognitive mechanism in processing static facial expressions (FEs) has been well documented, whereas the one underlying perceiving dynamic faces remains unclear. In this study, Fourier transformation and time-frequency analysis of Electroencephalography (EEG) data were carried out to detect the brain activation underlying dynamic or static FEs while twenty-one participants were viewing dynamic or static faces flicking at 10 Hz. In particular, steady-state visual evoked potentials (SSVEPs) were quantified through spectral power analysis of EEG recordings. Besides, Granger causality (GC) analysis (GCA) was also performed to capture the causal cortical network dynamics during dynamic or static FEs of emotion. It was discovered that the dynamic (from neural to happy (N2H) or vice versa (H2N)) FEs elicited larger SSVEPs than the static ones. Additionally, GCA demonstrated that the H2N case, in which happy FEs were being gradually changed into neutral ones, exhibited larger GC measure during the late processing stage than that from the early stage. Consequently, enhanced SSVEPs and effective brain connectivity for dynamic FEs illustrated that participants might need consume more attentional resources to process the dynamic faces, particularly for the change from happy to neutral faces. The new neural index might facilitate us to better understand the cognitive processing of dynamic and static FEs.

Estimating multiple latencies in the auditory system from auditory steady-state responses on a single EEG channel

The latency of the auditory steady-state response (ASSR) may provide valuable information regarding the integrity of the auditory system, as it could potentially reveal the presence of multiple intracerebral sources. To estimate multiple latencies from high-order ASSRs, we propose a novel two-stage procedure that consists of a nonparametric estimation method, called apparent latency from phase coherence (ALPC), followed by a heuristic sequential forward selection algorithm (SFS). Compared with existing methods, ALPC-SFS requires few prior assumptions, and is straightforward to implement for higher-order nonlinear responses to multi-cosine sound complexes with their initial phases set to zero. It systematically evaluates the nonlinear components of the ASSRs by estimating multiple latencies, automatically identifies involved ASSR components, and reports a latency consistency index. To verify the proposed method, we performed simulations for several scenarios: two nonlinear subsystems with different or overlapping outputs. We compared the results from our method with predictions from existing, parametric methods. We also recorded the EEG from ten normal-hearing adults by bilaterally presenting superimposed tones with four frequencies that evoke a unique set of ASSRs. From these ASSRs, two major latencies were found to be stable across subjects on repeated measurement days. The two latencies are dominated by low-frequency (LF) (near 40 Hz, at around 41-52 ms) and high-frequency (HF) (> 80 Hz, at around 21-27 ms) ASSR components. The frontal-central brain region showed longer latencies on LF components, but shorter latencies on HF components, when compared with temporal-lobe regions. In conclusion, the proposed nonparametric ALPC-SFS method, applied to zero-phase, multi-cosine sound complexes is more suitable for evaluating embedded nonlinear systems underlying ASSRs than existing methods. It may therefore be a promising objective measure for hearing performance and auditory cortex (dys)function.

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.

Multiple Midfrontal Thetas Revealed by Source Separation of Simultaneous MEG and EEG

