Endogenous modulation of low frequency oscillations by temporal expectations

Blocked versus interleaved: How range contexts modulate time perception and its EEG signatures

Accurate time perception is a crucial element in a wide range of cognitive tasks, including decision-making, memory, and motor control. One commonly observed phenomenon is that when given a range of time intervals to consider, people's estimates often cluster around the midpoint of those intervals. Previous studies have suggested that the range of these intervals can also influence our judgments, but the neural mechanisms behind this "range effect" are not yet understood. We used both behavioral tests and electroencephalographic (EEG) measures to understand how the range of sample time intervals affects the accuracy of people's subsequent time estimates. Study participants were exposed to two different setups: In the "blocked-range" (BR) session, short and long intervals were presented in separate blocks, whereas in the "interleaved-range" (IR) session, intervals of various lengths were presented randomly. Our findings indicated that the BR context led to more accurate time estimates compared to the IR context. In terms of EEG data, the BR context resulted in quicker buildup of contingent negative variation (CNV), which also reached higher amplitude levels and dissolved more rapidly during the encoding stage. We also observed an enhanced amplitude in the offset P2 component of the EEG signal. Overall, our results suggest that the variability in time intervals, as defined by their range, influences the neural processes that underlie time estimation.

Neuromodulation of inhibitory control using phase-lagged transcranial alternating current stimulation

BACKGROUND

Transcranial alternating current stimulation (tACS) is a prominent non-invasive brain stimulation method for modulating neural oscillations and enhancing human cognitive function. This study aimed to investigate the effects of individualized theta tACS delivered in-phase and out-of-phase between the dorsal anterior cingulate cortex (dACC) and left dorsolateral prefrontal cortex (lDLPFC) during inhibitory control performance.

METHODS

The participants engaged in a Stroop task with phase-lagged theta tACS over individually optimized high-density electrode montages targeting the dACC and lDLPFC. We analyzed task performance, event-related potentials, and prestimulus electroencephalographic theta and alpha power.

RESULTS

We observed significantly reduced reaction times following out-of-phase tACS, accompanied by reduced frontocentral N1 and N2 amplitudes, enhanced parieto-occipital P1 amplitudes, and pronounced frontocentral late sustained potentials. Out-of-phase stimulation also resulted in significantly higher prestimulus frontocentral theta and alpha activity.

CONCLUSIONS

These findings suggest that out-of-phase theta tACS potently modulates top-down inhibitory control, supporting the feasibility of phase-lagged tACS to enhance inhibitory control performance.

Temporal unpredictability increases error monitoring as revealed by EEG-EMG investigation

Reacting in an unpredictable context increases error monitoring as evidenced by greater error-related negativity (ERN), an electrophysiological marker linked to an evaluation of response outcomes. We investigated whether ERN also increased when participants evaluated their responses to events that appeared in unpredictable versus predictable moments in time. We complemented electroencephalographic (EEG) analysis of cortical activity by measuring performance monitoring processes at the peripheral level using electromyography (EMG). Specifically, we used EMG data to quantify how temporal unpredictability would affect motor time (MT), the interval between the onset of muscle activity, and the mechanical response. MT increases following errors, indexing online error detection, and an attempt to stop incorrect actions. In our temporally cued version of the stop-signal task, symbolic cues predicted (temporally predictable condition) or not (temporally unpredictable condition) the onset of a target. In 25% of trials, an auditory signal occurred shortly after the target presentation, informing participants that they should inhibit their response completely. Response times were slower, and fewer inhibitory errors were made during temporally unpredictable than predictable trials, indicating enhanced control of unwanted actions when target onset time was unknown. Importantly, the ERN to inhibitory errors was greater in temporally unpredictable relative to temporally predictable conditions. Similarly, EMG data revealed prolonged MT when reactions to temporally unpredictable targets had not been stopped. Taken together, our results show that a temporally unpredictable environment increases the control of unwanted actions, both at cortical and peripheral levels, suggesting a higher subjective cost of maladaptive responses to temporally uncertain events.

The Feeling of Time Passing Is Associated with Recurrent Sustained Activity and Theta Rhythms Across the Cortex

Introduction: We are constantly estimating how much time has passed, and yet know little about the brain mechanisms through which this process occurs. In this pilot study, we evaluated so-called subjective time estimation with the temporal bisection task, while recording brain activity from electroencephalography (EEG). Methods: Nine adult participants were trained to distinguish between two durations of visual stimuli as either "short" (400 msec) or "long" (1600 msec). They were then presented with stimulus durations in between the long and short stimuli. EEG data from 128 electrodes were examined with a novel analytical method that identifies segments of sustained cortical activity during the task. Results: Participants tended to categorize intermediate durations as "long" more frequently than "short" and were thus experiencing time as moving faster while overestimating the amount of time passing. Their mean bisection point (during which frequency of selecting short vs. long is equal) was closer to the geometric mean of task stimuli (800 msec) rather than the arithmetic mean (1000 msec). In contrast, sustained brain activity occurred closer to the arithmetic mean. The recurrence rate of this activity was highly related to the bisection point, especially when analyzed within naturally occurring theta oscillations (4-8 Hz) (r = -0.90). Discussion: Sustained activity across the cortex within the theta range may reflect temporal durations, whereas its repeated appearance relates to the subjective feeling of time passing.

Knowledge of Threat Biases Perceptual Decision Making in Anxiety: Evidence From Signal Detection Theory and Drift Diffusion Modeling

Background

Threat biases are considered key factors in the development and maintenance of anxiety. However, these biases are poorly operationalized and remain unquantified. Furthermore, it is unclear whether and how prior knowledge of threat and its uncertainty induce these biases and how they manifest in anxiety.

Method

Participants (n = 55) used prestimulus cues to decide whether the subsequently presented stimuli were threatening or neutral. The cues either provided no information about the probability (high uncertainty) or indicated high probability (low uncertainty) of encountering threatening or neutral targets. We used signal detection theory and hierarchical drift diffusion modeling to quantify bias.

Results

High-uncertainty threat cues improved discrimination of subsequent threatening and neutral stimuli more than neutral cues. However, anxiety was associated with worse discrimination of threatening versus neutral stimuli following high-uncertainty threat cues. Using hierarchical drift diffusion modeling, we found that threat cues biased decision making not only by shifting the starting point of evidence accumulation toward the threat decision but also by increasing the efficiency with which sensory evidence was accumulated for both threat-related and neutral decisions. However, higher anxiety was associated with a greater shift of starting point toward the threat decision but not with the efficiency of evidence accumulation.

