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

The role of brain oscillations in feature integration

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well-known. However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration. Alpha and beta power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top-down expectancies.

Overactivated contextual visual perception and response to a single dose of methylphenidate in children with ADHD

The pathogenesis of overactivated visual perception in attention-deficit hyperactivity disorder (ADHD) remains unclear, which is interpreted as a cognitive compensation. The existing studies have proposed that perceptual abnormalities in neurodevelopmental disorders are associated with dysfunction of the contextual knowledge system, which influences the development and formation of perception. We hypothesized that alterations in contextual states may also be responsible for inducing perceptual abnormalities in ADHD. Therefore, the present study evaluated the characteristics of pre-stimulus alpha and its response to a single dose of methylphenidate (MPH). A total of 135 Chinese children participated in the first study, including 70 children with ADHD (age = 10.61 ± 1.93 years, female = 17) and 65 age- and sex-matched control children (age = 10.73 ± 1.93 years, female = 20). The second clinical trial included 19 Chinese children with ADHD (age = 11.85 ± 1.72 years, female = 4), with an identical visual spatial search task. Pre-stimulus alpha oscillations and P1 activity were significantly greater in children with ADHD than in the controls. Overactivated pre-stimulus alpha positively predicted P1. Both pre-stimulus alpha and P1 overactivation have beneficial effects on cognitive performance in children with ADHD. No intervening effect of a single dose of MPH on the compensatory activation of pre-stimulus alpha and P1 were observed. Our findings extended the perceptual activation to the contextual knowledge system, suggesting that compensatory perception in children with ADHD is more likely to be a top-down regulated cognitive operational process.

Investigation of advanced mindfulness meditation "cessation" experiences using EEG spectral analysis in an intensively sampled case study

Mindfulness meditation is a contemplative practice informed by Buddhism that targets the development of present-focused awareness and non-judgment of experience. Interest in mindfulness is burgeoning, and it has been shown to be effective in improving mental and physical health in clinical and non-clinical contexts. In this report, for the first time, we used electroencephalography (EEG) combined with a neurophenomenological approach to examine the neural signature of "cessation" events, which are dramatic experiences of complete discontinuation in awareness similar to the loss of consciousness, which are reported to be experienced by very experienced meditators, and are proposed to be evidence of mastery of mindfulness meditation. We intensively sampled these cessations as experienced by a single advanced meditator (with over 23,000 h of meditation training) and analyzed 37 cessation events collected in 29 EEG sessions between November 12, 2019, and March 11, 2020. Spectral analyses of the EEG data surrounding cessations showed that these events were marked by a large-scale alpha-power decrease starting around 40 s before their onset, and that this alpha-power was lowest immediately following a cessation. Region-of-interest (ROI) based examination of this finding revealed that this alpha-suppression showed a linear decrease in the occipital and parietal regions of the brain during the pre-cessation time period. Additionally, there were modest increases in theta power for the central, parietal, and right temporal ROIs during the pre-cessation timeframe, whereas power in the Delta and Beta frequency bands were not significantly different surrounding cessations. By relating cessations to objective and intrinsic measures of brain activity (i.e., EEG power) that are related to consciousness and high-level psychological functioning, these results provide evidence for the ability of experienced meditators to voluntarily modulate their state of consciousness and lay the foundation for studying these unique states using a neuroscientific approach.

Storm on predictive brain: A neurocomputational account of ketamine antidepressant effect

For the past decade, ketamine, an N-methyl-D-aspartate receptor (NMDAr) antagonist, has been considered a promising treatment for major depressive disorder (MDD). Unlike the delayed effect of monoaminergic treatment, ketamine may produce fast-acting antidepressant effects hours after a single administration at subanesthetic dose. Along with these antidepressant effects, it may also induce transient dissociative (disturbing of the sense of self and reality) symptoms during acute administration which resolve within hours. To understand ketamine's rapid-acting antidepressant effect, several biological hypotheses have been explored, but despite these promising avenues, there is a lack of model to understand the timeframe of antidepressant and dissociative effects of ketamine. In this article, we propose a neurocomputational account of ketamine's antidepressant and dissociative effects based on the Predictive Processing (PP) theory, a framework for cognitive and sensory processing. PP theory suggests that the brain produces top-down predictions to process incoming sensory signals, and generates bottom-up prediction errors (PEs) which are then used to update predictions. This iterative dynamic neural process would relies on N-methyl-D-aspartate (NMDAr) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic receptors (AMPAr), two major component of the glutamatergic signaling. Furthermore, it has been suggested that MDD is characterized by over-rigid predictions which cannot be updated by the PEs, leading to miscalibration of hierarchical inference and self-reinforcing negative feedback loops. Based on former empirical studies using behavioral paradigms, neurophysiological recordings, and computational modeling, we suggest that ketamine impairs top-down predictions by blocking NMDA receptors, and enhances presynaptic glutamate release and PEs, producing transient dissociative symptoms and fast-acting antidepressant effect in hours following acute administration. Moreover, we present data showing that ketamine may enhance a delayed neural plasticity pathways through AMPAr potentiation, triggering a prolonged antidepressant effect up to seven days for unique administration. Taken together, the two sides of antidepressant effects with distinct timeframe could constitute the keystone of antidepressant properties of ketamine. These PP disturbances may also participate to a ketamine-induced time window of mental flexibility, which can be used to improve the psychotherapeutic process. Finally, these proposals could be used as a theoretical framework for future research into fast-acting antidepressants, and combination with existing antidepressant and psychotherapy.

Fluctuations in alpha and beta power provide neural states favourable for contextually relevant anticipatory processes

Cued sensory input occasionally fails to immediately ensue its respective trigger. Given that our environments are rich in sensory cues, we often end up processing other contextually relevant information in the meantime. The experimental design of the present study allowed us to investigate how such temporal delays and visual interferences may impact anticipatory processes. Thirty-four participants were trained to remember an individualised set of eight paired-up faces. These paired-up faces were presented pseudorandomly in sequences of unpaired face images. To keep participants engaged throughout the electroencephalography study, they were instructed to classify each face image, according to its sex, as fast as possible without compromising accuracy. We observed dissimilar modulations in alpha and beta power between the 6-s timeframe encompassing the onsets of predictive and expected images (temporal delay block) and the 6-s timeframe encompassing the predictive, interference and expected images (visual interference block). Furthermore, an expectation-facilitated reduction of the face-sensitive N170 component was only observed if an anticipated face image directly followed its corresponding predictive counterpart. This effect was no longer evident when the expected face was preceded by a distracting face image. Regardless of the block type, behavioural measures confirmed that anticipated faces were classified significantly faster and with fewer erroneous responses than faces not foretold by a predictive face. Collectively, these results demonstrate that whilst the brain continuously adjusts internal hierarchical generative models to account for temporal delays in stimulus onset and visual interferences, the higher levels, and subsequent predictions, fundamental for expectation-facilitated behaviours remain intact.