Theta-band (∼6 Hz) rhythmic activity within and over the medial PFC ("midfrontal theta") has been identified as a distinctive signature of "response conflict," the competition between multiple actions when only one action is goal-relevant. Midfrontal theta is traditionally conceptualized and analyzed under the assumption that it is a unitary signature of conflict that can be uniquely identified at one electrode (typically FCz). Here we recorded simultaneous MEG and EEG (total of 328 sensors) in 9 human subjects (7 female) and applied a feature-guided multivariate source-separation decomposition to determine whether conflict-related midfrontal theta is a unitary or multidimensional feature of the data. For each subject, a generalized eigendecomposition yielded spatial filters (components) that maximized the ratio between theta and broadband activity. Components were retained based on significance thresholding and midfrontal EEG topography. All of the subjects individually exhibited multiple (mean 5.89, SD 2.47) midfrontal components that contributed to sensor-level midfrontal theta power during the task. Component signals were temporally uncorrelated and asynchronous, suggesting that each midfrontal theta component was unique. Our findings call into question the dominant notion that midfrontal theta represents a unitary process. Instead, we suggest that midfrontal theta spans a multidimensional space, indicating multiple origins, but can manifest as a single feature at the sensor level because of signal mixing.SIGNIFICANCE STATEMENT "Midfrontal theta" is a rhythmic electrophysiological signature of the competition between multiple response options. Midfrontal theta is traditionally considered to reflect a single process. However, this assumption could be erroneous because of "mixing" (multiple sources contributing to the activity recorded at a single electrode). We investigated the dimensionality of midfrontal theta by applying advanced multivariate analysis methods to a multimodal MEG/EEG dataset. We identified multiple topographically overlapping neural sources that drove response conflict-related midfrontal theta. Midfrontal theta thus reflects multiple uncorrelated signals that manifest with similar EEG scalp projections. In addition to contributing to the cognitive control literature, we demonstrate both the feasibility and the necessity of signal demixing to understand the narrowband neural dynamics underlying cognitive processes.

Rapid processing of neutral and angry expressions within ongoing facial stimulus streams: Is it all about isolated facial features?

Our visual system extracts the emotional meaning of human facial expressions rapidly and automatically. Novel paradigms using fast periodic stimulations have provided insights into the electrophysiological processes underlying emotional content extraction: the regular occurrence of specific identities and/or emotional expressions alone can drive diagnostic brain responses. Consistent with a processing advantage for social cues of threat, we expected angry facial expressions to drive larger responses than neutral expressions. In a series of four EEG experiments, we studied the potential boundary conditions of such an effect: (i) we piloted emotional cue extraction using 9 facial identities and a fast presentation rate of 15 Hz (N = 16); (ii) we reduced the facial identities from 9 to 2, to assess whether (low or high) variability across emotional expressions would modulate brain responses (N = 16); (iii) we slowed the presentation rate from 15 Hz to 6 Hz (N = 31), the optimal presentation rate for facial feature extraction; (iv) we tested whether passive viewing instead of a concurrent task at fixation would play a role (N = 30). We consistently observed neural responses reflecting the rate of regularly presented emotional expressions (5 Hz and 2 Hz at presentation rates of 15 Hz and 6 Hz, respectively). Intriguingly, neutral expressions consistently produced stronger responses than angry expressions, contrary to the predicted processing advantage for threat-related stimuli. Our findings highlight the influence of physical differences across facial identities and emotional expressions.

A multiple-response frequency-tagging paradigm measures graded changes in consciousness during perceptual filling-in

Perceptual filling-in (PFI) occurs when a physically present visual target disappears from conscious perception, with its location filled-in by the surrounding visual background. These perceptual changes are complete, near instantaneous, and can occur for multiple separate locations simultaneously. Here, we show that contrasting neural activity during the presence or absence of multi-target PFI can complement other findings from multistable phenomena to reveal the neural correlates of consciousness (NCC). We presented four peripheral targets over a background dynamically updating at 20 Hz. While participants reported on target disappearances/reappearances via button press/release, we tracked neural activity entrained by the background during PFI using steady-state visually evoked potentials (SSVEPs) recorded in the electroencephalogram. We found background SSVEPs closely correlated with subjective report, and increased with an increasing amount of PFI. Unexpectedly, we found that as the number of filled-in targets increased, the duration of target disappearances also increased, suggesting that facilitatory interactions exist between targets in separate visual quadrants. We also found distinct spatiotemporal correlates for the background SSVEP harmonics. Prior to genuine PFI, the response at the second harmonic (40 Hz) increased before the first (20 Hz), which we tentatively link to an attentional effect, while no such difference between harmonics was observed for physically removed stimuli. These results demonstrate that PFI can be used to study multi-object perceptual suppression when frequency-tagging the background of a visual display, and because there are distinct neural correlates for endogenously and exogenously induced changes in consciousness, that it is ideally suited to study the NCC.