Conclusions

Using computational modeling, these results highlight the biases by which knowledge regarding uncertain threat improves perceptual decision making but impairs it in case of anxiety.

Spontaneous α Brain Dynamics Track the Episodic "When"

Across species, neurons track time over the course of seconds to minutes, which may feed the sense of time passing. Here, we asked whether neural signatures of time-tracking could be found in humans. Participants stayed quietly awake for a few minutes while being recorded with magnetoencephalography (MEG). They were unaware they would be asked how long the recording lasted (retrospective time) or instructed beforehand to estimate how long it will last (prospective timing). At rest, rhythmic brain activity is nonstationary and displays bursts of activity in the alpha range (α: 7-14 Hz). When participants were not instructed to attend to time, the relative duration of α bursts linearly predicted individuals' retrospective estimates of how long their quiet wakefulness lasted. The relative duration of α bursts was a better predictor than α power or burst amplitude. No other rhythmic or arrhythmic activity predicted retrospective duration. However, when participants timed prospectively, the relative duration of α bursts failed to predict their duration estimates. Consistent with this, the amount of α bursts was discriminant between prospective and retrospective timing. Last, with a control experiment, we demonstrate that the relation between α bursts and retrospective time is preserved even when participants are engaged in a visual counting task. Thus, at the time scale of minutes, we report that the relative time of spontaneous α burstiness predicts conscious retrospective time. We conclude that in the absence of overt attention to time, α bursts embody discrete states of awareness constitutive of episodic timing.SIGNIFICANCE STATEMENT The feeling that time passes is a core component of consciousness and episodic memory. A century ago, brain rhythms called "α" were hypothesized to embody an internal clock. However, rhythmic brain activity is nonstationary and displays on-and-off oscillatory bursts, which would serve irregular ticks to the hypothetical clock. Here, we discovered that in a given lapse of time, the relative bursting time of α rhythms is a good indicator of how much time an individual will report to have elapsed. Remarkably, this relation only holds true when the individual does not attend to time and vanishes when attending to it. Our observations suggest that at the scale of minutes, α brain activity tracks episodic time.

Attention in flux

Selective attention comprises essential infrastructural functions supporting cognition-anticipating, prioritizing, selecting, routing, integrating, and preparing signals to guide adaptive behavior. Most studies have examined its consequences, systems, and mechanisms in a static way, but attention is at the confluence of multiple sources of flux. The world advances, we operate within it, our minds change, and all resulting signals progress through multiple pathways within the dynamic networks of our brains. Our aim in this review is to raise awareness of and interest in three important facets of how timing impacts our understanding of attention. These include the challenges posed to attention by the timing of neural processing and psychological functions, the opportunities conferred to attention by various temporal structures in the environment, and how tracking the time courses of neural and behavioral modulations with continuous measures yields surprising insights into the workings and principles of attention.

Cortical oscillations and interareal synchronization as a preparatory activity for postural response

Neural mechanisms of human standing are expected to be elucidated for preventing fallings. Postural response evoked by sudden external perturbation originates from various areas in the central nervous system. Recent studies have revealed that the corticospinal pathway is one of the key nodes for an appropriate postural response. The corticospinal pathway that mediates the early part of the electromyographic response is modulated with prediction before a perturbation occurs. Temporal prediction explicitly exhibiting an onset timing contributes to enhancing corticospinal excitability. However, how the cortical activities in the sensorimotor area with temporal prediction are processed before the corticospinal pathway enhancement remains unclear. In this study, using electroencephalography, we investigated how temporal prediction affects both neural oscillations and synchronization between sensorimotor and distal areas. Our results revealed that desynchronization of cortical oscillation at α- and β-bands was observed in the sensorimotor and parietooccipital areas (Cz, CPz, Pz and POz), and those are nested in the phase at θ-band frequency. Furthermore, a reduction in the interareal phase synchrony in the α-band was induced after the timing cue for the perturbation onset. The phase synchrony at the low frequency can relay the temporal prediction among the distant areas and initiate the modulation of the local cortical activities. Such modulations contribute to the preparation for sensory processing and motor execution that are necessary for optimal responses.

Anticipation across modalities in children and adults: Relating anticipatory alpha rhythm lateralization, reaction time, and executive function

The development of the ability to anticipate-as manifested by preparatory actions and neural activation related to the expectation of an upcoming stimulus-may play a key role in the ontogeny of cognitive skills more broadly. This preregistered study examined anticipatory brain potentials and behavioral responses (reaction time; RT) to anticipated target stimuli in relation to individual differences in the ability to use goals to direct action (as indexed by measures of executive function; EF). A cross-sectional investigation was conducted in 40 adults (aged 18-25 years) and 40 children (aged 6-8 years) to examine the association of changes in the amplitude of modality-specific alpha-range rhythms in the electroencephalogram (EEG) during anticipation of lateralized visual, tactile, or auditory stimuli with inter- and intraindividual variation in RT and EF. Children and adults exhibited contralateral anticipatory reductions in the mu rhythm and the visual alpha rhythm for tactile and visual anticipation, respectively, indicating modality and spatially specific attention allocation. Variability in within-subject anticipatory alpha lateralization (the difference between contralateral and ipsilateral alpha power) was related to single-trial RT. This relation was more prominent in adults than in children, and was not apparent for auditory stimuli. Multilevel models indicated that interindividual differences in anticipatory mu rhythm lateralization contributed to the significant association with variability in EF, but this was not the case for visual or auditory alpha rhythms. Exploratory microstate analyses were undertaken to cluster global field power (GFP) into a distribution-free temporal analysis examining developmental differences across samples and in relation to RT and EF. Anticipation is suggested as a developmental bridge construct connecting neuroscience, behavior, and cognition, with anticipatory EEG oscillations being discussed as quantifiable and potentially malleable indicators of stimulus prediction.

Neurocognitive analyses reveal that video game players exhibit enhanced implicit temporal processing

Winning in action video games requires to predict timed events in order to react fast enough. In these games, repeated waiting for enemies may help to develop implicit (incidental) preparation mechanisms. We compared action video game players and non-video game players in a reaction time task involving both implicit time preparations and explicit (conscious) temporal attention cues. Participants were immersed in virtual reality and instructed to respond to a visual target appearing at variable delays after a warning signal. In half of the trials, an explicit cue indicated when the target would occur after the warning signal. Behavioral, oculomotor and EEG data consistently indicate that, compared with non-video game players, video game players better prepare in time using implicit mechanisms. This sheds light on the neglected role of implicit timing and related electrophysiological mechanisms in gaming research. The results further suggest that game-based interventions may help remediate implicit timing disorders found in psychiatric populations.

