Tracking Temporal Hazard in the Human Electroencephalogram Using a Forward Encoding Model

Cerebellar Direct Current Stimulation Reveals the Causal Role of the Cerebellum in Temporal Prediction

Temporal prediction (TP) influences our perception and cognition. The cerebellum could mediate this multi-level ability in a context-dependent manner. We tested whether a modulation of the cerebellar neural activity, induced by transcranial Direct Current Stimulation (tDCS), changed the TP ability according to the temporal features of the context and the duration of target interval. Fifteen healthy participants received anodal, cathodal, and sham tDCS (15 min × 2 mA intensity) over the right cerebellar hemisphere during a TP task. We recorded reaction times (RTs) to a target during the task in two contextual conditions of temporal anticipation: rhythmic (i.e., interstimulus intervals (ISIs) were constant) and single-interval condition (i.e., the estimation of the timing of the target was based on the prior exposure of the train of stimuli). Two ISIs durations were explored: 600 ms (short trials) and 900 ms (long trials). Cathodal tDCS improved the performance during the TP task (shorter RTs) specifically in the rhythmic condition only for the short trials and in the single-interval condition only for the long trials. Our results suggest that the inhibition of cerebellar activity induced a different improvement in the TP ability according to the temporal features of the context. In the rhythmic context, the cerebellum could integrate the temporal estimation with the anticipatory motor responses critically for the short target interval. In the single-interval context, for the long trials, the cerebellum could play a main role in integrating representation of time interval in memory with the elapsed time providing an accurate temporal prediction.

Attention to space and time: Independent or interactive systems? A narrative review

While there is ample evidence for the ability to selectively attend to where in space and when in time a relevant event might occur, it remains poorly understood whether spatial and temporal attention operate independently or interactively to optimize behavior. To elucidate this important issue, we provide a narrative review of the literature investigating the relationship between the two. The studies were organized based on the attentional manipulation employed (endogenous vs. exogenous) and the type of task (detection vs. discrimination). Although the reviewed findings depict a complex scenario, three aspects appear particularly important in promoting independent or interactive effects of spatial and temporal attention: task demands, attentional manipulation, and their combination. Overall, the present review provides key insights into the relationship between spatial and temporal attention and identifies some critical gaps that need to be addressed by future research.

Predictability awareness rather than mere predictability enhances the perceptual benefits for targets in auditory rhythms over targets following temporal cues

Sounds following a cue or embedded in a periodic rhythm are processed more effectively than sounds that are part of an aperiodic rhythm. One might also expect that a sound embedded in a periodic rhythm is processed more effectively than a sound following a single temporal cue. Such a finding would follow the theory that the entrainment of neural rhythmic activity by periodic stimuli renders the prediction of upcoming stimuli more efficient. We conducted a psychophysical experiment in which we tested the behavioral elements of this idea. Targets in periodic and aperiodic rhythms, if they occurred, always appeared at the same moment in time, and thus were fully predictable. In a first condition, participants remained unaware of this. In a second condition, an explicit instruction on the temporal location of the targets embedded in rhythms was provided. We assessed sensitivity and reaction times to the target stimuli in a difficult temporal detection task, and contrasted performance in this task to that obtained for targets temporally cued by a single preceding cue. Irrespective of explicit information about target predictability, target detection performance was always better in the periodic and temporal cue conditions, compared to the aperiodic condition. However, we found that the mere predictability of an acoustic target within a periodic rhythm did not allow participants to detect the target any better than in a condition where the target's timing was predicted by a single temporal cue. Only when participants were made aware of the specific moment in the periodic rhythm where the target could occur, did sensitivity increase. This finding suggests that a periodic rhythm is not automatically sufficient to provide perceptual benefits compared to a condition predictable yet not rhythmic condition (a cue). In some conditions, as shown here, these benefits may only occur in interaction with other factors such as explicit instruction and directed attention.

How Does Temporal Blurring Alter Movement Timing?

