Prestimulus neural alpha power predicts confidence in discriminating identical auditory stimuli

Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer's disease dementia

BACKGROUND

Developing non-invasive and affordable biomarkers to detect Alzheimer's disease (AD) at a prodromal stage is essential, particularly in the context of new disease-modifying therapies. Mild cognitive impairment (MCI) is a critical stage preceding dementia, but not all patients with MCI will progress to AD. This study explores the potential of magnetoencephalography (MEG) to predict cognitive decline from MCI to AD dementia.

METHODS

We analysed resting-state MEG data from the BioFIND dataset including 117 patients with MCI among whom 64 developed AD dementia (AD progression), while 53 remained cognitively stable (stable MCI), using spectral analysis. Logistic regression models estimated the additive explanation of selected clinical, MEG, and MRI variables for AD progression risk. We then built a high-dimensional classification model to combine all modalities and variables of interest.

FINDINGS

MEG 16-38Hz spectral power, particularly over parieto-occipital magnetometers, was significantly reduced in the AD progression group. In logistic regression models, decreased MEG 16-38Hz spectral power and reduced hippocampal volume/total grey matter ratio on MRI were independently linked to higher AD progression risk. The data-driven classification model confirmed, among other factors, the complementary information of MEG covariance (AUC = 0.74, SD = 0.13) and MRI cortical volumes (AUC = 0.77, SD = 0.14) to predict AD progression. Combining all inputs led to markedly improved classification scores (AUC = 0.81, SD = 0.12).

INTERPRETATION

These findings highlight the potential of spectral power and covariance as robust non-invasive electrophysiological biomarkers to predict AD progression, complementing other diagnostic measures, including cognitive scores and MRI.

FUNDING

This work was supported by: Fondation pour la Recherche Médicale (grant FDM202106013579).

Metacognition in the listening brain

How do you know you have heard right? Metacognition, the ability to assess and monitor one's own cognitive state, is key to understanding human communication in complex environments. However, the foundational role of metacognition in hearing and communication is only beginning to be explored, and the neuroscience behind it is an emerging field: how does confidence express in neural dynamics of the listening brain? What is known about auditory metaperceptual alterations as a hallmark phenomenon in psychosis, dementia, or hearing loss? Building on Bayesian ideas of auditory perception and auditory neuroscience, 'meta-listening' offers a framework for more comprehensive research into how metacognition in humans and non-humans shapes the listening brain.

Brain Network Interconnectivity Dynamics Explain Metacognitive Differences in Listening Behavior

Complex auditory scenes pose a challenge to attentive listening, rendering listeners slower and more uncertain in their perceptual decisions. How can we explain such behaviors from the dynamics of cortical networks that pertain to the control of listening behavior? We here follow up on the hypothesis that human adaptive perception in challenging listening situations is supported by modular reconfiguration of auditory-control networks in a sample of N = 40 participants (13 males) who underwent resting-state and task functional magnetic resonance imaging (fMRI). Individual titration of a spatial selective auditory attention task maintained an average accuracy of ∼70% but yielded considerable interindividual differences in listeners' response speed and reported confidence in their own perceptual decisions. Whole-brain network modularity increased from rest to task by reconfiguring auditory, cinguloopercular, and dorsal attention networks. Specifically, interconnectivity between the auditory network and cinguloopercular network decreased during the task relative to the resting state. Additionally, interconnectivity between the dorsal attention network and cinguloopercular network increased. These interconnectivity dynamics were predictive of individual differences in response confidence, the degree of which was more pronounced after incorrect judgments. Our findings uncover the behavioral relevance of functional cross talk between auditory and attentional-control networks during metacognitive assessment of one's own perception in challenging listening situations and suggest two functionally dissociable cortical networked systems that shape the considerable metacognitive differences between individuals in adaptive listening behavior.

Beyond task response-Pre-stimulus activity modulates contents of consciousness

The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).

Short-Term Effect of Auditory Stimulation on Neural Activities: A Scoping Review of Longitudinal Electroencephalography and Magnetoencephalography Studies

Explored through EEG/MEG, auditory stimuli function as a suitable research probe to reveal various neural activities, including event-related potentials, brain oscillations and functional connectivity. Accumulating evidence in this field stems from studies investigating neuroplasticity induced by long-term auditory training, specifically cross-sectional studies comparing musicians and non-musicians as well as longitudinal studies with musicians. In contrast, studies that address the neural effects of short-term interventions whose duration lasts from minutes to hours are only beginning to be featured. Over the past decade, an increasing body of evidence has shown that short-term auditory interventions evoke rapid changes in neural activities, and oscillatory fluctuations can be observed even in the prestimulus period. In this scoping review, we divided the extracted neurophysiological studies into three groups to discuss neural activities with short-term auditory interventions: the pre-stimulus period, during stimulation, and a comparison of before and after stimulation. We show that oscillatory activities vary depending on the context of the stimuli and are greatly affected by the interplay of bottom-up and top-down modulational mechanisms, including attention. We conclude that the observed rapid changes in neural activitiesin the auditory cortex and the higher-order cognitive part of the brain are causally attributed to short-term auditory interventions.