A cross-sectional EEG study reveals that individuals who consistently play action video games exhibit improved performance in a reaction time task involving implicit time preparations, compared with participants who did not normally play video games

A quantitative model reveals a frequency ordering of prediction and prediction-error signals in the human brain

The human brain is proposed to harbor a hierarchical predictive coding neuronal network underlying perception, cognition, and action. In support of this theory, feedforward signals for prediction error have been reported. However, the identification of feedback prediction signals has been elusive due to their causal entanglement with prediction-error signals. Here, we use a quantitative model to decompose these signals in electroencephalography during an auditory task, and identify their spatio-spectral-temporal signatures across two functional hierarchies. Two prediction signals are identified in the period prior to the sensory input: a low-level signal representing the tone-to-tone transition in the high beta frequency band, and a high-level signal for the multi-tone sequence structure in the low beta band. Subsequently, prediction-error signals dependent on the prior predictions are found in the gamma band. Our findings reveal a frequency ordering of prediction signals and their hierarchical interactions with prediction-error signals supporting predictive coding theory.

A computational framework can extract spatio-spectro-temporal neural signatures corresponding to hierarchical prediction and prediction errors in a local-global auditory task.

Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension

Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5-3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., "sheep white grass eat" instead of "white sheep eat grass"), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts.

Endogenous sources of interbrain synchrony in duetting pianists

When people interact with each other, their brains synchronize. However, it remains unclear whether interbrain synchrony (IBS) is functionally relevant for social interaction or stems from exposure of individual brains to identical sensorimotor information. To disentangle these views, the current dual-EEG study investigated amplitude-based IBS in pianists jointly performing duets containing a silent pause followed by a tempo change. First, we manipulated the similarity of the anticipated tempo change and measured IBS during the pause, hence, capturing the alignment of purely endogenous, temporal plans without sound or movement. Notably, right posterior gamma IBS was higher when partners planned similar tempi, it predicted whether partners' tempi matched after the pause, and it was modulated only in real, not in surrogate pairs. Second, we manipulated the familiarity with the partner's actions and measured IBS during joint performance with sound. Although sensorimotor information was similar across conditions, gamma IBS was higher when partners were unfamiliar with each other's part and had to attend more closely to the sound of the performance. These combined findings demonstrate that IBS is not merely an epiphenomenon of shared sensorimotor information but can also hinge on endogenous, cognitive processes crucial for behavioral synchrony and successful social interaction.

Dissociable Roles of Theta and Alpha in Sub-Second and Supra-Second Time Reproduction: An Investigation of their Links to Depression and Anxiety

A growing collection of observations has demonstrated the presence of multiple neural oscillations participating in human temporal cognition and psychiatric pathologies such as depression and anxiety. However, there remains a gap in the literature regarding the specific roles of these neural oscillations during interval timing, and how these oscillatory activities might vary with the different levels of mental health. The current study examined the participation of the frontal midline theta and occipital alpha oscillations, both of which are prevalent cortical oscillatory markers frequently reported in working memory and time perception paradigms. Participants performed a time reproduction task in the sub- (400, 600, 800 ms) and supra-second timescales (1600, 1800, 2000 ms) while undergoing scalp EEG recordings. Anxiety and depression levels were measured via self-report mental health inventories. Time–frequency analysis of scalp EEG revealed that both frontal midline and occipital alpha oscillations were engaged during the encoding of the durations. Furthermore, we observed that the correlational relationship between frontal midline theta power and the reproduction performance in the sub-second range was modulated by state anxiety. In contrast, the correlational relationship between occipital alpha and the reproduction performance of supra-second intervals was modulated by depression and trait anxiety. The results offer insights on how alpha and theta oscillations differentially play a role in interval timing and how mental health further differentially relates these neural oscillations to sub- and supra-second timescales.

The Blursday database as a resource to study subjective temporalities during COVID-19

The COVID-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides repeated measures of subjective time and related processes from participants in nine countries tested on 14 questionnaires and 15 behavioural tasks during the COVID-19 pandemic. A total of 2,840 participants completed at least one task, and 439 participants completed all tasks in the first session. The database and all data collection tools are accessible to researchers for studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception and mindfulness. Blursday includes quantitative statistics such as sleep patterns, personality traits, psychological well-being and lockdown indices. The database provides quantitative insights on the effects of lockdown (stringency and mobility) and subjective confinement on time perception (duration, passage of time and temporal distances). Perceived isolation affects time perception, and we report an inter-individual central tendency effect in retrospective duration estimation.

Implicit Versus Explicit Timing-Separate or Shared Mechanisms?

Time implicitly shapes cognition, but time is also explicitly represented, for instance, in the form of durations. Parsimoniously, the brain could use the same mechanisms for implicit and explicit timing. Yet, the evidence has been equivocal, revealing both joint versus separate signatures of timing. Here, we directly compared implicit and explicit timing using magnetoencephalography, whose temporal resolution allows investigating the different stages of the timing processes. Implicit temporal predictability was induced in an auditory paradigm by a manipulation of the foreperiod. Participants received two consecutive task instructions: discriminate pitch (indirect measure of implicit timing) or duration (direct measure of explicit timing). The results show that the human brain efficiently extracts implicit temporal statistics of sensory environments, to enhance the behavioral and neural responses to auditory stimuli, but that those temporal predictions did not improve explicit timing. In both tasks, attentional orienting in time during predictive foreperiods was indexed by an increase in alpha power over visual and parietal areas. Furthermore, pretarget induced beta power in sensorimotor and parietal areas increased during implicit compared to explicit timing, in line with the suggested role for beta oscillations in temporal prediction. Interestingly, no distinct neural dynamics emerged when participants explicitly paid attention to time, compared to implicit timing. Our work thus indicates that implicit timing shapes the behavioral and sensory response in an automatic way and is reflected in oscillatory neural dynamics, whereas the translation of implicit temporal statistics to explicit durations remains somewhat inconclusive, possibly because of the more abstract nature of this task.

Mismatch of Visual-Vestibular Information in Virtual Reality: Is Motion Sickness Part of the Brains Attempt to Reduce the Prediction Error?

