Adaptive Timing

Four minutes at the bus stop can feel like an eternity, while time flies when we are watching an enjoyable movie. Our sense of time is very elastic. In this thesis, we investigate how people use previous experiences to predict how long something will last and when something will happen.We show that experiences in memory have a direct influence on the way we experience time. When participants estimated a duration, we observed a faster build-up of brain activity if they had just estimated shorter durations. The brain does not seem to work like a static stopwatch, but instead creates active expectations based on previous experiences.Does this mechanism of expectations still work when we are doing something else, for example, when we are listening to music while working? Our results show that people perceive drum rhythms in a musical way, even when they are performing another task. We observed that the size of the pupil increased when a beat was omitted from the rhythm. And the more important the beat, the larger the pupil. Thus, our eyes reveal how musical we subconsciously are.All in all, this thesis shows that time can be seen as an inherent part of brain processes that adapt to a dynamically changing world

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

VR : Time Machine

Time Machine is an immersive Virtual Reality installation that explains – in simple terms – the Striatal Beat Frequency (SBF) model of time perception. The installation was created as a collaboration between neuroscientists within the field of time perception along with a team of digital designers and audio composers/engineers. This paper outlines the process, as well as the lessons learned, while designing the virtual reality experience that aims to simplify a complex idea to a novice audience. The authors describe in detail the process of creating the world, the user experience mechanics and the methods of placing information in the virtual place in order to enhance the learning experience. The work was showcased at the 4th International Conference on Time Perspective, where the authors collected feedback from the audience. The paper concludes with a reflection on the work and some suggestions for the next iteration of the project

Neural markers of memory consolidation do not predict temporal estimates of encoded items

In contrast to the paradigms used in most laboratory experiments on interval timing, everyday tasks often involve tracking multiple, concurrent intervals without an explicit starting signal. As these characteristics are problematic for most existing clock-based models of interval timing, here we explore an alternative notion that suggests that time perception and working memory encoding might be closely connected. In this integrative model, the consolidation of a new item in working memory initiates cortical oscillations that also signal the onset of a time interval. The objective of this study was to test whether memory consolidation indeed acts as the starting signal of interval timing. Participants performed an attentional blink task in which they not only reported the targets, but also the estimated target onsets, allowing us to calculate estimated lag. In the attentional blink task, the second target (T2) in a rapid serial visual presentation is often not reported when it follows quickly after the first target (T1). However, if this fast T2 is reported, memory consolidation of T2 is presumably delayed. Consequently, if memory consolidation determines interval onset, we would expect a later estimated onset when consolidation is delayed. Furthermore, as the P3 ERP component is assumed to reflect memory consolidation, we expect that the estimated onsets and subjective lag are functions of the P3 latencies. The behavioral data show that the presumed delay in memory consolidation did not lead to later estimated onsets. In addition, the EEG results suggest that there was no relationship between P3 latency and subjective lag or estimated onset. Overall, our results suggest that there is no direct link between the encoding of items in working memory and sub-second interval timing of these items in the attentional blink task

Individual optimization of risky decisions in duration and distance estimations

Many everyday decisions require an accurate perception of how much time has passed since a previous event. Although humans estimate time intervals with a high degree of mean accuracy, the precision of estimations varies greatly between individuals. In situations in which accurate timing is rewarded but responding too early is punished, the optimal amount of risk is directly dependent on the precision of the timer. Previously, it was found that humans and rodents displayed near-optimal adjustment of their mean response time based on their individual precision and the level of punishment. It is as of yet unknown whether these strategies of optimality in interval timing are specific to the timing domain, or instead reflect an ability that generalizes to other sensorimotor modalities of decision making. Here, we address this by combining a temporal reproduction experiment and a distance estimation experiment with an identical reward scheme. We found that participants approached optimality in both tasks, but generally underadjusted their responses in the face of high risk. As this individual adjustment was consistent over modalities, these results can best be explained by assuming that the adjustment of behavior towards optimal performance is driven by a modality independent mechanism

Temporal context influences the perceived duration of everyday actions:Assessing the ecological validity of lab-based timing phenomena

