Alpha-Band Oscillations Enable Spatially and Temporally Resolved Tracking of Covert Spatial Attention

Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data

Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.

EEG decoding reveals task-dependent recoding of sensory information in working memory

Working memory (WM) supports future behavior by retaining perceptual information obtained in the recent past. The present study tested the hypothesis that WM recodes sensory information in a format that better supports behavioral goals. We recorded EEG while participants performed color delayed-estimation tasks where the colorwheel for the response was either randomly rotated or held fixed across trials. Accordingly, observers had to remember the exact colors in the Rotation condition, whereas they could prepare for a response based on the fixed mapping between the colors and their corresponding locations on the colorwheel in the No-Rotation condition. Results showed that the color reports were faster and more precise in the No-Rotation condition even when exactly the same set of colors were tested in both conditions. To investigate how the color information was maintained in the brain, we decoded the color using a multivariate EEG classification method. The decoding was limited to the stimulus encoding period in the Rotation condition, whereas it continued to be significant during the maintenance period in the No-Rotation condition, indicating that the color information was actively maintained in the condition. Follow-up analyses suggested that the prolonged decoding was not merely driven by the covert shift of attention but rather by the recoding of sensory information into an action-oriented response format. Together, these results provide converging evidence that WM flexibly recodes sensory information depending on the specific task context to optimize subsequent behavioral performance.

Discriminating orientation information with phase consistency in alpha and low-gamma frequency bands: an EEG study

Recent studies suggest that noninvasive imaging methods (EEG, MEG) in the human brain scalp can decode the content of visual features information (orientation, color, motion, etc.) in Visual-Working Memory (VWM). Previous work demonstrated that with the sustained low-frequency Event-Related Potential (ERP under 6 Hz) of scalp EEG distributions, it is possible to accurately decode the content of orientation information in VWM during the delay interval. In addition, previous studies showed that the raw data captured by a combination of the occi-parietal electrodes could be used to decode the orientation. However, it is unclear whether the orientation information is available in other frequency bands (higher than 6 Hz) or whether this information is feasible with fewer electrodes. Furthermore, the exploration of orientation information in the phase values of the signal has not been well-addressed. In this study, we propose that orientation information is also accessible through the phase consistency of the occipital region in the alpha band frequency. Our results reveal a significant difference between orientations within 200 ms after stimulus offset in early visual sensory processing, with no apparent effect in power and Event-Related Oscillation (ERO) during this period. Additionally, in later periods (420-500 ms after stimulus offset), a noticeable difference is observed in the phase consistency of low gamma-band activity in the occipital area. Importantly, our findings suggest that phase consistency between trials of the orientation feature in the occipital alpha and low gamma-band can serve as a measure to obtain orientation information in VWM. Furthermore, the study demonstrates that phase consistency in the alpha and low gamma band can reflect the distribution of orientation-selective neuron numbers in the four main orientations in the occipital area.

Dynamic alpha power modulations and slow negative potentials track natural shifts of spatio-temporal attention

Alpha power modulations and slow negative potentials have previously been associated with anticipatory processes in spatial and temporal top-down attention. In typical experimental designs, however, neural responses triggered by transient stimulus onsets can interfere with attention-driven activity patterns and our interpretation of such. Here, we investigated these signatures of spatio-temporal attention in a dynamic paradigm free from potentially confounding stimulus-driven activity using electroencephalography. Participants attended the cued side of a bilateral stimulus rotation and mentally counted how often one of two remembered sample orientations (i.e., the target) was displayed while ignoring the uncued side and non-target orientation. Afterwards, participants performed a delayed match-to-sample task, in which they indicated if the orientation of a probe stimulus matched the corresponding sample orientation (previously target or non-target). We observed dynamic alpha power reductions and slow negative waves around task-relevant points in space and time (i.e., onset of the target orientation in the cued hemifield) over posterior electrodes contralateral to the locus of attention. In contrast to static alpha power lateralization, these dynamic signatures correlated with subsequent memory performance (primarily detriments for matching probes of the non-target orientation), suggesting a preferential allocation of attention to task-relevant locations and time points at the expense of reduced resources and impaired performance for information outside the current focus of attention. Our findings suggest that humans can naturally and dynamically focus their attention at relevant points in space and time and that such spatio-temporal attention shifts can be reflected by dynamic alpha power modulations and slow negative potentials.

Neural evidence for attentional capture by salient distractors

Salient objects often capture our attention, serving as distractors and hindering our current goals. It remains unclear when and how salient distractors interact with our goals, and our knowledge on the neural mechanisms responsible for attentional capture is limited to a few brain regions recorded from non-human primates. Here we conducted a multivariate analysis on human intracranial signals covering most brain regions and successfully dissociated distractor-specific representations from target-arousal signals in the high-frequency (60-100 Hz) activity. We found that salient distractors were processed rapidly around 220 ms, while target-tuning attention was attenuated simultaneously, supporting initial capture by distractors. Notably, neuronal activity specific to the distractor representation was strongest in the superior and middle temporal gyrus, amygdala and anterior cingulate cortex, while there were smaller contributions from the parietal and frontal cortices. These results provide neural evidence for attentional capture by salient distractors engaging a much larger network than previously appreciated.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

Kir6.2-K ATP channels alter glycolytic flux to modulate cortical activity, arousal, and sleep-wake homeostasis

Metabolism plays an important role in the maintenance of vigilance states (e.g. wake, NREM, and REM). Brain lactate fluctuations are a biomarker of sleep. Increased interstitial fluid (ISF) lactate levels are necessary for arousal and wake-associated behaviors, while decreased ISF lactate is required for sleep. ATP-sensitive potassium (K ATP ) channels couple glucose-lactate metabolism with neuronal excitability. Therefore, we explored how deletion of neuronal K ATP channel activity (Kir6.2-/- mice) affected the relationship between glycolytic flux, neuronal activity, and sleep/wake homeostasis. Kir6.2-/- mice shunt glucose towards glycolysis, reduce neurotransmitter synthesis, dampen cortical EEG activity, and decrease arousal. Kir6.2-/- mice spent more time awake at the onset of the light period due to altered ISF lactate dynamics. Together, we show that Kir6.2-K ATP channels act as metabolic sensors to gate arousal by maintaining the metabolic stability of each vigilance state and providing the metabolic flexibility to transition between states.