Alpha oscillations encode Bayesian belief updating underlying attentional allocation in dynamic environments

In a dynamic environment, expectations of the future constantly change based on updated evidence and affect the dynamic allocation of attention. To further investigate the neural mechanisms underlying attentional expectancies, we employed a modified Central Cue Posner Paradigm in which the probability of cues being valid (that is, accurately indicated the upcoming target location) was manipulated. Attentional deployment to the cued location (α), which was governed by precision of predictions on previous trials, was estimated using a hierarchical Bayesian model and was included as a regressor in the analyses of electrophysiological (EEG) data. Our results revealed that before the target appeared, alpha oscillations (8∼13 Hz) for high-predictability cues (88 % valid) were significantly predicted by precision-dependent attention (α). This relationship was not observed under low-predictability conditions (69 % and 50 % valid cues). After the target appeared, precision-dependent attention (α) correlated with alpha band oscillations only in the valid cue condition and not in the invalid condition. Further analysis under conditions of significant attentional modulation by precision suggested a separate effect of cue orientation. These results provide new insights on how trial-by-trial Bayesian belief updating relates to alpha band encoding of environmentally-sensitive allocation of visual spatial attention.

Neural oscillations reflect the individual differences in the temporal perception of audiovisual speech

Multisensory integration occurs within a limited time interval between multimodal stimuli. Multisensory temporal perception varies widely among individuals and involves perceptual synchrony and temporal sensitivity processes. Previous studies explored the neural mechanisms of individual differences for beep-flash stimuli, whereas there was no study for speech. In this study, 28 subjects (16 male) performed an audiovisual speech/ba/simultaneity judgment task while recording their electroencephalography. We examined the relationship between prestimulus neural oscillations (i.e. the pre-pronunciation movement-related oscillations) and temporal perception. The perceptual synchrony was quantified using the Point of Subjective Simultaneity and temporal sensitivity using the Temporal Binding Window. Our results revealed dissociated neural mechanisms for individual differences in Temporal Binding Window and Point of Subjective Simultaneity. The frontocentral delta power, reflecting top-down attention control, is positively related to the magnitude of individual auditory leading Temporal Binding Windows (auditory Temporal Binding Windows; LTBWs), whereas the parieto-occipital theta power, indexing bottom-up visual temporal attention specific to speech, is negatively associated with the magnitude of individual visual leading Temporal Binding Windows (visual Temporal Binding Windows; RTBWs). In addition, increased left frontal and bilateral temporoparietal occipital alpha power, reflecting general attentional states, is associated with increased Points of Subjective Simultaneity. Strengthening attention abilities might improve the audiovisual temporal perception of speech and further impact speech integration.

Spontaneous alpha-band oscillations reflect individual differences in audiovisual temporal perception

Light, and sound are persistently out of sync for subjective temporal perception called point of subjective simultaneity (PSS). It is stable within individuals but variable among individuals. Previous studies found that spontaneous alpha power, functioning in attention-related brain states, predicts individual PSS in the temporal order judgment (TOJ) task. However, the neural mechanisms underlying individual differences in audiovisual PSS have not been elucidated in the simultaneity judgment (SJ) task. A hypothesis that the spontaneous alpha band power might reflect the individual subjective temporal bias was proposed. We designed an SJ task EEG experiment where subjects judged whether the beep-flash stimuli are synchronous to test the above hypothesis. We primarily explored the correlation between the alpha-band power differences (visual- and auditory-leading conditions) with individual PSS. We used the V50A (~50% proportion of synchronous responses) to represent visual-leading conditions while A50V represents auditory-leading ones. We found the higher alpha power difference (V50A - A50V) predicted larger individual PSS. This study extends previous results and found that individual difference effects in the alpha band power also exist in the SJ task. The results suggested that alpha power might be associated with a spontaneous attentional state and reflect individuals' subjective temporal bias.

Target enhancement but not distractor suppression in auditory neural tracking during continuous speech

Selective attention modulates the neural tracking of speech in auditory cortical regions. It is unclear whether this attentional modulation is dominated by enhanced target tracking, or suppression of distraction. To settle this long-standing debate, we employed an augmented electroencephalography (EEG) speech-tracking paradigm with target, distractor, and neutral streams. Concurrent target speech and distractor (i.e., sometimes relevant) speech were juxtaposed with a third, never task-relevant speech stream serving as neutral baseline. Listeners had to detect short target repeats and committed more false alarms originating from the distractor than from the neutral stream. Speech tracking revealed target enhancement but no distractor suppression below the neutral baseline. Speech tracking of the target (not distractor or neutral speech) explained single-trial accuracy in repeat detection. In sum, the enhanced neural representation of target speech is specific to processes of attentional gain for behaviorally relevant target speech rather than neural suppression of distraction.

Accounting for endogenous effects in decision-making with a non-linear diffusion decision model

The Drift-Diffusion Model (DDM) is widely accepted for two-alternative forced-choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter-trial dynamics at the single-trial level and endogenous influences. We propose a novel model, the non-linear Drift-Diffusion Model (nl-DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non-linear model performs better than the drift-diffusion model for an equivalent complexity. To give better intuition on the meaning of nl-DDM parameters, we compare the DDM and the nl-DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl-DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across-trial variability for perceptual decisions and accounts for peri-stimulus influences.