Visually induced motion sickness (VIMS) is a relevant limiting factor in the use of virtual reality (VR) devices. Understanding the origin of this problem might help to develop strategies to circumvent this limitation. Previous studies have attributed VIMS to a mismatch between visual, and vestibular information, causing ambiguity of the position of the body in relation to its surrounding. Studies using EEG have shown a shift of the power spectrum to lower frequencies while VIMS is experienced. However, little is known about the relationship between the intensity of the VIMS and the changes in these power spectra. Moreover, the effect of different varieties of VIMS on the causal relationship between brain areas is largely unknown. Here, we used EEG to study 14 healthy subjects in a VR environment who were exposed to increasing levels of mismatch between vestibular and visual information. The frequency power and the bivariate transfer entropy as a measure for the information transfer were calculated. We found a direct association between increasing mismatch levels and subjective VIMS. With increasing VIMS, the proportion of slow EEG waves (especially 1–10 Hz) increases, especially in temporo-occipital regions. Furthermore, we found a general decrease in the information flow in most brain areas but especially in brain areas involved in the processing of vestibular signals and the detection of self-motion. We hypothesize that the general shift of frequency power and the decrease in information flow while experiencing high intensity VIMS represent a brain state of a reduced ability to receive, transmit and process information. We further hypothesize that the mechanism of reduced information flow is a general reaction of the brain to an unresolvable mismatch of information. This reaction aims on transforming a currently unstable model with a high prediction error into a stable model in an environment of minimal contradictory information.

Investigating time-based expectancy beyond binary timing scenarios: evidence from a paradigm employing three predictive pre-target intervals

When the duration of a pre-target interval probabilistically predicts the identity of the target, participants typically form time-based expectancies: they respond faster to frequent interval-target combinations than to infrequent ones. Yet, previous research investigating the cognitive time-processing mechanisms underlying time-based expectancy assessed time-based expectancy always in situations with a binary set of intervals (i.e. short vs. long). Here we aim to test whether time-based expectancy transfers to more complex settings with three different predictive time intervals (short, medium, long) in which each predicts one of three different target stimuli with 80% probability. In three experiments we varied how the medium interval was computed (arithmetic mean, geometric mean, or in between both). Our results showed that participants were able to learn the time-event contingencies for the short and the long as well as for the medium interval, and were, thus able to flexibly redirect their target expectancy two times during the course of a trial. The evidence concerning the impact of the manipulation of the medium intervals’ absolute duration on time-based expectancy was, however, mixed, as time-based expectancy for the medium interval could only be observed in one of three reported experiments. In sum, the findings of the present study suggest a previously unknown cognitive flexibility underlying time-based expectancy and offer important theoretical implications, challenging future research on the timing mechanisms involved in time-based expectancy.

Beta and Theta Oscillations Correlate With Subjective Time During Musical Improvisation in Ecological and Controlled Settings: A Single Subject Study

In this paper, we describe the results of a single subject study attempting at a better understanding of the subjective mental state during musical improvisation. In a first experiment, we setup an ecological paradigm measuring EEG on a musician in free improvised concerts with an audience, followed by retrospective rating of the mental state of the improviser. We introduce Subjective Temporal Resolution (STR), a retrospective rating assessing the instantaneous quantization of subjective timing of the improviser. We identified high and low STR states using Hidden Markov Models in two performances, and were able to decode those states using supervised learning on instantaneous EEG power spectrum, showing increases in theta and alpha power with high STR values. In a second experiment, we found an increase of theta and beta power when experimentally manipulating STR in a musical improvisation imagery experiment. These results are interpreted with respect to previous research on flow state in creativity, as well as with the temporal processing literature. We suggest that a component of the subjective state of musical improvisation may be reflected in an underlying mechanism related to the subjective quantization of time. We also demonstrate the feasibility of single case studies of musical improvisation using brain activity measurements and retrospective reports, by obtaining consistent results across multiple sessions.

Two sources of uncertainty independently modulate temporal expectancy

The environment is shaped by two sources of temporal uncertainty: the discrete probability of whether an event will occur and-if it does-the continuous probability of when it will happen. These two types of uncertainty are fundamental to every form of anticipatory behavior including learning, decision-making, and motor planning. It remains unknown how the brain models the two uncertainty parameters and how they interact in anticipation. It is commonly assumed that the discrete probability of whether an event will occur has a fixed effect on event expectancy over time. In contrast, we first demonstrate that this pattern is highly dynamic and monotonically increases across time. Intriguingly, this behavior is independent of the continuous probability of when an event will occur. The effect of this continuous probability on anticipation is commonly proposed to be driven by the hazard rate (HR) of events. We next show that the HR fails to account for behavior and propose a model of event expectancy based on the probability density function of events. Our results hold for both vision and audition, suggesting independence of the representation of the two uncertainties from sensory input modality. These findings enrich the understanding of fundamental anticipatory processes and have provocative implications for many aspects of behavior and its neural underpinnings.

Temporal Regularity May Not Improve Memory for Item-Specific Detail

Regularities in event timing allow for the allocation of attention to critical time-points when an event is most likely to occur, leading to improved visual perception. Results from recent studies indicate that similar benefits may extend to memory for scenes and objects. Here, we investigated whether benefits of temporal regularity are evident when detailed, item-specific representations are necessary for successful recognition memory performance. In Experiments 1 and 2, pictures of objects were presented with either predictable or randomized event timing, in separate encoding blocks. In the test phase, old and new objects were presented, intermixed with perceptually similar exemplars of encoded objects. In Experiment 3 we attempted to replicate previously reported memory enhancements for scenes. In contrast to predictions, temporal regularity did not affect response times (RT) or improve recognition memory accuracy in any of our experiments. These results suggest that any effects of temporal expectation on memory are subtle and may be sensitive to minor changes in task parameters. In sum, indirect upregulation of attention through imposed temporal structure may not be sufficient to have downstream effects on memory performance.

Language prediction mechanisms in human auditory cortex

Spoken language, both perception and production, is thought to be facilitated by an ensemble of predictive mechanisms. We obtain intracranial recordings in 37 patients using depth probes implanted along the anteroposterior extent of the supratemporal plane during rhythm listening, speech perception, and speech production. These reveal two predictive mechanisms in early auditory cortex with distinct anatomical and functional characteristics. The first, localized to bilateral Heschl's gyri and indexed by low-frequency phase, predicts the timing of acoustic events. The second, localized to planum temporale only in language-dominant cortex and indexed by high-gamma power, shows a transient response to acoustic stimuli that is uniquely suppressed during speech production. Chronometric stimulation of Heschl's gyrus selectively disrupts speech perception, while stimulation of planum temporale selectively disrupts speech production. This work illuminates the fundamental acoustic infrastructure-both architecture and function-for spoken language, grounding cognitive models of speech perception and production in human neurobiology.