Highlights

Glycolytic flux is necessary for neurotransmitter synthesis. In its absence, neuronal activity is compromised causing changes in arousal and vigilance states despite sufficient energy availability. With Kir6.2-K ATP channel deficiency, the ability to both maintain and shift between different vigilance states is compromised due to changes in glucose utilization. Kir6.2-K ATP channels are metabolic sensors under circadian control that gate arousal and sleep/wake transitions.

Alpha-Band Lateralization and Microsaccades Elicited by Exogenous Cues Do Not Track Attentional Orienting

We explore the world by constantly shifting our focus of attention toward salient stimuli and then disengaging from them in search of new ones. The alpha rhythm (8-13 Hz) has been suggested as a pivotal neural substrate of these attentional shifts, due to its local synchronization and desynchronization that suppress irrelevant cortical areas and facilitate relevant areas, a phenomenon called alpha lateralization. Whether alpha lateralization tracks the focus of attention from orienting toward a salient stimulus to disengaging from it is still an open question. We addressed it by leveraging the phenomenon of inhibition of return (IOR), consisting of an initial facilitation in response times (RTs) for stimuli appearing at an exogenously cued location, followed by a suppression of that location. Our behavioral data from human participants showed a typical IOR effect with both early facilitation and subsequent inhibition. In contrast, alpha lateralized in the cued direction after the behavioral facilitation effect and never re-lateralized compatibly with the behavioral inhibition. Furthermore, we analyzed the interaction between alpha lateralization and microsaccades: while alpha was lateralized toward the cued location, microsaccades were mostly oriented away from it. Crucially, the two phenomena showed a significant positive correlation. These results indicate that alpha lateralization reflects primarily the processing of salient stimuli, challenging the view that alpha lateralization is directly involved in exogenous attentional orienting per se. We discuss the relevance of the present findings for an oculomotor account of alpha lateralization as a modulator of cortical excitability in preparation of a saccade.

A lateralized alpha-band marker of the interference of exogenous attention over endogenous attention

Current theories of attention differentiate exogenous from endogenous orienting of visuospatial attention. While both forms of attention orienting engage different functional systems, endogenous and exogenous attention are thought to share resources, as shown by empirical evidence of their functional interactions. The present study aims to uncover the neurobiological basis of how salient events that drive exogenous attention disrupts endogenous attention processes. We hypothesize that interference from exogenous attention over endogenous attention involves alpha-band activity, a neural marker of visuospatial attention. To test this hypothesis, we contrast the effects of endogenous attention across two experimental tasks while we recorded electroencephalography (n = 32, both sexes): a single cueing task where endogenous attention is engaged in isolation, and a double cueing task where endogenous attention is concurrently engaged with exogenous attention. Our results confirm that the concurrent engagement of exogenous attention interferes with endogenous attention processes. We also found that changes in alpha-band activity mediate the relationship between endogenous attention and its effect on task performance, and that the interference of exogenous attention on endogenous attention occurs via the moderation of this indirect effect. Altogether, our results substantiate a model of attention, whereby endogenous and exogenous attentional processes involve the same neurophysiological resources.

SIGNIFICANCE STATEMENT

Scientists differentiate top-down from bottom-up visuospatial attention processes. While bottom-up attention is rapidly engaged by emerging demands from the environment, top-down attention in contrast reflects slow voluntary shifts of spatial attention. Several lines of research substantiate the idea that top-down and bottom-up attentional processes involve distinct functional systems. An increasing number of studies, however, argue that both attention systems share brain processing resources. The current study examines how salient visual events that engage bottom-up processes interfere with top-down attentional processes. Using neurophysiological recordings and multivariate pattern classification techniques, the authors show that these patterns of interference occur within the alpha-band of neural activity (8-12 Hz), which implies that bottom-up and top-down attention processes share this narrow-band frequency brain resource. The results further demonstrate that patterns of alpha-band activity explains, in part, the interference between top-down and bottom-up attention at the behavioral level.

Just a phase? Causal probing reveals spurious phasic dependence of sustained attention

For over a decade, electrophysiological studies have reported correlations between attention / perception and the phase of spontaneous brain oscillations. To date, these findings have been interpreted as evidence that the brain uses neural oscillations to sample and predict upcoming stimuli. Yet, evidence from simulations have shown that analysis artefacts could also lead to spurious pre-stimulus oscillations that appear to predict future brain responses. To address this discrepancy, we conducted an experiment in which visual stimuli were presented in time to specific phases of spontaneous alpha and theta oscillations. This allowed us to causally probe the role of ongoing neural activity in visual processing independent of the stimulus-evoked dynamics. Our findings did not support a causal link between spontaneous alpha / theta rhythms and behaviour. However, spurious correlations between theta phase and behaviour emerged offline using gold-standard time-frequency analyses. These findings are a reminder that care should be taken when inferring causal relationships between neural activity and behaviour using acausal analysis methods.

The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency-based Mechanism

It is well established that attention can be sharpened through the process of statistical learning (e.g., visual search becomes faster when targets appear at high-relative-to-low probability locations). Although this process of statistically learned attentional enhancement differs behaviorally from the well-studied top-down and bottom-up forms of attention, relatively little work has been done to characterize the electrophysiological correlates of statistically learned attentional enhancement. It thus remains unclear whether statistically learned enhancement recruits any of the same cognitive mechanisms as top-down or bottom-up attention. In the current study, EEG data were collected while participants searched for an ambiguous unique shape in a visual array (the additional singleton task). Unbeknownst to the participants, targets appeared more frequently in one location in space (probability cuing). Encephalographic data were then analyzed in two phases: an anticipatory phase and a reactive phase. In the anticipatory phase preceding search stimuli onset, alpha lateralization as well as the Anterior Directing Attention Negativity and Late Directing Attention Positivity components-signs of preparatory attention known to characterize top-down enhancement-were tested. In the reactive phase, the N2pc component-a well-studied marker of target processing-was examined following stimuli onset. Our results showed that statistically learned attentional enhancement is not characterized by any of the well-known anticipatory markers of top-down attention; yet targets at high probability locations did reliably evoke larger N2pc amplitudes, a finding that is associated with bottom-up attention and saliency. Overall, our findings are consistent with the notion that statistically learned attentional enhancement increases the perceptual salience of items appearing at high-probability locations relative to low-probability locations.

