Evoked traveling alpha waves predict visual-semantic categorization-speed

Event-related modulation of alpha rhythm explains the auditory P300-evoked response in EEG

Evoked responses and oscillations represent two major electrophysiological phenomena in the human brain yet the link between them remains rather obscure. Here we show how most frequently studied EEG signals: the P300-evoked response and alpha oscillations (8-12 Hz) can be linked with the baseline-shift mechanism. This mechanism states that oscillations generate evoked responses if oscillations have a non-zero mean and their amplitude is modulated by the stimulus. Therefore, the following predictions should hold: (1) the temporal evolution of P300 and alpha amplitude is similar, (2) spatial localisations of the P300 and alpha amplitude modulation overlap, (3) oscillations are non-zero mean, (4) P300 and alpha amplitude correlate with cognitive scores in a similar fashion. To validate these predictions, we analysed the data set of elderly participants (N=2230, 60-82 years old), using (a) resting-state EEG recordings to quantify the mean of oscillations, (b) the event-related data, to extract parameters of P300 and alpha rhythm amplitude envelope. We showed that P300 is indeed linked to alpha rhythm, according to all four predictions. Our results provide an unifying view on the interdependency of evoked responses and neuronal oscillations and suggest that P300, at least partly, is generated by the modulation of alpha oscillations.

Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions

Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.

Electrophysiological Changes in Patients with Post-stroke Aphasia: A Systematic Review

Background Magnetoencephalography (MEG) and electroencephalography (EEG) record two main types of data: continuous measurements at rest or during sleep, and event-related potentials/evoked magnetic fields (ERPs/EMFs) that involve specific and repetitive tasks. In this systematic review, we summarized longitudinal studies on recovery from post-stroke aphasia that used continuous or event-related temporal imaging (EEG or MEG). Methods We searched PubMed and Scopus for English articles published from 1950 to May 31, 2022. Results 34 studies were included in this review: 11 were non-interventional studies and 23 were clinical trials that used specific rehabilitation methods, neuromodulation, or drugs. The results of the non-interventional studies suggested that poor language recovery was associated with slow-wave activity persisting over time. The results of some clinical trials indicated that behavioral improvements were correlated with significant modulation of the N400 component. Discussion Compared with continuous EEG, ERP/EMF may more reliably identify biomarkers of therapy-induced effects. Electrophysiology should be used more often to explore language processes that are impaired after a stroke, as it may highlight treatment challenges for patients with post-stroke aphasia.

Sleep-Specific Processing of Auditory Stimuli Is Reflected by Alpha and Sigma Oscillations

Recent research revealed a surprisingly large range of cognitive operations to be preserved during sleep in humans. The new challenge is therefore to understand functions and mechanisms of processes, which so far have been mainly investigated in awake subjects. The current study focuses on dynamic changes of brain oscillations and connectivity patterns in response to environmental stimulation during non-REM sleep. Our results indicate that aurally presented names were processed and neuronally differentiated across the wake-sleep spectrum. Simultaneously recorded EEG and MEG signals revealed two distinct clusters of oscillatory power increase in response to the stimuli: (1) vigilance state-independent θ synchronization occurring immediately after stimulus onset, followed by (2) sleep-specific α/σ synchronization peaking after stimulus offset. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep, and work toward a unified theory of brain rhythms and their functions during sleep.SIGNIFICANCE STATEMENT Previous research has revealed (residual) capacity of the sleeping human brain to interact with the environment. How sensory processing is realized by the neural assemblies in different stages of sleep is however unclear. To tackle this question, we examined simultaneously recorded MEG and EEG data. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep. In contrast to versatile θ band response that reflected early stimulus processing step, succeeding α and σ band activity was sensitive to the saliency of the incoming information, and contingent on the sleep stage. Our findings suggest that the specific reorganization of mechanisms involved in later stages of sensory processing takes place upon falling asleep.

