Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language.

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations.

Interdependence of "What" and "When" in the Brain.

From a brain's-eye-view, when a stimulus occurs and what it is are interrelated aspects of interpreting the perceptual world. Yet in practice, the putative perceptual inferences about sensory content and timing are often dichotomized and not investigated as an integrated process. We here argue that neural temporal dynamics can influence what is perceived, and in turn, stimulus content can influence the time at which perception is achieved. This computational principle results from the highly interdependent relationship of what and when in the environment. Both brain processes and perceptual events display strong temporal variability that is not always modeled; we argue that understanding-and, minimally, modeling-this temporal variability is key for theories of how the brain generates unified and consistent neural representations and that we ignore temporal variability in our analysis practice at the peril of both data interpretation and theory-building. Here, we review what and when interactions in the brain, demonstrate via simulations how temporal variability can result in misguided interpretations and conclusions, and outline how to integrate and synthesize what and when in theories and models of brain computation.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Inferring the nature of linguistic computations in the brain.

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

No evidence of rhythmic visuospatial attention at cued locations in a spatial cuing paradigm, regardless of their behavioural relevance.

Recent evidence suggests that visuospatial attentional performance is not stable over time but fluctuates in a rhythmic fashion. These attentional rhythms allow for sampling of different visuospatial locations in each cycle of this rhythm. However, it is still unclear in which paradigmatic circumstances rhythmic attention becomes evident. First, it is unclear at what spatial locations rhythmic attention occurs. Second, it is unclear how the behavioural relevance of each spatial location determines the rhythmic sampling patterns. Here, we aim to elucidate these two issues. Firstly, we aim to find evidence of rhythmic attention at the predicted (i.e. cued) location under moderately informative predictor value, replicating earlier studies. Secondly, we hypothesise that rhythmic attentional sampling behaviour will be affected by the behavioural relevance of the sampled location, ranging from non-informative to fully informative. To these aims, we used a modified Egly-Driver task with three conditions: a fully informative cue, a moderately informative cue (replication condition), and a non-informative cue. We did not find evidence of rhythmic sampling at cued locations, failing to replicate earlier studies. Nor did we find differences in rhythmic sampling under different predictive values of the cue. The current data does not allow for robust conclusions regarding the non-cued locations due to the absence of a priori hypotheses. Post-hoc explorative data analyses, however, clearly indicate that attention samples non-cued locations in a theta-rhythmic manner, specifically when the cued location bears higher behavioural relevance than the non-cued locations.

Calibrating rhythmic stimulation parameters to individual electroencephalography markers: The consistency of individual alpha frequency in practical lab settings.

Rhythmic stimulation can be applied to modulate neuronal oscillations. Such 'entrainment' is optimized when stimulation frequency is individually calibrated based on magneto/encephalography markers. It remains unknown how consistent such individual markers are across days/sessions, within a session, or across cognitive states, hemispheres and estimation methods, especially in a realistic, practical, lab setting. We here estimated individual alpha frequency (IAF) repeatedly from short electroencephalography (EEG) measurements at rest or during an attention task (cognitive state), using single parieto-occipital electrodes in 24 participants on 4 days (between-sessions), with multiple measurements over an hour on 1 day (within-session). First, we introduce an algorithm to automatically reject power spectra without a sufficiently clear peak to ensure unbiased IAF estimations. Then we estimated IAF via the traditional 'maximum' method and a 'Gaussian fit' method. IAF was reliable within- and between-sessions for both cognitive states and hemispheres, though task-IAF estimates tended to be more variable. Overall, the 'Gaussian fit' method was more reliable than the 'maximum' method. Furthermore, we evaluated how far from an approximated 'true' task-related IAF the selected 'stimulation frequency' was, when calibrating this frequency based on a short rest-EEG, a short task-EEG, or simply selecting 10 Hz for all participants. For the 'maximum' method, rest-EEG calibration was best, followed by task-EEG, and then 10 Hz. For the 'Gaussian fit' method, rest-EEG and task-EEG-based calibration were similarly accurate, and better than 10 Hz. These results lead to concrete recommendations about valid, and automated, estimation of individual oscillation markers in experimental and clinical settings.

Linguistic Structure and Meaning Organize Neural Oscillations into a Content-Specific Hierarchy.