Revisiting the effects of configuration, predictability, and relevance on visual detection during interocular suppression

Statistical regularities and predictions can influence the earliest stages of visual processing. Studies examining their effects on detection, however, have yielded inconsistent results. In continuous flash suppression (CFS), where a static image projected to one eye is suppressed by a dynamic image presented to the other, the predictability of the suppressed signal may facilitate or delay detection. To identify the factors that differentiate these outcomes and dissociate the effects of expectation from those of behavioral relevance, we conducted three CFS experiments that addressed confounds related to the use of reaction time measures and complex images. In experiment 1, orientation recognition performance and visibility rates increased when a suppressed line segment completed a partial shape surrounding the CFS patch, demonstrating that valid configuration cues facilitate detection. In Experiment 2, however, predictive cues marginally affected visibility and did not modulate localization performance, challenging existing findings. In experiment 3, a relevance manipulation was introduced; participants pressed a key upon detecting lines of a particular orientation, ignoring the other possible orientation. Visibility and localization were enhanced for relevant orientations. Predictive cues modulated visibility, orientation recognition sensitivity, and response latencies, but not localization-an objective measure sensitive to partial breakthrough. Thus, while a consistent surround can strongly enhance detection during passive observation, predictive cueing primarily affects post-detection factors such as response readiness and recognition confidence. Relevance and predictability did not interact, suggesting that the contributions of these two processes to detection are mostly orthogonal.

Alpha oscillations protect working memory against distracters in a modality-specific way

Alpha oscillations are thought to be involved in suppressing distracting input in working-memory tasks. Yet, the spatial-temporal dynamics of such suppression remain unclear. Key questions are whether such suppression reflects a domain-general inattentiveness mechanism, or occurs in a stimulus- or modality-specific manner within cortical areas most responsive to the distracters; and whether the suppression is proactive (i.e., preparatory) or reactive. Here, we addressed these questions using a working-memory task where participants had to memorize an array of visually presented digits and reproduce one of them upon being probed. We manipulated the presence of distracters and the sensory modality in which distracters were presented during memory maintenance. Our results show that sensory areas most responsive to visual and auditory distracters exhibited stronger alpha power increase after visual and auditory distracter presentation respectively. These results suggest that alpha oscillations underlie distracter suppression in a reactive, modality-specific manner.

Prior Knowledge Uses Prestimulus Alpha Band Oscillations and Persistent Poststimulus Neural Templates for Conscious Perception

Prior knowledge has a profound impact on the way we perceive the world. However, it remains unclear how the prior knowledge is maintained in our brains and thereby influences the subsequent conscious perception. The Dalmatian dog illusion is a perfect tool to study prior knowledge, where the picture is initially perceived as noise. Once the prior knowledge was introduced, a Dalmatian dog could be consciously seen, and the picture immediately became meaningful. Using pictures with hidden objects as standard stimuli and similar pictures without hidden objects as deviant stimuli, we investigated the neural representation of prior knowledge and its impact on conscious perception in an oddball paradigm using electroencephalogram (EEG) in both male and female human subjects. We found that the neural patterns between the prestimulus alpha band oscillations and poststimulus EEG activity were significantly more similar for the standard stimuli than for the deviant stimuli after prior knowledge was provided. Furthermore, decoding analysis revealed that persistent neural templates were evoked after the introduction of prior knowledge, similar to that evoked in the early stages of visual processing. In conclusion, the current study suggests that prior knowledge uses alpha band oscillations in a multivariate manner in the prestimulus period and induces specific persistent neural templates in the poststimulus period, enabling the conscious perception of the hidden objects.SIGNIFICANCE STATEMENT The visual world we live in is not always optimal. In dark or noisy environments, prior knowledge can help us interpret imperfect sensory signals and enable us to consciously perceive hidden objects. However, we still know very little about how prior knowledge works at the neural level. Using the Dalmatian dog illusion and multivariate methods, we found that prior knowledge uses prestimulus alpha band oscillations to carry information about the hidden object and exerts a persistent influence in the poststimulus period by inducing specific neural templates. Our findings provide a window into the neural underpinnings of prior knowledge and offer new insights into the role of alpha band oscillations and neural templates associated with conscious perception.

Rhythmic TMS as a Feasible Tool to Uncover the Oscillatory Signatures of Audiovisual Integration

Multisensory integration is quintessential to adaptive behavior, with clinical populations showing significant impairments in this domain, most notably hallucinatory reports. Interestingly, altered cross-modal interactions have also been reported in healthy individuals when engaged in tasks such as the Sound-Induced Flash-Illusion (SIFI). The temporal dynamics of the SIFI have been recently tied to the speed of occipital alpha rhythms (IAF), with faster oscillations entailing reduced temporal windows within which the illusion is experienced. In this regard, entrainment-based protocols have not yet implemented rhythmic transcranial magnetic stimulation (rhTMS) to causally test for this relationship. It thus remains to be evaluated whether rhTMS-induced acoustic and somatosensory sensations may not specifically interfere with the illusion. Here, we addressed this issue by asking 27 volunteers to perform a SIFI paradigm under different Sham and active rhTMS protocols, delivered over the occipital pole at the IAF. Although TMS has been proven to act upon brain tissues excitability, results show that the SIFI occurred for both Sham and active rhTMS, with the illusory rate not being significantly different between baseline and stimulation conditions. This aligns with the discrete sampling hypothesis, for which alpha amplitude modulation, known to reflect changes in cortical excitability, should not account for changes in the illusory rate. Moreover, these findings highlight the viability of rhTMS-based interventions as a means to probe the neuroelectric signatures of illusory and hallucinatory audiovisual experiences, in healthy and neuropsychiatric populations.