Visual short-term memory-related EEG components in a virtual reality setup

Virtual reality (VR) offers a powerful tool for investigating cognitive processes, as it allows researchers to gauge behaviors and mental states in complex, yet highly controlled, scenarios. The use of VR head-mounted displays in combination with physiological measures such as EEG presents new challenges and raises the question whether established findings also generalize to a VR setup. Here, we used a VR headset to assess the spatial constraints underlying two well-established EEG correlates of visual short-term memory: the amplitude of the contralateral delay activity (CDA) and the lateralization of induced alpha power during memory retention. We tested observers' visual memory in a change detection task with bilateral stimulus arrays of either two or four items while varying the horizontal eccentricity of the memory arrays (4, 9, or 14 degrees of visual angle). The CDA amplitude differed between high and low memory load at the two smaller eccentricities, but not at the largest eccentricity. Neither memory load nor eccentricity significantly influenced the observed alpha lateralization. We further fitted time-resolved spatial filters to decode memory load from the event-related potential as well as from its time-frequency decomposition. Classification performance during the retention interval was above-chance level for both approaches and did not vary significantly across eccentricities. We conclude that commercial VR hardware can be utilized to study the CDA and lateralized alpha power, and we provide caveats for future studies targeting these EEG markers of visual memory in a VR setup.

Technical and clinical considerations for electroencephalography-based biomarkers for major depressive disorder

Major depressive disorder (MDD) is a prevalent and debilitating psychiatric disease that leads to substantial loss of quality of life. There has been little progress in developing new MDD therapeutics due to a poor understanding of disease heterogeneity and individuals' responses to treatments. Electroencephalography (EEG) is poised to improve this, owing to the ease of large-scale data collection and the advancement of computational methods to address artifacts. This review summarizes the viability of EEG for developing brain-based biomarkers in MDD. We examine the properties of well-established EEG preprocessing pipelines and consider factors leading to the discovery of sensitive and reliable biomarkers.

Dissociable Neural Mechanisms Underlie the Effects of Attention on Visual Appearance and Response Bias

A prominent theoretical framework spanning philosophy, psychology, and neuroscience holds that selective attention penetrates early stages of perceptual processing to alter the subjective visual experience of behaviorally relevant stimuli. For example, searching for a red apple at the grocery store might make the relevant color appear brighter and more saturated compared with seeing the exact same red apple while searching for a yellow banana. In contrast, recent proposals argue that data supporting attention-related changes in appearance reflect decision- and motor-level response biases without concurrent changes in perceptual experience. Here, we tested these accounts by evaluating attentional modulations of EEG responses recorded from male and female human subjects while they compared the perceived contrast of attended and unattended visual stimuli rendered at different levels of physical contrast. We found that attention enhanced the amplitude of the P1 component, an early evoked potential measured over visual cortex. A linking model based on signal detection theory suggests that response gain modulations of the P1 component track attention-induced changes in perceived contrast as measured with behavior. In contrast, attentional cues induced changes in the baseline amplitude of posterior alpha band oscillations (∼9-12 Hz), an effect that best accounts for cue-induced response biases, particularly when no stimuli are presented or when competing stimuli are similar and decisional uncertainty is high. The observation of dissociable neural markers that are linked to changes in subjective appearance and response bias supports a more unified theoretical account and demonstrates an approach to isolate subjective aspects of selective information processing.SIGNIFICANCE STATEMENT Does attention alter visual appearance, or does it simply induce response bias? In the present study, we examined these competing accounts using EEG and linking models based on signal detection theory. We found that response gain modulations of the visually evoked P1 component best accounted for attention-induced changes in visual appearance. In contrast, cue-induced baseline shifts in alpha band activity better explained response biases. Together, these results suggest that attention concurrently impacts visual appearance and response bias, and that these processes can be experimentally isolated.

Using occipital ⍺-bursts to modulate behavior in real-time

Pre-stimulus endogenous neural activity can influence the processing of upcoming sensory input and subsequent behavioral reactions. Despite it is known that spontaneous oscillatory activity mostly appears in stochastic bursts, typical approaches based on trial averaging fail to capture this. We aimed at relating spontaneous oscillatory bursts in the alpha band (8-13 Hz) to visual detection behavior, via an electroencephalography-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time. According to alpha theories, we hypothesized that visual targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts (low alpha activity) should lead to faster responses and higher false alarm rates. Our findings support the role of bursts of alpha oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioral theories.

Distinct roles of theta and alpha oscillations in the process of contingent attentional capture

Introduction

Visual spatial attention can be captured by a salient color singleton that is contingent on the target feature. A previous study reported that theta (4-7 Hz) and alpha (8-14 Hz) oscillations were related to contingent attentional capture, but the corresponding attentional mechanisms of these oscillations remain unclear.

Methods

In this study, we analyzed the electroencephalogram data of our previous study to investigate the roles of capture-related theta and alpha oscillation activities. Different from the previous study that used color-changed placeholders as irrelevant cues, the present study adopted abrupt onsets of color singleton cues which tend to elicit phase-locked neural activities. In Experiment 1, participants completed a peripheral visual search task in which spatially uninformative color singleton cues were inside the spatial attentional window and a central rapid serial visual presentation (RSVP) task in which the same cues were outside the spatial attentional window. In Experiment 2, participants completed a color RSVP task and a size RSVP task in which the peripheral color singleton cues were contingent and not contingent on target feature, respectively.

Results

In Experiment 1, spatially uninformative color singleton cues elicited lateralized theta activities when they were contingent on target feature, irrespective of whether they were inside or outside the spatial attentional window. In contrast, the same color singleton cues elicited alpha lateralization only when they were inside the spatial attentional window. In Experiment 2, we further found that theta lateralization vanished if the color singleton cues were not contingent on target feature.

Discussion

These results suggest distinct roles of theta and alpha oscillations in the process of contingent attentional capture initiated by abrupt onsets of singleton cues. Theta activities may reflect global enhancement of target feature, while alpha activities may be related to attentional engagement to spatially relevant singleton cues. These lateralized neural oscillations, together with the distractor-elicited N2pc component, might consist of multiple stages of attentional processes during contingent attentional capture.