Magnifying Traveling Waves on the Scalp

Traveling waves appear in various signals that measure neuronal activity. Some signals measured in animals have singles-cell resolution and directly point to neuronal activity. In those cases, activation of distributed neurons forms a wave front, and the front propagates across the cortical surface. Other signals are variants of neuroelectric potentials, i.e. electroencephalography, electrocorticography and field potentials. Instead of having fine spatial resolution, these signals reflect the activity of neuronal populations via volume conduction (VC). Sources of traveling waves in neuroelectric potentials have not been well addressed so far. As animal studies show propagating activation of neurons that spread in measured areas, it is often considered that neuronal activations during scalp waves have similar trajectories of activation, spreading like scalp waves. However, traveling waves on the scalp differ from those found directly on the cortical surface in several dimensions: traveling velocity, traveling distance and areal size occupied by single polarity. We describe that the simplest sources can produce scalp waves with perceived spatial dimensions which are actually a magnification of neuronal activity emanating from local sources due to VC. This viewpoint is not a rigorous proof of our magnification concept. However, we suggest the possibility that the actual dimensions of neuronal activity producing traveling waves is not as large as the dimension of the traveling waves.

Cross Laminar Traveling Components of Field Potentials due to Volume Conduction of Non-Traveling Neuronal Activity in Macaque Sensory Cortices

Field potentials (FPs) reflect neuronal activities in the brain, and often exhibit traveling peaks across recording sites. While traveling FPs are interpreted as propagation of neuronal activity, not all studies directly reveal such propagating patterns of neuronal activation. Neuronal activity is associated with transmembrane currents that form dipoles and produce negative and positive fields. Thereby, FP components reverse polarity between those fields and have minimal amplitudes at the center of dipoles. Although their amplitudes could be smaller, FPs are never flat even around these reversals. What occurs around the reversal has not been addressed explicitly, although those are rationally in the middle of active neurons. We show that sensory FPs around the reversal appeared with peaks traveling across cortical laminae in macaque sensory cortices. Interestingly, analyses of current source density did not depict traveling patterns but lamina-delimited current sinks and sources. We simulated FPs produced by volume conduction of a simplified 2 dipoles' model mimicking sensory cortical laminar current source density components. While FPs generated by single dipoles followed the temporal patterns of the dipole moments without traveling peaks, FPs generated by concurrently active dipole moments appeared with traveling components in the vicinity of dipoles by superimposition of individually non-traveling FPs generated by single dipoles. These results indicate that not all traveling FP are generated by traveling neuronal activity, and that recording positions need to be taken into account to describe FP peak components around active neuronal populations.SIGNIFICANCE STATEMENT Field potentials (FPs) generated by neuronal activity in the brain occur with fields of opposite polarity. Likewise, in the cerebral cortices, they have mirror-imaged waveforms in upper and lower layers. We show that FPs appear like traveling across the cortical layers. Interestingly, the traveling FPs occur without traveling components of current source density, which represents transmembrane currents associated with neuronal activity. These seemingly odd findings are explained using current source density models of multiple dipoles. Concurrently active, non-traveling dipoles produce FPs as mixtures of FPs produced by individual dipoles, and result in traveling FP waveforms as the mixing ratio depends on the distances from those dipoles. The results suggest that not all traveling FP components are associated with propagating neuronal activity.

Probing the Functional and Structural Connectivity Underlying EEG Traveling Waves

