Atser Damsma

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 two 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.

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

ABSTRACT 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. HighlightsWe have tested whether memory consolidation determines interval timing onset.Behavioral data showed that delayed encoding did not lead to later temporal estimates.We found no relationship between P3 latency and temporal estimates.Thus, interval timing might not directly depend on working memory consolidation.

Pupillary response indexes the metrical hierarchy of unattended rhythmic violations

HighlightsPupillary responses reflect hierarchical meter even while participants are engaged in another task.Hierarchical beat perception thus requires no or only minimal attention.Beat perception was not modulated by musical expertise.Pupil dilation indexes the violation of expectancy in the absence of attention. Abstract The perception of music is a complex interaction between what we hear and our interpretation. This is reflected in beat perception, in which a listener infers a regular pulse from a musical rhythm. Although beat perception is a fundamental human ability, it is still unknown whether attention to the music is necessary to establish the perception of stronger and weaker beats, or meter. In addition, to what extent beat perception is dependent on musical expertise is still a matter of debate. Here, we address these questions by measuring the pupillary response to omissions at different metrical positions in drum rhythms, while participants attended to another task. We found that the omission of the salient first beat elicited a larger pupil dilation than the omission of the less‐salient second beat. This result shows that participants not only detected the beat without explicit attention to the music, but also perceived a metrical hierarchy of stronger and weaker beats. This suggests that hierarchical beat perception is an automatic process that requires no or minimal attentional resources. In addition, we found no evidence for the hypothesis that hierarchical beat perception is affected by musical expertise, suggesting that elementary beat perception might be independent from musical expertise. Finally, our results show that pupil dilation reflects surprise without explicit attention, demonstrating that the pupil is an accessible index to signatures of unattentive processing.

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.