Effects of Rhythmic Transcranial Magnetic Stimulation in the Alpha-Band on Visual Perception Depend on Deviation From Alpha-Peak Frequency: Faster Relative Transcranial Magnetic Stimulation Alpha-Pace Improves Performance

Alpha-band oscillatory activity over occipito-parietal areas is involved in shaping perceptual and cognitive processes, with a growing body of electroencephalographic (EEG) evidence indicating that pre-stimulus alpha-band amplitude relates to the subjective perceptual experience, but not to objective measures of visual task performance (discrimination accuracy). The primary aim of the present transcranial magnetic stimulation (TMS) study was to investigate whether causality can be established for this relationship, using rhythmic (alpha-band) TMS entrainment protocols. It was anticipated that pre-stimulus 10 Hz-TMS would induce changes in subjective awareness ratings but not accuracy, in the visual hemifield contralateral to TMS. To test this, we administered 10 Hz-TMS over the right intraparietal sulcus prior to visual stimulus presentation in 17 participants, while measuring their objective performance and subjective awareness in a visual discrimination task. Arrhythmic and 10 Hz sham-TMS served as control conditions (within-participant design). Resting EEG was used to record individual alpha frequency (IAF). A study conducted in parallel to ours with a similar design but reported after we completed data collection informed further, secondary analyses for a causal relationship between pre-stimulus alpha-frequency and discrimination accuracy. This was explored through a regression analysis between rhythmic-TMS alpha-pace relative to IAF and performance measures. Our results revealed that contrary to our primary expectation, pre-stimulus 10 Hz-TMS did not affect subjective measures of performance, nor accuracy, relative to control-TMS. This null result is in accord with a recent finding showing that for influencing subjective measures of performance, alpha-TMS needs to be applied post-stimulus. In addition, our secondary analysis showed that IAF was positively correlated with task accuracy across participants, and that 10 Hz-TMS effects on accuracy—but not awareness ratings—depended on IAF: The slower (or faster) the IAF, relative to the fixed 10 Hz TMS frequency, the stronger the TMS-induced performance improvement (or worsening), indicating that 10 Hz-TMS produced a gain (or a loss) in individual performance, directly depending on TMS-pace relative to IAF. In support of recent reports, this is evidence for alpha-frequency playing a causal role in perceptual sensitivity likely through regulating the speed of sensory sampling.

Spontaneous alpha-band amplitude predicts subjective visibility but not discrimination accuracy during high-level perception

Near-threshold perception is a paradigm case of awareness diverging from reality - the perception of an unchanging stimulus can vacillate from undetected to clearly perceived. The amplitude of low-frequency brain oscillations - particularly in the alpha-band (8-13 Hz) - has emerged as a reliable predictor of trial-to-trial variability in perceptual decisions based on simple, low-level stimuli. Here, we addressed the question of how spontaneous oscillatory amplitude impacts subjective and objective aspects of perception using high-level visual stimuli. Human observers completed a near-threshold face/house discrimination task with subjective visibility ratings while electroencephalograms (EEG) were recorded. Using single-trial multiple regression analysis, we found that spontaneous fluctuations in prestimulus alpha-band amplitude were negatively related to visibility judgments but did not predict trial-by-trial accuracy. These results extend previous findings that indicate that strong prestimulus alpha diminishes subjective perception without affecting the accuracy or sensitivity (d') of perceptual decisions into the domain of high-level perception.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

Decoding Object-Based Auditory Attention from Source-Reconstructed MEG Alpha Oscillations

How do we attend to relevant auditory information in complex naturalistic scenes? Much research has focused on detecting which information is attended, without regarding underlying top-down control mechanisms. Studies investigating attentional control generally manipulate and cue specific features in simple stimuli. However, in naturalistic scenes it is impossible to dissociate relevant from irrelevant information based on low-level features. Instead, the brain has to parse and select auditory objects of interest. The neural underpinnings of object-based auditory attention remain not well understood. Here we recorded MEG while 15 healthy human subjects (9 female) prepared for the repetition of an auditory object presented in one of two overlapping naturalistic auditory streams. The stream containing the repetition was prospectively cued with 70% validity. Crucially, this task could not be solved by attending low-level features, but only by processing the objects fully. We trained a linear classifier on the cortical distribution of source-reconstructed oscillatory activity to distinguish which auditory stream was attended. We could successfully classify the attended stream from alpha (8-14 Hz) activity in anticipation of repetition onset. Importantly, attention could only be classified from trials in which subjects subsequently detected the repetition, but not from miss trials. Behavioral relevance was further supported by a correlation between classification accuracy and detection performance. Decodability was not sustained throughout stimulus presentation, but peaked shortly before repetition onset, suggesting that attention acted transiently according to temporal expectations. We thus demonstrate anticipatory alpha oscillations to underlie top-down control of object-based auditory attention in complex naturalistic scenes.SIGNIFICANCE STATEMENT In everyday life, we often find ourselves bombarded with auditory information, from which we need to select what is relevant to our current goals. Previous research has highlighted how we attend to specific highly controlled aspects of the auditory input. Although invaluable, it is still unclear how this relates to attentional control in naturalistic auditory scenes. Here we used the high precision of magnetoencephalography in space and time to investigate the brain mechanisms underlying top-down control of object-based attention in ecologically valid sound scenes. We show that rhythmic activity in auditory association cortex at a frequency of ∼10 Hz (alpha waves) controls attention to currently relevant segments within the auditory scene and predicts whether these segments are subsequently detected.