Neural oscillations play an important role in the maintenance of brain function by regulating multi-scale neural activity. Characterizing the traveling properties of EEG is helpful for understanding the spatiotemporal dynamics of neural oscillations. However, traveling EEG based on non-invasive approach has little been investigated, and the relationship with brain intrinsic connectivity is not well known. In this study, traveling EEG of different frequency bands on the scalp in terms of the center of mass (EEG-CM) was examined. Then, two quantitative indexes describing the spatiotemporal features of EEG-CM were proposed, i.e., the traveling lateralization and velocity of EEG-CM. Further, based on simultaneous EEG-MRI approach, the relationship between traveling EEG-CM and the resting-state functional networks, as well as the microstructural connectivity of white matter was investigated. The results showed that there was similar spatial distribution of EEG-CM under different frequency bands, while the velocity of rhythmic EEG-CM increased in higher frequency bands. The lateralization of EEG-CM in low frequency bands (< 30 Hz) demonstrated negative relationship with the basal ganglia network (BGN). In addition, the velocity of the traveling EEG-CM was associated with the fractional anisotropy (FA) in corpus callosum and corona radiate. These results provided valid quantitative EEG index for understanding the spatiotemporal characteristics of the scalp EEG, and implied that the EEG dynamics were representations of functional and structural organization of cortical and subcortical structures.

The Deficit of Multimodal Perception of Congruent and Non-Congruent Fearful Expressions in Patients with Schizophrenia: The ERP Study

Emotional dysfunction, including flat affect and emotional perception deficits, is a specific symptom of schizophrenia disorder. We used a modified multimodal odd-ball paradigm with fearful facial expressions accompanied by congruent and non-congruent emotional vocalizations (sounds of women screaming and laughing) to investigate the impairment of emotional perception and reactions to other people's emotions in schizophrenia. We compared subjective ratings of emotional state and event-related potentials (EPPs) in response to congruent and non-congruent stimuli in patients with schizophrenia and healthy controls. The results showed the altered multimodal perception of fearful stimuli in patients with schizophrenia. The amplitude of N50 was significantly higher for non-congruent stimuli than congruent ones in the control group and did not differ in patients. The P100 and N200 amplitudes were higher in response to non-congruent stimuli in patients than in controls, implying impaired sensory gating in schizophrenia. The observed decrease of P3a and P3b amplitudes in patients could be associated with less attention, less emotional arousal, or incorrect interpretation of emotional valence, as patients differed from healthy controls in the emotion scores of non-congruent stimuli. The difficulties in identifying the incoherence of facial and audial components of emotional expression could be significant in understanding the psychopathology of schizophrenia.

Turning the Stimulus On and Off Changes the Direction of α Traveling Waves

Traveling waves have been studied to characterize the complex spatiotemporal dynamics of the brain. Several studies have suggested that the propagation direction of α traveling waves can be task dependent. For example, a recent electroencephalography (EEG) study from our group found that forward waves (i.e., occipital to frontal, FW waves) were observed during visual processing, whereas backward waves (i.e., frontal to occipital, BW waves) mostly occurred in the absence of sensory input. These EEG recordings, however, were obtained from different experimental sessions and different groups of subjects. To further examine how the waves’ direction changes between task conditions, 13 human participants were tested on a target detection task while EEG signals were recorded simultaneously. We alternated visual stimulation (5-s display of visual luminance sequences) and resting state (5 s of black screen) within each single trial, allowing us to monitor the moment-to-moment progression of traveling waves. As expected, the direction of α waves was closely linked with task conditions. First, FW waves from occipital to frontal regions, absent during rest, emerged as a result of visual processing, while BW waves in the opposite direction dominated in the absence of visual inputs, and were reduced (but not eliminated) by external visual inputs. Second, during visual stimulation (but not rest), both waves coexisted on average, but were negatively correlated. In summary, we conclude that the functional role of α traveling waves is closely related with their propagating direction, with stimulus-evoked FW waves supporting visual processing and spontaneous BW waves involved more in top-down control.

Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.