Subjective uncertainty arises because the estimation of the timing of an event into the future is error prone. This impact of stimulus-bound uncertainty on movement preparation has often been investigated using reaction time tasks where a warning stimulus (WS) predicts the occurrence of a "go" signal. The timing of the "go" signal can be chosen from a particular probability distribution with a given variance or uncertainty. It has been repeatedly shown that reaction times covary with the shape of the used "go" signal distribution. This is interpreted as evidence for temporal preparation. Moreover, the variance of the response time should always increase with the duration of the delay between the WS and the "go" signal. This increasing variance has been interpreted as a consequence of the temporal "blurring" of future events (scalar expectancy). The present paper tested the validity of the temporal "blurring" hypothesis in humans with a simple oculomotor reaction time task where subjective and stimulus-bound uncertainties were increased. Subjective uncertainty about the timing of a "go" signal was increased by lengthening the delay between the WS and the "go" signal. Objective uncertainty was altered by increasing the variance of "go" signal timing. Contrary to temporal blurring hypotheses, the study has shown that increasing the delay between events did not significantly increase movement timing variability. These results suggest that temporal blurring could not be a property of movement timing in an implicit timing context.

P3-like signatures of temporal predictions: a computational EEG study

Many cognitive processes, ranging from perception to action, depend on the ability to predict the timing of forthcoming events. Yet, how the brain uses predictive models in the temporal domain is still an unsolved question. In previous work, we began to explore the neural correlates of temporal predictions by using a computational approach in which an ideal Bayesian observer learned the temporal probabilities of target onsets in a simple reaction time task. Because the task was specifically designed to disambiguate updating of predictive models and surprise, changes in temporal probabilities were explicitly cued. However, in the real world, we are usually incidentally exposed to changes in the statistics of the environment. Here, we thus aimed to further investigate the electroencephalographic (EEG) correlates of Bayesian belief updating and surprise associated with incidental learning of temporal probabilities. In line with our previous EEG study, results showed distinct P3-like modulations for updating and surprise. While surprise was indexed by an early fronto-central P3-like modulation, updating was associated with a later and more posterior P3 modulation. Moreover, updating was associated with a P2-like potential at centro-parietal electrodes, likely capturing integration processes between prior beliefs and likelihood of the observed event. These findings support previous evidence of trial-by-trial variability of P3 amplitudes as an index of dissociable inferential processes. Coupled with our previous findings, the present study strongly bolsters the view of the P3 as a key brain signature of temporal Bayesian inference. Data and scripts are shared on OSF: osf.io/sdy8j/.

A transcranial magnetic stimulation study on the role of the left intraparietal sulcus in temporal orienting of attention

Adaptive behavior requires the ability to orient attention to the moment in time at which a relevant event is likely to occur. Temporal orienting of attention has been consistently associated with activation of the left intraparietal sulcus (IPS) in prior fMRI studies. However, a direct test of its causal involvement in temporal orienting is still lacking. The present study tackled this issue by transiently perturbing left IPS activity with either online (Experiment 1) or offline (Experiment 2) transcranial magnetic stimulation (TMS). In both experiments, participants performed a temporal orienting task, alternating between blocks in which a temporal cue predicted when a subsequent target would appear and blocks in which a neutral cue provided no information about target timing. In Experiment 1 we used an online TMS protocol, aiming to interfere specifically with cue-related temporal processes, whereas in Experiment 2 we employed an offline protocol whereby participants performed the temporal orienting task before and after receiving TMS. The right IPS and/or the vertex were stimulated as active control regions. While results replicated the canonical pattern of temporal orienting effects on reaction time, with faster responses for temporal than neutral trials, these effects were not modulated by TMS over the left IPS (as compared to the right IPS and/or vertex regions) regardless of the online or offline protocol used. Overall, these findings challenge the causal role of the left IPS in temporal orienting of attention inviting further research on its underlying neural substrates.

Temporal scaling of human scalp-recorded potentials

Much of human behavior is governed by common processes that unfold over varying timescales. Standard event-related potential analysis assumes fixed-duration responses relative to experimental events. However, recent single-unit recordings in animals have revealed neural activity scales to span different durations during behaviors demanding flexible timing. Here, we employed a general linear modeling approach using a combination of fixed-duration and variable-duration regressors to unmix fixed-time and scaled-time components in human magneto-/electroencephalography (M/EEG) data. We use this to reveal consistent temporal scaling of human scalp-recorded potentials across four independent electroencephalogram (EEG) datasets, including interval perception, production, prediction, and value-based decision making. Between-trial variation in the temporally scaled response predicts between-trial variation in subject reaction times, demonstrating the relevance of this temporally scaled signal for temporal variation in behavior. Our results provide a general approach for studying flexibly timed behavior in the human brain.