Steady-state visual evoked potential temporal dynamics reveal correlates of cognitive decline

OBJECTIVE

A central concern in aging is the preservation of cognitive skills. Tools to detect cognitive decline are sparse. The aim of this study was to ascertain whether cognitive decline is accompanied by alterations in the temporal dynamics of steady-state visual evoked potentials (SSVEPs).

METHODS

We included 162 men from the Danish Metropolit birth cohort. Their cognitive trajectory was based on their intelligence test score at youth (age ~18), middle age (age ~56), and late middle age (age ~62). Subjects underwent cognitive tests and steady-state visual stimulation. Temporal dynamics of SSVEPs were assessed in terms of amplitude and phase coherence.

RESULTS

The latency and magnitude of the amplitude modulation of the 36-Hz response correlated negatively with subjects' cognition indices. Furthermore, negative cognition index was associated with loss of SSVEPs at 36 Hz, and both 8 Hz and 36 Hz in severe cases.

CONCLUSION

Latency and magnitude of gamma frequency SSVEPs increase with cognitive decline. This suggests that the facilitation of SSVEPs first becomes problematic at gamma frequencies, then at alpha frequencies.

SIGNIFICANCE

Our data suggests that the temporal dynamics of SSVEPs can be used as an indicator of cognitive impairment. Furthermore, evoked gamma oscillations are especially vulnerable in cognitive decline.

A bayesian approach to the spectral F-Test: Application to auditory steady-state responses

BACKGROUND AND OBJECTIVE

Auditory steady-state responses (ASSRs) represent an objective method used in clinical practice to assess hearing thresholds. The steady-state nature of these signals allows response detection by means of statistical techniques in the frequency domain as spectral F-test. This objective response detection (ORD) compares the power of the response bin against the power of the neighboring frequency noise bins. Most ORD algorithms are based on the Neyman-Pearson approach to the hypothesis test provided that the likelihood ratio test is the most powerful test for a given significance level alpha (also called Type I error). On the other hand, the Bayesian approach allows the inclusion of prior information in the model and enables the updating of this information with posterior knowledge. This approach, however, has not been explored with respect to ORD techniques, thus enabling the exploration of new paradigms, which may contribute to this field of study, especially in terms of the time required for response detection. The aim of this study is to use the Bayesian approach in the implementation of the spectral F-test for application to ASSRs.

METHODS

Monte Carlo simulations were performed to evaluate Neyman-Pearson and Bayesian detectors' performances with the spectral F-test as a function of the signal-to-noise ratio. Then, the two detectors were applied to ASSR recordings of nine normal-hearing individuals subjected to amplitude-modulated tones of various intensities.

RESULTS

Both simulation and ASSR data analyses showed that among the scenarios analyzed, the most promising case was that in which the lowest possible values for the a priori probability were selected for the null hypothesis (H0), allowing detection at low signal-to-noise ratios. The worst performance occurred when the a priori probabilities for both hypotheses were equal. The ASSR data also showed that higher stimulus intensity led to better performance and faster detection due to improvements in the signal-to-noise ratio.

CONCLUSIONS

The a priori probabilities can affect the Bayesian detector's performance, directly impacting the time needed to identify responses. The parallel behaviors observed between the performances of both approaches showed that the Bayesian detector can achieve its ideal performance at lower signal-to-noise ratios compared to the optimal performance of the Neyman-Pearson detector, reflecting the promising applicability of the Bayesian approach to evoked potentials.