Two Oscillatory Correlates of Attention Control in the Alpha-Band with Distinct Consequences on Perceptual Gain and Metacognition

Behavioral consequences and neural underpinnings of visuospatial attention have long been investigated. Classical studies using the Posner paradigm have found that visual perception systematically benefits from the use of a spatially informative cue pointing to the to-be-attended spatial location, compared with a noninformative cue. Lateralized α amplitude modulation during visuospatial attention shifts has been suggested to account for such perceptual gain. However, recent studies on spontaneous fluctuations of prestimulus α amplitude have challenged this notion. These studies showed that spontaneous fluctuations of prestimulus α amplitude were associated with the subjective appreciation of stimulus occurrence, while objective accuracy was instead best predicted by the frequency of α oscillations, with faster prestimulus α frequency accounting for better perceptual performance. Here, in male and female humans, by using an informative cue in anticipation of lateralized stimulus presentation, we found that the predictive cue not only modulates preparatory α amplitude but also α frequency in a retinotopic manner. Behaviorally, the cue significantly impacted subjective performance measures (metacognitive abilities [meta-d']) and objective performance gain (d'). Importantly, α amplitude directly accounted for confidence levels, with ipsilateral synchronization and contralateral desynchronization coding for high-confidence responses. Crucially, the contralateral α amplitude selectively predicted interindividual differences in metacognitive abilities (meta-d'), thus anticipating decision strategy and not perceptual sensitivity, probably via excitability modulations. Instead, higher perceptual accuracy both within and across participants (d') was associated with faster contralateral α frequency, likely by implementing higher sampling at the attended location. These findings provide critical new insights into the neural mechanisms of attention control and its perceptual consequences.SIGNIFICANCE STATEMENT Prior knowledge serves the anticipation of sensory input to reduce sensory ambiguity. The growing interest in the neural mechanisms governing the integration of sensory input into our internal representations has highlighted a pivotal role of brain oscillations. Here we show that distinct but interacting oscillatory mechanisms are engaged during attentional deployment: one relying on α amplitude modulations and reflecting internal decision processes, associated with subjective perceptual experience and metacognitive abilities; the other relying on α frequency modulations and enabling mechanistic sampling of the sensory input at the attended location to influence objective performance. These insights are crucial for understanding how we reduce sensory ambiguity to maximize the efficiency of our conscious experience, but also in interpreting the mechanisms of atypical perceptual experiences.

Between alpha and gamma oscillations: Neural signatures of linguistic predictions and listener's attention to speaker's communication intention

When listeners hear a message produced by their interlocutor, they can predict upcoming words thanks to the sentential context and their attention can be focused on the speaker's communication intention. In two electroencephalographical (EEG) studies, we investigated the oscillatory correlates of prediction in spoken-language comprehension and how they are modulated by the listener's attention. Sentential contexts which were strongly predictive of a particular word were ended by a possessive adjective either matching the gender of the predicted word or not. Alpha, beta and gamma oscillations were studied as they were considered to play a crucial role in the predictive process. While evidence of word prediction was related to alpha fluctuations when listeners focused their attention on sentence meaning, changes in high-gamma oscillations were triggered by word prediction when listeners focused their attention on the speaker's communication intention. Independently of the endogenous attention to a level of linguistic information, the oscillatory correlates of word predictions in language comprehension were sensitive to the prosodic emphasis produced by the speaker at a late stage. These findings thus bear major implications for understanding the neural mechanisms that support predictive processing in spoken-language comprehension.

The neural representations underlying asymmetric cross-modal prediction of words

Cross-modal prediction serves a crucial adaptive role in the multisensory world, yet the neural mechanisms underlying this prediction are poorly understood. The present study addressed this important question by combining a novel audiovisual sequence memory task, functional magnetic resonance imaging (fMRI), and multivariate neural representational analyses. Our behavioral results revealed a reliable asymmetric cross-modal predictive effect, with a stronger prediction from visual to auditory (VA) modality than auditory to visual (AV) modality. Mirroring the behavioral pattern, we found the superior parietal lobe (SPL) showed higher pattern similarity for VA than AV pairs, and the strength of the predictive coding in the SPL was positively correlated with the behavioral predictive effect in the VA condition. Representational connectivity analyses further revealed that the SPL mediated the neural pathway from the visual to the auditory cortex in the VA condition but was not involved in the auditory to visual cortex pathway in the AV condition. Direct neural pathways within the unimodal regions were found for the visual-to-visual and auditory-to-auditory predictions. Together, these results provide novel insights into the neural mechanisms underlying cross-modal sequence prediction.

Tactile expectancy modulates occipital alpha oscillations in early blindness

Alpha oscillatory activity is thought to contribute to visual expectancy through the engagement of task-relevant occipital regions. In early blindness, occipital alpha oscillations are systematically reduced, suggesting that occipital alpha depends on visual experience. However, it remains possible that alpha activity could serve expectancy in non-visual modalities in blind people, especially considering that previous research has shown the recruitment of the occipital cortex for non-visual processing. To test this idea, we used electroencephalography to examine whether alpha oscillations reflected a differential recruitment of task-relevant regions between expected and unexpected conditions in two haptic tasks (texture and shape discrimination). As expected, sensor-level analyses showed that alpha suppression in parieto-occipital sites was significantly reduced in early blind individuals compared with sighted participants. The source reconstruction analysis revealed that group differences originated in the middle occipital cortex. In that region, expected trials evoked higher alpha desynchronization than unexpected trials in the early blind group only. Our results support the role of alpha rhythms in the recruitment of occipital areas in early blind participants, and for the first time we show that although posterior alpha activity is reduced in blindness, it remains sensitive to expectancy factors. Our findings therefore suggest that occipital alpha activity is involved in tactile expectancy in blind individuals, serving a similar function to visual anticipation in sighted populations but switched to the tactile modality. Altogether, our results indicate that expectancy-dependent modulation of alpha oscillatory activity does not depend on visual experience. SIGNIFICANCE STATEMENT: Are posterior alpha oscillations and their role in expectancy and anticipation dependent on visual experience? Our results show that tactile expectancy can modulate posterior alpha activity in blind (but not sighted) individuals through the engagement of occipital regions, suggesting that in early blindness, alpha oscillations maintain their proposed role in visual anticipation but subserve tactile processing. Our findings bring a new understanding of the role that alpha oscillatory activity plays in blindness, contrasting with the view that alpha activity is task unspecific in blind populations.

