Memory traces of duration and location in the right intraparietal sulcus.

Time and space form an integral part of every human experience, and for the neuronal representation of these perceptual dimensions, previous studies point to the involvement of the right-hemispheric intraparietal sulcus and structures in the medial temporal lobe. Here we used multi-voxel pattern analysis (MVPA) to investigate long-term memory traces for temporal and spatial stimulus features in those areas. Participants were trained on four images associated with short versus long durations and with left versus right locations. Our results demonstrate stable representations of both temporal and spatial information in the right posterior intraparietal sulcus. Building upon previous findings of stable neuronal codes for directly perceived durations and locations, these results show that the reactivation of long-term memory traces for temporal and spatial features can be decoded from neuronal activation patterns in the right parietal cortex.

Adaptive Encoding Speed in Working Memory.

Humans can adapt when complex patterns unfold at a faster or slower pace, for instance when remembering a grocery list that is dictated at an increasingly fast rate. Integrating information over such timescales crucially depends on working memory, but although recent findings have shown that working memory capacity can be flexibly adapted, such adaptations have not yet been demonstrated for encoding speed. In a series of experiments, we found that young adults encoded at a faster rate when they were adapted to overall and recent stimulus duration. Interestingly, our participants were unable to use explicit cues to speed up encoding, even though these cues were objectively more informative than statistical information. Our findings suggest that adaptive tuning of encoding speed in working memory is a fundamental but largely implicit mechanism underlying our ability to keep up with the pace of our surroundings.

Prior Knowledge Norms for Naming Country Outlines: An Open Stimulus Set.

Paired-associate stimuli are an important tool in learning and memory research. In cognitive psychology, many studies use materials of which the learners are expected to have little to no prior knowledge. Despite their theoretical usefulness, conclusions from these studies are difficult to generalize to real-world learning contexts, where learners can be expected to have varying degrees of prior knowledge. Here, we present an ecologically valid stimulus set with 112 country outline-name pairs, and report response times and prior knowledge for these items in 285 largely Western European participants. Prior knowledge per item ranged from very high (94.4%) to zero (0.3%), thereby allowing researchers to select materials of which participants can be expected to have any given amount of prior knowledge. As such, this database provides a useful tool for research on real-world learning. The database can be accessed at: https://osf.io/q25rd/.

Addendum: Implicit learning of temporal behavior in complex dynamic environments.

New analyses of the data in this study (Salet et al., 2021, Psychonomic Bulletin & Review, https://doi.org/10.3758/s13423-020-01873-x ) have led us to reinterpret our main finding. Previously, we had attributed better performance for targets appearing at regular intervals versus irregular intervals to "temporal statistical learning." That is, we surmised that this benefit for the regular intervals arises because participants implicitly distilled the regular 3000 ms interval from the otherwise variable environment (i.e., irregular intervals) to predict future (regular) targets. The analyses presented in this Addendum, however, show that this benefit can be attributed to ongoing "temporal preparation" rather than temporal statistical learning.

Still stuck with the stopwatch.

Time is an integral part of all adaptive behavior; we continuously adapt to the dynamic structure of an ever-changing environment. Recent theoretical approaches have moved from the idea that time arises from specialized stopwatch-like mechanisms, instead proposing the view that time is inherently encoded in a host of neural dynamics. However, we argue that much of our theorizing is-even when an intrinsic view is proposed-still driven by the implicit assumption that clearly marked, isolated stopwatch-like intervals are the fundamental unit of time in our environment. This assumption ignores the challenges of interacting with an uncertain, ever-changing environment: (a) Relevant intervals need to be distilled from a continuous stream of actions and events, and (b) time is never estimated for its own sake but instead used to adaptively tune cognition. We discuss an "intrinsic-adaptive" view that, in contrast to studying isolated stopwatch intervals, considers how organisms learn and adapt behavior to temporal structures from experience in natural worlds. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Reducing the tendency for chronometric counting in duration discrimination tasks.