Neural oscillations track linguistic information during speech comprehension (Ding et al., 2016; Keitel et al., 2018), and are known to be modulated by acoustic landmarks and speech intelligibility (Doelling et al., 2014; Zoefel and VanRullen, 2015). However, studies investigating linguistic tracking have either relied on non-naturalistic isochronous stimuli or failed to fully control for prosody. Therefore, it is still unclear whether low-frequency activity tracks linguistic structure during natural speech, where linguistic structure does not follow such a palpable temporal pattern. Here, we measured electroencephalography (EEG) and manipulated the presence of semantic and syntactic information apart from the timescale of their occurrence, while carefully controlling for the acoustic-prosodic and lexical-semantic information in the signal. EEG was recorded while 29 adult native speakers (22 women, 7 men) listened to naturally spoken Dutch sentences, jabberwocky controls with morphemes and sentential prosody, word lists with lexical content but no phrase structure, and backward acoustically matched controls. Mutual information (MI) analysis revealed sensitivity to linguistic content: MI was highest for sentences at the phrasal (0.8-1.1 Hz) and lexical (1.9-2.8 Hz) timescales, suggesting that the delta-band is modulated by lexically driven combinatorial processing beyond prosody, and that linguistic content (i.e., structure and meaning) organizes neural oscillations beyond the timescale and rhythmicity of the stimulus. This pattern is consistent with neurophysiologically inspired models of language comprehension (Martin, 2016, 2020; Martin and Doumas, 2017) where oscillations encode endogenously generated linguistic content over and above exogenous or stimulus-driven timing and rhythm information.SIGNIFICANCE STATEMENT Biological systems like the brain encode their environment not only by reacting in a series of stimulus-driven responses, but by combining stimulus-driven information with endogenous, internally generated, inferential knowledge and meaning. Understanding language from speech is the human benchmark for this. Much research focuses on the purely stimulus-driven response, but here, we focus on the goal of language behavior: conveying structure and meaning. To that end, we use naturalistic stimuli that contrast acoustic-prosodic and lexical-semantic information to show that, during spoken language comprehension, oscillatory modulations reflect computations related to inferring structure and meaning from the acoustic signal. Our experiment provides the first evidence to date that compositional structure and meaning organize the oscillatory response, above and beyond prosodic and lexical controls.

Information redundancy across spatial scales modulates early visual cortical processing.

Visual images contain redundant information across spatial scales where low spatial frequency contrast is informative towards the location and likely content of high spatial frequency detail. Previous research suggests that the visual system makes use of those redundancies to facilitate efficient processing. In this framework, a fast, initial analysis of low-spatial frequency (LSF) information guides the slower and later processing of high spatial frequency (HSF) detail. Here, we used multivariate classification as well as time-frequency analysis of MEG responses to the viewing of intact and phase scrambled images of human faces to demonstrate that the availability of redundant LSF information, as found in broadband intact images, correlates with a reduction in HSF representational dominance in both early and higher-level visual areas as well as a reduction of gamma-band power in early visual cortex. Our results indicate that the cross spatial frequency information redundancy that can be found in all natural images might be a driving factor in the efficient integration of fine image details.

Does alpha phase modulate visual target detection? Three experiments with tACS-phase-based stimulus presentation.

In recent years, the influence of alpha (7-13 Hz) phase on visual processing has received a lot of attention. Magneto-/encephalography (M/EEG) studies showed that alpha phase indexes visual excitability and task performance. Studies with transcranial alternating current stimulation (tACS) aim to modulate oscillations and causally impact task performance. Here, we applied right occipital tACS (O2 location) to assess the functional role of alpha phase in a series of experiments. We presented visual stimuli at different pre-determined, experimentally controlled, phases of the entraining tACS signal, hypothesizing that this should result in an oscillatory pattern of visual performance in specifically left hemifield detection tasks. In experiment 1, we applied 10 Hz tACS and used separate psychophysical staircases for six equidistant tACS-phase conditions, obtaining contrast thresholds for detection of visual gratings in left or right hemifield. In experiments 2 and 3, tACS was at EEG-based individual peak alpha frequency. In experiment 2, we measured detection rates for gratings with (pseudo-)fixed contrast. In experiment 3, participants detected brief luminance changes in a custom-built LED device, at eight equidistant alpha phases. In none of the experiments did the primary outcome measure over phase conditions consistently reflect a one-cycle sinusoid. However, post hoc analyses of reaction times (RT) suggested that tACS alpha phase did modulate RT for specifically left hemifield targets in both experiments 1 and 2 (not measured in experiment 3). This observation requires future confirmation, but is in line with the idea that alpha phase causally gates visual inputs through cortical excitability modulation.

Coarse-to-fine information integration in human vision.

Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in naturalistic broad-band stimuli is still unclear. Here we used multivariate decoding of EEG signals to separate the respective contribution of LSF and HSF to the neural response evoked by broad-band images. Participants viewed images of human faces, monkey faces and phase-scrambled versions that were either broad-band or filtered to contain LSF or HSF. We trained classifiers on EEG scalp-patterns evoked by filtered scrambled stimuli and evaluated the derived models on broad-band scrambled and intact trials. We found reduced HSF contribution when LSF was informative towards image content, indicating that coarse information does guide the processing of fine detail, in line with coarse-to-fine theories. We discuss the potential cortical mechanisms underlying such coarse-to-fine feedback.

Low-Frequency Cortical Oscillations Entrain to Subthreshold Rhythmic Auditory Stimuli.

Many environmental stimuli contain temporal regularities, a feature that can help predict forthcoming input. Phase locking (entrainment) of ongoing low-frequency neuronal oscillations to rhythmic stimuli is proposed as a potential mechanism for enhancing neuronal responses and perceptual sensitivity, by aligning high-excitability phases to events within a stimulus stream. Previous experiments show that rhythmic structure has a behavioral benefit even when the rhythm itself is below perceptual detection thresholds (ten Oever et al., 2014). It is not known whether this "inaudible" rhythmic sound stream also induces entrainment. Here we tested this hypothesis using magnetoencephalography and electrocorticography in humans to record changes in neuronal activity as subthreshold rhythmic stimuli gradually became audible. We found that significant phase locking to the rhythmic sounds preceded participants' detection of them. Moreover, no significant auditory-evoked responses accompanied this prethreshold entrainment. These auditory-evoked responses, distinguished by robust, broad-band increases in intertrial coherence, only appeared after sounds were reported as audible. Taken together with the reduced perceptual thresholds observed for rhythmic sequences, these findings support the proposition that entrainment of low-frequency oscillations serves a mechanistic role in enhancing perceptual sensitivity for temporally predictive sounds. This framework has broad implications for understanding the neural mechanisms involved in generating temporal predictions and their relevance for perception, attention, and awareness.SIGNIFICANCE STATEMENT The environment is full of rhythmically structured signals that the nervous system can exploit for information processing. Thus, it is important to understand how the brain processes such temporally structured, regular features of external stimuli. Here we report the alignment of slowly fluctuating oscillatory brain activity to external rhythmic structure before its behavioral detection. These results indicate that phase alignment is a general mechanism of the brain to process rhythmic structure and can occur without the perceptual detection of this temporal structure.

Single-trial log transformation is optimal in frequency analysis of resting EEG alpha.

The appropriate definition and scaling of the magnitude of electroencephalogram (EEG) oscillations is an underdeveloped area. The aim of this study was to optimize the analysis of resting EEG alpha magnitude, focusing on alpha peak frequency and nonlinear transformation of alpha power. A family of nonlinear transforms, Box-Cox transforms, were applied to find the transform that (a) maximized a non-disputed effect: the increase in alpha magnitude when the eyes are closed (Berger effect), and (b) made the distribution of alpha magnitude closest to normal across epochs within each participant, or across participants. The transformations were performed either at the single epoch level or at the epoch-average level. Alpha peak frequency showed large individual differences, yet good correspondence between various ways to estimate it in 2 min of eyes-closed and 2 min of eyes-open resting EEG data. Both alpha magnitude and the Berger effect were larger for individual alpha than for a generic (8-12 Hz) alpha band. The log-transform on single epochs (a) maximized the t-value of the contrast between the eyes-open and eyes-closed conditions when tested within each participant, and (b) rendered near-normally distributed alpha power across epochs and participants, thereby making further transformation of epoch averages superfluous. The results suggest that the log-normal distribution is a fundamental property of variations in alpha power across time in the order of seconds. Moreover, effects on alpha power appear to be multiplicative rather than additive. These findings support the use of the log-transform on single epochs to achieve appropriate scaling of alpha magnitude.

Oscillatory phase shapes syllable perception.

The role of oscillatory phase for perceptual and cognitive processes is being increasingly acknowledged. To date, little is known about the direct role of phase in categorical perception. Here we show in two separate experiments that the identification of ambiguous syllables that can either be perceived as /da/ or /ga/ is biased by the underlying oscillatory phase as measured with EEG and sensory entrainment to rhythmic stimuli. The measured phase difference in which perception is biased toward /da/ or /ga/ exactly matched the different temporal onset delays in natural audiovisual speech between mouth movements and speech sounds, which last 80 ms longer for /ga/ than for /da/. These results indicate the functional relationship between prestimulus phase and syllable identification, and signify that the origin of this phase relationship could lie in exposure and subsequent learning of unique audiovisual temporal onset differences.