Large-scale cortical travelling waves predict localized future cortical signals

Predicting future brain signal is highly sought-after, yet difficult to achieve. To predict the future phase of cortical activity at localized ECoG and MEG recording sites, we exploit its predominant, large-scale, spatiotemporal dynamics. The dynamics are extracted from the brain signal through Fourier analysis and principal components analysis (PCA) only, and cast in a data model that predicts future signal at each site and frequency of interest. The dominant eigenvectors of the PCA that map the large-scale patterns of past cortical phase to future ones take the form of smoothly propagating waves over the entire measurement array. In ECoG data from 3 subjects and MEG data from 20 subjects collected during a self-initiated motor task, mean phase prediction errors were as low as 0.5 radians at local sites, surpassing state-of-the-art methods of within-time-series or event-related models. Prediction accuracy was highest in delta to beta bands, depending on the subject, was more accurate during episodes of high global power, but was not strongly dependent on the time-course of the task. Prediction results did not require past data from the to-be-predicted site. Rather, best accuracy depended on the availability in the model of long wavelength information. The utility of large-scale, low spatial frequency traveling waves in predicting future phase activity at local sites allows estimation of the error introduced by failing to account for irreducible trajectories in the activity dynamics.

Prediction is an important step in scientific progress, often leading to real-world applications. Prediction of future brain activity could lead to improvements in detecting driver and pilot error or real-time brain testing using transcranial magnetic stimulation. Previous studies have either supposed that the ‘noise’ level in the cortex is high, setting the prediction bar rather low; or used localized measurements to predict future activity, with modest success. A long-held but controversial hypothesis is that the cortex is best characterized as a multi-scale dynamic structure, in which the flow of activity at one scale, say, the area responsible for motor control, is inextricably tied to activity at smaller and larger scales, for example within a cortical column and the whole cortex. We test this hypothesis by analyzing large-scale traveling waves of cortical activity. Like waves arriving on a beach, the ongoing wave motion allows better prediction of future activity compared to monitoring the local rise and fall; in the best cases the future wave cycle is predicted with as low as 20° average error angle. The prediction techniques developed for the present research rely on mathematics related to quantifying large-scale weather patterns or analysis of fluid dynamics.

Alpha oscillations and traveling waves: Signatures of predictive coding?

Predictive coding is a key mechanism to understand the computational processes underlying brain functioning: in a hierarchical network, higher levels predict the activity of lower levels, and the unexplained residuals (i.e., prediction errors) are passed back to higher layers. Because of its recursive nature, we wondered whether predictive coding could be related to brain oscillatory dynamics. First, we show that a simple 2-level predictive coding model of visual cortex, with physiological communication delays between levels, naturally gives rise to alpha-band rhythms, similar to experimental observations. Then, we demonstrate that a multilevel version of the same model can explain the occurrence of oscillatory traveling waves across levels, both forward (during visual stimulation) and backward (during rest). Remarkably, the predictions of our model are matched by the analysis of 2 independent electroencephalography (EEG) datasets, in which we observed oscillatory traveling waves in both directions.

The Hidden Spatial Dimension of Alpha: 10-Hz Perceptual Echoes Propagate as Periodic Traveling Waves in the Human Brain

EEG reverse-correlation techniques have revealed that visual information processing entails a ∼10-Hz (alpha) occipital response that reverberates sensory inputs up to 1 s. However, the spatial distribution of these perceptual echoes remains unknown: are they synchronized across the brain, or do they propagate like a traveling wave? Here, in two experiments with varying stimulus locations, we demonstrate the systematic phase propagation of perceptual echoes. A single stimulation in the upper visual field produced an "echo traveling wave" propagating from posterior to frontal sensors. The simultaneous presentation of two independent stimuli in separate visual hemifields produced two superimposed traveling waves propagating in opposite directions. Strikingly, in each sensor, the phase of the two echoes differed, with a phase advance for the contralateral stimulus. Thus, alpha traveling waves sweep across the human brain, encoding stimulus position in the phase domain, in line with the 70-year-old "cortical scanning" hypothesis (Pitts and McCulloch, 1947).