Temporal expectation based on the duration variability modulates alpha oscillations during working memory retention

While maintaining information over a delay of time, working memory (WM) also allows individuals to prepare the mnemonic contents for prospective utilisation. However, it remains unclear whether the expectation of the time of WM test could modulate neural responses during the retention interval of WM and subsequent performance. Here, we investigated whether temporal expectations based on the variability of delay duration can modulate 9-13 Hz alpha oscillations during WM retention and whether the expectation-induced alpha activity was associated with WM performance. Participants performed a retro-cueing WM task with magnetoencephalography (MEG) (Experiment 1) and a standard WM task with electroencephalography (EEG) (Experiment 2). The expectation of the timing of the WM test was manipulated by the temporal structure of the tasks with small or large variability in the delay durations. We showed that alpha oscillations during retention interval and WM performance varied with duration variability in both of the MEG and EEG experiments. The novel finding was greater alpha-power attenuation over the left frontal and parietal regions during WM retention when the duration variability was small and the test onset was predictable, compared to when the duration variability was large and the test onset was less predictable. Importantly, we observed a positive relationship in variability difference between the response benefit and alpha-power attenuation in the left posterior parietal regions at both MEG-source and EEG-electrode levels. Finally, we confirmed the behavioural benefit when a condition with a fixed delay-duration was included in a behavioural experiment (Experiment 3). When conjoined, the delay duration enables individuals to anticipate when the relevant information would be put to work, and alpha oscillations track the anticipatory states during WM maintenance.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Expectance of low contrast retro-cues does not modulate anticipatory alpha power

It has been proposed that alpha oscillations reflect the endogenous modulation of visual cortex excitability. In particular, alpha power increases during the maintenance period in Working Memory (WM) tasks have been interpreted as a mechanism to avoid potential interference of incoming stimuli. In this study we tested whether alpha power was modulated during the maintenance of WM to enhance the processing of relevant incoming perceptual stimuli. To this aim, we manipulated the contrast of a stimulus presented during the maintenance period of a WM task. The to-be-detected stimulus could indicate which of the encoded representations was going to be probed after the delay (spatial retro-cue) or could signal that all the representations had equal probability to be tested (neutral retro-cue). Time-frequency analysis revealed that alpha power preceding retro-cue presentation was not differently modulated by the two different contrast conditions. This is, participants did not endogenously modulate alpha oscillations upon low perceptual contrast stimuli incoming. These results suggest that alpha delay activity is not a goal directed mechanism to control the inflow of information during WM maintenance. Instead, current data suggest that alpha delayed activity might be an index of increased allocation of attentional resources to the processing of the WM representations.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Neural oscillations promoting perceptual stability and perceptual memory during bistable perception

Ambiguous images elicit bistable perception, wherein periods of momentary perceptual stability are interrupted by sudden perceptual switches. When intermittently presented, ambiguous images trigger a perceptual memory trace in the intervening blank periods. Understanding the neural bases of perceptual stability and perceptual memory during bistable perception may hold clues for explaining the apparent stability of visual experience in the natural world, where ambiguous and fleeting images are prevalent. Motivated by recent work showing the involvement of the right inferior frontal gyrus (rIFG) in bistable perception, we conducted a transcranial direct-current stimulation (tDCS) study with a double-blind, within-subject cross-over design to test a potential causal role of rIFG in these processes. Subjects viewed ambiguous images presented continuously or intermittently while under EEG recording. We did not find any significant tDCS effect on perceptual behavior. However, the fluctuations of oscillatory power in the alpha and beta bands predicted perceptual stability, with higher power corresponding to longer percept durations. In addition, higher alpha and beta power predicted enhanced perceptual memory during intermittent viewing. These results reveal a unified neurophysiological mechanism sustaining perceptual stability and perceptual memory when the visual system is faced with ambiguous input.

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

Smell-induced gamma oscillations in human olfactory cortex are required for accurate perception of odor identity

Studies of neuronal oscillations have contributed substantial insight into the mechanisms of visual, auditory, and somatosensory perception. However, progress in such research in the human olfactory system has lagged behind. As a result, the electrophysiological properties of the human olfactory system are poorly understood, and, in particular, whether stimulus-driven high-frequency oscillations play a role in odor processing is unknown. Here, we used direct intracranial recordings from human piriform cortex during an odor identification task to show that 3 key oscillatory rhythms are an integral part of the human olfactory cortical response to smell: Odor induces theta, beta, and gamma rhythms in human piriform cortex. We further show that these rhythms have distinct relationships with perceptual behavior. Odor-elicited gamma oscillations occur only during trials in which the odor is accurately perceived, and features of gamma oscillations predict odor identification accuracy, suggesting that they are critical for odor identity perception in humans. We also found that the amplitude of high-frequency oscillations is organized by the phase of low-frequency signals shortly following sniff onset, only when odor is present. Our findings reinforce previous work on theta oscillations, suggest that gamma oscillations in human piriform cortex are important for perception of odor identity, and constitute a robust identification of the characteristic electrophysiological response to smell in the human brain. Future work will determine whether the distinct oscillations we identified reflect distinct perceptual features of odor stimuli.

Intracranial recordings from human olfactory cortex reveal a characteristic spectrotemporal response to odors, including theta, beta and gamma oscillations, and show that high-frequency responses are critical for accurate perception of odors.

How Psychedelic-Assisted Treatment Works in the Bayesian Brain

Psychedelics are experiencing a renaissance in clinical research. In recent years, an increasing number of studies on psychedelic-assisted treatment have been conducted. So far, the results are promising, suggesting that this new (or rather, rediscovered) form of therapy has great potential. One particular reason for that appears to be the synergistic combination of the pharmacological and psychotherapeutic interventions in psychedelic-assisted treatment. But how exactly do these two interventions complement each other? This paper provides the first account of the interaction between pharmacological and psychological effects in psychedelic-assisted treatment. Building on the relaxed beliefs under psychedelics (REBUS) hypothesis of Carhart-Harris and Friston and the contextual model of Wampold, it argues that psychedelics amplify the common factors and thereby the remedial effects of psychotherapy. More precisely, psychedelics are assumed to attenuate the precision of high-level predictions, making them more revisable by bottom-up input. Psychotherapy constitutes an important source of such input. At best, it signalizes a safe and supportive environment (cf. setting) and induces remedial expectations (cf. set). During treatment, these signals should become incorporated when high-level predictions are revised: a process that is hypothesized to occur as a matter of course in psychotherapy but to get reinforced and accelerated under psychedelics. Ultimately, these revisions should lead to a relief of symptoms.