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.

Explicit and implicit timing in older adults: Dissociable associations with age and cognitive decline

This study aimed to test two common explanations for the general finding of age-related changes in the performance of timing tasks within the millisecond-to-second range intervals. The first explanation is that older adults have a real difficulty in temporal processing as compared to younger adults. The second explanation is that older adults perform poorly on timing tasks because of their reduced cognitive control functions. These explanations have been mostly contrasted in explicit timing tasks that overtly require participants to process interval durations. Fewer studies have instead focused on implicit timing tasks, where no explicit instructions to process time are provided. Moreover, the investigation of both explicit and implicit timing in older adults has been restricted so far to healthy older participants. Here, a large sample (N = 85) comprising not only healthy but also pathological older adults completed explicit (time bisection) and implicit (foreperiod) timing tasks within a single session. Participants’ age and cognitive decline, measured with the Mini-Mental State Examination (MMSE), were used as continuous variables to explain performance on explicit and implicit timing tasks. Results for the explicit timing task showed a flatter psychometric curve with increasing age or decreasing MMSE scores, pointing to a deficit at the level of cognitive control functions rather than of temporal processing. By contrast, for the implicit timing task, a decrease in the MMSE scores was associated with a reduced foreperiod effect, an index of implicit time processing. Overall, these findings extend previous studies on explicit and implicit timing in healthy aged samples by dissociating between age and cognitive decline (in the normal-to-pathological continuum) in older adults.

Expectancy-based rhythmic entrainment as continuous Bayesian inference

When presented with complex rhythmic auditory stimuli, humans are able to track underlying temporal structure (e.g., a "beat"), both covertly and with their movements. This capacity goes far beyond that of a simple entrained oscillator, drawing on contextual and enculturated timing expectations and adjusting rapidly to perturbations in event timing, phase, and tempo. Previous modeling work has described how entrainment to rhythms may be shaped by event timing expectations, but sheds little light on any underlying computational principles that could unify the phenomenon of expectation-based entrainment with other brain processes. Inspired by the predictive processing framework, we propose that the problem of rhythm tracking is naturally characterized as a problem of continuously estimating an underlying phase and tempo based on precise event times and their correspondence to timing expectations. We present two inference problems formalizing this insight: PIPPET (Phase Inference from Point Process Event Timing) and PATIPPET (Phase and Tempo Inference). Variational solutions to these inference problems resemble previous "Dynamic Attending" models of perceptual entrainment, but introduce new terms representing the dynamics of uncertainty and the influence of expectations in the absence of sensory events. These terms allow us to model multiple characteristics of covert and motor human rhythm tracking not addressed by other models, including sensitivity of error corrections to inter-event interval and perceived tempo changes induced by event omissions. We show that positing these novel influences in human entrainment yields a range of testable behavioral predictions. Guided by recent neurophysiological observations, we attempt to align the phase inference framework with a specific brain implementation. We also explore the potential of this normative framework to guide the interpretation of experimental data and serve as building blocks for even richer predictive processing and active inference models of timing.

Electroencephalographic correlates of temporal Bayesian belief updating and surprise

The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that neural encoding of surprise comprises neural activity in the cingulo-opercular network (CON) and parietal regions. These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/.

The warning stimulus as retrieval cue: The role of associative memory in temporal preparation

In a warned reaction time task, the warning stimulus (S1) initiates a process of temporal preparation, which promotes a speeded response to the impending target stimulus (S2). According to the multiple trace theory of temporal preparation (MTP), participants learn the timing of S2 by storing a memory trace on each trial, which contains a temporal profile of the events on that trial. On each new trial, S1 serves as a retrieval cue that implicitly and associatively activates memory traces created on earlier trials, which jointly drive temporal preparation for S2. The idea that S1 assumes this role as a retrieval cue was tested across eight experiments, in which two different S1s were associated with two different distributions of S1-S2 intervals: one with predominantly short and one with predominantly long intervals. Experiments differed regarding the S1 features that made up a pair, ranging from highly distinct (e.g., tone and flash) to more similar (e.g., red and green flash) and verbal (i.e., "short" vs "long"). Exclusively for pairs of highly distinct S1s, the results showed that the S1 cue modified temporal preparation, even in participants who showed no awareness of the contingency. This cueing effect persisted in a subsequent transfer phase, in which the contingency between S1 and the timing of S2 was broken - a fact participants were informed of in advance. Together, these findings support the role of S1 as an implicit retrieval cue, consistent with MTP.