Spatial attention enhances cortical tracking of quasi-rhythmic visual stimuli

Successfully interpreting and navigating our natural visual environment requires us to track its dynamics constantly. Additionally, we focus our attention on behaviorally relevant stimuli to enhance their neural processing. Little is known, however, about how sustained attention affects the ongoing tracking of stimuli with rich natural temporal dynamics. Here, we used MRI-informed source reconstructions of magnetoencephalography (MEG) data to map to what extent various cortical areas track concurrent continuous quasi-rhythmic visual stimulation. Further, we tested how top-down visuo-spatial attention influences this tracking process. Our bilaterally presented quasi-rhythmic stimuli covered a dynamic range of 4-20 ​Hz, subdivided into three distinct bands. As an experimental control, we also included strictly rhythmic stimulation (10 vs 12 ​Hz). Using a spectral measure of brain-stimulus coupling, we were able to track the neural processing of left vs. right stimuli independently, even while fluctuating within the same frequency range. The fidelity of neural tracking depended on the stimulation frequencies, decreasing for higher frequency bands. Both attended and non-attended stimuli were tracked beyond early visual cortices, in ventral and dorsal streams depending on the stimulus frequency. In general, tracking improved with the deployment of visuo-spatial attention to the stimulus location. Our results provide new insights into how human visual cortices process concurrent dynamic stimuli and provide a potential mechanism - namely increasing the temporal precision of tracking - for boosting the neural representation of attended input.

Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity

Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71-channel EEG recorded from 35 healthy adults at two sessions (1-week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal-to-noise ratio, participant-level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait-multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one low-variance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component-based identification of spectral activity (CSD/eLORETA-fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.

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

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

Frequency-tagged visual evoked responses track syllable effects in visual word recognition

The processing of syllables in visual word recognition was investigated using a novel paradigm based on steady-state visual evoked potentials (SSVEPs). French words were presented to proficient readers in a delayed naming task. Words were split into two segments, the first of which was flickered at 18.75 Hz and the second at 25 Hz. The first segment either matched (congruent condition) or did not match (incongruent condition) the first syllable. The SSVEP responses in the congruent condition showed increased power compared to the responses in the incongruent condition, providing new evidence that syllables are important sublexical units in visual word recognition and reading aloud. With respect to the neural correlates of the effect, syllables elicited an early activation of a right hemisphere network. This network is typically associated with the programming of complex motor sequences, cognitive control and timing. Subsequently, responses were obtained in left hemisphere areas related to phonological processing.

Visually evoked responses from the blind field of hemianopic patients

Hemianopia is a visual field defect characterized by decreased vision or blindness in the contralesional visual field of both eyes. The presence of well documented above-chance unconscious behavioural responses to visual stimuli presented to the blind hemifield (blindsight) has stimulated a great deal of research on the neural basis of this important phenomenon. The present study is concerned with electrophysiological responses from the blind field. Since previous studies found that transient Visual Evoked Potentials (VEPs) are not entirely suitable for this purpose here we propose to use Steady-State VEPs (SSVEPs). A positive result would have important implications for the understanding of the neural bases of conscious vision. We carried out a passive SSVEP stimulation with healthy participants and hemianopic patients. Stimuli consisted of four black-and-white sinusoidal Gabor gratings presented one in each visual field quadrant and flickering one at a time at a 12Hz rate. To assess response reliability a Signal-to-Noise Ratio analysis was conducted together with further analyses in time and frequency domains to make comparisons between groups (healthy participants and patients), side of brain lesion (left and right) and visual fields (sighted and blind). The important overall result was that stimulus presentation to the blind hemifield yielded highly reliable responses with time and frequency features broadly similar to those found for cortical extrastriate areas in healthy controls. Moreover, in the intact hemifield of hemianopics and in healthy controls there was evidence of a role of prefrontal structures in perceptual awareness. Finally, the presence of different patterns of brain reorganization depended upon the side of lesion.

Attentional Facilitation of Constituent Features of an Object Does Not Spread Automatically along Object-defining Cortical Boundaries

The integrated object account predicts that attention is spread across all features that constitute one object, regardless of their task relevance. We challenge that prediction with a novel stimulation technique that allows for simultaneous electrophysiological measurements of the allocation of attention to two distinct features within one object. A rotating square that flickers in different colors evoked two distinct steady-state visual evoked potentials (SSVEPs) for rotation and color, respectively. If the integrated object account were true, we would expect identical SSVEP amplitudes regardless of what feature participants attended. We found greater SSVEP amplitudes for the to-be-attended feature compared with the to-be-ignored feature. SSVEP amplitudes averaged across both features were significantly reduced when participants attended to both features, which was mirrored in behavioral costs, implying competitive interactions or a division of attentional resources. Surprisingly, this reduction in amplitude was mainly driven by the SSVEP amplitude elicited by color changes. In conclusion, our results challenge the integrated object account and highlight the extent to which color is "special" within feature space.