Pinging the brain to reveal the hidden attentional priority map using encephalography

Attention has been usefully thought of as organized in priority maps - putative maps of space where attentional priority is weighted across spatial regions in a winner-take-all competition for attentional deployment. Recent work has highlighted the influence of past experiences on the weighting of spatial priority - called selection history. Aside from being distinct from more well-studied, top-down forms of attentional enhancement, little is known about the neural substrates of history-mediated attentional priority. Using a task known to induce statistical learning of target distributions, in an EEG study we demonstrate that this otherwise invisible, latent attentional priority map can be visualized during the intertrial period using a 'pinging' technique in conjunction with multivariate pattern analyses. Our findings not only offer a method of visualizing the history-mediated attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behavior.

Visual Information Is Predictively Encoded in Occipital Alpha/Low-Beta Oscillations

Hierarchical predictive coding networks are a general model of sensory processing in the brain. Under neural delays, these networks have been suggested to naturally generate oscillatory activity in approximately the α frequency range (∼8-12 Hz). This suggests that α oscillations, a prominent feature of EEG recordings, may be a spectral "fingerprint" of predictive sensory processing. Here, we probed this possibility by investigating whether oscillations over the visual cortex predictively encode visual information. Specifically, we examined whether their power carries information about the position of a moving stimulus, in a temporally predictive fashion. In two experiments (N = 32, 18 female; N = 34, 17 female), participants viewed an apparent-motion stimulus moving along a circular path while EEG was recorded. To investigate the encoding of stimulus-position information, we developed a method of deriving probabilistic spatial maps from oscillatory power estimates. With this method, we demonstrate that it is possible to reconstruct the trajectory of a moving stimulus from α/low-β oscillations, tracking its position even across unexpected motion reversals. We also show that future position representations are activated in the absence of direct visual input, demonstrating that temporally predictive mechanisms manifest in α/β band oscillations. In a second experiment, we replicate these findings and show that the encoding of information in this range is not driven by visual entrainment. By demonstrating that occipital α/β oscillations carry stimulus-related information, in a temporally predictive fashion, we provide empirical evidence of these rhythms as a spectral "fingerprint" of hierarchical predictive processing in the human visual system.SIGNIFICANCE STATEMENT "Hierarchical predictive coding" is a general model of sensory information processing in the brain. When in silico predictive coding models are constrained by neural transmission delays, their activity naturally oscillates in roughly the α range (∼8-12 Hz). Using time-resolved EEG decoding, we show that neural rhythms in this approximate range (α/low-β) over the human visual cortex predictively encode the position of a moving stimulus. From the amplitude of these oscillations, we are able to reconstruct the stimulus' trajectory, revealing signatures of temporally predictive processing. This provides direct neural evidence linking occipital α/β rhythms to predictive visual processing, supporting the emerging view of such oscillations as a potential spectral "fingerprint" of hierarchical predictive processing in the human visual system.

Precise Spatial Tuning of Visually Driven Alpha Oscillations in Human Visual Cortex

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across occipital cortex, reflecting general cognitive states such as arousal and alertness. However, there is also evidence that modulation of alpha oscillations in visual cortex can be spatially specific. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We separated the alpha oscillatory power from broadband power changes. The variation in alpha oscillatory power with stimulus position was then fit by a population receptive field (pRF) model. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power (70-180 Hz), but are several times larger. The results demonstrate that alpha suppression in human visual cortex can be precisely tuned. Finally, we show how the pattern of alpha responses can explain several features of exogenous visual attention.

Significance Statement

The alpha oscillation is the largest electrical signal generated by the human brain. An important question in systems neuroscience is the degree to which this oscillation reflects system-wide states and behaviors such as arousal, alertness, and attention, versus much more specific functions in the routing and processing of information. We examined alpha oscillations at high spatial precision in human patients with intracranial electrodes implanted over visual cortex. We discovered a surprisingly high spatial specificity of visually driven alpha oscillations, which we quantified with receptive field models. We further use our discoveries about properties of the alpha response to show a link between these oscillations and the spread of visual attention.

Tracking drivers' minds: Continuous evaluation of mental load and cognitive processing in a realistic driving simulator scenario by means of the EEG

Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states.

Dynamic neural reconstructions of attended object location and features using EEG

Attention allows us to select relevant and ignore irrelevant information from our complex environments. What happens when attention shifts from one item to another? To answer this question, it is critical to have tools that accurately recover neural representations of both feature and location information with high temporal resolution. In the present study, we used human electroencephalography (EEG) and machine learning to explore how neural representations of object features and locations update across dynamic shifts of attention. We demonstrate that EEG can be used to create simultaneous time courses of neural representations of attended features (time point-by-time point inverted encoding model reconstructions) and attended location (time point-by-time point decoding) during both stable periods and across dynamic shifts of attention. Each trial presented two oriented gratings that flickered at the same frequency but had different orientations; participants were cued to attend one of them and on half of trials received a shift cue midtrial. We trained models on a stable period from Hold attention trials and then reconstructed/decoded the attended orientation/location at each time point on Shift attention trials. Our results showed that both feature reconstruction and location decoding dynamically track the shift of attention and that there may be time points during the shifting of attention when 1) feature and location representations become uncoupled and 2) both the previously attended and currently attended orientations are represented with roughly equal strength. The results offer insight into our understanding of attentional shifts, and the noninvasive techniques developed in the present study lend themselves well to a wide variety of future applications.NEW & NOTEWORTHY We used human EEG and machine learning to reconstruct neural response profiles during dynamic shifts of attention. Specifically, we demonstrated that we could simultaneously read out both location and feature information from an attended item in a multistimulus display. Moreover, we examined how that readout evolves over time during the dynamic process of attentional shifts. These results provide insight into our understanding of attention, and this technique carries substantial potential for versatile extensions and applications.