High-pass filtering artifacts in multivariate classification of neural time series data

BACKGROUND

Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown.

NEW METHOD

To prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending.

RESULTS

In both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements.

COMPARISON WITH EXISTING METHOD(S)

Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial.

CONCLUSIONS

Decoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

Dissociable neural effects of temporal expectations due to passage of time and contextual probability

The human brain is equipped with complex mechanisms to track the changing probability of events in time. While the passage of time itself usually leads to a mounting expectation, context can provide additional information about when events are likely to happen. In this study we dissociate these two sources of temporal expectation in terms of their neural correlates and underlying brain connectivity patterns. We analysed magnetoencephalographic (MEG) data acquired from N = 24 healthy participants listening to auditory stimuli. These stimuli could be presented at different temporal intervals but occurred most often at intermediate intervals, forming a contextual probability distribution. Evoked MEG response amplitude was sensitive to both passage of time (time elapsed since the cue) and contextual probability, albeit at different latencies: the effects of passage of time were observed earlier than the effects of context. The underlying sources of MEG activity were also different across the two types of temporal prediction: the effects of passage of time were localised to early auditory regions and superior temporal gyri, while context was additionally linked to activity in inferior parietal cortices. Finally, these differences were modelled using biophysical (dynamic causal) modelling: passage of time was explained in terms of widespread gain modulation and decreased prediction error signalling at lower levels of the hierarchy, while contextual expectation led to more localised gain modulation and decreased prediction error signalling at higher levels of the hierarchy. These results present a comprehensive account of how independent sources of temporal prediction may be differentially expressed in cortical circuits.

Bayesian modeling of temporal expectations in the human brain

The brain predicts the timing of forthcoming events to optimize processes in response to them. Temporal predictions are driven by both our prior expectations on the likely timing of stimulus occurrence and the information conveyed by the passage of time. Specifically, such predictions can be described in terms of the hazard function, that is, the conditional probability that an event will occur, given it has not yet occurred. Events violating expectations cause surprise and often induce updating of prior expectations. While it is well-known that the brain is able to track the temporal hazard of event occurrence, the question of how prior temporal expectations are updated is still unsettled. Here we combined a Bayesian computational approach with brain imaging to map updating of temporal expectations in the human brain. Moreover, since updating is usually highly correlated with surprise, participants performed a task that allowed partially differentiating between the two processes. Results showed that updating and surprise differently modulated activity in areas belonging to two critical networks for cognitive control, the fronto-parietal (FPN) and the cingulo-opercular network (CON). Overall, these data provide a first computational characterization of the neural correlates associated with updating and surprise related to temporal expectation.

Immediate versus delayed control demands elicit distinct mechanisms for instantiating proactive control

Cognitive control is critical for dynamically guiding goal-directed behavior, particularly when applying preparatory, or proactive, control processes. However, it is unknown how proactive control is modulated by timing demands. This study investigated how timing demands may instantiate distinct neural processes and contribute to the use of different types of proactive control. In two experiments, healthy young adults performed the AX-Continuous Performance Task (AX-CPT) or Dot Pattern Expectancy (DPX) task. The delay between informative cue and test probe was manipulated by block to be short (1s) or long (~3s). We hypothesized that short cue-probe delays would rely more on a rapid goal updating process (akin to task-switching), whereas long cue-probe delays would utilize more of an active maintenance process (akin to working memory). Short delay lengths were associated with specific impairments in rare probe accuracy. EEG responses to control-demanding cues revealed delay-specific neural signatures, which replicated across studies. In the short delay condition, EEG activities associated with task-switching were specifically enhanced, including increased early anterior positivity ERP amplitude (accompanying greater mid-frontal theta power) and a larger late differential switch positivity. In the long delay condition, we observed study-specific sustained increases in ERP amplitude following control-demanding cues, which may be suggestive of active maintenance. Collectively, these findings suggest that timing demands may instantiate distinct proactive control processes. These findings suggest a reevaluation of AX-CPT and DPX as pure assessments of working memory and highlight the need to understand how presumably benign task parameters, such as cue-probe delay length, significantly alter cognitive control.