Perception of illusory contours forms intermodulation responses of steady state visual evoked potentials as a neural signature of spatial integration

Optimal gamma-band entrainment of visual cortex

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14-16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma-band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma-band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma-band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high-density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma-band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. PRACTITIONER POINTS: Gamma-band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown. We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma-band frequencies. These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions.

Measuring attentional selection of object categories using hierarchical frequency tagging

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

The development of oscillatory and aperiodic resting state activity is linked to a sensitive period in humans

Congenital blindness leads to profound changes in electroencephalographic (EEG) resting state activity. A well-known consequence of congenital blindness in humans is the reduction of alpha activity which seems to go together with increased gamma activity during rest. These results have been interpreted as indicating a higher excitatory/inhibitory (E/I) ratio in visual cortex compared to normally sighted controls. Yet it is unknown whether the spectral profile of EEG during rest would recover if sight were restored. To test this question, the present study evaluated periodic and aperiodic components of the EEG resting state power spectrum. Previous research has linked the aperiodic components, which exhibit a power-law distribution and are operationalized as a linear fit of the spectrum in log-log space, to cortical E/I ratio. Moreover, by correcting for the aperiodic components from the power spectrum, a more valid estimate of the periodic activity is possible. Here we analyzed resting state EEG activity from two studies involving (1) 27 permanently congenitally blind adults (CB) and 27 age-matched normally sighted controls (MCB); (2) 38 individuals with reversed blindness due to bilateral, dense, congenital cataracts (CC) and 77 age-matched sighted controls (MCC). Based on a data driven approach, aperiodic components of the spectra were extracted for the low frequency (Lf-Slope 1.5 to 19.5 Hz) and high frequency (Hf-Slope 20 to 45 Hz) range. The Lf-Slope of the aperiodic component was significantly steeper (more negative slope), and the Hf-Slope of the aperiodic component was significantly flatter (less negative slope) in CB and CC participants compared to the typically sighted controls. Alpha power was significantly reduced, and gamma power was higher in the CB and the CC groups. These results suggest a sensitive period for the typical development of the spectral profile during rest and thus likely an irreversible change in the E/I ratio in visual cortex due to congenital blindness. We speculate that these changes are a consequence of impaired inhibitory circuits and imbalanced feedforward and feedback processing in early visual areas of individuals with a history of congenital blindness.

Effects of altered-reality training on interocular disinhibition in amblyopia

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

Intermodulation from Unisensory to Multisensory Perception: A Review

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

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

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

Nonlinear System Identification of Neural Systems from Neurophysiological Signals

The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a certain amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention.

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

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

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

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

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

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

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

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

Quantifying the Nonlinear Interaction in the Nervous System Based on Phase-Locked Amplitude Relationship

OBJECTIVE

This paper introduces the Cross-frequency Amplitude Transfer Function (CATF), a model-free method for quantifying nonlinear stimulus-response interaction based on phase-locked amplitude relationship.

METHOD

The CATF estimates the amplitude transfer from input frequencies at stimulation signal to their harmonics/intermodulation at the response signal. We first verified the performance of CATF in simulation tests with systems containing a static nonlinear function and a linear dynamic, i.e., Hammerstein and Wiener systems. We then applied the CATF to investigate the second-order nonlinear amplitude transfer in the human proprioceptive system from the periphery to the cortex.

RESULT

The simulation demonstrated that the CATF is a general method, which can well quantify nonlinear stimulus-response amplitude transfer for different orders of nonlinearity in Wiener or Hammerstein system configurations. Applied to the human proprioceptive system, we found a complicated nonlinear system behavior with substantial amplitude transfer from the periphery stimulation to cortical response signals in the alpha band. This complicated system behavior may be associated with the nonlinear behavior of the muscle spindle and the dynamic interaction in the thalamocortical radiation.

CONCLUSION

This paper provides a new tool to identify nonlinear interaction in the nervous system.

SIGNIFICANCE

The results provide novel insight of nonlinear dynamics in the human proprioceptive system.

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.

From intermodulation components to visual perception and cognition-a review

Perception results from complex interactions among sensory and cognitive processes across hierarchical levels in the brain. Intermodulation (IM) components, used in frequency tagging neuroimaging designs, have emerged as a promising direct measure of such neural interactions. IMs have initially been used in electroencephalography (EEG) to investigate low-level visual processing. In a more recent trend, IMs in EEG and other neuroimaging methods are being used to shed light on mechanisms of mid- and high-level perceptual processes, including the involvement of cognitive functions such as attention and expectation. Here, we provide an account of various mechanisms that may give rise to IMs in neuroimaging data, and what these IMs may look like. We discuss methodologies that can be implemented for different uses of IMs and we demonstrate how IMs can provide insights into the existence, the degree and the type of neural integration mechanisms at hand. We then review a range of recent studies exploiting IMs in visual perception research, placing an emphasis on high-level vision and the influence of awareness and cognition on visual processing. We conclude by suggesting future directions that can enhance the benefits of IM-methodology in perception research.