The COGs (context, object, and goals) in multisensory processing.

Our understanding of how perception operates in real-world environments has been substantially advanced by studying both multisensory processes and "top-down" control processes influencing sensory processing via activity from higher-order brain areas, such as attention, memory, and expectations. As the two topics have been traditionally studied separately, the mechanisms orchestrating real-world multisensory processing remain unclear. Past work has revealed that the observer's goals gate the influence of many multisensory processes on brain and behavioural responses, whereas some other multisensory processes might occur independently of these goals. Consequently, other forms of top-down control beyond goal dependence are necessary to explain the full range of multisensory effects currently reported at the brain and the cognitive level. These forms of control include sensitivity to stimulus context as well as the detection of matches (or lack thereof) between a multisensory stimulus and categorical attributes of naturalistic objects (e.g. tools, animals). In this review we discuss and integrate the existing findings that demonstrate the importance of such goal-, object- and context-based top-down control over multisensory processing. We then put forward a few principles emerging from this literature review with respect to the mechanisms underlying multisensory processing and discuss their possible broader implications.

Increased Stimulus Expectancy Triggers Low-frequency Phase Reset during Restricted Vigilance.

Temporal cues can be used to selectively attend to relevant information during abundant sensory stimulation. However, such cues differ vastly in the accuracy of their temporal estimates, ranging from very predictable to very unpredictable. When cues are strongly predictable, attention may facilitate selective processing by aligning relevant incoming information to high neuronal excitability phases of ongoing low-frequency oscillations. However, top-down effects on ongoing oscillations when temporal cues have some predictability, but also contain temporal uncertainties, are unknown. Here, we experimentally created such a situation of mixed predictability and uncertainty: A target could occur within a limited time window after cue but was always unpredictable in exact timing. Crucially to assess top-down effects in such a mixed situation, we manipulated target probability. High target likelihood, compared with low likelihood, enhanced delta oscillations more strongly as measured by evoked power and intertrial coherence. Moreover, delta phase modulated detection rates for probable targets. The delta frequency range corresponds with half-a-period to the target occurrence window and therefore suggests that low-frequency phase reset is engaged to produce a long window of high excitability when event timing is uncertain within a restricted temporal window.

Investigating the role of task relevance during rhythmic sampling of spatial locations.

Recently it has been discovered that visuospatial attention operates rhythmically, rather than being stably employed over time. A low-frequency 7-8 Hz rhythmic mechanism coordinates periodic windows to sample relevant locations and to shift towards other, less relevant locations in a visual scene. Rhythmic sampling theories would predict that when two locations are relevant 8 Hz sampling mechanisms split into two, effectively resulting in a 4 Hz sampling frequency at each location. Therefore, it is expected that rhythmic sampling is influenced by the relative importance of locations for the task at hand. To test this, we employed an orienting task with an arrow cue, where participants were asked to respond to a target presented in one visual field. The cue-to-target interval was systematically varied, allowing us to assess whether performance follows a rhythmic pattern across cue-to-target delays. We manipulated a location's task relevance by altering the validity of the cue, thereby predicting the correct location in 60%, 80% or 100% of trials. Results revealed significant 4 Hz performance fluctuations at cued right visual field targets with low cue validity (60%), suggesting regular sampling of both locations. With high cue validity (80%), we observed a peak at 8 Hz towards non-cued targets, although not significant. These results were in line with our hypothesis suggesting a goal-directed balancing of attentional sampling (cued location) and shifting (non-cued location) depending on the relevance of locations in a visual scene. However, considering the hemifield specificity of the effect together with the absence of expected effects for cued trials in the high valid conditions we further discuss the interpretation of the data.

The sound of size: crossmodal binding in pitch-size synesthesia: a combined TMS, EEG and psychophysics study.