Parkinson's disease affects the neural alpha oscillations associated with speech-in-noise processing

Parkinson's disease (PD) has increasingly been associated with auditory dysfunction, including alterations regarding the control of auditory information processing. Although these alterations may interfere with the processing of speech in degraded listening conditions, behavioural studies have generally found preserved speech-in-noise recognition in PD. However, behavioural speech audiometry does not capture the neurophysiological mechanisms supporting speech-in-noise processing. Therefore, the aim of this study was to investigate the neural oscillatory mechanisms associated with speech-in-noise processing in PD. Twelve persons with PD and 12 age- and gender-matched healthy controls (HCs) were included in this study. Persons with PD were studied in the medication off condition. All subjects underwent an audiometric screening and performed a sentence-in-noise recognition task under simultaneous electroencephalography (EEG) recording. Behavioural speech recognition scores and self-reported ratings of effort, performance, and motivation were collected. Time-frequency analysis of EEG data revealed no significant difference between persons with PD and HCs regarding delta-theta (2-8 Hz) inter-trial phase coherence to noise and sentence onset. In contrast, significantly increased alpha (8-12 Hz) power was found in persons with PD compared with HCs during the sentence-in-noise recognition task. Behaviourally, persons with PD demonstrated significantly decreased speech recognition scores, whereas no significant differences were found regarding effort, performance, and motivation ratings. These results suggest that persons with PD allocate more cognitive resources to support speech-in-noise processing. The interpretation of this finding is discussed in the context of a top-down mediated compensation mechanism for inefficient filtering and degradation of auditory input in PD.

Dynamics underlying auditory-object-boundary detection in primary auditory cortex

Auditory object analysis requires the fundamental perceptual process of detecting boundaries between auditory objects. However, the dynamics underlying the identification of discontinuities at object boundaries are not well understood. Here, we employed a synthetic stimulus composed of frequency-modulated ramps known as 'acoustic textures', where boundaries were created by changing the underlying spectrotemporal statistics. We collected magnetoencephalographic (MEG) data from human volunteers and observed a slow (<1 Hz) post-boundary drift in the neuromagnetic signal. The response evoking this drift signal was source localised close to Heschl's gyrus (HG) bilaterally, which is in agreement with a previous functional magnetic resonance imaging (fMRI) study that found HG to be involved in the detection of similar auditory object boundaries. Time-frequency analysis demonstrated suppression in alpha and beta bands that occurred after the drift signal.

Preparatory delta phase response is correlated with naturalistic speech comprehension performance

While human speech comprehension is thought to be an active process that involves top-down predictions, it remains unclear how predictive information is used to prepare for the processing of upcoming speech information. We aimed to identify the neural signatures of the preparatory processing of upcoming speech. Participants selectively attended to one of two competing naturalistic, narrative speech streams, and a temporal response function (TRF) method was applied to derive event-related-like neural responses from electroencephalographic data. The phase responses to the attended speech at the delta band (1-4 Hz) were correlated with the comprehension performance of individual participants, with a latency of - 200-0 ms relative to the onset of speech amplitude envelope fluctuations over the fronto-central and left-lateralized parietal electrodes. The phase responses to the attended speech at the alpha band also correlated with comprehension performance but with a latency of 650-980 ms post-onset over the fronto-central electrodes. Distinct neural signatures were found for the attentional modulation, taking the form of TRF-based amplitude responses at a latency of 240-320 ms post-onset over the left-lateralized fronto-central and occipital electrodes. Our findings reveal how the brain gets prepared to process an upcoming speech in a continuous, naturalistic speech context.

A neural-based account of sequential bias during perceptual judgment

Sequential effects are prominent and pervasive phenomena that exist in most perceptual judgments. Of importance, these effects reflect dynamic aspects in our judgment bias induced by the recent context. When making successive judgments in response to a sequence of stimuli, two opposing consequences have frequently been observed: assimilation effects - current stimuli judged as being closer to preceding stimuli than they actually are, and contrast effects - current stimuli judged as being further from preceding stimuli than they actually are. Although several cognitive accounts have been previously proposed, there is still a lack of consensus on the underlying mechanism, particularly regarding the insights of the temporal dynamics. Building upon accumulating human M/EEG findings, I propose a framework to explain how sequential bias is generated, unfolded over time, and eventually incorporated into the formation of current biased judgment. By bringing sequential effects closer to a biologically plausible framework, this synthetic view could account for how the opposing consequences of sequential effects differentially evolve, distinguish the effects from other perceptual phenomena with similar behavioral outcomes (such as aftereffects and priming), and illuminate how perceptual judgment is adaptively adjusted under the impact of temporal context.

