Our behavior is guided by the statistical regularities in the environment. Prior research on temporal context effects has highlighted the dynamic processes through which humans adapt to the environment's temporal regularities. Whereas earlier approaches have focused on the adaptation to traces of previous individual events, real-world performance often requires extracting and retaining summary statistics (e.g., the mean) of temporal distributions. To investigate these summary representations for temporal distributions and to test their sensitivity to distributional changes, we explicitly asked participants to extract the mean of different distributions of time intervals, which shared the same mean but varied in their variability specifically operationalized by the width and presentation frequency of the intervals. Our findings showed that the variability of the estimated mean increased with the distributions' variability, even though the actual mean remained constant. We further examined how such learning of temporal distributions modulates EEG signals during subsequent temporal judgments. An analysis revealed that the contingent negative variation, predictive of single-trial RTs, was correlated with how much individuals' estimates of the mean were affected by the distributions' variability. Conversely, the postinterval P2 was not modulated by the distributions but predicted participants' responses, suggesting that P2 reflects the perceived duration of an interval. Taken together, our results demonstrate not only that humans can accurately estimate the mean of a temporal distribution but also that the representation of the mean becomes more uncertain as the variability of the distribution increases, as reflected neurally in the preparation-related contingent negative variation during temporal decisions.

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.

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.

Dating back to the 19th century, the discovery of processing stages has been of great interest to researchers in cognitive science. The goal of this paper is to demonstrate the validity of a recently developed method, hidden semi-Markov model multivariate pattern analysis (HsMM-MVPA), for discovering stages directly from EEG data, in contrast to classical reaction-time-based methods. To test the validity of stages discovered with the HsMM-MVPA method, we applied it to two relatively simple tasks where the interpretation of processing stages is straightforward. In these visual discrimination EEG data experiments, perceptual processing and decision difficulty were manipulated. The HsMM-MVPA revealed that participants progressed through five cognitive processing stages while performing these tasks. The brain activation of one of those stages was dependent on perceptual processing, whereas the brain activation and the duration of two other stages were dependent on decision difficulty. In addition, evidence accumulation models (EAMs) were used to assess to what extent the results of HsMM-MVPA are comparable to standard reaction-time-based methods. Consistent with the HsMM-MVPA results, EAMs showed that nondecision time varied with perceptual difficulty and drift rate varied with decision difficulty. Moreover, nondecision and decision time of the EAMs correlated highly with the first two and last three stages of the HsMM-MVPA, respectively, indicating that the HsMM-MVPA gives a more detailed description of stages discovered with this more classical method. The results demonstrate that cognitive stages can be robustly inferred with the HsMM-MVPA.

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

Human memory benefits from information clustering, which can be accomplished by chunking. Chunking typically relies on expertise and strategy, and it is unknown whether perceptual clustering over time, through temporal integration, can also enhance working memory. The current study examined the attentional and working memory costs of temporal integration of successive target stimulus pairs embedded in rapid serial visual presentation. ERPs were measured as a function of behavioral reports: One target, two separate targets, or two targets reported as a single integrated target. N2pc amplitude, reflecting attentional processing, depended on the actual number of successive targets. The memory-related CDA and P3 components instead depended on the perceived number of targets irrespective of their actual succession. The report of two separate targets was associated with elevated amplitude, whereas integrated as well as actual single targets exhibited lower amplitude. Temporal integration thus provided an efficient means of processing sensory input, offloading working memory so that the features of two targets were consolidated and maintained at a cost similar to that of a single target.