Foreperiod Distribution Research Articles

FMTP: A unifying computational framework of temporal preparation across time scales.

Temporal preparation is the cognitive function that takes place when anticipating future events. This is commonly considered to involve a process that maximizes preparation at time points that yield a high hazard. However, despite their prominence in the literature, hazard-based theories fail to explain the full range of empirical preparation phenomena. Here, we present the formalized multiple trace theory of temporal preparation (fMTP), an integrative model which develops the alternative perspective that temporal preparation results from associative learning. fMTP builds on established computational principles from the domains of interval timing, motor planning, and associative memory. In fMTP, temporal preparation results from associative learning between a representation of time on the one hand and inhibitory and activating motor units on the other hand. Simulations demonstrate that fMTP can explain phenomena across a range of time scales, from sequential effects operating on a time scale of seconds to long-term memory effects occurring over weeks. We contrast fMTP with models that rely on the hazard function and show that fMTP's learning mechanisms are essential to capture the full range of empirical effects. In a critical experiment using a Gaussian distribution of foreperiods, we show the data to be consistent with fMTP's predictions and to deviate from the hazard function. Additionally, we demonstrate how changing fMTP's parameters can account for participant-to-participant variations in preparation. In sum, with fMTP we put forward a unifying computational framework that explains a family of phenomena in temporal preparation that cannot be jointly explained by conventional theoretical frameworks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Revisiting variable-foreperiod effects: evaluating the repetition priming account.

A warning signal preceding an imperative stimulus by a certain foreperiod can accelerate responses (foreperiod effect). When foreperiod is varied within a block, the foreperiod effect on reaction time (RT) is modulated by both the current and the prior foreperiods. Using a non-aging foreperiod distribution in a simple-reaction task, Capizzi et al. (Cognition, 134, 39-49, 2015) found equal sequential effects for different foreperiods, which they credited to repetition priming. The multiple-trace theory of Los et al. (Frontiers in Psychology, 5, Article 1058, 2014) attributes the slope of the foreperiod-RT function to the foreperiod distribution. We conducted three experiments that examined these predicted relations. Experiment 1 tested Capizzi et al.’s prediction in a choice-reaction task and found an increasing foreperiod-RT function but a larger sequential effect at the shorter foreperiod. Experiment 2 used two distinct short foreperiods with the same foreperiod distribution and found a decreasing foreperiod-RT function. By increasing the difference between the foreperiods used in Experiment 2, Experiment 3 yielded a larger sequential effect overall. The experiments provide evidence that, with a non-aging foreperiod distribution, the variable-foreperiod paradigm yields unequal sequential-effect sizes at the different foreperiods, consistent with the multiple-trace theory but contrary to Capizzi et al.’s repetition-priming account. The foreperiod-RT functions are similar to those of the fixed-foreperiod paradigm, which is not predicted by the multiple trace theory.

Temporal expectancy modulates stimulus\u2013response integration

We can use information derived from passing time to anticipate an upcoming event. If time before an event varies, responses towards this event become faster with increasing waiting time. This variable-foreperiod effect has been often observed in response-speed studies. Different action control frameworks assume that response and stimulus features are integrated into an event file that is retrieved later if features repeat. Yet the role of foreperiods has so far not been investigated in action control. Thus, we investigated the influence of foreperiod on the integration of action-perception features. Participants worked through a standard distractor–response binding paradigm where two consecutive responses are made towards target letters while distractor letters are present. Responses and/or distractors can repeat or change from first to second display, leading to partial repetition costs when only some features repeat or repetition benefits when all features repeat (the difference constituting distractor–response binding). To investigate the effect of foreperiod, we also introduced an anti-geometric distribution of foreperiods to the time interval before the first response display. We observed that distractor–response binding increased with increasing foreperiod duration, and speculate that this was driven by an increase in motor readiness induced by temporal expectancy.

Transfer effects in auditory temporal preparation occur using an unfilled but not filled foreperiod.