Chronometric counting is a prevalent issue in the study of human time perception as it reduces the construct validity of tasks and can conceal existing timing deficits. Several methods have been proposed to prevent counting strategies, but the factors promoting those strategies in specific tasks are largely uninvestigated. Here, we modified a classical two-interval duration discrimination task in two aspects that could affect the tendency to apply counting strategies. We removed the pause between the two intervals and changed the task instructions: Participants decided whether a short event occurred in the first or in the second half of a reference duration. In Experiment 1, both classical and modified task versions were performed under timing conditions, in which participants were asked not to count, and counting conditions, in which counting was explicitly instructed. The task modifications led to (i) a general decrease in judgment precision, (ii) a shift of the point of subjective equality, and (iii) a counting-related increase in reaction times, suggesting enhanced cognitive effort of counting during the modified task version. Precision in the two task versions was not differently affected by instructed counting. Experiment 2 demonstrates that-in the absence of any counting-related instructions-participants are less likely to engage in spontaneous counting in the modified task version. These results enhance our understanding of the two-interval duration discrimination task and demonstrate that the modifications tested here-although they do not significantly reduce the effectiveness of instructed counting-can diminish the spontaneous tendency to adopt counting strategies.

Capturing Dynamic Performance in a Cognitive Model: Estimating ACT-R Memory Parameters With the Linear Ballistic Accumulator.

The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT-R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competition between evidence accumulation processes. We show that this mapping provides a method for inferring individual ACT-R parameters without requiring the modeler to build and fit an entire ACT-R model. Existing parameter estimation methods for the LBA can be used, instead of the computationally expensive parameter sweeps that are traditionally done. We conduct a parameter recovery study to confirm that the LBA can recover ACT-R parameters from simulated data. Then, as a proof of concept, we use the LBA to estimate ACT-R parameters from an empirical dataset. The resulting parameter estimates provide a cognitively meaningful explanation for observed differences in behavior over time and between individuals. In addition, we find that the mapping between ACT-R and LBA lends a more concrete interpretation to ACT-R's latency factor parameter, namely as a measure of response caution. This work contributes to a growing movement towards integrating formal modeling approaches in cognitive science.

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).

Temporal context effects are associated with cognitive status in advanced age.

The perception of temporal intervals changes during the life-span, and especially older adults demonstrate specific impairments of timing abilities. Recently, we demonstrated that timing performance and cognitive status are correlated in older adults, suggesting that timing tasks can serve as a behavioral marker for the development of dementia. Easy-to-administer and retest-capable timing tasks therefore have potential as diagnostic tools for tracking cognitive decline. However, before being tested in a clinical cohort study, a further validation and specification of the original findings is warranted. Here we introduce several modifications of the original task and investigated the effects of temporal context on time perception in older adults (> 65 years) with low versus high scores in the Montreal Cognitive Assessment survey (MoCA) and a test of memory functioning. In line with our previous work, we found that temporal context effects were more pronounced with increasing memory deficits, but also that these effects are stronger for realistic compared to abstract visual stimuli. Furthermore, we show that two distinct temporal contexts influence timing behavior in separate experimental blocks, as well as in a mixed block in which both contexts are presented together. These results replicate and extend our previous findings. They demonstrate the stability of the effect for different stimulus material and show that timing tasks can reveal valuable information about the cognitive status of older adults. In the future, these findings could serve as a basis for the development of a diagnostic tool for pathological cognitive decline at an early, pre-clinical stage.

Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning.

Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in word learning where spoken instead of typed input is used. Here we present a framework for speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes. We extend earlier findings demonstrating that a response-time based adaptive learning approach outperforms an accuracy-based, Leitner flashcard approach in learning efficiency (demonstrated by higher average accuracy and lower response times after a learning session). In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner's pronunciations. We discuss the implications for our approach for the development of educationally relevant, adaptive speech-based learning applications.

Change biases identify the features that drive time perception.