Target enhancement or distractor suppression? Functionally distinct alpha oscillations form the basis of attention

Recent advances in attention research have been propelled by the debate on target enhancement versus distractor suppression. A predominant neural correlate of attention is the modulation of alpha oscillatory power (~10 Hz), which signifies shifts of attention in time, space and between sensory modalities. However, the underspecified functional role of alpha oscillations limits the progress of tracking down the neurocognitive basis of attention. In this short opinion article, we review and critically examine a synthesis of three conceptual and methodological aspects that are indispensable for a mechanistic understanding of the role of alpha oscillations for attention. (a) Precise mapping of the anatomical source and the temporal response profile of neural signals reveals distinct alpha oscillatory processes that implement facilitatory versus suppressive components of attention. (b) A testable framework enables unanimous association of alpha modulation with either target enhancement or different forms of distractor suppression (active vs. automatic). (c) Linking anatomically specified alpha oscillations to behavior reveals the causal nature of alpha oscillations for attention. The three reviewed aspects substantially enrich study design, data analysis and interpretation of results to achieve the goal of understanding how anatomically specified and functionally relevant neural oscillations contribute to the implementation of facilitatory versus suppressive components of attention.

Associations between pre-stimulus alpha power, hearing level and performance in a digits-in-noise task

OBJECTIVE

Baseline electroencephalography (EEG) alpha power, i.e. that measured prior to stimulus presentation, is a potential objective predictor of task performance. Here we assessed the predictive power of EEG alpha on performance accuracy in a digits-in-noise recognition task, factoring in hearing thresholds and age.

DESIGN

EEG alpha power, recorded while participants listened to target digits presented in a noise background, was analysed during two different baseline periods: i) a pre-stimulus baseline (pre-STIM) free from any acoustic stimulus, and ii) a pre-target baseline (pre-TARG) recorded in background noise only.

STUDY SAMPLE

Eighty-five participants with either normal hearing or aided hearing impairment (age range: 55-85 years old, 42 male).

RESULTS

Hierarchical multiple regression analyses indicated that i) lower hearing thresholds and, to a lesser extent, higher pre-STIM alpha power were associated with improved performance accuracy ii) alpha power in pre-STIM and pre-TARG were highly correlated across individuals but pre-TARG alpha power was not a significant predictor of performance accuracy.

CONCLUSION

Investigations of baseline EEG alpha power as a predictor of speech-in-noise performance accuracy should control for associations between hearing thresholds and measures of EEG baseline periods.

Low pre-stimulus EEG alpha power amplifies visual awareness but not visual sensitivity

Pre-stimulus oscillatory neural activity has been linked to the level of awareness of sensory stimuli. More specifically, the power of low-frequency oscillations (primarily in the alpha-band, i.e., 8-14 Hz) prior to stimulus onset is inversely related to measures of subjective performance in visual tasks, such as confidence and visual awareness. Intriguingly, the same EEG signature does not seem to influence objective measures of task performance (i.e., accuracy). We here examined whether this dissociation holds when stringent accuracy measures are used. Previous EEG-studies have employed 2-alternative forced choice (2-AFC) discrimination tasks to link pre-stimulus oscillatory activity to correct/incorrect responses as an index of accuracy/objective performance at the single-trial level. However, 2-AFC tasks do not provide a good estimate of single-trial accuracy, as many of the responses classified as correct will be contaminated by guesses (with the chance correct response rate being 50%). Here instead, we employed a 19-AFC letter identification task to measure accuracy and the subjectively reported level of perceptual awareness on each trial. As the correct guess rate is negligible (~5%), this task provides a purer measure of accuracy. Our results replicate the inverse relationship between pre-stimulus alpha/beta-band power and perceptual awareness ratings in the absence of a link to discrimination accuracy. Pre-stimulus oscillatory phase did not predict either subjective awareness or accuracy. Our results hence confirm a dissociation of the pre-stimulus EEG power-task performance link for subjective versus objective measures of performance, and further substantiate pre-stimulus alpha power as a neural predictor of visual awareness.

Delta/Theta band EEG activity shapes the rhythmic perceptual sampling of auditory scenes

Many studies speak in favor of a rhythmic mode of listening, by which the encoding of acoustic information is structured by rhythmic neural processes at the time scale of about 1 to 4 Hz. Indeed, psychophysical data suggest that humans sample acoustic information in extended soundscapes not uniformly, but weigh the evidence at different moments for their perceptual decision at the time scale of about 2 Hz. We here test the critical prediction that such rhythmic perceptual sampling is directly related to the state of ongoing brain activity prior to the stimulus. Human participants judged the direction of frequency sweeps in 1.2 s long soundscapes while their EEG was recorded. We computed the perceptual weights attributed to different epochs within these soundscapes contingent on the phase or power of pre-stimulus EEG activity. This revealed a direct link between 4 Hz EEG phase and power prior to the stimulus and the phase of the rhythmic component of these perceptual weights. Hence, the temporal pattern by which the acoustic information is sampled over time for behavior is directly related to pre-stimulus brain activity in the delta/theta band. These results close a gap in the mechanistic picture linking ongoing delta band activity with their role in shaping the segmentation and perceptual influence of subsequent acoustic information.