Eye movements disrupt EEG alpha-band coding of behaviorally relevant and irrelevant spatial locations held in working memory

Oscillations in the alpha frequency band (∼8-12 Hz) of the human electroencephalogram play an important role in supporting selective attention to visual items and maintaining their spatial locations in working memory (WM). Recent findings suggest that spatial information maintained in alpha is modulated by interruptions to continuous visual input, such that attention shifts, eye closure, and backward masking of the encoded item cause reconstructed representations of remembered locations to become degraded. Here, we investigated how another common visual disruption-eye movements-modulates reconstructions of behaviorally relevant and irrelevant item locations held in WM. Participants completed a delayed estimation task, where they encoded and recalled either the location or color of an object after a brief retention period. During retention, participants either fixated at the center or executed a sequence of eye movements. Electroencephalography (EEG) was recorded at the scalp and eye position was monitored with an eye tracker. Inverted encoding modeling (IEM) was applied to reconstruct location-selective responses across multiple frequency bands during encoding and retention. Location-selective responses were successfully reconstructed from alpha activity during retention where participants fixated at the center, but these reconstructions were disrupted during eye movements. Recall performance decreased during eye-movements conditions but remained largely intact, and further analyses revealed that under specific task conditions, it was possible to reconstruct retained location information from lower frequency bands (1-4 Hz) during eye movements. These results suggest that eye movements disrupt maintained spatial information in alpha in a manner consistent with other acute interruptions to continuous visual input, but this information may be represented in other frequency bands.NEW & NOTEWORTHY Neural oscillations in the alpha frequency band support selective attention to visual items and maintenance of their spatial locations in human working memory. Here, we investigate how eye movements disrupt representations of item locations held in working memory. Although it was not possible to recover item locations from alpha during eye movements, retained location information could be recovered from select lower frequency bands. This suggests that during eye movements, stored spatial information may be represented in other frequencies.

Hierarchy of Intra- and Cross-modal Redundancy Gains in Visuo-tactile Search: Evidence from the Posterior Contralateral Negativity

Redundant combination of target features from separable dimensions can expedite visual search. The dimension-weighting account explains these "redundancy gains" by assuming that the attention-guiding priority map integrates the feature-contrast signals generated by targets within the respective dimensions. The present study investigated whether this hierarchical architecture is sufficient to explain the gains accruing from redundant targets defined by features in different modalities, or whether an additional level of modality-specific priority coding is necessary, as postulated by the modality-weighting account (MWA). To address this, we had observers perform a visuo-tactile search task in which targets popped out by a visual feature (color or shape) or a tactile feature (vibro-tactile frequency) as well as any combination of these features. The RT gains turned out larger for visuo-tactile versus visual redundant targets, as predicted by the MWA. In addition, we analyzed two lateralized event-related EEG components: the posterior (PCN) and central (CCN) contralateral negativities, which are associated with visual and tactile attentional selection, respectively. The CCN proved to be a stable somatosensory component, unaffected by cross-modal redundancies. In contrast, the PCN was sensitive to cross-modal redundancies, evidenced by earlier onsets and higher amplitudes, which could not be explained by linear superposition of the earlier CCN onto the later PCN. Moreover, linear mixed-effect modeling of the PCN amplitude and timing parameters accounted for approximately 25% of the behavioral RT variance. Together, these behavioral and PCN effects support the hierarchy of priority-signal computation assumed by the MWA.

Suppression of distracting inputs by visual-spatial cues is driven by anticipatory alpha activity

A growing body of research demonstrates that distracting inputs can be proactively suppressed via spatial cues, nonspatial cues, or experience, which are governed by more than one top-down mechanism of attention. However, how the neural mechanisms underlying spatial distractor cues guide proactive suppression of distracting inputs remains unresolved. Here, we recorded electroencephalography signals from 110 participants in 3 experiments to identify the role of alpha activity in proactive distractor suppression induced by spatial cues and its influence on subsequent distractor inhibition. Behaviorally, we found novel changes in the spatial proximity of the distractor: Cueing distractors far away from the target improves search performance for the target, while cueing distractors close to the target hampers performance. Crucially, we found dynamic characteristics of spatial representation for distractor suppression during anticipation. This result was further verified by alpha power increased relatively contralateral to the cued distractor. At both the between- and within-subjects levels, we found that these activities further predicted the decrement of the subsequent PD component, which was indicative of reduced distractor interference. Moreover, anticipatory alpha activity and its link with the subsequent PD component were specific to the high predictive validity of distractor cue. Together, our results reveal the underlying neural mechanisms by which cueing the spatial distractor may contribute to reduced distractor interference. These results also provide evidence supporting the role of alpha activity as gating by proactive suppression.

Long-Range α-Synchronization as Control Signal for BCI: A Feasibility Study

Shifts in spatial attention are associated with variations in α band (α, 8-14 Hz) activity, specifically in interhemispheric imbalance. The underlying mechanism is attributed to local α-synchronization, which regulates local inhibition of neural excitability, and frontoparietal synchronization reflecting long-range communication. The direction-specific nature of this neural correlate brings forward its potential as a control signal in brain-computer interfaces (BCIs). In the present study, we explored whether long-range α-synchronization presents lateralized patterns dependent on voluntary attention orienting and whether these neural patterns can be picked up at a single-trial level to provide a control signal for active BCI. We collected electroencephalography (EEG) data from a cohort of healthy adults (n = 10) while performing a covert visuospatial attention (CVSA) task. The data show a lateralized pattern of α-band phase coupling between frontal and parieto-occipital regions after target presentation, replicating previous findings. This pattern, however, was not evident during the cue-to-target orienting interval, the ideal time window for BCI. Furthermore, decoding the direction of attention trial-by-trial from cue-locked synchronization with support vector machines (SVMs) was at chance level. The present findings suggest EEG may not be capable of detecting long-range α-synchronization in attentional orienting on a single-trial basis and, thus, highlight the limitations of this metric as a reliable signal for BCI control.

Bias of Attentional Oscillations in Individuals with Subthreshold Depression: Evidence from a Pre-Cueing Facial Expression Judgment Task

Background: Study results regarding attentional bias in depressed individuals are inconsistent. Recent studies have found that attention is a discrete process, alternating between periods of either enhanced or diminished attention sensitivity. Whether a visual target can be detected depends on when it occurs relative to these oscillation rhythms. We infer that the inconsistency of attentional bias may be related to the abnormality of attentional oscillations in depressed individuals. Methods: A pre-cueing attentional task was used. We set 48 levels of stimulus onset asynchrony (SOA) between cues and targets and measured the response time (RT) of participants, as well as their EEG signals. Results: The RTs showed patterns of behavioral oscillations. Repeated-measure ANOVA indicated that subthreshold depressed participants had significantly higher RTs for negative expressions than for neutral but significantly lower RTs for positive than for neutral. The frequency analysis indicated that the RT oscillational frequency of subthreshold depressed participants to negative/positive expressions was different from that to neutral. The EEG time-frequency analysis showed that when faced with negative expressions, the intensity of the neural alpha oscillatory power of subthreshold depressed participants was significantly lower than that of normal controls. When faced with positive expressions, the intensity of neural alpha oscillatory power was significantly higher than that of normal controls. Conclusion: Compared to normal persons, subthreshold depressed individuals may have biases in both the amplitude and frequency of attentional oscillations. These attentional biases correspond to the intensity of their neural alpha wave rhythms.