How quickly participants respond to a “go” after a “warning” signal is partly determined by the time between the two signals (the foreperiod) and the distribution of foreperiods. According to Multiple Trace Theory of Temporal Preparation (MTP), participants use memory traces of previous foreperiods to prepare for the upcoming go signal. If the processes underlying temporal preparation reflect general encoding and memory principles, transfer effects (the carryover effect of a previous block’s distribution of foreperiods to the current block) should be observed regardless of the sensory modality in which signals are presented. Despite convincing evidence for transfer effects in the visual domain, only weak evidence for transfer effects has been documented in the auditory domain. Three experiments were conducted to examine whether such differences in results are due to the modality of the stimulus or other procedural factors. In each experiment, two groups of participants were exposed to different foreperiod distributions in the acquisition phase and to the same foreperiod distribution in the transfer phase. Experiment 1 used a choice-reaction time (RT) task, and the warning signal remained on until the go signal, but there was no evidence for transfer effects. Experiments 2 and 3 used a simple- and choice-RT task, respectively, and there was silence between the warning and go signals. Both experiments revealed evidence for transfer effects, which suggests that transfer effects are most evident when there is no auditory stimulation between the warning and go signals.

Pre-target oculomotor inhibition reflects temporal orienting rather than certainty

Recent studies suggested that eye movements are linked to temporal predictability. These studies manipulated predictability by setting the cue-target interval (foreperiod) to be fixed or random throughout the block. Findings showed that pre-target oculomotor behavior was reduced in the fixed relative to the random condition. This effect was interpreted as reflecting the formation of temporal expectation. However, it is unknown whether the effect is driven by target-specific temporal orienting, or rather a result of a more context-dependent state of certainty that participants may experience during blocks with a high predictability rate. In this study we dissociated certainty and orienting in a tilt-discrimination task. In each trial, a temporal cue (fixation color change) was followed by a tilted grating-patch. The foreperiod distribution was varied between blocks to be either fully fixed (same foreperiod in 100% of trials), mostly fixed (80% of trials with one foreperiod and 20% with another) or random (five foreperiods in equal probabilities). The two hypotheses led to different prediction models which were tested against the experimental data. Results were consistent with the orienting hypothesis and inconsistent with the certainty hypothesis, supporting the link between oculomotor inhibition and temporal orienting and its validity as a temporal expectations marker.

Dissociable influences of implicit temporal expectation on attentional performance and mind wandering

Mind wandering at critical moments during a cognitive task degrades performance. At other moments, mind wandering could serve to conserve task-relevant resources, allowing a brief mental respite. Recent research has shown that, if target timing is predictable, mind wandering episodes coincide with moments of low target likelihood. Conversely, mind wandering can be avoided at moments when targets are expected. In the current study, we tested whether mind wandering can be guided by implicit temporal expectations when target timing is less predictable. In two experiments (Experiment 1: N = 37, Experiment 2: N = 61), participants performed a sustained attention task in which target events were preceded by a variable pre-target interval (foreperiod). As time passes over the foreperiod duration, implicit target expectation increases, given that it has not yet appeared. In Experiment 1, all foreperiod durations were equally probable (uniform distribution: 2–10 s). This resulted in faster responses when targets were preceded by long compared to short foreperiods (foreperiod-effect). In contrast, mind wandering, assessed by thought probes inserted following short or long foreperiods, did not follow this pattern. In Experiment 2, alterations in the foreperiod distribution (left or right-skewed) resulted in changes in the behavioral foreperiod-effect, but mind wandering was unaffected. Our findings indicate that implicit timing strongly affects behavioral response to target events, but has no bearing on the mind wandering. Contrastingly, mind wandering did correlate with performance deterioration due to fatigue (time-on-task), suggesting that the thought probe method was sufficiently sensitive to behaviorally relevant changes in mental state.