The frequency architecture of brain and brain body oscillations: an analysis

Research on brain oscillations has brought up a picture of coupled oscillators. Some of the most important questions that will be analyzed are, how many frequencies are there, what are the coupling principles, what their functional meaning is, and whether body oscillations follow similar coupling principles. It is argued that physiologically, two basic coupling principles govern brain as well as body oscillations: (i) amplitude (envelope) modulation between any frequencies m and n, where the phase of the slower frequency m modulates the envelope of the faster frequency n, and (ii) phase coupling between m and n, where the frequency of n is a harmonic multiple of m. An analysis of the center frequency of traditional frequency bands and their coupling principles suggest a binary hierarchy of frequencies. This principle leads to the foundation of the binary hierarchy brain body oscillation theory. Its central hypotheses are that the frequencies of body oscillations can be predicted from brain oscillations and that brain and body oscillations are aligned to each other. The empirical evaluation of the predicted frequencies for body oscillations is discussed on the basis of findings for heart rate, heart rate variability, breathing frequencies, fluctuations in the BOLD signal, and other body oscillations. The conclusion is that brain and many body oscillations can be described by a single system, where the cross talk - reflecting communication - within and between brain and body oscillations is governed by m : n phase to envelope and phase to phase coupling.

Seeing music: The perception of melodic 'ups and downs' modulates the spatial processing of visual stimuli

Musical melodies have "peaks" and "valleys". Although the vertical component of pitch and music is well-known, the mechanisms underlying its mental representation still remain elusive. We show evidence regarding the importance of previous experience with melodies for crossmodal interactions to emerge. The impact of these crossmodal interactions on other perceptual and attentional processes was also studied. Melodies including two tones with different frequency (e.g., E4 and D3) were repeatedly presented during the study. These melodies could either generate strong predictions (e.g., E4-D3-E4-D3-E4-[D3]) or not (e.g., E4-D3-E4-E4-D3-[?]). After the presentation of each melody, the participants had to judge the colour of a visual stimulus that appeared in a position that was, according to the traditional vertical connotations of pitch, either congruent (e.g., high-low-high-low-[up]), incongruent (high-low-high-low-[down]) or unpredicted with respect to the melody. Behavioural and electroencephalographic responses to the visual stimuli were obtained. Congruent visual stimuli elicited faster responses at the end of the experiment than at the beginning. Additionally, incongruent visual stimuli that broke the spatial prediction generated by the melody elicited larger P3b amplitudes (reflecting 'surprise' responses). Our results suggest that the passive (but repeated) exposure to melodies elicits spatial predictions that modulate the processing of other sensory events.

Large-Scale Traveling Waves in EEG Activity Following Eye Movement

In spontaneous, stimulus-evoked, and eye-movement evoked EEG, the oscillatory signal shows large scale, dynamically organized patterns of phase. We investigated eye-movement evoked patterns in free-viewing conditions. Participants viewed photographs of natural scenes in anticipation of a memory test. From 200 ms intervals following saccades, we estimated the EEG phase gradient over the entire scalp, and the wave activity, i.e. the goodness of fit of a wave model involving a phase gradient assumed to be smooth over the scalp. In frequencies centered at 6.5 Hz, large-scale phase organization occurred, peaking around 70 ms after fixation onset and taking the form of a traveling wave. According to the wave gradient, most of the times the wave spreads from the posterior-inferior to anterior-superior direction. In these directions, the gradients depended on the size and direction of the saccade. Wave propagation velocity decreased in the course of the fixation, particularly in the interval from 50 to 150 ms after fixation onset. This interval corresponds to the fixation-related lambda activity, which reflects early perceptual processes following fixation onset. We conclude that lambda activity has a prominent traveling wave component. This component consists of a short-term whole-head phase pattern of specific direction and velocity, which may reflect feedforward propagation of visual information at fixation.