Non-rhythmic temporal prediction involves phase resets of low-frequency delta oscillations

The phase of neural oscillatory signals aligns to the predicted onset of upcoming stimulation. Whether such phase alignments represent phase resets of underlying neural oscillations or just rhythmically evoked activity, and whether they can be observed in a rhythm-free visual context, however, remains unclear. Here, we recorded the magnetoencephalogram while participants were engaged in a temporal prediction task, judging the visual or tactile reappearance of a uniformly moving stimulus. The prediction conditions were contrasted with a control condition to dissociate phase adjustments of neural oscillations from stimulus-driven activity. We observed stronger delta band inter-trial phase consistency (ITPC) in a network of sensory, parietal and frontal brain areas, but no power increase reflecting stimulus-driven or prediction-related evoked activity. Delta ITPC further correlated with prediction performance in the cerebellum and visual cortex. Our results provide evidence that phase alignments of low-frequency neural oscillations underlie temporal predictions in a non-rhythmic visual and crossmodal context.

Temporal attention is not affected by working memory load

Temporal attention refers to the ability to orient attention in time, which serves to enhance performance such as target detection and discrimination and is a fundamental component of cognitive function. Although some research indicates that temporal attention ability is affected by working memory updating, it is unclear whether temporal attention is also affected by the availability of working memory stores. To address this, participants were presented a dual-task paradigm requiring zero, three, or six digits to be held in working memory while engaged in a temporally cued visual discrimination task. Results show that working memory load did not differentially affect the ability to benefit from predictive temporal cues during the visual discrimination task. This indicates that temporal attention is not affected by available working memory stores. Interestingly, posterior beta band (12-30 Hz) activity was differentially modulated by temporal attention and working memory load, such that it decreased prior to expected targets and increased with load. Analysis across participants indicated that those individuals who exhibited greater temporal attention-based modulation of beta activity (i.e., predictive < neutrally cued) displayed improved discrimination performance, but also yielded lowered working memory accuracy. Thus, the ability to benefit from temporal attention processes while multitasking comes at the cost of lowered secondary task performance. Together, these results indicate that available working memory stores do not affect temporal attention ability. Rather, limitations in divided attention ability result in a performance cost that prioritizes one task over another, which may be indexed by beta band activity.

Audiovisual Modulation in Music Perception for Musicians and Non-musicians

In audiovisual music perception, visual information from a musical instrument being played is available prior to the onset of the corresponding musical sound and consequently allows a perceiver to form a prediction about the upcoming audio music. This prediction in audiovisual music perception, compared to auditory music perception, leads to lower N1 and P2 amplitudes and latencies. Although previous research suggests that audiovisual experience, such as previous musical experience may enhance this prediction, a remaining question is to what extent musical experience modifies N1 and P2 amplitudes and latencies. Furthermore, corresponding event-related phase modulations quantified as inter-trial phase coherence (ITPC) have not previously been reported for audiovisual music perception. In the current study, audio video recordings of a keyboard key being played were presented to musicians and non-musicians in audio only (AO), video only (VO), and audiovisual (AV) conditions. With predictive movements from playing the keyboard isolated from AV music perception (AV-VO), the current findings demonstrated that, compared to the AO condition, both groups had a similar decrease in N1 amplitude and latency, and P2 amplitude, along with correspondingly lower ITPC values in the delta, theta, and alpha frequency bands. However, while musicians showed lower ITPC values in the beta-band in AV-VO compared to the AO, non-musicians did not show this pattern. Findings indicate that AV perception may be broadly correlated with auditory perception, and differences between musicians and non-musicians further indicate musical experience to be a specific factor influencing AV perception. Predicting an upcoming sound in AV music perception may involve visual predictory processes, as well as beta-band oscillations, which may be influenced by years of musical training. This study highlights possible interconnectivity in AV perception as well as potential modulation with experience.

Dynamic Brain Responses Modulated by Precise Timing Prediction in an Opposing Process

The brain function of prediction is fundamental for human beings to shape perceptions efficiently and successively. Through decades of effort, a valuable brain activation map has been obtained for prediction. However, much less is known about how the brain manages the prediction process over time using traditional neuropsychological paradigms. Here, we implemented an innovative paradigm for timing prediction to precisely study the temporal dynamics of neural oscillations. In the experiment recruiting 45 participants, expectation suppression was found for the overall electroencephalographic activity, consistent with previous hemodynamic studies. Notably, we found that N1 was positively associated with predictability while N2 showed a reversed relation to predictability. Furthermore, the matching prediction had a similar profile with no timing prediction, both showing an almost saturated N1 and an absence of N2. The results indicate that the N1 process showed a 'sharpening' effect for predictable inputs, while the N2 process showed a 'dampening' effect. Therefore, these two paradoxical neural effects of prediction, which have provoked wide confusion in accounting for expectation suppression, actually co-exist in the procedure of timing prediction but work in separate time windows. These findings strongly support a recently-proposed opposing process theory.

The 'Narcissus Effect': Top-down alpha-beta band modulation of face-related brain areas during self-face processing

Self-related information, such as one's own face, is prioritized by our cognitive system. Whilst recent theoretical developments suggest that this is achieved by an interplay between bottom-up and top-down attentional mechanisms, their underlying neural dynamics are still poorly understood. Furthermore, it is still matter of discussion as to whether these attentional mechanisms are truly self-specific or instead driven by face familiarity. To address these questions, we used EEG to record the brain activity of twenty-five healthy participants whilst identifying their own face, a friend's face and a stranger's face. Time-frequency analysis revealed a greater sustained power decrease in the alpha and beta frequency bands for the self-face, which emerged at late latencies and was maintained even when the face was no longer present. Critically, source analysis showed that this activity was generated in key brain regions for self-face recognition, such as the fusiform gyrus. As in the Myth of Narcissus, our results indicate that one's own face might have the potential to hijack attention. We suggest that this effect is specific to the self and driven by a top-down attentional control mechanism, which might facilitate further processing of personally relevant events.