EEG time-warping to study non-strictly-periodic EEG signals related to the production of rhythmic movements

BACKGROUND

Many sensorimotor functions are intrinsically rhythmic, and are underlined by neural processes that are functionally distinct from neural responses related to the processing of transient events. EEG frequency tagging is a technique that is increasingly used in neuroscience to study these processes. It relies on the fact that perceiving and/or producing rhythms generates periodic neural activity that translates into periodic variations of the EEG signal. In the EEG spectrum, those variations appear as peaks localized at the frequency of the rhythm and its harmonics.

NEW METHOD

Many natural rhythms, such as music or dance, are not strictly periodic and, instead, show fluctuations of their period over time. Here, we introduce a time-warping method to identify non-strictly-periodic EEG activities in the frequency domain.

RESULTS

EEG time-warping can be used to characterize the sensorimotor activity related to the performance of self-paced rhythmic finger movements. Furthermore, the EEG time-warping method can disentangle auditory- and movement-related EEG activity produced when participants perform rhythmic movements synchronized to an acoustic rhythm. This is possible because the movement-related activity has different period fluctuations than the auditory-related activity.

COMPARISON WITH EXISTING METHODS

With the classic frequency-tagging approach, rhythm fluctuations result in a spreading of the peaks to neighboring frequencies, to the point that they cannot be distinguished from background noise.

CONCLUSIONS

The proposed time-warping procedure is as a simple and effective mean to study natural non-strictly-periodic rhythmic neural processes such as rhythmic movement production, acoustic rhythm perception and sensorimotor synchronization.

Background Suppression and its Relation to Foreground Processing of Speech Versus Non-speech Streams

Since sound perception takes place against a background with a certain amount of noise, both speech and non-speech processing involve extraction of target signals and suppression of background noise. Previous works on early processing of speech phonemes largely neglected how background noise is encoded and suppressed. This study aimed to fill in this gap. We adopted an oddball paradigm where speech (vowels) or non-speech stimuli (complex tones) were presented with or without a background of amplitude-modulated noise and analyzed cortical responses related to foreground stimulus processing, including mismatch negativity (MMN), N2b, and P300, as well as neural representations of the background noise, that is, auditory steady-state response (ASSR). We found that speech deviants elicited later and weaker MMN, later N2b, and later P300 than non-speech ones, but N2b and P300 had similar strength, suggesting more complex processing of certain acoustic features in speech. Only for vowels, background noise enhanced N2b strength relative to silence, suggesting an attention-related speech-specific process to improve perception of foreground targets. In addition, noise suppression in speech contexts, quantified by ASSR amplitude reduction after stimulus onset, was lateralized towards the left hemisphere. The left-lateralized suppression following N2b was associated with the N2b enhancement in noise for speech, indicating that foreground processing may interact with background suppression, particularly during speech processing. Together, our findings indicate that the differences between perception of speech and non-speech sounds involve not only the processing of target information in the foreground but also the suppression of irrelevant aspects in the background.

Individual Alpha Peak Frequency Predicts 10 Hz Flicker Effects on Selective Attention