Predictive Feedback, Early Sensory Representations, and Fast Responses to Predicted Stimuli Depend on NMDA Receptors

Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audiovisual delayed match-to-sample task which elicited predictions. Predictive β feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, an NMDAR blocker, but not the control drug dexmedetomidine, perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex, and pre-activation of sensory templates in higher-order sensory cortex. This study suggests that predictions depend on alpha activity in higher-order cortex, β feedback, and NMDARs, and ketamine blocks access to learned predictive information.SIGNIFICANCE STATEMENT We learn the statistical regularities around us, creating associations between sensory stimuli. These associations can be exploited by generating predictions, which enable fast and efficient behavior. When predictions are perturbed, it can negatively influence perception and even contribute to psychiatric disorders, such as schizophrenia. Here we show that the frontal lobe generates predictions and sends them to posterior brain areas, to activate representations of predicted sensory stimuli before their appearance. Oscillations in neural activity (α and β waves) are vital for these predictive mechanisms. The drug ketamine blocks predictions and the underlying mechanisms. This suggests that the generation of predictions in the frontal lobe, and the feedback pre-activating sensory representations in advance of stimuli, depend on NMDARs.

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.

Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model

The brain is a predictive machine. Converging data suggests a diametric predictive strategy from autism spectrum disorders (ASD) to schizophrenic spectrum disorders (SSD). Whereas perceptual inference in ASD is rigidly shaped by incoming sensory information, the SSD population is prone to overestimate the precision of their priors' models. Growing evidence considers brain oscillations pivotal biomarkers to understand how top-down predictions integrate bottom-up input. Starting from the conceptualization of ASD and SSD as oscillopathies, we introduce an integrated perspective that ascribes the maladjustments of the predictive mechanism to dysregulation of neural synchronization. According to this proposal, disturbances in the oscillatory profile do not allow the appropriate trade-off between descending predictive signal, overweighted in SSD, and ascending prediction errors, overweighted in ASD. These opposing imbalances both result in an ill-adapted reaction to external challenges. This approach offers a neuro-computational model capable of linking predictive coding theories with electrophysiological findings, aiming to increase knowledge on the neuronal foundations of the two spectra features and stimulate hypothesis-driven rehabilitation/research perspectives.

The Directionality of Fronto-Posterior Brain Connectivity Is Associated with the Degree of Individual Autistic Traits

Altered patterns of brain connectivity have been found in autism spectrum disorder (ASD) and associated with specific symptoms and behavioral features. Growing evidence suggests that the autistic peculiarities are not confined to the clinical population but extend along a continuum between healthy and maladaptive conditions. The aim of this study was to investigate whether a differentiated connectivity pattern could also be tracked along the continuum of autistic traits in a non-clinical population. A Granger causality analysis conducted on a resting-state EEG recording showed that connectivity along the posterior-frontal gradient is sensitive to the magnitude of individual autistic traits and mostly conveyed through fast oscillatory activity. Specifically, participants with higher autistic traits were characterized by a prevalence of ascending connections starting from posterior regions ramping the cortical hierarchy. These findings point to the presence of a tendency within the neural mapping of individuals with higher autistic features in conveying proportionally more bottom-up information. This pattern of findings mimics those found in clinical forms of autism, supporting the idea of a neurobiological continuum between autistic traits and ASD.

The Effect of Sound and Stimulus Expectation on Transcranial Magnetic Stimulation-Elicited Motor Evoked Potentials

The amplitude of motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) over the motor cortex is influenced by multiple factors. TMS delivery is accompanied by an abrupt clicking noise which can induce a startle response. This study investigated how masking/attenuating the sound produced by the TMS system discharging influences MEP amplitudes. In addition, the effects of increasing the time between consecutive stimuli and of making participants aware of the time at which they would be stimulated were studied. MEPs were recorded from the Flexor Carpi Radialis (FCR) muscle at rest by stimulation at motor threshold (MT), 120% MT and 140% MT intensity. Participants (N = 23) received stimulation under normal (NORMAL) conditions and while: wearing sound-attenuating earmuffs (EAR); listening to white noise (NOISE); the interval between stimuli were prolonged (LONG); stimulation timing was presented on a screen (READY). The results showed that masking (p = 0.020) and attenuating (p = 0.004) the incoming sound significantly reduced the amplitude of MEPs recorded across the intensities of stimulation. Increasing the interval between pulses had no effect on the recorded traces if a jitter was introduced (p = 1), but making participants aware of stimulation timing decreased MEP amplitudes (p = 0.049). These findings suggest that the sound produced by TMS at discharging increases MEP amplitudes and that MEP amplitudes are influenced by stimulus expectation. These confounding factors need to be considered when using TMS to assess corticospinal excitability.

Early alpha/beta oscillations reflect the formation of face-related expectations in the brain

Although statistical regularities in the environment often go explicitly unnoticed, traces of implicit learning are evident in our neural activity. Recent perspectives have offered evidence that both pre-stimulus oscillations and peri-stimulus event-related potentials are reliable biomarkers of implicit expectations arising from statistical learning. What remains ambiguous, however, is the origination and development of these implicit expectations. To address this lack of knowledge and determine the temporal constraints of expectation formation, pre-stimulus increases in alpha/beta power were investigated alongside a reduction in the N170 and a suppression in peri-/post-stimulus gamma power. Electroencephalography was acquired from naive participants who engaged in a gender classification task. Participants were uninformed, that eight face images were sorted into four reoccurring pairs which were pseudorandomly hidden amongst randomly occurring face images. We found a reduced N170 for statistically expected images at left parietal and temporo-parietal electrodes. Furthermore, enhanced gamma power following the presentation of random images emphasized the bottom-up processing of these arbitrary occurrences. In contrast, enhanced alpha/beta power was evident pre-stimulus for expected relative to random faces. A particularly interesting finding was the early onset of alpha/beta power enhancement which peaked immediately after the depiction of the predictive face. Hence, our findings propose an approximate timeframe throughout which consistent traces of enhanced alpha/beta power illustrate the early prioritisation of top-down processes to facilitate the development of implicitly cued face-related expectations.