Global and local oscillatory entrainment of visual behavior across retinotopic space

Ongoing brain oscillations (7–10 Hz) modulate visual perception; in particular, their precise phase can predict target perception. Here, we employ this phase-dependence of perception in a psychophysical experiment to track spatial properties of entrained oscillations of visual perception across the visual field. Is this entrainment local, or a more global phenomenon? If the latter, does oscillatory phase synchronize over space, or vary with increasing distance from the oscillatory source? We presented a disc stimulus in the upper left quadrant, oscillating in luminance at different frequencies (individual alpha frequency (IAF), 5 Hz, and 15 Hz) to entrain an oscillation with specific frequency and spatial origin. Observers fixated centrally, while flash stimuli at perceptual threshold appeared at different positions and times with respect to the oscillating stimulus. IAF and 5 Hz luminance oscillations modulated detection performance at all tested positions, whereas at 15 Hz, the effect was weaker and less consistent. Furthermore, for IAF and 5 Hz entrainment, preferred phases for target detection differed significantly between spatial locations, suggesting “local” entrainment of detection performance next to the oscillatory source, whereas more distant target locations shared a “global” effect with a significantly different phase. This unexpected global component of entrainment is tentatively attributed to widespread connectivity from thalamic nuclei such as the pulvinar.

Global Neuromagnetic Cortical Fields Have Non-Zero Velocity

Globally coherent patterns of phase can be obscured by analysis techniques that aggregate brain activity measures across-trials, whether prior to source localization or for estimating inter-areal coherence. We analyzed, at single-trial level, whole head MEG recorded during an observer-triggered apparent motion task. Episodes of globally coherent activity occurred in the delta, theta, alpha and beta bands of the signal in the form of large-scale waves, which propagated with a variety of velocities. Their mean speed at each frequency band was proportional to temporal frequency, giving a range of 0.06 to 4.0 m/s, from delta to beta. The wave peaks moved over the entire measurement array, during both ongoing activity and task-relevant intervals; direction of motion was more predictable during the latter. A large proportion of the cortical signal, measurable at the scalp, exists as large-scale coherent motion. We argue that the distribution of observable phase velocities in MEG is dominated by spatial filtering considerations in combination with group velocity of cortical activity. Traveling waves may index processes involved in global coordination of cortical activity.

Diverse Phase Relations among Neuronal Rhythms and Their Potential Function

Neuronal oscillations at nearby sites in the brain often show phase relations that are consistent across time, yet diverse across space. We discuss recent demonstrations of this phase relation diversity, and show that, contrary to earlier beliefs, this diversity is a general property of oscillations that is neither restricted to low-frequency oscillations nor to periods outside of stimulus processing. Arguing for the computational relevance of phase relation diversity, we discuss that it can be modulated by sensory and motor events, and put forward the idea that phase relation diversity may support effective neuronal communication by (i) enhancing selectivity and (ii) allowing for the concurrent segregation of multiple information streams.

Expecting to See a Letter: Alpha Oscillations as Carriers of Top-Down Sensory Predictions

Predictions strongly influence perception. However, the neurophysiological processes that implement predictions remain underexplored. It has been proposed that high- and low-frequency neuronal oscillations act as carriers of sensory evidence and top-down predictions, respectively (von Stein and Sarnthein 2000; Bastos et al. 2012). However, evidence for the latter hypothesis remains scarce. In particular, it remains to be shown whether slow prestimulus alpha oscillations in task-relevant brain regions are stronger in the presence of predictions, whether they influence early categorization processes, and whether this interplay indeed boosts perception. Here, we directly address these questions by manipulating subjects' prior expectations about the identity of visually presented letters while collecting magnetoencephalographic recordings. We find that predictions lead to increased prestimulus alpha oscillations in a multisensory network representing grapheme/phoneme associations. Furthermore, alpha power interacts with stimulus degradation and top-down expectations to predict visibility ratings, and correlates with the amplitude of early sensory components (P1/N1m complex), suggesting a role in the selective amplification of predicted information. Our results thus indicate that low-frequency alpha oscillations can serve as a mechanism to carry and test sensory predictions about letters.