Phase-Coded Oscillatory Ordering Promotes the Separation of Closely Matched Representations to Optimize Perceptual Discrimination

Low-frequency oscillations are proposed to be involved in separating neuronal representations belonging to different items. Although item-specific neuronal activity was found to cluster on different oscillatory phases, the influence of this mechanism on perception is unknown. Here, we investigated the perceptual consequences of neuronal item separation through oscillatory clustering. In an electroencephalographic experiment, participants categorized sounds parametrically varying in pitch, relative to an arbitrary pitch boundary. Pre-stimulus theta and alpha phase biased near-boundary sound categorization to one category or the other. Phase also modulated whether evoked neuronal responses contributed stronger to the fit of the sound envelope of one or another category. Intriguingly, participants with stronger oscillatory clustering (phase strongly biasing sound categorization) in the theta, but not alpha, range had steeper perceptual psychometric slopes (sharper sound category discrimination). These results indicate that neuronal sorting by phase directly influences subsequent perception and has a positive impact on discrimination performance.

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Pre-stimulus theta/alpha phase co-determines how we perceive ambiguous sounds

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Phase influences to which sound envelope evoked potentials fit better

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Neural separation through phase clustering promotes sound discrimination

Spontaneous Brain Oscillations and Perceptual Decision-Making

Making rapid decisions on the basis of sensory information is essential to everyday behaviors. Why, then, are perceptual decisions so variable despite unchanging inputs? Spontaneous neural oscillations have emerged as a key predictor of trial-to-trial perceptual variability. New work casting these effects in the framework of models of perceptual decision-making has driven novel insight into how the amplitude of spontaneous oscillations impact decision-making. This synthesis reveals that the amplitude of ongoing low-frequency oscillations (<30 Hz), particularly in the alpha-band (8-13 Hz), bias sensory responses and change conscious perception but not, surprisingly, the underlying sensitivity of perception. A key model-based insight is that various decision thresholds do not adapt to alpha-related changes in sensory activity, demonstrating a seeming suboptimality of decision mechanisms in tracking endogenous changes in sensory responses.

Alpha Activity Reflects the Magnitude of an Individual Bias in Human Perception

Biases in sensory perception can arise from both experimental manipulations and personal trait-like features. These idiosyncratic biases and their neural underpinnings are often overlooked in studies on the physiology underlying perception. A potential candidate mechanism reflecting such idiosyncratic biases could be spontaneous alpha band activity, a prominent brain rhythm known to influence perceptual reports in general. Using a temporal order judgment task, we here tested the hypothesis that alpha power reflects the overcoming of an idiosyncratic bias. Importantly, to understand the interplay between idiosyncratic biases and contextual (temporary) biases induced by experimental manipulations, we quantified this relation before and after temporal recalibration. Using EEG recordings in human participants (male and female), we find that prestimulus frontal alpha power correlates with the tendency to respond relative to an own idiosyncratic bias, with stronger α leading to responses matching the bias. In contrast, alpha power does not predict response correctness. These results also hold after temporal recalibration and are specific to the alpha band, suggesting that alpha band activity reflects, directly or indirectly, processes that help to overcome an individual's momentary bias in perception. We propose that combined with established roles of parietal α in the encoding of sensory information frontal α reflects complementary mechanisms influencing perceptual decisions.SIGNIFICANCE STATEMENT The brain is a biased organ, frequently generating systematically distorted percepts of the world, leading each of us to evolve in our own subjective reality. However, such biases are often overlooked or considered noise when studying the neural mechanisms underlying perception. We show that spontaneous alpha band activity predicts the degree of biasedness of human choices in a time perception task, suggesting that alpha activity indexes processes needed to overcome an individual's idiosyncratic bias. This result provides a window onto the neural underpinnings of subjective perception, and offers the possibility to quantify or manipulate such priors in future studies.

Aberrant Prestimulus Oscillations in Developmental Dyslexia Support an Underlying Attention Shifting Deficit

Developmental dyslexia (DD) impairs reading and writing acquisition in 5–10% of children, compromising schooling, academic success, and everyday adult life. DD associates with reduced phonological skills, evident from a reduced auditory mismatch negativity (MMN) in the electroencephalogram (EEG). It was argued that such phonological deficits are secondary to an underlying deficit in the shifting of attention to upcoming speech sounds. Here, we tested whether the aberrant MMN in individuals with DD is a function of EEG correlates of prestimulus attention shifting; based on prior findings, we focused prestimulus analyses on alpha-band oscillations. We administered an audio–visual oddball paradigm to school children with and without DD. Children with DD showed EEG markers of deficient attention switching (i.e., increased prestimulus alpha-band intertrial phase coherence [ITPC]) to precede and predict their reduced MMN—aberrantly increased ITPC predicted an aberrantly reduced MMN. In interaction, ITPC and MMN predicted reading abilities, such that poor readers showed both high ITPC and a reduced MMN, the reverse being true in good readers. Prestimulus ITPC may be an overlooked biomarker of deficient attention shifting in DD. The findings support the proposal that an attention shifting deficit underlies phonological deficits in DD, entailing new opportunities for targeted intervention.