Human circadian rhythm studies: Practical guidelines for inclusion/exclusion criteria and protocol

As interest in circadian rhythms and their effects continues to grow, there is an increasing need to perform circadian studies in humans. Although the constant routine is the gold standard for these studies, there are advantages to performing more naturalistic studies. Here, a review of protocols for such studies is provided along with sample inclusion and exclusion criteria. Sleep routines, drug use, shift work, and menstrual cycle are addressed as screening considerations. Regarding protocol, best practices for measuring melatonin, including light settings, posture, exercise, and dietary habits are described. The inclusion/exclusion recommendations and protocol guidelines are intended to reduce confounding variables in studies that do not involve the constant routine. Given practical limitations, a range of recommendations is provided from stringent to lenient. The scientific rationale behind these recommendations is discussed. However, where the science is equivocal, recommendations are based on empirical decisions made in previous studies. While not all of the recommendations listed may be practical in all research settings and with limited potential participants, the goal is to allow investigators to make well informed decisions about their screening procedures and protocol techniques and to improve rigor and reproducibility, in line with the objectives of the National Institutes of Health.

Information-based multivariate decoding reveals imprecise neural encoding in children with attention deficit hyperactivity disorder during visual selective attention

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-age children. Attentional orientation is a potential clinical diagnostic marker to aid in the early diagnosis of ADHD. However, the underlying pathophysiological substrates of impaired attentional orienting in childhood ADHD remain unclear. Electroencephalography (EEG) was measured in 135 school-age children (70 with childhood ADHD and 65 matched typically developing children) to directly investigate target localization during spatial selective attention through univariate ERP analysis and information-based multivariate pattern machine learning analysis. Compared with children with typical development, a smaller N2pc was found in the ADHD group through univariate ERP analysis. Children with ADHD showed a lower parieto-occipital multivariate decoding accuracy approximately 240-340 ms after visual search onset, which predicts a slower reaction time and larger standard deviation of reaction time. Furthermore, a significant correlation was found between N2pc and decoding accuracy in typically developing children but not in children with ADHD. These observations reveal that impaired attentional orienting in ADHD may be due to inefficient neural encoding responses. By using a personalized information-based multivariate machine learning approach, we have advanced the understanding of cognitive deficits in neurodevelopmental disorders. Our study provides potential research directions for the early diagnosis and optimization of personalized intervention in children with ADHD.

Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches

Vision plays a peculiar role in intelligence. Visual information, forming a large part of the sensory information, is fed into the human brain to formulate various types of cognition and behaviours that make humans become intelligent agents. Recent advances have led to the development of brain-inspired algorithms and models for machine vision. One of the key components of these methods is the utilization of the computational principles underlying biological neurons. Additionally, advanced experimental neuroscience techniques have generated different types of neural signals that carry essential visual information. Thus, there is a high demand for mapping out functional models for reading out visual information from neural signals. Here, we briefly review recent progress on this issue with a focus on how machine learning techniques can help in the development of models for contending various types of neural signals, from fine-scale neural spikes and single-cell calcium imaging to coarse-scale electroencephalography (EEG) and functional magnetic resonance imaging recordings of brain signals.

Wired for sound: The effect of sound on the epileptic brain

Sound waves are all around us resonating at audible and inaudible frequencies. Our ability to hear is crucial in providing information and enabling interaction with our environment. The human brain generates neural oscillations or brainwaves through synchronised electrical impulses. In epilepsy these brainwaves can change and form rhythmic bursts of abnormal activity outwardly appearing as seizures. When two waveforms meet, they can superimpose onto one another forming constructive, destructive or mixed interference. The effects of audible soundwaves on epileptic brainwaves has been largely explored with music. The Mozart Sonata for Two Pianos in D major, K. 448 has been examined in a number of studies where significant clinical and methodological heterogeneity exists. These studies report variable reductions in seizures and interictal epileptiform discharges. Treatment effects of Mozart Piano Sonata in C Major, K.545 and other composer interventions have been examined with some musical exposures, for example Hayden's Symphony No. 94 appearing pro-epileptic. The underlying anti-epileptic mechanism of Mozart music is currently unknown, but interesting research is moving away from dopamine reward system theories to computational analysis of specific auditory parameters. In the last decade several studies have examined inaudible low intensity focused ultrasound as a neuro-modulatory intervention in focal epilepsy. Whilst acute and chronic epilepsy rodent model studies have consistently demonstrated an anti-epileptic treatment effect this is yet to be reported within large scale human trials. Inaudible infrasound is of concern since at present there are no reported studies on the effects of exposure to infrasound on epilepsy. Understanding the impact of infrasound on epilepsy is critical in an era where sustainable energies are likely to increase exposure.

Stress effects on the top-down control of visuospatial attention: Evidence from cue-dependent alpha oscillations

Stress is assumed to inhibit the top-down control of attention and to facilitate bottom-up processing. Evidence from human experiments, however, remains scarce. Previous studies have addressed how stress affects the interplay of bottom-up and top-down mechanisms of attention. A key open question is in how far such effects can actually be attributed to a stress-induced modulation of top-down attention control. We sought to isolate top-down from bottom-up effects by assessing stress effects on anticipatory changes in alpha oscillations that precede stimulus processing. Participants performed in a cued target detection task in which a cue prompted them to covertly shift their attention to left or right screen positions, 20 min after being exposed to the bilateral feet cold pressor test or a warm water control procedure. The stressor led to a substantial increase in cortisol, peaking 20 min post stressor, along with rises in heart rate, blood pressure, and subjective ratings of stress and arousal. As expected, cued attention deployment led to higher alpha power over posterior electrodes contralateral versus ipsilateral to the attended hemifield during the cue-target interval. Importantly, this purely endogenous effect was potentiated by stress, however, significant differences were restricted to the middle of the cue-target interval and thus temporally separated from the appearance of the target. These results indicate that stress does not impair top-down attentional control per se but may introduce a qualitative change modulating the way attention is deployed to meet action goals.