Donders is dead: cortical traveling waves and the limits of mental chronometry in cognitive neuroscience

An assumption nearly all researchers in cognitive neuroscience tacitly adhere to is that of space–time separability. Historically, it forms the basis of Donders’ difference method, and to date, it underwrites all difference imaging and trial-averaging of cortical activity, including the customary techniques for analyzing fMRI and EEG/MEG data. We describe the assumption and how it licenses common methods in cognitive neuroscience; in particular, we show how it plays out in signal differencing and averaging, and how it misleads us into seeing the brain as a set of static activity sources. In fact, rather than being static, the domains of cortical activity change from moment to moment: Recent research has suggested the importance of traveling waves of activation in the cortex. Traveling waves have been described at a range of different spatial scales in the cortex; they explain a large proportion of the variance in phase measurements of EEG, MEG and ECoG, and are important for understanding cortical function. Critically, traveling waves are not space–time separable. Their prominence suggests that the correct frame of reference for analyzing cortical activity is the dynamical trajectory of the system, rather than the time and space coordinates of measurements. We illustrate what the failure of space–time separability implies for cortical activation, and what consequences this should have for cognitive neuroscience.

Prestimulus amplitudes modulate P1 latencies and evoked traveling alpha waves

Traveling waves have been well documented in the ongoing, and more recently also in the evoked EEG. In the present study we investigate what kind of physiological process might be responsible for inducing an evoked traveling wave. We used a semantic judgment task which already proved useful to study evoked traveling alpha waves that coincide with the appearance of the P1 component. We found that the P1 latency of the leading electrode is significantly correlated with prestimulus amplitude size and that this event is associated with a transient change in alpha frequency. We assume that cortical background excitability, as reflected by an increase in prestimulus amplitude, is responsible for the observed change in alpha frequency and the initiation of an evoked traveling trajectory.

Associations of endogenous 17-β-estradiol with theta amplitude and performance in semantic categorization in young women

In semantic categorization processes, individuals form a relation between perceived or imagined objects and knowledge about these objects. In the present semantic categorization study, we correlated endogenous 17-β-estradiol levels (E2) with performance as well as amplitude of theta oscillations in young women (age 23.1±3.4 years). The semantic categorization task consisted of nouns representing either living or non-living items. Each item was characterized either by many or by few features. We identified parameters associated or not associated with menstrual cycle phases. Irrespective of the menstrual cycle phase, women (1) responded faster to living items as well as to nouns characterized by many features compared to non-living items and items characterized by few features, (2) showed higher accuracy to non-living items and items having many features, and (3) showed negative correlation between response time (RT) and theta amplitude. RT, accuracy and post-stimulus theta amplitude were not statistically significantly different among early follicular, late follicular or luteal women. In early follicular but not in late follicular or luteal women, we observed (1) a positive correlation between E2 and latency in RT, (2) a negative correlation between E2 and accuracy, and (3) a negative correlation between E2 and post-stimulus theta amplitude. A mosaic of menstrual cycle phase-dependent and -independent associations may indicate that a similar performance in each menstrual cycle phase is related to different modulation of synaptic activity by hormones.

Neural bases of event knowledge and syntax integration in comprehension of complex sentences

Comprehension of complex sentences is necessarily supported by both syntactic and semantic knowledge, but what linguistic factors trigger a readers' reliance on a specific system? This functional neuroimaging study orthogonally manipulated argument plausibility and verb event type to investigate cortical bases of the semantic effect on argument comprehension during reading. The data suggest that telic verbs facilitate online processing by means of consolidating the event schemas in episodic memory and by easing the computation of syntactico-thematic hierarchies in the left inferior frontal gyrus. The results demonstrate that syntax-semantics integration relies on trade-offs among a distributed network of regions for maximum comprehension efficiency.