Topographic specificity of alpha power during auditory spatial attention

Visual and somatosensory spatial attention both induce parietal alpha (8-14 ​Hz) oscillations whose topographical distribution depends on the direction of spatial attentional focus. In the auditory domain, contrasts of parietal alpha power for leftward and rightward attention reveal qualitatively similar lateralization; however, it is not clear whether alpha lateralization changes monotonically with the direction of auditory attention as it does for visual spatial attention. In addition, most previous studies of alpha oscillation did not consider individual differences in alpha frequency, but simply analyzed power in a fixed spectral band. Here, we recorded electroencephalography in human subjects when they directed attention to one of five azimuthal locations. After a cue indicating the direction of an upcoming target sequence of spoken syllables (yet before the target began), alpha power changed in a task-specific manner. Individual peak alpha frequencies differed consistently between central electrodes and parieto-occipital electrodes, suggesting multiple neural generators of task-related alpha. Parieto-occipital alpha increased over the hemisphere ipsilateral to attentional focus compared to the contralateral hemisphere, and changed systematically as the direction of attention shifted from far left to far right. These results showing that parietal alpha lateralization changes smoothly with the direction of auditory attention as in visual spatial attention provide further support to the growing evidence that the frontoparietal attention network is supramodal.

Does Closing the Eyes Enhance Auditory Attention? Eye Closure Increases Attentional Alpha-Power Modulation but Not Listening Performance

In challenging listening conditions, closing the eyes is a strategy with intuitive appeal to improve auditory attention and perception. On the neural level, closing the eyes increases the power of alpha oscillations (∼10 Hz), which are a prime signature of auditory attention. Here, we test whether eye closure benefits neural and behavioral signatures of auditory attention and perception. Participants (n = 22) attended to one of two alternating streams of spoken numbers with open or closed eyes in a darkened chamber. After each trial, participants indicated whether probes had been among the to-be-attended or to-be-ignored numbers. In the EEG, states of relative high versus low alpha power accompanied the presentation of attended versus ignored numbers. Importantly, eye closure did not only increase the overall level of absolute alpha power but also the attentional modulation thereof. Behaviorally, however, neither perceptual sensitivity nor response criterion was affected by eye closure. To further examine whether this behavioral null result would conceptually replicate in a simple auditory detection task, a follow-up experiment was conducted that required participants (n = 19) to detect a near-threshold target tone in noise. As in the main experiment, our results provide evidence for the absence of any difference in perceptual sensitivity and criterion for open versus closed eyes. In summary, we demonstrate here that the modulation of the human alpha rhythm by auditory attention is increased when participants close their eyes. However, our results speak against the widely held belief that eye closure per se improves listening behavior.

Spatial Attentional Selection Modulates Early Visual Stimulus Processing Independently of Visual Alpha Modulations

The capacity-limited human brain is constantly confronted with a huge amount of sensory information. Selective attention is needed for biasing neural processing towards relevant information and consequently allows meaningful interaction with the environment. Activity in the alpha-band has been proposed to be related to top-down modulation of neural inhibition and could thus represent a viable candidate to control the priority of stimulus processing. It is, however, unknown whether modulations in the alpha-band directly relate to changes in the sensory gain control of the early visual cortex. Here, we used a spatial cueing paradigm while simultaneously measuring ongoing alpha-band oscillations and steady-state visual evoked potentials (SSVEPs) as a marker of continuous early sensory processing in the human visual cortex. Thereby, the effects of spatial attention for both of these signals and their potential interactions were assessed. As expected, spatial attention modulated both alpha-band and SSVEP responses. However, their modulations were independent of each other and the corresponding activity profiles differed across task demands. Thus, our results challenge the view that modulations of alpha-band activity represent a mechanism that directly alters or controls sensory gain. The potential role of alpha-band oscillations beyond sensory processing will be discussed in light of the present results.

Local cortical desynchronization and pupil-linked arousal differentially shape brain states for optimal sensory performance

Instantaneous brain states have consequences for our sensation, perception, and behaviour. Fluctuations in arousal and neural desynchronization likely pose perceptually relevant states. However, their relationship and their relative impact on perception is unclear. We here show that, at the single-trial level in humans, local desynchronization in sensory cortex (expressed as time-series entropy) versus pupil-linked arousal differentially impact perceptual processing. While we recorded electroencephalography (EEG) and pupillometry data, stimuli of a demanding auditory discrimination task were presented into states of high or low desynchronization of auditory cortex via a real-time closed-loop setup. Desynchronization and arousal distinctly influenced stimulus-evoked activity and shaped behaviour displaying an inverted u-shaped relationship: States of intermediate desynchronization elicited minimal response bias and fastest responses, while states of intermediate arousal gave rise to highest response sensitivity. Our results speak to a model in which independent states of local desynchronization and global arousal jointly optimise sensory processing and performance.

Alpha/beta power decreases track the fidelity of stimulus-specific information

Massed synchronised neuronal firing is detrimental to information processing. When networks of task-irrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, such synchronisation can contribute to alpha/beta (8-30 Hz) oscillations. Reducing the amplitude of these oscillations, therefore, may enhance information processing. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as post-stimulus alpha/beta power decreased, stimulus-specific information increased. Critically, we found this effect in three unique tasks: visual perception, auditory perception, and visual memory retrieval, indicating that this phenomenon transcends both stimulus modality and cognitive task. These results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internally-generated stimulus-specific information represented within the cortex.

