Measuring event segmentation: An investigation into the stability of event boundary agreement across groups.

People spontaneously divide everyday experience into smaller units (event segmentation). To measure event segmentation, studies typically ask participants to explicitly mark the boundaries between events as they watch a movie (segmentation task). Their data may then be used to infer how others are likely to segment the same movie. However, significant variability in performance across individuals could undermine the ability to generalize across groups, especially as more research moves online. To address this concern, we used several widely employed and novel measures to quantify segmentation agreement across different sized groups (n = 2-32) using data collected on different platforms and movie types (in-lab & commercial film vs. online & everyday activities). All measures captured nonrandom and video-specific boundaries, but with notable between-sample variability. Samples of 6-18 participants were required to reliably detect video-driven segmentation behavior within a single sample. As sample size increased, agreement values improved and eventually stabilized at comparable sample sizes for in-lab & commercial film data and online & everyday activities data. Stabilization occurred at smaller sample sizes when measures reflected (1) agreement between two groups versus agreement between an individual and group, and (2) boundary identification between small (fine-grained) rather than large (coarse-grained) events. These analyses inform the tailoring of sample sizes based on the comparison of interest, materials, and data collection platform. In addition to demonstrating the reliability of online and in-lab segmentation performance at moderate sample sizes, this study supports the use of segmentation data to infer when events are likely to be segmented.

Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning.

Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.

Sleep deprivation increases the costs of attentional effort: Performance, preference and pupil size.

Sleep deprivation (SD) consistently degrades performance in tasks requiring sustained attention, resulting in slower and more variable response times that worsen with time-on-task. Loss of motivation to exert effort may exacerbate performance degradation during SD. To test this, we evaluated sustained performance on a vigilance task, combining this with an effort-based decision-making task and pupillometry. Vigilance was tested at rest and after sleep deprivation, under different incentive conditions (1, 5 or 15 cents for fast responses). Subsequently, preference measures were collected from an effort-discounting task, in which a commensurate reward was offered for maintaining attentional performance for different durations (1, 5, 10, 20 or 30 min). Vigilance was impaired during SD, in a manner modulated by reward value. Preference metrics showed that the value of available rewards was discounted by task duration, an effect compounded by SD. Pupillometry revealed that arousal was modulated during SD in a value-based manner, and moment-to-moment fluctuations in pupil diameter were directly predictive of performance. Together, these data demonstrate that attentional performance can be interpreted within a value-based effort allocation framework, such that the perceived cost of attentional effort increases after sleep deprivation.

Reward motivation normalises temporal attention after sleep deprivation.

Preparation of attention facilitates speeded responding at time points with a high probability of target occurrence. Conversely, time points with low target probability are disadvantaged due to lower readiness. When targets are uniformly distributed in time, this effect results in higher readiness after longer preparation times (foreperiods). During sleep deprivation, this temporal bias is amplified, resulting in greater performance decrement when stimuli occur at unfavourable times. In this study, we examined whether reward motivation could modulate this increased temporal bias in response speed. Participants (n = 24) performed the psychomotor vigilance task under four reward conditions (0, 1, 5 or 15c per fast response), both after normal sleep (rested wakefulness) and sleep deprivation. To assess temporal preparation (foreperiod-effect), trials were binned based on the lead time prior to target presentation (short foreperiod: 1-6 s; long foreperiod: 6-10 s). As previously observed, the foreperiod-effect (slower reaction time for short foreperiod trials) increased after sleep deprivation. However, this state effect was attenuated with reward, reaching a response speed comparable to that observed in the unrewarded, well-rested condition. The current findings, therefore, suggest that reward improves overall response performance and normalises temporal attention in sleep-deprived individuals.

Motivation alters implicit temporal attention through sustained and transient mechanisms: A behavioral and pupillometric study.