Intra-cortical propagation of EEG alpha oscillations

The most salient feature of spontaneous human brain activity as recorded with electroencephalography (EEG) are rhythmic fluctuations around 10Hz. These alpha oscillations have been reported to propagate over the scalp with velocities in the range of 5-15m/s. Since these velocities are in the range of action potential velocities through cortico-cortical axons, it has been hypothesized that the observed scalp waves reflect cortico-cortically mediated propagation of cortical oscillations. The reported scalp velocities however, appear to be inconsistent with those estimated from local field potential recordings in dogs, which are <1m/s and agree with the propagation velocity of action potentials in intra-cortical axons. In this study, we resolve these diverging findings using a combination of EEG data-analysis and biophysical modeling. In particular, we demonstrate that the observed scalp velocities can be accounted for by slow traveling oscillations, which provides support for the claim that spatial propagation of alpha oscillations is mediated by intra-cortical axons.

Lexical access and evoked traveling alpha waves

Retrieval from semantic memory is usually considered within a time window around 300-600ms. Here we suggest that lexical access already occurs at around 100ms. This interpretation is based on the finding that semantically rich and frequent words exhibit a significantly shorter topographical latency difference between the site with the shortest P1 latency (leading site) and that with the longest P1 latency (trailing site). This latency difference can be described in terms of an evoked traveling alpha wave as was already shown in earlier studies.

Propagating neocortical gamma bursts are coordinated by traveling alpha waves

Neocortical neuronal activity is characterized by complex spatiotemporal dynamics. Although slow oscillations have been shown to travel over space in terms of consistent phase advances, it is unknown how this phenomenon relates to neuronal activity in other frequency bands. We here present electrocorticographic data from three male and one female human subject and demonstrate that gamma power is phase locked to traveling alpha waves. Given that alpha activity has been proposed to coordinate neuronal processing reflected in the gamma band, we suggest that alpha waves are involved in coordinating neuronal processing in both space and time.

Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing

Background

Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.)

Methods

Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80–100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.

Results

ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13–30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset.

Conclusions

Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

Brain communication in the locked-in state

Patients in the completely locked-in state have no means of communication and they represent the target population for brain-computer interface research in the last 15 years. Although different paradigms have been tested and different physiological signals used, to date no sufficiently documented completely locked-in state patient was able to control a brain-computer interface over an extended time period. We introduce Pavlovian semantic conditioning to enable basic communication in completely locked-in state. This novel paradigm is based on semantic conditioning for online classification of neuroelectric or any other physiological signals to discriminate between covert (cognitive) 'yes' and 'no' responses. The paradigm comprised the presentation of affirmative and negative statements used as conditioned stimuli, while the unconditioned stimulus consisted of electrical stimulation of the skin paired with affirmative statements. Three patients with advanced amyotrophic lateral sclerosis participated over an extended time period, one of which was in a completely locked-in state, the other two in the locked-in state. The patients' level of vigilance was assessed through auditory oddball procedures to study the correlation between vigilance level and the classifier's performance. The average online classification accuracies of slow cortical components of electroencephalographic signals were around chance level for all the patients. The use of a non-linear classifier in the offline classification procedure resulted in a substantial improvement of the accuracy in one locked-in state patient achieving 70% correct classification. A reliable level of performance in the completely locked-in state patient was not achieved uniformly throughout the 37 sessions despite intact cognitive processing capacity, but in some sessions communication accuracies up to 70% were achieved. Paradigm modifications are proposed. Rapid drop of vigilance was detected suggesting attentional variations or variations of circadian period as important factors in brain-computer interface communication with locked-in state and completely locked-in state.

α-band oscillations, attention, and controlled access to stored information

Alpha-band oscillations are the dominant oscillations in the human brain and recent evidence suggests that they have an inhibitory function. Nonetheless, there is little doubt that alpha-band oscillations also play an active role in information processing. In this article, I suggest that alpha-band oscillations have two roles (inhibition and timing) that are closely linked to two fundamental functions of attention (suppression and selection), which enable controlled knowledge access and semantic orientation (the ability to be consciously oriented in time, space, and context). As such, alpha-band oscillations reflect one of the most basic cognitive processes and can also be shown to play a key role in the coalescence of brain activity in different frequencies.