Deep Predictive Learning in Neocortex and Pulvinar

How do humans learn from raw sensory experience? Throughout life, but most obviously in infancy, we learn without explicit instruction. We propose a detailed biological mechanism for the widely embraced idea that learning is driven by the differences between predictions and actual outcomes (i.e., predictive error-driven learning). Specifically, numerous weak projections into the pulvinar nucleus of the thalamus generate top-down predictions, and sparse driver inputs from lower areas supply the actual outcome, originating in Layer 5 intrinsic bursting neurons. Thus, the outcome representation is only briefly activated, roughly every 100 msec (i.e., 10 Hz, alpha), resulting in a temporal difference error signal, which drives local synaptic changes throughout the neocortex. This results in a biologically plausible form of error backpropagation learning. We implemented these mechanisms in a large-scale model of the visual system and found that the simulated inferotemporal pathway learns to systematically categorize 3-D objects according to invariant shape properties, based solely on predictive learning from raw visual inputs. These categories match human judgments on the same stimuli and are consistent with neural representations in inferotemporal cortex in primates.

Brain Entropy During Aging Through a Free Energy Principle Approach

Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of "the entropic brain hypothesis." In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

Harnessing the Spatial Foundation of Mind in Breaking Vicious Cycles in Anxiety, Insomnia, and Depression: The Future of Virtual Reality Therapy Applications

Mental Illnesses, particularly anxiety, insomnia, and depression often involve vicious cycles which are self-perpetuating and can trap one into a more chronic state. For example in the case of insomnia, sympathetic overactivity, intrusive thoughts, and emotional instability due to sleep loss can perpetuate further sleep loss the next night and so on. In this article, we put forward a perspective on breaking these vicious cycles based on preeminent theories in global and spatial cognition, that the foundation of the conscious mind is a spatial coordinate system. Based on this we discuss the potential and future of virtual reality therapeutic applications which utilize massive virtual spaces along with biofeedback designed to help break perpetual cycles in depression, anxiety, and insomnia. "Massive spaces" are those which are truly expansive such as when looking to the clear night sky. These virtual realities may take the form of a night sky, fantastical cosmic scenes, or other scenes such as mountain tops. We also hope to inspire research into such a spatial foundation of mind, use of perceived massive spaces for therapy, and the integration of biofeedback into virtual therapies.

Pre-stimulus alpha predicts inattentional blindness

Pre- and post-stimulus oscillatory activity between 8 and 12 hertz, referred to as the alpha-band, correlates with conscious visual awareness of stimuli across a variety of psychophysical tasks. Within an EEG-adapted inattentional blindness task, the current study sought to examine whether this relationship holds for conscious awareness of stimuli under conditions of inattentional blindness. Noticing rates of the task-irrelevant unexpected stimulus were correlated with a significant decrease in alpha power over bilateral parietal-occipital areas during the pre-stimulus interval, and a significant decrease in alpha power over parietal-occipital regions in the right hemisphere during the post-stimulus interval. Findings are taken to imply alpha-band neural activity represents a valid correlate of consciousness that is not confounded by task relevancy or the need for report.

Layer and rhythm specificity for predictive routing

An established theoretical model, predictive coding, states that the brain is constantly building models (signifying changing predictions) of the environment. The brain does this by forming predictions and signaling sensory inputs which deviate from predictions (“prediction errors”). Various hypotheses exist about how predictive coding could be implemented in the brain. We recorded neural spiking and oscillations with laminar resolution in a network of cortical areas as monkeys performed a working memory task with changing stimulus predictability. Predictability modulated the patterns of feedforward/feedback flow, cortical layers, and oscillations used to process a visual stimulus. These data support the theory of predictive coding but suggest an alternate model for its neural implementation: predictive routing.

In predictive coding, experience generates predictions that attenuate the feeding forward of predicted stimuli while passing forward unpredicted “errors.” Different models have suggested distinct cortical layers, and rhythms implement predictive coding. We recorded spikes and local field potentials from laminar electrodes in five cortical areas (visual area 4 [V4], lateral intraparietal [LIP], posterior parietal area 7A, frontal eye field [FEF], and prefrontal cortex [PFC]) while monkeys performed a task that modulated visual stimulus predictability. During predictable blocks, there was enhanced alpha (8 to 14 Hz) or beta (15 to 30 Hz) power in all areas during stimulus processing and prestimulus beta (15 to 30 Hz) functional connectivity in deep layers of PFC to the other areas. Unpredictable stimuli were associated with increases in spiking and in gamma-band (40 to 90 Hz) power/connectivity that fed forward up the cortical hierarchy via superficial-layer cortex. Power and spiking modulation by predictability was stimulus specific. Alpha/beta power in LIP, FEF, and PFC inhibited spiking in deep layers of V4. Area 7A uniquely showed increases in high-beta (∼22 to 28 Hz) power/connectivity to unpredictable stimuli. These results motivate a conceptual model, predictive routing. It suggests that predictive coding may be implemented via lower-frequency alpha/beta rhythms that “prepare” pathways processing-predicted inputs by inhibiting feedforward gamma rhythms and associated spiking.

Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations

Neurobehavioral studies in humans have long concentrated on changes in local activity levels during repetitive executions of a task. Spontaneous neural coupling within extended networks has latterly been found to also influence performance. Here, we intend to uncover the underlying mechanisms, the relative importance, and the interaction between spontaneous coupling and task-induced activations. To do so, we recorded two groups of healthy participants (male and female) during rest and while they performed either a visual perception or a motor sequence task. We demonstrate that, for both tasks, stronger activations during the task as well as greater network coupling through spontaneous α rhythms at rest predict performance. However, high performers present an absence of classical task-induced activations and, instead, stronger spontaneous network coupling. Activations were thus a compensation mechanism needed only in subjects with lower spontaneous network interactions. This challenges classical models of neural processing and calls for new strategies in attempts to train and enhance performance.SIGNIFICANCE STATEMENT Our findings challenge the widely accepted notion that task-induced activations are of paramount importance for behavior. This will have an important impact on interpretations of human neurobehavioral research. They further link the widely used techniques of quantifying network communication in the brain with classical neuroscience methods and demonstrate possible ways of how network communication influences human behavior. Traditional training methods attempt to enhance neural activations through task repetitions. Our findings suggest a more efficient neural target for learning: enhancing spontaneous neural interactions. This will be of major interest for a large variety of scientific fields with very broad applications in schools, work, and others.