Rapid Extraction of Emotion Regularities from Complex Scenes in the Human Brain

Adaptive behavior requires the rapid extraction of behaviorally relevant information in the environment, with particular emphasis on emotional cues. However, the speed of emotional feature extraction from complex visual environments is largely undetermined. Here we use objective electrophysiological recordings in combination with frequency tagging to demonstrate that the extraction of emotional information from neutral, pleasant, or unpleasant naturalistic scenes can be completed at a presentation speed of 167 ms (i.e., 6 Hz) under high perceptual load. Emotional compared to neutral pictures evoked enhanced electrophysiological responses with distinct topographical activation patterns originating from different neural sources. Cortical facilitation in early visual cortex was also more pronounced for scenes with pleasant compared to unpleasant or neutral content, suggesting a positivity offset mechanism dominating under conditions of rapid scene processing. These results significantly advance our knowledge of complex scene processing in demonstrating rapid integrative content identification, particularly for emotional cues relevant for adaptive behavior in complex environments.

Steady-state visual evoked potentials reveal enhanced neural responses to illusory surfaces during a concurrent visual attention task

Under natural viewing conditions, visual stimuli are often obscured by occluding surfaces. To aid object recognition, the visual system actively reconstructs the missing information, as exemplified in the classic Kanizsa illusion, a phenomenon termed "modal completion". Single-cell recordings in monkeys have shown that neurons in early visual cortex respond to illusory contours, but it has proven difficult to measure the neural correlates of modal completion in humans. We used electroencephalography (EEG) to measure steady-state visual-evoked potentials (SSVEPs) from disks with quarter segments removed to induce an illusory shape (or rotated to eliminate the illusory square in control trials). Opposing pairs of inducers were tagged with one of two flicker frequencies (2.5 or 4 Hz). During stimulus presentations, participants performed an attention task at fixation that required them to judge the orientation of a briefly flashed central bar while ignoring congruent (same orientation) or incongruent (different orientation) flanker bars that appeared on or off the illusory surface. Importantly, the occurrence of any illusory shape was never task relevant. Frequency-based analyses revealed that SSVEP amplitudes were reliably enhanced for trials in which an illusory square appeared, relative to control trials, at 4, 5 and 8 Hz and at an intermodulation frequency of 13 Hz. Participants' reaction times in the flanker task were significantly slower for incongruent versus congruent trials, and this distractor interference effect occurred only in the presence of an illusory surface and not in the control condition. Our results reveal a robust neural correlate of modal completion in the human visual system and provide evidence that visual completion can affect attentional control processes as deployed in a flanker task.

Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways

Perception likely results from the interplay between sensory information and top-down signals. In this electroencephalography (EEG) study, we utilised the hierarchical frequency tagging (HFT) method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of nonlinear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on a multispectral phase coherence (MSPC) measure, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention, which would not have been possible using other amplitude-based measures. Our results link expectation to the modulation of descending signals and to the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, the results link attention to the modulation of ascending signals and to the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.

Enhanced perceptual processing of self-generated motion: Evidence from steady-state visual evoked potentials

The sense of agency emerges when our voluntary actions produce anticipated or predictable outcomes in the external world. It remains unclear how the sense of control also influences our perception of the external world. The present study examined perceptual processing of self-generated motion versus non-self-generated motion using steady-state visual evoked potentials (SSVEPs). Participants continuously moved their finger on a touchpad to trigger the movements of two shapes (Experiment 1) or two groups of dots (Experiment 2) on a monitor. Degree of control was manipulated by varying the spatial relation between finger movement and stimulus trajectory across conditions. However, the velocity, onset time, and offset time of visual stimuli always corresponded to participants' finger movement. Stimuli flickered at a frequency of either 7.5 Hz or 10 Hz, thus SSVEPs of these frequencies and their harmonics provided a frequency-tagged measurement of perceptual processing. Participants triggered the motion of all stimuli simultaneously, but had greater levels of control over some stimuli than over others. Their task was to detect a brief colour change on the border(s) of one shape (Experiment 1) or of one group of dots (Experiment 2). Although control over shapes/dots was irrelevant to the visual detection task, we found stronger SSVEPs for stimuli that were under a high level of control, compared with the stimuli that were under a low level of control. Our results suggest that the spatial regularity between self-generated movements and visual input boosted the neural responses underlying perceptual processing. Our results support the preactivation account of sensory attenuation, suggesting that perceptual processing of self-generated events is enhanced rather than inhibited.