Temporal expectations aid performance by allowing the optimization of attentional readiness at moment of highest target probability. Reward enhances cognitive performance through its action on preparatory and reactive attentional processes. To elucidate how motivation interacts with mechanisms of implicit temporal attention, we studied healthy young adult participants (N = 73) performing a sustained attention task with simultaneous pupillometric recording, under different reward conditions (baseline: 0 c; reward: 10 c/fast response). Target timing was temporally unpredictable (variable foreperiod: 2-10 s, uniformly distributed), in which case implicitly formed timing expectations. Trials were binned according to current foreperiod (FPn ; short: 2-6 s; long: 6-10 s) and preceding foreperiod (FPn-1 ; short: 2-6 s; long: 6-10 s). Overall, performance data showed the expected temporal attention effects, with slower responses after shorter FPn s, particularly when they followed longer FPn-1 s. Moreover, these temporal effects were significantly reduced in the reward condition. While performance improved in all trial types, the largest benefit appeared in trials that were normally most disadvantaged by invalid temporal expectation. Furthermore, reward motivation was accompanied by an increase in sustained (prestimulus) and transient (poststimulus response) pupil diameter. The latter effect was particularly evident following short FPn s. The current findings suggest that reward motivation can improve overall attentional performance and reduce implicit temporal bias, both through preparatory and reactive attentional mechanisms.

Sustained benefits of delaying school start time on adolescent sleep and well-being.

Study Objectives: To investigate the short- and longer-term impact of a 45-min delay in school start time on sleep and well-being of adolescents. Methods: The sample consisted of 375 students in grades 7-10 (mean age ± SD: 14.6 ± 1.15 years) from an all-girls' secondary school in Singapore that delayed its start time from 07:30 to 08:15. Self-reports of sleep timing, sleepiness, and well-being (depressive symptoms and mood) were obtained at baseline prior to the delay, and at approximately 1 and 9 months after the delay. Total sleep time (TST) was evaluated via actigraphy. Results: After 1 month, bedtimes on school nights were delayed by 9.0 min, while rise times were delayed by 31.6 min, resulting in an increase in time in bed (TIB) of 23.2 min. After 9 months, the increase in TIB was sustained, and TST increased by 10.0 min relative to baseline. Participants also reported lower levels of subjective sleepiness and improvement in well-being at both follow-ups. Notably, greater increase in sleep duration on school nights was associated with greater improvement in alertness and well-being. Conclusions: Delaying school start time can result in sustained benefits on sleep duration, daytime alertness, and mental well-being even within a culture where trading sleep for academic success is widespread.

Memory encoding is impaired after multiple nights of partial sleep restriction.

Sleep is important for normative cognitive functioning. A single night of total sleep deprivation can reduce the capacity to encode new memories. However, it is unclear how sleep restriction during several consecutive nights affects memory encoding. To explore this, we employed a parallel-group design with 59 adolescents randomized into sleep-restricted (SR) and control groups. Both groups were afforded 9 h time in bed (TIB) for 2 baseline nights, followed by 5 consecutive nights of 5 h TIB for the SR group (n = 29) and 9 h TIB for the control group (n = 30). Participants then performed a picture-encoding task. Encoding ability was measured with a recognition test after 3 nights of 9 h TIB recovery sleep for both groups, allowing the assessment of encoding ability without the confounding effects of fatigue at retrieval. Memory was significantly worse in the sleep-restricted group (P = 0.001), and this impairment was not correlated with decline in vigilance. We conclude that memory-encoding deteriorates after several nights of partial sleep restriction, and this typical pattern of sleep negatively affects adolescents' ability to learn declarative information.

Rewards boost sustained attention through higher effort: A value-based decision making approach.

Maintaining sustained attention over time is an effortful process limited by finite cognitive resources. Recent theories describe the role of motivation in the allocation of such resources as a decision process: the costs of effortful performance are weighed against its gains. We examined this hypothesis by combining methods from attention research and decision neuroscience. Participants first performed a sustained attention task at different levels of reward. They then performed a reward-discounting task, measuring the subjective costs of performance. Results demonstrated that higher rewards led to improved performance (Exp 1-3), and enhanced attentional effort (i.e. pupil diameter; Exp 2 & 3). Moreover, discounting curves constructed from the choice task indicated that subjects devalued rewards that came at the cost of staying vigilant for a longer duration (Exp 1 & 2). Motivation can thus boost sustained attention through increased effort, while sustained performance is regarded as a cost against which rewards are discounted.