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in, eg, perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Perceptual variability may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients (N = 20), synesthetes (N = 20), and controls (N = 26). Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors-introduced during the hysteresis experiment-lowered thresholds but did not normalize perception. Our results imply that perceptual variability might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.

Transition From Sublexical to Lexico-Semantic Stimulus Processing

Resembling letter-by-letter translation, Morse code can be used to investigate various linguistic components by slowing down the cognitive process of language decoding. Using fMRI and Morse code, we investigated patterns of brain activation associated with decoding three-letter words or non-words and making a lexical decision. Our data suggest that early sublexical processing is associated with activation in brain regions that are involved in sound-patterns to phoneme conversion (inferior parietal lobule), phonological output buffer (inferior frontal cortex: pars opercularis) as well as phonological and semantic top-down predictions (inferior frontal cortex: pars triangularis). In addition, later lexico-semantic processing of meaningful stimuli is associated with activation of the phonological lexicon (angular gyrus) and the semantic system (default mode network). Overall, our data indicate that sublexical and lexico-semantic analyses comprise two cognitive processes that rely on neighboring networks in the left frontal cortex and parietal lobule.

Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state

Understanding why identical stimuli give differing neuronal responses and percepts is a central challenge in research on attention and consciousness. Ongoing oscillations reflect functional states that bias processing of incoming signals through amplitude and phase. It is not known, however, whether the effect of phase or amplitude on stimulus processing depends on the long-term global dynamics of the networks generating the oscillations. Here, we show, using a computational model, that the ability of networks to regulate stimulus response based on pre-stimulus activity requires near-critical dynamics-a dynamical state that emerges from networks with balanced excitation and inhibition, and that is characterized by scale-free fluctuations. We also find that networks exhibiting critical oscillations produce differing responses to the largest range of stimulus intensities. Thus, the brain may bring its dynamics close to the critical state whenever such network versatility is required.

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.

Shared Physiological Correlates of Multisensory and Expectation-Based Facilitation

Perceptual performance in a visual task can be enhanced by simultaneous multisensory information, but can also be enhanced by a symbolic or amodal cue inducing a specific expectation. That similar benefits can arise from multisensory information and within-modality expectation raises the question of whether the underlying neurophysiological processes are the same or distinct. We investigated this by comparing the influence of the following three types of auxiliary probabilistic cues on visual motion discrimination in humans: (1) acoustic motion, (2) a premotion visual symbolic cue, and (3) a postmotion symbolic cue. Using multivariate analysis of the EEG data, we show that both the multisensory and preceding visual symbolic cue enhance the encoding of visual motion direction as reflected by cerebral activity arising from occipital regions ∼200–400 ms post-stimulus onset. This suggests a common or overlapping physiological correlate of cross-modal and intramodal auxiliary information, pointing to a neural mechanism susceptive to both multisensory and more abstract probabilistic cues. We also asked how prestimulus activity shapes the cue–stimulus combination and found a differential influence on the cross-modal and intramodal combination: while alpha power modulated the relative weight of visual motion and the acoustic cue, it did not modulate the behavioral influence of a visual symbolic cue, pointing to differences in how prestimulus activity shapes the combination of multisensory and abstract cues with task-relevant information.

Cortical functional connectivity indexes arousal state during sleep and anesthesia

Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five adult neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index, wPLI) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S), and unresponsive (U)]. Analysis of alpha-band connectivity indicated a transition boundary distinguishing states of maintained and reduced conscious experience in both sleep and anesthesia. In wake states WS and WA, alpha-band wPLI within the temporal lobe was dominant. This pattern was largely unchanged in N1, REM, and S. Transitions into states of reduced consciousness N2, N3, and U were characterized by dramatic changes in connectivity, with dominant connections shifting to prefrontal cortex. Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.

Neural Control of Emotional Actions in Response to Affective Vocalizations

Social-emotional cues, such as affective vocalizations and emotional faces, automatically elicit emotional action tendencies. Adaptive social-emotional behavior depends on the ability to control these automatic action tendencies. It remains unknown whether neural control over automatic action tendencies is supramodal or relies on parallel modality-specific neural circuits. Here, we address this largely unexplored issue in humans. We consider neural circuits supporting emotional action control in response to affective vocalizations, using an approach-avoidance task known to reliably index control over emotional action tendencies elicited by emotional faces. We isolate supramodal neural contributions to emotional action control through a conjunction analysis of control-related neural activity evoked by auditory and visual affective stimuli, the latter from a previously published data set obtained in an independent sample. We show that the anterior pFC (aPFC) supports control of automatic action tendencies in a supramodal manner, that is, triggered by either emotional faces or affective vocalizations. When affective vocalizations are heard and emotional control is required, the aPFC supports control through negative functional connectivity with the posterior insula. When emotional faces are seen and emotional control is required, control relies on the same aPFC territory downregulating the amygdala. The findings provide evidence for a novel mechanism of emotional action control with a hybrid hierarchical architecture, relying on a supramodal node (aPFC) implementing an abstract goal by modulating modality-specific nodes (posterior insula, amygdala) involved in signaling motivational significance of either affective vocalizations or faces.

Perceptual Expectations Modulate Low-Frequency Activity: A Statistical Learning Magnetoencephalography Study

Perceptual expectations can change how a visual stimulus is perceived. Recent studies have shown mixed results in terms of whether expectations modulate sensory representations. Here, we used a statistical learning paradigm to study the temporal characteristics of perceptual expectations. We presented participants with pairs of object images organized in a predictive manner and then recorded their brain activity with magnetoencephalography while they viewed expected and unexpected image pairs on the subsequent day. We observed stronger alpha-band (7-14 Hz) activity in response to unexpected compared with expected object images. Specifically, the alpha-band modulation occurred as early as the onset of the stimuli and was most pronounced in left occipito-temporal cortex. Given that the differential response to expected versus unexpected stimuli occurred in sensory regions early in time, our results suggest that expectations modulate perceptual decision-making by changing the sensory response elicited by the stimuli.

Neural correlates of the DMT experience assessed with multivariate EEG

Studying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT - a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced and neurophenomenological analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience - particularly its eyes-closed visual component. These findings highlight marked changes in oscillatory activity and signal diversity with DMT that parallel broad and specific components of the subjective experience, thus advancing our understanding of the neurobiological underpinnings of immersive states of consciousness.