Evidence for short-term, but not long-term, transfer effects in the temporal preparation of auditory stimuli.

Starting procedures in racing sports consist of a warning (e.g., "Set") followed by a target (e.g., "Go") signal. During this interval (the foreperiod), athletes engage in temporal preparation whereby they prepare to respond to the target as quickly as possible. Despite a long history, the cognitive mechanisms underlying this process are debated. Recently, it has been suggested that traces of previous temporal durations drive temporal preparation performance rather than the traditional explanation that performance is related to the currently perceived hazard function. Los and colleagues used visual stimuli for the warning and target signals. As racing sports typically rely upon auditory stimuli, we investigated the role of memory on temporal preparation in the auditory domain. Experiment 1 investigated long-term transfer effects. In an acquisition phase, two groups of participants were exposed to different foreperiod distributions. One week later, during a transfer phase, both groups received the same distribution of foreperiods. There was no evidence for transfer effects. Therefore, Experiment 2 examined short-term transfer effects in which acquisition and transfer phases were completed in the same testing session. There was some evidence for transfer effects, but this was limited, suggesting that there may be modality-specific memory differences.

Monocular channels have a functional role in phasic alertness and temporal expectancy.

The literature has long emphasized the neocortex's role in the tangled phasic-alertness and temporal-expectancy processes. In this work, we examined whether subcortical, monocular mechanisms have a functional role in these processes. This was done by assessing phasic alertness and temporal expectancy independently using a cue-target eye-of-origin manipulation. Participants performed target detection tasks in which a central cue and its ensuing peripheral target were each presented either to the same eye or to a different eye. In Experiment 1, phasic alertness, independent of temporal expectancy, was manipulated by presenting an alerting cue prior to the target presentation. The alerting effect elicited by the cue lasted for a longer duration when the cue and target were presented to the same eye than when they were presented to different eyes, indicating the involvement of subcortical regions in phasic alertness. In Experiment 2, the cue's temporal predictability regarding the target's onset time was manipulated by changing the cue-target interval's foreperiod distribution. A modulation in temporal expectancy was found when both the cue and the target were presented to the same eye, demonstrating the importance of subcortical mechanisms in temporal expectancy. Together, the results demonstrate that monocular channels are functionally involved in both phasic alertness and temporal expectancy. This study suggests that both phasic alertness and temporal expectancy are functionally dependent on monocular channels of the visual stream, and highlights the importance of direct examination of primitive, subcortical regions in higher cognitive functioning (e.g., temporal expectancy).

The expected oddball: effects of implicit and explicit positional expectation on duration perception.

The oddball duration effect describes how a rare stimulus amongst a string of standard stimuli is perceived to have a longer duration than the standards, even if they are of the same objective duration. Several theories have been proposed to explain this phenomenon. In order to adjudicate between opposing explanations, we have borrowed three extensively studied paradigms from the variable foreperiod literature: the sequential foreperiod, temporal cueing and a skewed foreperiod distribution. This approach allowed us to examine the effects of positional expectation on perceived oddball duration, while avoiding confounds from first-order positioning of the oddball in a sequence of standards. Through these three experiments, we demonstrate a clear role of positional expectation in the lengthening of the perceived duration of an oddball. We show that this expectation effect is separable from other drivers of the oddball duration illusion.

Implicit variations of temporal predictability: Shaping the neural oscillatory and behavioural response.