Timing is key to accurate performance, for example when learning a new complex sequence by mimicry. However, most timing research utilizes artificial tasks and simple stimuli with clearly marked onset and offset cues. Here we address the question whether existing interval timing findings generalize to real-world timing tasks. In this study, animated video clips of a person performing different everyday actions were presented and participants had to reproduce the main action’s duration. Although reproduced durations are more variable then observed in laboratory studies, the data adheres to two interval timing laws: Relative timing sensitivity is constant across durations (scalar property), and the subjective duration of a previous action influenced the current action’s perceived duration (temporal context effect). Taken together, this demonstrates that laboratory findings generalize, and paves the way for studying interval timing as a component of complex, everyday cognitive performance

Estimating time: comparing the accuracy of estimation methods for interval timing

In interval timing experiments, motor reproduction is the predominant method used when participants are asked to estimate an interval. However, it is unknown how its accuracy, precision and efficiency compare to alternative methods, such as indicating the duration by spatial estimation on a timeline. In two experiments, we compared different interval estimation methods. In the first experiment, participants were asked to reproduce an interval by means of motor reproduction, timeline estimation, or verbal estimation. We found that, on average, verbal estimates were more accurate and precise than line estimates and motor reproductions. However, we found a bias towards familiar whole second units when giving verbal estimates. Motor reproductions were more precise, but not more accurate than timeline estimates. In the second experiment, we used a more complex task: Participants were presented a stream of digits and one target letter and were subsequently asked to reproduce both the interval to target onset and the duration of the total stream by means of motor reproduction and timeline estimation. We found that motor reproductions were more accurate, but not more precise than timeline estimates. In both experiments, timeline estimates had the lowest reaction times. Overall, our results suggest that the transformation of time into space has only a relatively minor cost. In addition, they show that each estimation method comes with its own advantages, and that the choice of estimation method depends on choices in the experimental design: for example, when using durations with integer durations verbal estimates are superior, yet when testing long durations, motor reproductions are time intensive making timeline estimates a more sensible choice

Training-induced Changes in the Dynamics of Attention as Reflected in Pupil Dilation

One of the major topics in attention literature is the attentional blink (AB), which demonstrates a limited ability to identify the second of two targets (T1 and T2) when presented in close temporal succession (200–500 msec). Given that the effect has been thought of as robust and resistant to training for over 2 decades, one of the most remarkable findings in recent years is that the AB can be eliminated after a 1-hr training with a color-salient T2. However, the underlying mechanism of the training effect as well as the AB itself is as of yet still poorly understood. To elucidate this training effect, we employed a refined version of our recently developed pupil dilation deconvolution method to track any training-induced changes in the amount and onset of attentional processing in response to target stimuli. Behaviorally, we replicated the original training effect with a color-salient T2. However, we showed that training without a salient target, but with a consistent short target interval, is already sufficient to attenuate the AB. Pupil deconvolution did not reveal any posttraining changes in T2-related dilation but instead an earlier onset of dilation around T1. Moreover, normalized pupil dilation was enhanced posttraining compared with pretraining. We conclude that the AB can be eliminated by training without a salient cue. Furthermore, our data point to the existence of temporal expectations at the time points of the trained targets posttraining. Therefore, we tentatively conclude that temporal expectations arise as a result of training

No evidence for an attentional bias towards implicit temporal regularities

Action and perception are optimized by exploiting temporal regularities, and it has been suggested that the attentional system prioritizes information that contains some form of structure. Indeed, Zhao, Al-Aidroos, and Turk-Browne (Psychological Science, 24(5), 667-677, 2013) found that attention was biased towards the location and low-level visual features of shapes that appeared with a regular order but were irrelevant for the main search task. Here, we investigate whether this bias also holds for irrelevant metrical temporal regularities. In six experiments, participants were asked to perform search tasks. In Experiments 1a-d, sequences of squares, each presented at one of four locations, appeared in between the search trials. Crucially, in one location, the square appeared with a regular rhythm, whereas the timing in the other locations was random. In Experiments 2a and 2b, a sequence of centrally presented colored circles was shown in between the search trials, of which one specific color appeared regularly. We expected that, if attention is automatically biased towards these temporal regularities, reaction times would be faster if the target matches the location (Experiments 1a-d) or color (Experiments 2a-b) of the regular stimulus. However, no reaction time benefit was observed for these targets, suggesting that there was no attentional bias towards the regularity. In addition, we found no evidence for attentional entrainment to the rhythmic stimulus. These results suggest that people do not use implicit rhythmic temporal regularities to guide their attention in the same way as they use order regularities