Rhythmic visual stimulation ("flicker") is primarily used to "tag" processing of low-level visual and high-level cognitive phenomena. However, preliminary evidence suggests that flicker may also entrain endogenous brain oscillations, thereby modulating cognitive processes supported by those brain rhythms. Here we tested the interaction between 10 Hz flicker and endogenous alpha-band (∼10 Hz) oscillations during a selective visuospatial attention task. We recorded EEG from human participants (both genders) while they performed a modified Eriksen flanker task in which distractors and targets flickered within (10 Hz) or outside (7.5 or 15 Hz) the alpha band. By using a combination of EEG source separation, time-frequency, and single-trial linear mixed-effects modeling, we demonstrate that 10 Hz flicker interfered with stimulus processing more on incongruent than congruent trials (high vs low selective attention demands). Crucially, the effect of 10 Hz flicker on task performance was predicted by the distance between 10 Hz and individual alpha peak frequency (estimated during the task). Finally, the flicker effect on task performance was more strongly predicted by EEG flicker responses during stimulus processing than during preparation for the upcoming stimulus, suggesting that 10 Hz flicker interfered more with reactive than proactive selective attention. These findings are consistent with our hypothesis that visual flicker entrained endogenous alpha-band networks, which in turn impaired task performance. Our findings also provide novel evidence for frequency-dependent exogenous modulation of cognition that is determined by the correspondence between the exogenous flicker frequency and the endogenous brain rhythms.SIGNIFICANCE STATEMENT Here we provide novel evidence that the interaction between exogenous rhythmic visual stimulation and endogenous brain rhythms can have frequency-specific behavioral effects. We show that alpha-band (10 Hz) flicker impairs stimulus processing in a selective attention task when the stimulus flicker rate matches individual alpha peak frequency. The effect of sensory flicker on task performance was stronger when selective attention demands were high, and was stronger during stimulus processing and response selection compared with the prestimulus anticipatory period. These findings provide novel evidence that frequency-specific sensory flicker affects online attentional processing, and also demonstrate that the correspondence between exogenous and endogenous rhythms is an overlooked prerequisite when testing for frequency-specific cognitive effects of flicker.

Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles

Sleep spindles are transient oscillatory waveforms that occur during non-rapid eye movement (NREM) sleep across widespread cortical areas. In humans, spindles can be classified as either slow or fast, but large individual differences in spindle frequency as well as methodological difficulties have hindered progress towards understanding their function. Using two nights of high-density electroencephalography recordings from 28 healthy individuals, we first characterize the individual variability of NREM spectra and demonstrate the difficulty of determining subject-specific spindle frequencies. We then introduce a novel spatial filtering approach that can reliably separate subject-specific spindle activity into slow and fast components that are stable across nights and across N2 and N3 sleep. We then proceed to provide detailed analyses of the topographical expression of individualized slow and fast spindle activity. Group-level analyses conform to known spatial properties of spindles, but also uncover novel differences between sleep stages and spindle classes. Moreover, subject-specific examinations reveal that individual topographies show considerable variability that is stable across nights. Finally, we demonstrate that topographical maps depend nontrivially on the spindle metric employed. In sum, our findings indicate that group-level approaches mask substantial individual variability of spindle dynamics, in both the spectral and spatial domains. We suggest that leveraging, rather than ignoring, such differences may prove useful to further our understanding of the physiology and functional role of sleep spindles.

Entrainment of visual steady-state responses is modulated by global spatial statistics

The rhythmic delivery of visual stimuli evokes large-scale neuronal entrainment in the form of steady-state oscillatory field potentials. The spatiotemporal properties of stimulus drive appear to constrain the relative degrees of neuronal entrainment. Specific frequency ranges, for example, are uniquely suited for enhancing the strength of stimulus-driven brain oscillations. When it comes to the nature of the visual stimulus itself, studies have used a plethora of inputs ranging from spatially unstructured empty fields to simple contrast patterns (checkerboards, gratings, stripes) and complex arrays (human faces, houses, natural scenes). At present, little is known about how the global spatial statistics of the input stimulus influence entrainment of scalp-recorded electrophysiological signals. In this study, we used rhythmic entrainment source separation of scalp EEG to compare stimulus-driven phase alignment for distinct classes of visual inputs, including broadband spatial noise ensembles with varying second-order statistics, natural scenes, and narrowband sine-wave gratings delivered at a constant flicker frequency. The relative magnitude of visual entrainment was modulated by the global properties of the driving stimulus. Entrainment was strongest for pseudo-naturalistic broadband visual noise patterns in which luminance contrast is greatest at low spatial frequencies (a power spectrum slope characterized by 1/ƒ-2).NEW & NOTEWORTHY Rhythmically modulated visual stimuli entrain the activity of neuronal populations, but the effect of global stimulus statistics on this entrainment is unknown. We assessed entrainment evoked by 1) visual noise ensembles with different spectral slopes, 2) complex natural scenes, and 3) narrowband sinusoidal gratings. Entrainment was most effective for broadband noise with naturalistic luminance contrast. This reveals some global properties shaping stimulus-driven brain oscillations in the human visual system.