Neuroscience and architecture: Modulating behavior through sensorimotor responses to the built environment

As we move through the world, natural and built environments implicitly guide behavior by appealing to certain sensory and motor dynamics. This process can be motivated by automatic attention to environmental features that resonate with specific sensorimotor responses. This review aims at providing a psychobiological framework describing how environmental features can lead to automated sensorimotor responses through defined neurophysiological mechanisms underlying attention. Through the use of automated processes in subsets of cortical structures, the goal of this framework is to describe on a neuronal level the functional link between the designed environment and sensorimotor responses. By distinguishing between environmental features and sensorimotor responses we elaborate on how automatic behavior employs the environment for sensorimotor adaptation. This is realized through a thalamo-cortical network integrating environmental features with motor aspects of behavior. We highlight the underlying transthalamic transmission from an Enactive and predictive perspective and review recent studies that effectively modulated behavior by systematically manipulating environmental features. We end by suggesting a promising combination of neuroimaging and computational analysis for future studies.

Phasic modulation of visual representations during sustained attention

Sustained attention has long been thought to benefit perception in a continuous fashion, but recent evidence suggests that it affects perception in a discrete, rhythmic way. Periodic fluctuations in behavioral performance over time, and modulations of behavioral performance by the phase of spontaneous oscillatory brain activity point to an attentional sampling rate in the theta or alpha frequency range. We investigated whether such discrete sampling by attention is reflected in periodic fluctuations in the decodability of visual stimulus orientation from magnetoencephalographic (MEG) brain signals. In this exploratory study, human subjects attended one of the two grating stimuli, while MEG was being recorded. We assessed the strength of the visual representation of the attended stimulus using a support vector machine (SVM) to decode the orientation of the grating (clockwise vs. counterclockwise) from the MEG signal. We tested whether decoder performance depended on the theta/alpha phase of local brain activity. While the phase of ongoing activity in the visual cortex did not modulate decoding performance, theta/alpha phase of activity in the frontal eye fields and parietal cortex, contralateral to the attended stimulus did modulate decoding performance. These findings suggest that phasic modulations of visual stimulus representations in the brain are caused by frequency-specific top-down activity in the frontoparietal attention network, though the behavioral relevance of these effects could not be established.

Target-Related Alpha Attenuation in a Brain-Computer Interface Rapid Serial Visual Presentation Calibration

This study evaluated the feasibility of using occipitoparietal alpha activity to drive target/non-target classification in a brain-computer interface (BCI) for communication. EEG data were collected from 12 participants who completed BCI Rapid Serial Visual Presentation (RSVP) calibrations at two different presentation rates: 1 and 4 Hz. Attention-related changes in posterior alpha activity were compared to two event-related potentials (ERPs): N200 and P300. Machine learning approaches evaluated target/non-target classification accuracy using alpha activity. Results indicated significant alpha attenuation following target letters at both 1 and 4 Hz presentation rates, though this effect was significantly reduced in the 4 Hz condition. Target-related alpha attenuation was not correlated with coincident N200 or P300 target effects. Classification using posterior alpha activity was above chance and benefitted from individualized tuning procedures. These findings suggest that target-related posterior alpha attenuation is detectable in a BCI RSVP calibration and that this signal could be leveraged in machine learning algorithms used for RSVP or comparable attention-based BCI paradigms.

Suppression of alpha-band power underlies exogenous attention to emotional distractors

Alpha-band oscillations (8-14 Hz) are essential for attention and perception processes by facilitating the selection of relevant information. Directing visuospatial endogenous (voluntary) attention to a given location consistently results in a power suppression of alpha activity over occipito-parietal areas contralateral to the attended visual field. In contrast, the neural oscillatory dynamics underlying the involuntary capture of attention, or exogenous attention, are currently under debate. By exploiting the inherent capacity of emotionally salient visual stimuli to capture attention, we aimed to investigate whether exogenous attention is characterized by either a reduction or an increase in alpha-band activity. Electroencephalographic activity was recorded while participants completed a Posner visuospatial cueing task, in which a lateralized image with either positive, negative, or neutral emotional content competed with a target stimulus presented in the opposite hemifield. Compared with trials with no distractors, alpha power was reduced over occipital regions contralateral to distracting images. This reduction of alpha activity turned out to be functionally relevant, as it correlated with impaired behavioral performance on the ongoing task and was enhanced for distractors with negative valence. Taken together, our results demonstrate that visuospatial exogenous attention is characterized by a suppression of alpha-band activity contralateral to distractor location, similar to the oscillatory underpinnings of endogenous attention. Further, these results highlight the key role of exogenous attention as an adaptive mechanism for the efficient detection of biologically salient stimuli.

Identification of Lower-Limb Motor Tasks via Brain–Computer Interfaces: A Topical Overview

Recent engineering and neuroscience applications have led to the development of brain–computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy.

Neural correlates of unpredictable Stop and non‐Stop cues in overt and imagined execution

The ability to inhibit incorrect behaviors is crucial for survival. In real contexts, cues that require stopping usually appear intermixed with indications to continue the ongoing action. However, in the classical Stop‐signal task (SST), the unpredictable stimuli are always signals that require inhibition. To understand the neural mechanisms activated by low‐probability nonstop cues, we recorded the electroencephalography from 23 young volunteers while they performed a modified SST where the unpredictable stimuli could be either Stop or confirmatory Go signals (CGo). To isolate the influence of motor output, the SST was performed during overt and covert execution. We found that, paradoxically, CGo stimuli activated motor inhibition processes, and evoked patterns of brain activity similar to those obtained after Stop signals (N2/P3 event‐related potentials and midfrontal theta power increase), though in lesser magnitude. These patterns were also observed during the imagined performance. Finally, applying machine learning procedures, we found that the brain activity evoked after CGo versus Stop signals can be classified above chance during both, overt and imagined execution. Our results provide evidence that unpredictable signals cause motor inhibition even when they require to continue an ongoing action.

This study advances our understanding of the neural correlates of inhibition by using a modified Stop‐signal task where Stop signals were intermixed with cues to continue the ongoing action (CGo signals). CGo signals produced motor inhibition and EEG activity similar to Stop signals (both during overt and imagined performance). The neural activity related to CGo vs Stop signals could be decoded using a machine learning algorithm, indicating that Stop signals evoke a specific pattern of EEG activity.