Time perception is malleable, and the perceived duration of stimuli can be strongly affected by the sensory response they evoke. Such "temporal illusions" provide a window on how different sensory systems contribute to our sense of time. Evidence suggests that the sensory response to different features affects time perception to different extents, mediated by the level of arousal or surprise that they evoke. This, however, makes it difficult to disentangle effects of the sensory response itself from the derived arousal or surprise effects. Here, we demonstrate that time perception is differentially affected by different stimulus features when arousal and surprise are kept constant. In four temporal discrimination experiments, participants were presented with empty intervals (1.25 s-2.25 s) marked by two briefly presented visual marker stimuli, and judged whether the duration was longer or shorter than a 1.75 s reference. Markers either repeated or changed along one of six feature dimensions, in a manner fully predictable to participants. Repetitions and changes would modulate sensory response magnitudes due to neural repetition suppression. Results showed that intervals were perceived as longer when markers changed in location, size, or numerosity. Conversely, changes in face identity, orientation or luminance did not affect time perception. These results point to neural and functional selectivity in the way different stimulus features affect time perception. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Neural Repetition Suppression Modulates Time Perception: Evidence From Electrophysiology and Pupillometry.

Human time perception is malleable and subject to many biases. For example, it has repeatedly been shown that stimuli that are physically intense or that are unexpected seem to last longer. Two competing hypotheses have been proposed to account for such biases: One states that these temporal illusions are the result of increased levels of arousal that speeds up neural clock dynamics, whereas the alternative "magnitude coding" account states that the magnitude of sensory responses causally modulates perceived durations. Common experimental paradigms used to study temporal biases cannot dissociate between these accounts, as arousal and sensory magnitude covary and modulate each other. Here, we present two temporal discrimination experiments where two flashing stimuli demarcated the start and end of a to-be-timed interval. These stimuli could be either in the same or a different location, which led to different sensory responses because of neural repetition suppression. Crucially, changes and repetitions were fully predictable, which allowed us to explore effects of sensory response magnitude without changes in arousal or surprise. Intervals with changing markers were perceived as lasting longer than those with repeating markers. We measured EEG (Experiment 1) and pupil size (Experiment 2) and found that temporal perception was related to changes in ERPs (P2) and pupil constriction, both of which have been related to responses in the sensory cortex. Conversely, correlates of surprise and arousal (P3 amplitude and pupil dilation) were unaffected by stimulus repetitions and changes. These results demonstrate, for the first time, that sensory magnitude affects time perception even under constant levels of arousal.

Memory for Stimulus Duration Is Not Bound to Spatial Information.

Different theories have been proposed to explain how the human brain derives an accurate sense of time. One specific class of theories, intrinsic clock theories, postulate that temporal information of a stimulus is represented much like other features such as color and location, bound together to form a coherent percept. Here, we explored to what extent this holds for temporal information after it has been perceived and is held in working memory for subsequent comparison. We recorded EEG of participants who were asked to time stimuli at lateral positions of the screen followed by comparison stimuli presented in the center. Using well-established markers of working memory maintenance, we investigated whether the usage of temporal information evoked neural signatures that were indicative of the location where the stimuli had been presented, both during maintenance and during comparison. Behavior and neural measures including the contralateral delay activity, lateralized alpha suppression, and decoding analyses through time all supported the same conclusion: The representation of location was strongly involved during perception of temporal information, but when temporal information was to be used for comparison, it no longer showed a relation to spatial information. These results support a model where the initial perception of a stimulus involves intrinsic computations, but that this information is subsequently translated to a stimulus-independent format to be used to further guide behavior.

Conceptually plausible Bayesian inference in interval timing.

In a world that is uncertain and noisy, perception makes use of optimization procedures that rely on the statistical properties of previous experiences. A well-known example of this phenomenon is the central tendency effect observed in many psychophysical modalities. For example, in interval timing tasks, previous experiences influence the current percept, pulling behavioural responses towards the mean. In Bayesian observer models, these previous experiences are typically modelled by unimodal statistical distributions, referred to as the prior. Here, we critically assess the validity of the assumptions underlying these models and propose a model that allows for more flexible, yet conceptually more plausible, modelling of empirical distributions. By representing previous experiences as a mixture of lognormal distributions, this model can be parametrized to mimic different unimodal distributions and thus extends previous instantiations of Bayesian observer models. We fit the mixture lognormal model to published interval timing data of healthy young adults and a clinical population of aged mild cognitive impairment patients and age-matched controls, and demonstrate that this model better explains behavioural data and provides new insights into the mechanisms that underlie the behaviour of a memory-affected clinical population.