Protecting visual short-term memory during maintenance: Attentional modulation of target and distractor representations

In the presence of distraction, attentional filtering is a key predictor of efficient information storage in visual short-term memory (VSTM). Yet, the role of attention in distractor filtering, and the extent to which attentional filtering continues to protect information during post-perceptual stages of VSTM, remains largely unknown. In the current study, we investigated the role of spatial attention in distractor filtering during VSTM encoding and maintenance. Participants performed a change detection task with varying distractor load. Attentional deployment to target and distractor locations was tracked continuously by means of Steady-State Visual Evoked Potentials (SSVEPs). Analyses revealed that attention strongly modulated the amplitude of the second harmonic SSVEP response, with larger amplitudes at target compared to distractor locations. These attentional modulations commenced during encoding, and remained present during maintenance. Furthermore, the amount of attention paid to distractor locations was directly related to behavioral distractor costs: Individuals who paid more attention to target compared to distractor locations during VSTM maintenance generally suffered less from the presence of distractors. Together, these findings support an important role of spatial attention in distractor filtering at multiple stages of VSTM, and highlight the usefulness of SSVEPs in continuously tracking attention to multiple locations during VSTM.

Exploring the temporal dynamics of sustained and transient spatial attention using steady-state visual evoked potentials

While the behavioral dynamics as well as the functional network of sustained and transient attention have extensively been studied, their underlying neural mechanisms have most often been investigated in separate experiments. In the present study, participants were instructed to perform an audio-visual spatial attention task. They were asked to attend to either the left or the right hemifield and to respond to deviant transient either auditory or visual stimuli. Steady-state visual evoked potentials (SSVEPs) elicited by two task irrelevant pattern reversing checkerboards flickering at 10 and 15 Hz in the left and the right hemifields, respectively, were used to continuously monitor the locus of spatial attention. The amplitude and phase of the SSVEPs were extracted for single trials and were separately analyzed. Sustained attention to one hemifield (spatial attention) as well as to the auditory modality (intermodal attention) increased the inter-trial phase locking of the SSVEP responses, whereas briefly presented visual and auditory stimuli decreased the single-trial SSVEP amplitude between 200 and 500 ms post-stimulus. This transient change of the single-trial amplitude was restricted to the SSVEPs elicited by the reversing checkerboard in the spatially attended hemifield and thus might reflect a transient re-orienting of attention towards the brief stimuli. Thus, the present results demonstrate independent, but interacting neural mechanisms of sustained and transient attentional orienting.

Multivariate cross-frequency coupling via generalized eigendecomposition

This paper presents a new framework for analyzing cross-frequency coupling in multichannel electrophysiological recordings. The generalized eigendecomposition-based cross-frequency coupling framework (gedCFC) is inspired by source-separation algorithms combined with dynamics of mesoscopic neurophysiological processes. It is unaffected by factors that confound traditional CFC methods—such as non-stationarities, non-sinusoidality, and non-uniform phase angle distributions—attractive properties considering that brain activity is neither stationary nor perfectly sinusoidal. The gedCFC framework opens new opportunities for conceptualizing CFC as network interactions with diverse spatial/topographical distributions. Five specific methods within the gedCFC framework are detailed, these are validated in simulated data and applied in several empirical datasets. gedCFC accurately recovers physiologically plausible CFC patterns embedded in noise that causes traditional CFC methods to perform poorly. The paper also demonstrates that spike-field coherence in multichannel local field potential data can be analyzed using the gedCFC framework, which provides significant advantages over traditional spike-field coherence analyses. Null-hypothesis testing is also discussed.

DOI:http://dx.doi.org/10.7554/eLife.21792.001