Crossmodal binding usually relies on bottom-up stimulus characteristics such as spatial and temporal correspondence. However, in case of ambiguity the brain has to decide whether to combine or segregate sensory inputs. We hypothesise that widespread, subtle forms of synesthesia provide crossmodal mapping patterns which underlie and influence multisensory perception. Our aim was to investigate if such a mechanism plays a role in the case of pitch-size stimulus combinations. Using a combination of psychophysics and ERPs, we could show that despite violations of spatial correspondence, the brain specifically integrates certain stimulus combinations which are congruent with respect to our hypothesis of pitch-size synesthesia, thereby impairing performance on an auditory spatial localisation task (Ventriloquist effect). Subsequently, we perturbed this process by functionally disrupting a brain area known for its role in multisensory processes, the right intraparietal sulcus, and observed how the Ventriloquist effect was abolished, thereby increasing behavioural performance. Correlating behavioural, TMS and ERP results, we could retrace the origin of the synesthestic pitch-size mappings to a right intraparietal involvement around 250 ms. The results of this combined psychophysics, TMS and ERP study provide evidence for shifting the current viewpoint on synesthesia more towards synesthesia being at the extremity of a spectrum of normal, adaptive perceptual processes, entailing close interplay between the different sensory systems. Our results support this spectrum view of synesthesia by demonstrating that its neural basis crucially depends on normal multisensory processes.

Neural tracking of phrases in spoken language comprehension is automatic and task-dependent.

Linguistic phrases are tracked in sentences even though there is no one-to-one acoustic phrase marker in the physical signal. This phenomenon suggests an automatic tracking of abstract linguistic structure that is endogenously generated by the brain. However, all studies investigating linguistic tracking compare conditions where either relevant information at linguistic timescales is available, or where this information is absent altogether (e.g., sentences versus word lists during passive listening). It is therefore unclear whether tracking at phrasal timescales is related to the content of language, or rather, results as a consequence of attending to the timescales that happen to match behaviourally relevant information. To investigate this question, we presented participants with sentences and word lists while recording their brain activity with magnetoencephalography (MEG). Participants performed passive, syllable, word, and word-combination tasks corresponding to attending to four different rates: one they would naturally attend to, syllable-rates, word-rates, and phrasal-rates, respectively. We replicated overall findings of stronger phrasal-rate tracking measured with mutual information for sentences compared to word lists across the classical language network. However, in the inferior frontal gyrus (IFG) we found a task effect suggesting stronger phrasal-rate tracking during the word-combination task independent of the presence of linguistic structure, as well as stronger delta-band connectivity during this task. These results suggest that extracting linguistic information at phrasal rates occurs automatically with or without the presence of an additional task, but also that IFG might be important for temporal integration across various perceptual domains.

Parietal but not temporoparietal alpha-tACS modulates endogenous visuospatial attention.

Visuospatial attention can either be voluntarily directed (endogenous/top-down attention) or automatically triggered (exogenous/bottom-up attention). Recent research showed that dorsal parietal transcranial alternating current stimulation (tACS) at alpha frequency modulates the spatial attentional bias in an endogenous but not in an exogenous visuospatial attention task. Yet, the reason for this task-specificity remains unexplored. Here, we tested whether this dissociation relates to the proposed differential role of the dorsal attention network (DAN) and ventral attention network (VAN) in endogenous and exogenous attention processes respectively. To that aim, we targeted the left and right dorsal parietal node of the DAN, as well as the left and right ventral temporoparietal node of the VAN using tACS at the individual alpha frequency. Every participant completed all four stimulation conditions and a sham condition in five separate sessions. During tACS, we assessed the behavioral visuospatial attention bias via an endogenous and exogenous visuospatial attention task. Additionally, we measured offline alpha power immediately before and after tACS using electroencephalography (EEG). The behavioral data revealed an effect of tACS on the endogenous but not exogenous attention bias, with a greater leftward bias during (sham-corrected) left than right hemispheric stimulation. In line with our hypothesis, this effect was brain area-specific, i.e., present for dorsal parietal but not ventral temporoparietal tACS. However, contrary to our expectations, there was no effect of ventral temporoparietal tACS on the exogenous visuospatial attention bias. Hence, no double dissociation between the two targeted attention networks. There was no effect of either tACS condition on offline alpha power. Our behavioral data reveal that dorsal parietal but not ventral temporoparietal alpha oscillations steer endogenous visuospatial attention. This brain-area specific tACS effect matches the previously proposed dissociation between the DAN and VAN and, by showing that the spatial attention bias effect does not generalize to any lateral posterior tACS montage, renders lateral cutaneous and retinal effects for the spatial attention bias in the dorsal parietal condition unlikely. Yet the absence of tACS effects on the exogenous attention task suggests that ventral temporoparietal alpha oscillations are not functionally relevant for exogenous visuospatial attention. We discuss the potential implications of this finding in the context of an emerging theory on the role of the ventral temporoparietal node.