Being able to predict when an event will occur (temporal predictability) can help us prepare and time our responses. We here sought to delineate the neural and behavioural corollaries of highly implicit, probabilistic temporal predictability in an auditory foreperiod paradigm. To this end, we measured electroencephalography (EEG) and response times in two independent experiments (total N =46). Unbeknownst to participants, we induced a probabilistic variation of cue-target delays (i.e., foreperiods) in a pitch-discrimination task on a noise-embedded tone: The smaller the standard deviation of the underlying foreperiod distribution, the more predictable the time of target occurrence should be. Both experiments showed that more predictive foreperiods sped up listeners' responses. Crucially, neural signatures of temporal predictability emerged when comparing EEG activity between conditions of varying temporal predictability. First, cue-related P2 evoked responses were less pronounced for cues that implicitly signalled temporal predictability of target occurrence. Second, in both experiments, fronto-central delta (1-4Hz) phase coherence was found relatively reduced during predictive foreperiods. Concomitantly, in Experiment II, the most predictive condition yielded a central alpha (7-12Hz) power increase just before the most likely time point of tone onset, likely reflecting improved temporal orienting of attention. In sum, neural oscillations in anticipation of, and response times to a target show that humans are susceptible to even strictly implicit, probabilistic temporal regularities.

Timing a week later: The role of long-term memory in temporal preparation

Temporal preparation has been investigated extensively by manipulating the foreperiod, the interval between a warning stimulus and target stimulus requiring a speeded response. Although such research has revealed many effects of both the duration and distribution of foreperiods on reaction times, the underlying cognitive mechanism is still largely unknown. Here, we test a recent proposal that temporal preparation is driven by the retrieval of memory traces of past experiences from long-term memory rather than by knowledge about upcoming events. Two groups of participants received different foreperiod distributions in an acquisition phase, which was followed a week later by a transfer phase, in which both groups received the same distribution of foreperiods. We found that the effects of the different foreperiod distributions presented in the acquisition phase were still apparent a week later during the transfer phase, as the reaction time patterns of both groups reflected the old distributions. This occurred even though both groups were provided with full information about the change in the distribution of foreperiods at the start of the transfer phase. These findings provide compelling evidence that long-term memory plays an important role in temporal preparation.

How and where does the brain predict the when: a Bayesian approach to modeling temporal expectation

How does the brain learn to predict when an event is going to occur? We know from studies that vary the foreperiod – the time between a warning and a response stimulus – that people can model the temporal variability of stimulus onset, i.e. react faster when a stimulus is statistically more likely [1]. We also know that reaction time (RT) decreases with the passage of time, showing that people dynamically update the temporal expectation of the stimulus [2]. Recent neurophysiological investigations and brain lesion studies have also revealed that areas in the dorsolateral prefrontal cortex, inferior parietal cortex and posterior cerebellum perform functionally distinct roles in the generation of temporal expectations [3]. In the current study, we use both behavioral and neurophysiological findings to develop a theoretical account of the computational processes that underlie the generation of temporal expectations. We identify four independent processes that are critical to generating temporal expectation: (a) a pulse-generator (oscillator or other tonic activity) that relates the sensory stimulus to an internal signal (b) an integrator, that accumulates the tonic activity, generating a temporal percept, (c) a predictor, that forms a probabilistic model based on the combination of the sensory signal and its temporal percept, and (d) a process that monitors the temporal percept and dynamically updates predictions, generating a temporal expectation (see Figure ​Figure1).1). The novelty of our work lies in laying out the computational principles behind the processes (c) and (d). We propose that the brain learns to predict time by modeling sensory signals as a finite mixture of hidden temporal causes. The problem of prediction can then be translated to a Bayesian inference problem and learning can be performed through well known algorithms such as expectation maximization. The monitor updates predictions dynamically by moving through the sequence of temporal causes, a process that can be modeled as a Hidden Markov Model that progressively invalidates temporal causes with the passage of time. Figure 1 Independent stages in generation of temporal expectation. Simulating this model reproduces the faster RTs with increasing foreperiods for a rectangular distribution of foreperiods and the lack of change in RTs when using an exponential distribution of foreperiods, a well known behavioral finding [2]. In addition to these implicit timing results, simulations on the model also reproduce explicit timing results where top-down, cue-based learning is used to orient participants' attention in time [4]. Thus, our research identifies the distinct computational steps involved in the generation of temporal expectation. Prediction itself seems to require a forward modelling of sensory signals, a function typically attributed to the parietal cortex and the cerebellum [5], while dynamically updating these predictions seems to require maintaining and moving through a sequence of hypotheses, a high-level cognitive function typically attributed to the prefrontal cortex. Thus, by laying out the computations underlying each process, our study paves the way for understanding the role of different regions of the brain in predicting the time at which to expect a stimulus.