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

One Thing Leads to Another: Anticipating Visual Object Identity Based on Associative-Memory Templates

Probabilistic associations between stimuli afford memory templates that guide perception through proactive anticipatory mechanisms. A great deal of work has examined the behavioral consequences and human electrophysiological substrates of anticipation following probabilistic memory cues that carry spatial or temporal information to guide perception. However, less is understood about the electrophysiological substrates linked to anticipating the sensory content of events based on recurring associations between successive events. Here, we demonstrate behavioral and electrophysiological signatures of using associative-memory templates to guide perception, while equating spatial and temporal anticipation (experiments 1 and 2), as well as target probability and response demands (experiment 2). By recording the electroencephalogram in the two experiments (N = 55; 24 females), we show that two markers in human electrophysiology implicated in spatial and temporal anticipation also contribute to the anticipation of perceptual identity, as follows: attenuation of alpha-band oscillations and the contingent negative variation (CNV). Together, our results show that memory-guided identity templates proactively impact perception and are associated with anticipatory states of attenuated alpha oscillations and the CNV. Furthermore, by isolating object-identity anticipation from spatial and temporal anticipation, our results suggest a role for alpha attenuation and the CNV in specific visual content anticipation beyond general changes in neural excitability or readiness.SIGNIFICANCE STATEMENT Probabilistic associations between stimuli afford memory templates that guide perception through proactive anticipatory mechanisms. The current work isolates the behavioral benefits and electrophysiological signatures of memory-guided identity-based anticipation, while equating anticipation of space, time, motor responses, and task relevance. Our results show that anticipation of the specific identity of a forthcoming percept impacts performance and is associated with states of attenuated alpha oscillations and the contingent negative variation, extending previous work implicating these neural substrates in spatial and temporal preparatory attention. Together, this work bridges fields of attention, memory, and perception, providing new insights into the neural mechanisms that support complex attentional templates.

Precision Timing with α-β Oscillatory Coupling: Stopwatch or Motor Control?

Precise timing is crucial for many behaviors ranging from conversational speech to athletic performance. The precision of motor timing has been suggested to result from the strength of phase-amplitude coupling (PAC) between the phase of alpha oscillations (α, 8-12 Hz) and the power of beta activity (β, 14-30 Hz), herein referred to as α-β PAC. The amplitude of β oscillations has been proposed to code for temporally relevant information and the locking of β power to the phase of α oscillations to maintain timing precision. Motor timing precision has at least two sources of variability: variability of timekeeping mechanism and variability of motor control. It is ambiguous to which of these two factors α-β PAC should be ascribed: α-β PAC could index precision of stopwatch-like internal timekeeping mechanisms, or α-β PAC could index motor control precision. To disentangle these two hypotheses, we tested how oscillatory coupling at different stages of a time reproduction task related to temporal precision. Human participants encoded and subsequently reproduced a time interval while magnetoencephalography was recorded. The data show a robust α-β PAC during both the encoding and reproduction of a temporal interval, a pattern that cannot be predicted by motor control accounts. Specifically, we found that timing precision resulted from the trade-off between the strength of α-β PAC during the encoding and during the reproduction of intervals. These results support the hypothesis that α-β PAC codes for the precision of temporal representations in the human brain.

Spatial attention affects the early processing of neutral versus fearful faces when they are task-irrelevant: a classifier study of the EEG C1 component

EEG studies suggest that the emotional content of visual stimuli is processed rapidly. In particular, the C1 component, which occurs up to 100 ms after stimulus onset and likely reflects activity in primary visual cortex V1, has been reported to be sensitive to emotional faces. However, difficulties replicating these results have been reported. We hypothesized that the nature of the task and attentional condition are key to reconcile the conflicting findings. We report three experiments of EEG activity during the C1 time range elicited by peripherally presented neutral and fearful faces under various attentional conditions: the faces were spatially attended or unattended and were either task-relevant or not. Using traditional event-related potential analysis, we found that the early activity changed depending on facial expression, attentional condition, and task. In addition, we trained classifiers to discriminate the different conditions from the EEG signals. Although the classifiers were not able to discriminate between facial expressions in any condition, they uncovered differences between spatially attended and unattended faces but solely when these were task-irrelevant. In addition, this effect was only present for neutral faces. Our study provides further indication that attention and task are key parameters when measuring early differences between emotional and neutral visual stimuli.

EEG Complexity and Functional Connectivity During Precise Timing Prediction

Predictive timing in millisecond-scale is crucial for human beings to efficiently accomplish ongoing perceptions and actions. It is believed that the predictive timing process is an implementation of the predictive coding model in time domain, which can flexibly deal with both the matching and mismatching predictions. However, it's still far from being understood how the neural signature differs between the two conditions during precise timing prediction. As the brain is a complex system, it is necessary to use nonlinear measures and functional connectivity to investigate the brain function of timing prediction. Here, we probe into the EEG signatures during predictive timing process by the sample entropy (SampEn), Lempel-Ziv complexity (LZC) and partial directed coherence methods. Significant lower EEG complexity and stronger brain functional connectivity were observed when the stimulus matches the timing prediction. The current observation may shed light on the modeling of the precise predictive timing process.

The anticipation of events in time

Humans anticipate events signaled by sensory cues. It is commonly assumed that two uncertainty parameters modulate the brain's capacity to predict: the hazard rate (HR) of event probability and the uncertainty in time estimation which increases with elapsed time. We investigate both assumptions by presenting event probability density functions (PDFs) in each of three sensory modalities. We show that perceptual systems use the reciprocal PDF and not the HR to model event probability density. We also demonstrate that temporal uncertainty does not necessarily grow with elapsed time but can also diminish, depending on the event PDF. Previous research identified neuronal activity related to event probability in multiple levels of the cortical hierarchy (sensory (V4), association (LIP), motor and other areas) proposing the HR as an elementary neuronal computation. Our results-consistent across vision, audition, and somatosensation-suggest that the neurobiological implementation of event anticipation is based on a different, simpler and more stable computation than HR: the reciprocal PDF of events in time.

Premembering Experience: A Hierarchy of Time-Scales for Proactive Attention

Memories are about the past, but they serve the future. Memory research often emphasizes the former aspect: focusing on the functions that re-constitute (re-member) experience and elucidating the various types of memories and their interrelations, timescales, and neural bases. Here we highlight the prospective nature of memory in guiding selective attention, focusing on functions that use previous experience to anticipate the relevant events about to unfold-to "premember" experience. Memories of various types and timescales play a fundamental role in guiding perception and performance adaptively, proactively, and dynamically. Consonant with this perspective, memories are often recorded according to expected future demands. Using working memory as an example, we consider how mnemonic content is selected and represented for future use. This perspective moves away from the traditional representational account of memory toward a functional account in which forward-looking memory traces are informationally and computationally tuned for interacting with incoming sensory signals to guide adaptive behavior.