Discovering the brain stages of lexical decision: Behavioral effects originate from a single neural decision process.

Lexical decision (LD) - judging whether a sequence of letters constitutes a word - has been widely investigated. In a typical lexical decision task (LDT), participants are asked to respond whether a sequence of letters is an actual word or a nonword. Although behavioral differences between types of words/nonwords have been robustly detected in LDT, there is an ongoing discussion about the exact cognitive processes that underlie the word identification process in this task. To obtain data-driven evidence on the underlying processes, we recorded electroencephalographic (EEG) data and applied a novel machine-learning method, hidden semi-Markov model multivariate pattern analysis (HsMM-MVPA). In the current study, participants performed an LDT in which we varied the frequency of words (high, low frequency) and "wordlikeness" of non-words (pseudowords, random non-words). The results revealed that models with six processing stages accounted best for the data in all conditions. While most stages were shared, Stage 5 differed between conditions. Together, these results indicate that the differences in word frequency and lexicality effects are driven by a single cognitive processing stage. Based on its latency and topology, we interpret this stage as a Decision process during which participants discriminate between words and nonwords using activated lexical information.

Age-related changes in time perception: The impact of naturalistic environments and retrospective judgements on timing performance.

Reduced timing abilities have been reported in older adults and are associated with pathological cognitive decline. However, time perception experiments often lack ecological validity. Especially the reduced complexity of experimental stimuli and the participants' awareness of the time-related nature of the task can influence lab-assessed timing performance and thereby conceal age-related differences. An approximation of more naturalistic paradigms can provide important information about age-related changes in timing abilities. To determine the impact of higher ecological validity on timing experiments, we implemented a paradigm that allowed us to test (1) the effect of embedding the to-be-timed stimuli within a naturalistic visual scene and (2) the effect of retrospective time judgements, which are more common in real life than prospective judgements. The results show that compared with out-of-context stimuli, younger adults benefit from a naturalistic embedding of stimuli (reflected in higher precision and less errors), whereas the performance of older adults is reduced when confronted with naturalistic stimuli. Differences between retrospective and prospective time judgements were not modulated by age. We conclude that, potentially driven by difficulties in suppressing temporally irrelevant environmental information, the contextual embedding of naturalistic stimuli can affect the degree to which age influences the performance in time perception tasks.

Implicit learning of temporal behavior in complex dynamic environments.

Humans can automatically detect and learn to exploit repeated aspects (regularities) of the environment. Timing research suggests that such learning is not only used to anticipate what will happen, but also when it will happen. However, in timing experiments, the intervals to be timed are presented in isolation from other stimuli and explicitly cued, contrasting with naturalistic environments in which intervals are embedded in a constant stream of events and individuals are hardly aware of them. It is unclear whether laboratory findings from timing research translate to a more ecologically valid, implicit environment. Here we show in a game-like experiment, specifically designed to measure naturalistic behavior, that participants implicitly use regular intervals to anticipate future events, even when these intervals are constantly interrupted by irregular yet behaviorally relevant events. This finding extends previous research by showing that individuals not only detect such regularities but can also use this knowledge to decide when to act in a complex environment. Furthermore, this finding demonstrates that this type of learning can occur independently from the ordinal sequence of motor actions, which contrasts this work with earlier motor learning studies. Taken together, our results demonstrate that regularities in the time between events are implicitly monitored and used to predict and act on what happens when, thereby showing that laboratory findings from timing research can generalize to naturalistic environments. Additionally, with the development of our game-like experiment, we demonstrate an approach to test cognitive theories in less controlled, ecologically more valid environments.

How Children Process Reduced Forms: A Computational Cognitive Modeling Approach to Pronoun Processing in Discourse.