EEG frequency tagging reveals higher order intermodulation components as neural markers of learned holistic shape representations

Shape perception is intrinsically holistic: combinations of features give rise to configurations with emergent properties that are different from the sum of the parts. The current study investigated neural markers of holistic shape representations learned by means of categorization training. We used the EEG frequency tagging technique, where two parts of a shape stimulus were 'tagged' by modifying their contrast at different temporal frequencies. Signals from both parts are integrated and, as a result, emergent frequency components (so-called, intermodulation responses, IMs), caused by nonlinear interaction of two frequency signals, are observed in the EEG spectrum. First, participants were trained in 4 sessions to discriminate highly similar, unfamiliar shapes into two categories, defined based on the combination of features. After training, EEG was recorded while frequency-tagged shapes from either the trained or the untrained shape family were presented. For all IMs combined, no learning effects were detected, but post hoc analyses of higher-order IMs revealed stronger occipital and occipito-temporal IMs for both trained and untrained exemplars of the trained shape family as compared to the untrained shape family. In line with recent findings, we suggest that the higher-order IMs may reflect high-level visual computations, like holistic shape categorization, resulting from a cascade of non-linear operations. Higher order frequency responses are relatively low in power, hence results should be interpreted cautiously and future research is needed to confirm these effects. In general, these findings are, to our knowledge, the first to show IMs as a neural correlate of perceptual learning.

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.

Attention to Multiple Objects Facilitates Their Integration in Prefrontal and Parietal Cortex

Selective attention is known to interact with perceptual organization. In visual scenes, individual objects that are distinct and discriminable may occur on their own, or in groups such as a stack of books. The main objective of this study is to probe the neural interaction that occurs between individual objects when attention is directed toward one or more objects. Here we record steady-state visual evoked potentials via electrocorticography to directly assess the responses to individual stimuli and to their interaction. When human participants attend to two adjacent stimuli, prefrontal and parietal cortex shows a selective enhancement of only the neural interaction between stimuli, but not the responses to individual stimuli. When only one stimulus is attended, the neural response to that stimulus is selectively enhanced in prefrontal and parietal cortex. In contrast, early visual areas generally manifest responses to individual stimuli and to their interaction regardless of attentional task, although a subset of the responses is modulated similarly to prefrontal and parietal cortex. Thus, the neural representation of the visual scene as one progresses up the cortical hierarchy becomes more highly task-specific and represents either individual stimuli or their interaction, depending on the behavioral goal. Attention to multiple objects facilitates an integration of objects akin to perceptual grouping.SIGNIFICANCE STATEMENT Individual objects in a visual scene are seen as distinct entities or as parts of a whole. Here we examine how attention to multiple objects affects their neural representation. Previous studies measured single-cell or fMRI responses and obtained only aggregate measures that combined the activity to individual stimuli as well as their potential interaction. Here, we directly measure electrocorticographic steady-state responses corresponding to individual objects and to their interaction using a frequency-tagging technique. Attention to two stimuli increases the interaction component that is a hallmark for perceptual integration of stimuli. Furthermore, this stimulus-specific interaction is represented in prefrontal and parietal cortex in a task-dependent manner.

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

There is a growing understanding that both top-down and bottom-up signals underlie perception. But it is not known how these signals integrate with each other and how this depends on the perceived stimuli’s predictability. ‘Predictive coding’ theories describe this integration in terms of how well top-down predictions fit with bottom-up sensory input. Identifying neural markers for such signal integration is therefore essential for the study of perception and predictive coding theories. To achieve this, we combined EEG methods that preferentially tag different levels in the visual hierarchy. Importantly, we examined intermodulation components as a measure of integration between these signals. Our results link the different signals to core aspects of predictive coding, and suggest that top-down predictions indeed integrate with bottom-up signals in a manner that is modulated by the predictability of the sensory input, providing evidence for predictive coding and opening new avenues to studying such interactions in perception.

DOI:http://dx.doi.org/10.7554/eLife.22749.001

Connections between intraparietal sulcus and a sensorimotor network underpin sustained tactile attention

Previous studies on sustained tactile attention draw conclusions about underlying cortical networks by averaging over experimental conditions without considering attentional variance in single trials. This may have formed an imprecise picture of brain processes underpinning sustained tactile attention. In the present study, we simultaneously recorded EEG-fMRI and used modulations of steady-state somatosensory evoked potentials (SSSEPs) as a measure of attentional trial-by-trial variability. Therefore, frequency-tagged streams of vibrotactile stimulations were simultaneously presented to both index fingers. Human participants were cued to sustain attention to either the left or right finger stimulation and to press a button whenever they perceived a target pulse embedded in the to-be-attended stream. In-line with previous studies, a classical general linear model (GLM) analysis based on cued attention conditions revealed increased activity mainly in somatosensory and cerebellar regions. Yet, parametric modeling of the BOLD response using simultaneously recorded SSSEPs as a marker of attentional trial-by-trial variability quarried the intraparietal sulcus (IPS). The IPS in turn showed enhanced functional connectivity to a modality-unspecific attention network. However, this was only revealed on the basis of cued attention conditions in the classical GLM. By considering attentional variability as captured by SSSEPs, the IPS showed increased connectivity to a sensorimotor network, underpinning attentional selection processes between competing tactile stimuli and action choices (press a button or not). Thus, the current findings highlight the potential value by considering attentional variations in single trials and extend previous knowledge on the role of the IPS in tactile attention.

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

Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.