Reaction time changes with the hazard rate for a behaviorally relevant event when monkeys perform a delayed wrist movement task

Anticipating the timing of behaviorally relevant events is crucial for organizing movement. The time to initiate actions based on events (i.e., reaction time (RT)) is a useful measure to quantify states of anticipation. Few studies have examined how anticipation affects the timing of limb movements. We addressed this question behaviorally with two macaque monkeys performing delayed wrist movement tasks. The interval between target onset and go signal (i.e., foreperiod) varied randomly from 1 to 2 s. The probability that the go signal was about to occur (i.e., hazard rate) increased as the foreperiod increased. The kinematics of wrist movements was not influenced by foreperiod duration. Analyzing RT data with the LATER model indicated that RT distributions swiveled on reciprobit plots as foreperiods increased, suggesting that changes in RT distributions were due to changes in anticipation. RT was inversely related to hazard rate. To better understand the general implications of anticipatory states, we introduced an additional rectangular foreperiod distribution that ranged from 0.9 to 1.5 s. For that distribution, the hazard rate peaks were higher than those of the 1-2 s distribution. Changes in RT were clearly explained by quantitative differences in hazard rate. The decrease in RT in the 0.9-1.5 s foreperiod distribution was greater than that in the 1-2 s foreperiod. Thus, monkeys learned the temporal structure of foreperiod distributions and anticipated the onset of the go signal, based on hazard rates.

Effects of a Timing Signal on Simple Reaction Time with a Rectangular Distribution of Foreperiods

It was hypothesized that the time course of preparation during a variable interstimulus interval (ISI) of a simple reaction time (RT) experiment was partly determined by the subjective distribution of conditional probabilities of the executive signal (ES). Sixty subjects performed a simple auditory RT task with various ranges of six ISI durations organized in rectangular frequency distributions. In order to give the subjects information about elapsed time during ISI, a recurring time-marking click, the periodicity of which was varied, was introduced during the ISI in one of the three series of trials each subject performed. A strong decreasing RT–-ISI relationship was observed supporting the main hypothesis. However, a clear increase of mean RT over all ISIs combined, was also found. Because these two mixed effects were greatest when the click intervened at the possible times of ES occurrence only, three functions of time-information given by the click are discussed: (a) a reduction of the usual increase of time estimation error with increased ISI; (b) an increase of the subjects knowledge of the ISI range resulting from the discontinuity of the time-marking click which makes easier a discrete time-intervals numbering process; (c) a change of the simple-RT task into a discrimination task.

The diminishing time-uncertainty with the lapse of time after the warning signal in reaction-time experiments with varying fore-periods

The author deals with the problem as to why the shortest anticipatory, or ‘fore’-periods in a randomized series of such periods of different durations usually yield the longest reaction times, whereas the fastest reaction times are experienced with the shortest (to a certain limit) fore-periods when the fore-period is maintained constant within each set of trials. A proposed explanation is examined, one based on the increasing probability of delivery of the stimulus with the passage of time following the warning signal in experiments conducted with randomized fore periods of different durations. This explanation is tested with 13 subjects (each participating twice). It is found that when the factor of increasing probability is eliminated, the shortest fore-periods in the series no longer yield the longest reaction times. The conclusion is drawn that the main reason for the diverging tendencies noted is the information-generating nature of the passage of time following the warning signal in reaction time experiments with randomized foreperiods of different durations. Finally, four factors are proposed as exerting an influence on the relationship between the fore-period and the reaction time when varying fore-periods are delivered in random order following a rectangular distribution of fore-periods.