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 in the Human Brain Implement Distractor Suppression Independent of Target Selection

In principle, selective attention is the net result of target selection and distractor suppression. The way in which both mechanisms are implemented neurally has remained contested. Neural oscillatory power in the alpha frequency band (∼10 Hz) has been implicated in the selection of to-be-attended targets, but there is lack of empirical evidence for its involvement in the suppression of to-be-ignored distractors. Here, we use electroencephalography recordings of N = 33 human participants (males and females) to test the preregistered hypothesis that alpha power directly relates to distractor suppression and thus operates independently from target selection. In an auditory spatial pitch discrimination task, we modulated the location (left vs right) of either a target or a distractor tone sequence, while fixing the other in the front. When the distractor was fixed in the front, alpha power relatively decreased contralaterally to the target and increased ipsilaterally. Most importantly, when the target was fixed in the front, alpha lateralization reversed in direction for the suppression of distractors on the left versus right. These data show that target-selection-independent alpha power modulation is involved in distractor suppression. Although both lateralized alpha responses for selection and for suppression proved reliable, they were uncorrelated and distractor-related alpha power emerged from more anterior, frontal cortical regions. Lending functional significance to suppression-related alpha oscillations, alpha lateralization at the individual, single-trial level was predictive of behavioral accuracy. These results fuel a renewed look at neurobiological accounts of selection-independent suppressive filtering in attention.SIGNIFICANCE STATEMENT Although well established models of attention rest on the assumption that irrelevant sensory information is filtered out, the neural implementation of such a filter mechanism is unclear. Using an auditory attention task that decouples target selection from distractor suppression, we demonstrate that two sign-reversed lateralized alpha responses reflect target selection versus distractor suppression. Critically, these alpha responses are reliable, independent of each other, and generated in more anterior, frontal regions for suppression versus selection. Prediction of single-trial task performance from alpha modulation after stimulus onset agrees with the view that alpha modulation bears direct functional relevance as a neural implementation of attention. Results demonstrate that the neurobiological foundation of attention implies a selection-independent alpha oscillatory mechanism to suppress distraction.

Pre-stimulus brain state predicts auditory pattern identification accuracy

Recent studies show that pre-stimulus band-specific power and phase in the electroencephalogram (EEG) can predict accuracy on tasks involving the detection of near-threshold stimuli. However, results in the auditory modality have been mixed, and few works have examined pre-stimulus features when more complex decisions are made (e.g. identifying supra-threshold sounds). Further, most auditory studies have used background sounds known to induce oscillatory EEG states, leaving it unclear whether phase predicts accuracy without such background sounds. To address this gap in knowledge, the present study examined pre-stimulus EEG as it relates to accuracy in a tone pattern identification task. On each trial, participants heard a triad of 40-ms sinusoidal tones (separated by 40-ms intervals), one of which was at a different frequency than the other two. Participants' task was to indicate the tone pattern (low-low-high, low-high-low, etc.). No background sounds were employed. Using a phase opposition measure based on inter-trial phase consistencies, pre-stimulus 7-10 Hz phase was found to differ between correct and incorrect trials ∼200 to 100 ms prior to tone-pattern onset. After sorting trials into bins based on phase, accuracy was found to be lowest at around π-+ relative to individuals' most accurate phase bin. No significant effects were found for pre-stimulus power. In the context of the literature, findings suggest an important relationship between the complexity of task demands and pre-stimulus activity within the auditory domain. Results also raise interesting questions about the role of induced oscillatory states or rhythmic processing modes in obtaining pre-stimulus effects of phase in auditory tasks.

Frequency and power of human alpha oscillations drift systematically with time-on-task

Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (∼1 h), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8-13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (∼8-10 Hz), while components with unique changes oscillated primarily in the higher alpha-band (∼9-13 Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation.

Attention and speech-processing related functional brain networks activated in a multi-speaker environment

Human listeners can focus on one speech stream out of several concurrent ones. The present study aimed to assess the whole-brain functional networks underlying a) the process of focusing attention on a single speech stream vs. dividing attention between two streams and 2) speech processing on different time-scales and depth. Two spoken narratives were presented simultaneously while listeners were instructed to a) track and memorize the contents of a speech stream and b) detect the presence of numerals or syntactic violations in the same ("focused attended condition") or in the parallel stream ("divided attended condition"). Speech content tracking was found to be associated with stronger connectivity in lower frequency bands (delta band- 0,5-4 Hz), whereas the detection tasks were linked with networks operating in the faster alpha (8-10 Hz) and beta (13-30 Hz) bands. These results suggest that the oscillation frequencies of the dominant brain networks during speech processing may be related to the duration of the time window within which information is integrated. We also found that focusing attention on a single speaker compared to dividing attention between two concurrent speakers was predominantly associated with connections involving the frontal cortices in the delta (0.5-4 Hz), alpha (8-10 Hz), and beta bands (13-30 Hz), whereas dividing attention between two parallel speech streams was linked with stronger connectivity involving the parietal cortices in the delta and beta frequency bands. Overall, connections strengthened by focused attention may reflect control over information selection, whereas connections strengthened by divided attention may reflect the need for maintaining two streams in parallel and the related control processes necessary for performing the tasks.