Reduced forms such as the pronoun he provide little information about their intended meaning compared to more elaborate descriptions such as the lead singer of Coldplay. Listeners must therefore use contextual information to recover their meaning. Across languages, there appears to be a trade-off between the informativity of a form and the prominence of its referent. For example, Italian adults generally interpret informationally empty null pronouns as in the sentence Corre (meaning "He/She/It runs") as referring to the most prominent referent in the discourse, and more informative overt pronouns (e.g., lui in Lui corre, "He runs") as referring to less prominent referents. Although children acquiring Italian are known to experience difficulties interpreting pronouns, it is unclear how they acquire this division of pragmatic labor between null and overt subject pronouns, and how this relates to the development of their cognitive capacities. Here we show that cognitive development can account for the general interpretation patterns displayed by Italian-speaking children and adults. Using experimental studies and computational simulations in a framework modeling bounded-rational behavior, we argue that null pronoun interpretation is influenced by working memory capacity and thus appears to depend on discourse context, whereas overt pronoun interpretation is influenced by processing speed, suggesting that listeners must reason about the speaker's choices. Our results demonstrate that cognitive capacities may constrain the acquisition of linguistic forms and their meanings in various ways. The novel predictions generated by the computational simulations point out several directions for future research.

Temporal Context Actively Shapes EEG Signatures of Time Perception.

Our subjective perception of time is optimized to temporal regularities in the environment. This is illustrated by the central tendency effect: When estimating a range of intervals, short intervals are overestimated, whereas long intervals are underestimated to reduce the overall estimation error. Most models of interval timing ascribe this effect to the weighting of the current interval with previous memory traces after the interval has been perceived. Alternatively, the perception of the duration could already be flexibly tuned to its temporal context. We investigated this hypothesis using an interval reproduction task in which human participants (both sexes) reproduced a shorter and longer interval range. As expected, reproductions were biased toward the subjective mean of each presented range. EEG analyses showed that temporal context indeed affected neural dynamics during the perception phase. Specifically, longer previous durations decreased contingent negative variation and P2 amplitude and increased beta power. In addition, multivariate pattern analysis showed that it is possible to decode context from the transient EEG signal quickly after both onset and offset of the perception phase. Together, these results suggest that temporal context creates dynamic expectations which actively affect the perception of duration.SIGNIFICANCE STATEMENT The subjective sense of duration does not arise in isolation, but is informed by previous experiences. This is demonstrated by abundant evidence showing that the production of duration estimates is biased toward previously experienced time intervals. However, it is yet unknown whether this temporal context actively affects perception or only asserts its influence in later, postperceptual stages as proposed by most current formal models of this task. Using an interval reproduction task, we show that EEG signatures flexibly adapt to the temporal context during perceptual encoding. Furthermore, interval history can be decoded from the transient EEG signal even when the current duration was identical. Thus, our results demonstrate that context actively influences perception.

Attention Does Not Affect the Speed of Subjective Time, but Whether Temporal Information Guides Performance: A Large-Scale Study of Intrinsically Motivated Timers in a Real-Time Strategy Game.

Many prepared actions have to be withheld for a certain amount of time in order to have the most beneficial outcome. Therefore, keeping track of time accurately is vital to using temporal regularities in our environment. Traditional theories assume that time is tracked by means of a clock and an "attentional gate" (AG) that modulates subjective time if not enough attentional resources are directed toward the temporal process. According to the AG theory, the moment of distraction does not have an influence on the subjective modulation. Here, we show, based on an analysis of 28,354 datasets, that highly motivated players of the online multiplayer real-time strategy game StarCraft2 indeed respond later to timed events when they are distracted by other tasks during the interval. However, transient periods of distraction during the interval influence the response time to a lesser degree than distraction just before the required response. We extend the work of Taatgen, van Rijn, and Anderson (2007) and propose an alternative active check theory that postulates that distracted attention prevents people from checking their internal clock; we demonstrate that this account better predicts variance observed in response time. By analyzing StarCraft2 data, we assessed the role of attention in a naturalistic setting that more directly generalizes to real-world settings than typical laboratory studies.