Implicit temporal predictability enhances pitch discrimination sensitivity and biases the phase of delta oscillations in auditory cortex

Can human listeners use implicit temporal contingencies in auditory input to form temporal predictions, and if so, how are these predictions represented endogenously? To assess this question, we implicitly manipulated temporal predictability in an auditory pitch discrimination task: unbeknownst to participants, the pitch of the standard tone could either be deterministically predictive of the temporal onset of the target tone, or convey no predictive information. Predictive and non-predictive conditions were presented interleaved in one stream, and separated by variable inter-stimulus intervals such that there was no dominant stimulus rhythm throughout. Even though participants were unaware of the implicit temporal contingencies, pitch discrimination sensitivity (the slope of the psychometric function) increased when the onset of the target tone was predictable in time (N = 49, 28 female, 21 male). Concurrently recorded EEG data (N = 24) revealed that standard tones that conveyed temporal predictions evoked a more negative N1 component than non-predictive standards. We observed no significant differences in oscillatory power or phase coherence between conditions during the foreperiod. Importantly, the phase angle of delta oscillations (1-3 Hz) in auditory areas in the post-standard and pre-target time windows predicted behavioral pitch discrimination sensitivity. This suggests that temporal predictions are encoded in delta oscillatory phase during the foreperiod interval. In sum, we show that auditory perception benefits from implicit temporal contingencies, and provide evidence for a role of slow neural oscillations in the endogenous representation of temporal predictions, in absence of exogenously driven entrainment to rhythmic input.

The tempos of performance

Human performance fluctuates over time. Rather than random, the complex time course of variation reflects, among other factors, influences from regular periodic processes operating at multiple time scales. In this review, we consider evidence for how our performance ebbs and flows over fractions of seconds as we engage with sensory objects, over minutes as we perform tasks, and over hours according to homeostatic factors. We propose that rhythms of performance at these multiple tempos arise from the interplay among three sources of influence: intrinsic fluctuations in brain activity, periodicity of external stimulation, and the anticipation of the temporal structure of external stimulation by the brain.

The Common Rhythm of Action and Perception

Research in the last decade has undermined the idea of perception as a continuous process, providing strong empirical support for its rhythmic modulation. More recently, it has been revealed that the ongoing motor processes influence the rhythmic sampling of sensory information. In this review, we will focus on a growing body of evidence suggesting that oscillation-based mechanisms may structure the dynamic interplay between the motor and sensory system and provide a unified temporal frame for their effective coordination. We will describe neurophysiological data, primarily collected in animals, showing phase-locking of neuronal oscillations to the onset of (eye) movements. These data are complemented by novel evidence in humans, which demonstrate the behavioral relevance of these oscillatory modulations and their domain-general nature. Finally, we will discuss the possible implications of these modulations for action-perception coupling mechanisms.

Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain–Machine Interface Control

Modulation of sensorimotor rhythm (SMR) power, a rhythmic brain oscillation physiologically linked to motor imagery, is a popular Brain–Machine Interface (BMI) paradigm, but its interplay with slower cortical rhythms, also involved in movement preparation and cognitive processing, is not entirely understood. In this study, we evaluated the changes in phase and power of slow cortical activity in delta and theta bands, during a motor imagery task controlled by an SMR-based BMI system. In Experiment I, EEG of 20 right-handed healthy volunteers was recorded performing a motor-imagery task using an SMR-based BMI controlling a visual animation, and during task-free intervals. In Experiment II, 10 subjects were evaluated along five daily sessions, while BMI-controlling same visual animation, a buzzer, and a robotic hand exoskeleton. In both experiments, feedback received from the controlled device was proportional to SMR power (11–14[Formula: see text]Hz) detected by a real-time EEG-based system. Synchronization of slow EEG frequencies along the trials was evaluated using inter-trial-phase coherence (ITPC). Results: cortical oscillations of EEG in delta and theta frequencies synchronized at the onset and at the end of both active and task-free trials; ITPC was significantly modulated by feedback sensory modality received during the tasks; and ITPC synchronization progressively increased along the training. These findings suggest that phase-locking of slow rhythms and resetting by sensory afferences might be a functionally relevant mechanism in cortical control of motor function. We propose that analysis of phase synchronization of slow cortical rhythms might also improve identification of temporal edges in BMI tasks and might help to develop physiological markers for identification of context task switching and practice-related changes in brain function, with potentially important implications for design and monitoring of motor imagery-based BMI systems, an emerging tool in neurorehabilitation of stroke.

Temporal Dynamics of Visual Attention Allocation

We often temporally prepare our attention for an upcoming event such as a starter pistol. In such cases, our attention should be properly allocated around the expected moment of the event to process relevant sensory input efficiently. In this study, we examined the dynamic changes of attention levels near the expected moment by measuring contrast sensitivity to a target that was temporally cued by a five-second countdown. We found that the overall attention level decreased rapidly after the expected moment, while it stayed relatively constant before it. Results were not consistent with the predictions of existing explanations of temporal attention such as the hazard rate or the stimulus-driven oscillations. A control experiment ruled out the possibility that the observed pattern was due to biased time perception. In a further experiment with a wider range of cue-stimulus-intervals, we observed that attention level increased until the last 500 ms of the interval range, and thereafter, started to decrease. Based on the performances of a generative computational model, we suggest that our results reflect the nature of temporal attention that takes into account the subjectively estimated hazard rate and the probability of relevant events occurring in the near future.

The beneficial effect of synchronized action on motor and perceptual timing in children

We examined the role of action in motor and perceptual timing across development. Adults and children aged 5 or 8 years old learned the duration of a rhythmic interval with or without concurrent action. We compared the effects of sensorimotor versus visual learning on subsequent timing behaviour in three different tasks: rhythm reproduction (Experiment 1), rhythm discrimination (Experiment 2) and interval discrimination (Experiment 3). Sensorimotor learning consisted of sensorimotor synchronization (tapping) to an isochronous visual rhythmic stimulus (ISI = 800 ms), whereas visual learning consisted of simply observing this rhythmic stimulus. Results confirmed our hypothesis that synchronized action during learning systematically benefitted subsequent timing performance, particularly for younger children. Action-related improvements in accuracy were observed for both motor and perceptual timing in 5 years olds and for perceptual timing in the two older age groups. Benefits on perceptual timing tasks indicate that action shapes the cognitive representation of interval duration. Moreover, correlations with neuropsychological scores indicated that while timing performance in the visual learning condition depended on motor and memory capacity, sensorimotor learning facilitated an accurate representation of time independently of individual differences in motor and memory skill. Overall, our findings support the idea that action helps children to construct an independent and flexible representation of time, which leads to coupled sensorimotor coding for action and time.