The influence of the respiratory cycle on reaction times in sensory-cognitive paradigms

Behavioural and electrophysiological studies point to an apparent influence of the state of respiration, i.e., whether we inhale or exhale, on brain activity and cognitive performance. Still, the prevalence and relevance of such respiratory-behavioural relations in typical sensory-cognitive tasks remain unclear. We here used a battery of six tasks probing sensory detection, discrimination and short-term memory to address the questions of whether and by how much behaviour covaries with the respiratory cycle. Our results show that participants tend to align their respiratory cycle to the experimental paradigm, in that they tend to inhale around stimulus presentation and exhale when submitting their responses. Furthermore, their reaction times, but not so much their response accuracy, consistently and significantly covary with the respiratory cycle, differing between inhalation and exhalation. This effect is strongest when analysed contingent on the respiratory state around participants' responses. The respective effect sizes of these respiration-behaviour relations are comparable to those seen in other typical experimental manipulations in sensory-cognitive tasks, highlighting the relevance of these effects. Overall, our results support a prominent relation between respiration and sensory-cognitive function and show that sensation is intricately linked to rhythmic bodily or interoceptive functions.

The Role of Conjunctive Representations in Stopping Actions

Action selection appears to rely on conjunctive representations that nonlinearly integrate task-relevant features. Here, we tested a corollary of this hypothesis: that such representations are also intricately involved during attempts to stop an action-a key aspect of action regulation. We tracked both conjunctive representations and those of constituent rule, stimulus, or response features through trial-by-trial representational similarity analysis of the electroencephalogram signal in a combined rule-selection and stop-signal paradigm. Across two experiments with student participants (N = 57), we found (a) that the strength of decoded conjunctive representations prior to the stop signal uniquely predicted trial-by-trial stopping success (Experiment 1) and (b) that these representations were selectively suppressed following the onset of the stop signal (Experiments 1 and 2). We conclude that conjunctive representations are key to successful action execution and therefore need to be suppressed when an intended action is no longer appropriate.

Neural Dynamics of Context-sensitive Adjustments in Cognitive Flexibility

To adaptively interact with the uncertainties of daily life, we must match our level of cognitive flexibility to situations that place different demands on our ability to focus on the current task while remaining sensitive to cues that signal other, more urgent tasks. Such cognitive-flexibility adjustments in response to changing contextual demands (metaflexibility) have been observed in cued task-switching paradigms, where the performance cost incurred by switching versus repeating tasks (switch cost) scales inversely with the proportion of switches (PS) within a block of trials. However, the neural underpinnings of these adjustments in cognitive flexibility are not well understood. Here, we recorded 64-channel EEG measures of electrical brain activity as participants switched between letter and digit categorization tasks in varying PS contexts, from which we extracted ERPs elicited by the task cue and EEG alpha-power differences during both the cue-to-target interval and the resting precue period. The temporal resolution of EEG/ERPs allowed us to test whether contextual adjustments in cognitive flexibility are mediated by tonic changes in processing mode, or by changes in phasic, task-cue-triggered processes. We observed reliable modulation of behavioral switch cost by PS context that were mirrored in both cue-evoked ERP and time-frequency effects, but not in blockwide precue EEG changes. These results indicate that different levels of cognitive flexibility are instantiated in response to the presentation of task cues, rather than by being maintained as a tonic neural-activity state difference between low- and high-switch contexts.

Diversity in Psychological Research Activities: Quantitative Approach With Topic Modeling

Recent cultural studies have discussed universality and diversity in human behavior using numerous samples investigated worldwide. We aimed to quantitatively extend this discussion to various research activities in psychology in terms of geographic regions and time trends. Most psychology departments have specialists in various fields of psychology. Further, research institutions in all regions typically aim to provide systematic and balanced research education. Nevertheless, most researchers recognize universal features and patterns of diversity in research activities in psychology in terms of regional differences and time trends. However, these arguments remain intuitive and vague, and no studies have conducted quantitative analyses. To this end, we conducted topic modeling for the abstracts of psychological articles with the regions of author affiliations and publication periods as covariates. The results showed that the topic proportions related to basic research were high in North-Central America, whereas those related to clinical research were high in Europe. Interestingly, the regional differences shown by topic modeling were not observed in the frequency analysis of keywords, indicating that topic modeling revealed implicit characteristics. Moreover, we observed an increasing trend of neuroscience topics across publication periods. However, this trend was not valid for the psychology journal Psychological Science. Taken together, our results suggest diversity of geographic regions and periods in research activities in psychology. More importantly, our findings indicate that universality holds neither for human behavior nor research activities on human mental processes.

Alpha suppression indexes a spotlight of visual-spatial attention that can shine on both perceptual and memory representations

Although researchers have been recording the human electroencephalogram (EEG) for almost a century, we still do not completely understand what cognitive processes are measured by the activity of different frequency bands. The 8- to 12-Hz activity in the alpha band has long been a focus of this research, but our understanding of its links to cognitive mechanisms has been rapidly evolving recently. Here, we review and discuss the existing evidence for two competing perspectives about alpha activity. One view proposes that the suppression of alpha-band power following the onset of a stimulus array measures attentional selection. The competing view is that this same activity measures the buffering of the task-relevant representations in working memory. We conclude that alpha-band activity following the presentation of stimuli appears to be due to the operation of an attentional selection mechanism, with characteristics that mirror the classic views of attention as selecting both perceptual inputs and representations already stored in memory.

Decoding subjective emotional arousal from EEG during an immersive virtual reality experience

Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continuous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial patterns and a long short-term memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience.

Sustained Attention and Spatial Attention Distinctly Influence Long-term Memory Encoding

Our attention is critically important for what we remember. Prior measures of the relationship between attention and memory, however, have largely treated "attention" as a monolith. Here, across three experiments, we provide evidence for two dissociable aspects of attention that influence encoding into long-term memory. Using spatial cues together with a sensitive continuous report procedure, we find that long-term memory response error is affected by both trial-by-trial fluctuations of sustained attention and prioritization via covert spatial attention. Furthermore, using multivariate analyses of EEG, we track both sustained attention and spatial attention before stimulus onset. Intriguingly, even during moments of low sustained attention, there is no decline in the representation of the spatially attended location, showing that these two aspects of attention have robust but independent effects on long-term memory encoding. Finally, sustained and spatial attention predicted distinct variance in long-term memory performance across individuals. That is, the relationship between attention and long-term memory suggests a composite model, wherein distinct attentional subcomponents influence encoding into long-term memory. These results point toward a taxonomy of the distinct attentional processes that constrain our memories.

Multi-scale neural decoding and analysis

Objective.

Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment.

Approach.

We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes.

Main results.

We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches.

Significance.

This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.