Transcranial alternating current stimulation of α but not β frequency sharpens multiple visual functions

BACKGROUND

Transcranial alternating current stimulation (tACS) can entrain and enhance cortical oscillatory activity in a frequency-dependent manner. In our previous study (Nakazono et al., 2016), 20 Hz (β) tACS significantly increased excitability of primary motor cortex compared with 10 Hz (α) tACS. α oscillations are a prominent feature of the primary visual cortex (V1) in a resting electroencephalogram. Hence, we investigated whether α and β tACS can differentially influence multiple visual functions.

METHODS

Firstly, we evaluated the after-effects of α and β tACS on pattern-reversal (PR) and focal-flash (FF) visual evoked potentials (VEPs). Secondly, we determined the relationship between resting α oscillations and PR-VEPs modulated by tACS. Thirdly, the behavioral effects of tACS were assessed by contrast sensitivity.

RESULTS

α tACS modulated the amplitudes of PR-VEPs, compared with β tACS, but did not modulate the FF-VEPs. Time-frequency analysis revealed that α tACS facilitated event-related α phase synchronizations without increasing power, which consequently increased the PR-VEP amplitudes. There was a significant positive correlation between PR-VEP amplitudes and resting α oscillations. These findings suggested that α tACS modulated α oscillations, and affected visual functions of contrast and spatial frequency. Indeed, α tACS also improved subjects' contrast sensitivity at the behavioral level. Conversely, β tACS increased posterior α activity, but did not change VEP amplitudes.

CONCLUSIONS

α tACS can influence different neuronal populations from those influenced by β tACS. Thus, our results provide evidence that α tACS sharpens multiple visual functions by modulating α oscillations in V1.

Exploring the role of expectations and stimulus relevance on stimulus-specific neural representations and conscious report

Subjective experience can be influenced by top-down factors, such as expectations and stimulus relevance. Recently, it has been shown that expectations can enhance the likelihood that a stimulus is consciously reported, but the neural mechanisms supporting this enhancement are still unclear. We manipulated stimulus expectations within the attentional blink (AB) paradigm using letters and combined visual psychophysics with magnetoencephalographic (MEG) recordings to investigate whether prior expectations may enhance conscious access by sharpening stimulus-specific neural representations. We further explored how stimulus-specific neural activity patterns are affected by the factors expectation, stimulus relevance and conscious report. First, we show that valid expectations about the identity of an upcoming stimulus increase the likelihood that it is consciously reported. Second, using a series of multivariate decoding analyses, we show that the identity of letters presented in and out of the AB can be reliably decoded from MEG data. Third, we show that early sensory stimulus-specific neural representations are similar for reported and missed target letters in the AB task (active report required) and an oddball task in which the letter was clearly presented but its identity was task-irrelevant. However, later sustained and stable stimulus-specific representations were uniquely observed when target letters were consciously reported (decision-dependent signal). Fourth, we show that global pre-stimulus neural activity biased perceptual decisions for a ‘seen’ response. Fifth and last, no evidence was obtained for the sharpening of sensory representations by top-down expectations. We discuss these findings in light of emerging models of perception and conscious report highlighting the role of expectations and stimulus relevance.

Prestimulus feedback connectivity biases the content of visual experiences

Ongoing fluctuations in neural excitability and in networkwide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms-that is, whether or not an object is perceived. Here, we investigated the impact of prestimulus neural fluctuations on the content of perception-that is, whether one or another object is perceived. We recorded neural activity with magnetoencephalography (MEG) before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation in each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the poststimulus period. Applying source localization to the classifier weights suggested early recruitment of primary visual cortex (V1) and ∼160-ms recruitment of the category-sensitive fusiform face area (FFA). These poststimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs. vase reports. In prestimulus intervals, we found no differences in oscillatory power between face vs. vase reports in V1 or in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA before face reports for low-frequency oscillations. Specifically, the strength of prestimulus feedback connectivity (i.e., Granger causality) from FFA to V1 predicted not only the category of the upcoming percept but also the strength of poststimulus neural activity associated with the percept. Our work shows that prestimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.

Aberrant occipital dynamics differentiate HIV-infected patients with and without cognitive impairment

Combination antiretroviral therapies have revolutionized the treatment of HIV infection, and many patients now enjoy a lifespan equal to that of the general population. However, HIV-associated neurocognitive disorders (HAND) remain a major health concern, with between 30% and 70% of all HIV-infected patients developing cognitive impairments during their life time. One important feature of HAND is visuo-perceptual deficits, but the systems-level neural dynamics underlying these impairments are poorly understood. In the current study, we use magnetoencephalography and advanced time series analyses to examine these neural dynamics during a visuospatial processing task in a group of HIV-infected patients without HAND (n = 25), patients with HAND (n = 18), and a group of demographically-matched uninfected controls (n = 24). All participants completed a thorough neuropsychological assessment, and underwent magnetoencephalography and structural MRI protocols. In agreement with previous studies, patients with HAND performed significantly worse than HIV-infected patients without HAND and controls on the cognitive task, in terms of increased reaction time and decreased accuracy. Our magnetoencephalography results demonstrated that both spontaneous and neural oscillatory activity within the occipital cortices were affected by HIV infection, and that these patterns predicted behavioural performance (i.e. accuracy) on the task. Specifically, spontaneous neural activity in the alpha (8–16 Hz) and gamma (52–70 Hz) bands during the prestimulus baseline period, as well as oscillatory theta responses (4–8 Hz) during task performance were aberrant in HIV-infected patients, with both spontaneous alpha and oscillatory theta activity significantly predicting accuracy on the task and neuropsychological performance outside of the magnetoencephalography scanner. Importantly, these rhythmic patterns of population-level neural activity also distinguished patients by HAND status, such that spontaneous alpha activity in patients with HAND was elevated relative to HIV-infected patients without HAND and controls. In contrast, HIV-infected patients with and without HAND had increased spontaneous gamma compared to controls. Finally, there was a stepwise decrease in oscillatory theta activity as a function of disease severity, such that the response diminished from controls to patients without HAND to patients with HAND. Interestingly, the strength of the relationship between this theta response and accuracy also dissociated patient groups in a similar manner (controls > HIV with no HAND > HIV with HAND), indicating a reduced coupling between neurophysiology and behaviour in HIV-infected patients. This study provides the first neuroimaging evidence of a dissociation between HIV-infected patients with and without HAND, and these findings shed new light on the neural bases of cognitive impairment in HIV infection.