The Strength of Alpha-Beta Oscillatory Coupling Predicts Motor Timing Precision

Precise timing makes the difference between harmony and cacophony, but how the brain achieves precision during timing is unknown. In this study, human participants (7 females, 5 males) generated a time interval while being recorded with magnetoencephalography. Building on the proposal that the coupling of neural oscillations provides a temporal code for information processing in the brain, we tested whether the strength of oscillatory coupling was sensitive to self-generated temporal precision. On a per individual basis, we show the presence of alpha-beta phase-amplitude coupling whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. Our results provide evidence that active oscillatory coupling engages α oscillations in maintaining the precision of an endogenous temporal motor goal encoded in β power; the when of self-timed actions. We propose that oscillatory coupling indexes the variance of neuronal computations, which translates into the precision of an individual's behavioral performance.SIGNIFICANCE STATEMENT Which neural mechanisms enable precise volitional timing in the brain is unknown, yet accurate and precise timing is essential in every realm of life. In this study, we build on the hypothesis that neural oscillations, and their coupling across time scales, are essential for the coding and for the transmission of information in the brain. We show the presence of alpha-beta phase-amplitude coupling (α-β PAC) whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. α-β PAC indexes the temporal precision with which information is represented in an individual's brain. Our results link large-scale neuronal variability on the one hand, and individuals' timing precision, on the other.

Directing Voluntary Temporal Attention Increases Fixational Stability

Our visual input is constantly changing, but not all moments are equally relevant. Visual temporal attention, the prioritization of visual information at specific points in time, increases perceptual sensitivity at behaviorally relevant times. The dynamic processes underlying this increase are unclear. During fixation, humans make small eye movements called microsaccades, and inhibiting microsaccades improves perception of brief stimuli. Here, we investigated whether temporal attention changes the pattern of microsaccades in anticipation of brief stimuli. Human observers (female and male) judged stimuli presented within a short sequence. Observers were given either an informative precue to attend to one of the stimuli, which was likely to be probed, or an uninformative (neutral) precue. We found strong microsaccadic inhibition before the stimulus sequence, likely due to its predictable onset. Critically, this anticipatory inhibition was stronger when the first target in the sequence (T1) was precued (task-relevant) than when the precue was uninformative. Moreover, the timing of the last microsaccade before T1 and the first microsaccade after T1 shifted such that both occurred earlier when T1 was precued than when the precue was uninformative. Finally, the timing of the nearest pre- and post-T1 microsaccades affected task performance. Directing voluntary temporal attention therefore affects microsaccades, helping to stabilize fixation at the most relevant moments over and above the effect of predictability. Just as saccading to a relevant stimulus can be an overt correlate of the allocation of spatial attention, precisely timed gaze stabilization can be an overt correlate of the allocation of temporal attention.SIGNIFICANCE STATEMENT We pay attention at moments in time when a relevant event is likely to occur. Such temporal attention improves our visual perception, but how it does so is not well understood. Here, we discovered a new behavioral correlate of voluntary, or goal-directed, temporal attention. We found that the pattern of small fixational eye movements called microsaccades changes around behaviorally relevant moments in a way that stabilizes the position of the eyes. Microsaccades during a brief visual stimulus can impair perception of that stimulus. Therefore, such fixation stabilization may contribute to the improvement of visual perception at attended times. This link suggests that, in addition to cortical areas, subcortical areas mediating eye movements may be recruited with temporal attention.

An EEG Experimental Study Evaluating the Performance of Texas Instruments ADS1299

Texas Instruments ADS1299 is an attractive choice for low cost electroencephalography (EEG) devices owing to its low power consumption and low input referred noise. To date, there have been no rigorous evaluations of its performance. In this EEG experimental study we evaluated the performance of the ADS1299 against a high quality laboratory-based system. Two self-paced lower limb motor tasks were performed by 22 healthy participants. Recorded power across delta, theta, alpha, and beta EEG bands, the power ratio across the motor tasks, pre-movement noise, and signal-to-noise ratio were obtained for evaluation. The amplitude and time of the negative peak in the movement-related cortical potentials (MRCPs) extracted from the EEG data were also obtained. Using linear mixed models, no statistically significant differences (p > 0.05) were found in any of these measures across the two systems. These findings were further supported by evaluation of cosine similarity, waveform differences, and topographic maps. There were statistically significant differences in MRCPs across the motor tasks in both systems. We conclude that the performance of the ADS1299 in combination with wet Ag/AgCl electrodes is analogous to that of a laboratory-based system in a low frequency (<40 Hz) EEG recording.

Not All Predictions Are Equal: "What" and "When" Predictions Modulate Activity in Auditory Cortex through Different Mechanisms

Using predictions based on environmental regularities is fundamental for adaptive behavior. While it is widely accepted that predictions across different stimulus attributes (e.g., time and content) facilitate sensory processing, it is unknown whether predictions across these attributes rely on the same neural mechanism. Here, to elucidate the neural mechanisms of predictions, we combine invasive electrophysiological recordings (human electrocorticography in 4 females and 2 males) with computational modeling while manipulating predictions about content ("what") and time ("when"). We found that "when" predictions increased evoked activity over motor and prefrontal regions both at early (∼180 ms) and late (430-450 ms) latencies. "What" predictability, however, increased evoked activity only over prefrontal areas late in time (420-460 ms). Beyond these dissociable influences, we found that "what" and "when" predictability interactively modulated the amplitude of early (165 ms) evoked responses in the superior temporal gyrus. We modeled the observed neural responses using biophysically realistic neural mass models, to better understand whether "what" and "when" predictions tap into similar or different neurophysiological mechanisms. Our modeling results suggest that "what" and "when" predictability rely on complementary neural processes: "what" predictions increased short-term plasticity in auditory areas, whereas "when" predictability increased synaptic gain in motor areas. Thus, content and temporal predictions engage complementary neural mechanisms in different regions, suggesting domain-specific prediction signaling along the cortical hierarchy. Encoding predictions through different mechanisms may endow the brain with the flexibility to efficiently signal different sources of predictions, weight them by their reliability, and allow for their encoding without mutual interference.SIGNIFICANCE STATEMENT Predictions of different stimulus features facilitate sensory processing. However, it is unclear whether predictions of different attributes rely on similar or different neural mechanisms. By combining invasive electrophysiological recordings of cortical activity with experimental manipulations of participants' predictions about content and time of acoustic events, we found that the two types of predictions had dissociable influences on cortical activity, both in terms of the regions involved and the timing of the observed effects. Further, our biophysical modeling analysis suggests that predictability of content and time rely on complementary neural processes: short-term plasticity in auditory areas and synaptic gain in motor areas, respectively. This suggests that predictions of different features are encoded with complementary neural mechanisms in different brain regions.