Humans anticipate events signaled by sensory cues. It is commonly assumed that two uncertainty parameters modulate the brain's capacity to predict: the hazard rate (HR) of event probability and the uncertainty in time estimation which increases with elapsed time. We investigate both assumptions by presenting event probability density functions (PDFs) in each of three sensory modalities. We show that perceptual systems use the reciprocal PDF and not the HR to model event probability density. We also demonstrate that temporal uncertainty does not necessarily grow with elapsed time but can also diminish, depending on the event PDF. Previous research identified neuronal activity related to event probability in multiple levels of the cortical hierarchy (sensory (V4), association (LIP), motor and other areas) proposing the HR as an elementary neuronal computation. Our results—consistent across vision, audition, and somatosensation—suggest that the neurobiological implementation of event anticipation is based on a different, simpler and more stable computation than HR: the reciprocal PDF of events in time.

The environment is shaped by two sources of temporal uncertainty: the discrete probability of whether an event will occur and—if it does—the continuous probability of when it will happen. These two types of uncertainty are fundamental to every form of anticipatory behavior including learning, decision-making, and motor planning. It remains unknown how the brain models the two uncertainty parameters and how they interact in anticipation. It is commonly assumed that the discrete probability of whether an event will occur has a fixed effect on event expectancy over time. In contrast, we first demonstrate that this pattern is highly dynamic and monotonically increases across time. Intriguingly, this behavior is independent of the continuous probability of when an event will occur. The effect of this continuous probability on anticipation is commonly proposed to be driven by the hazard rate (HR) of events. We next show that the HR fails to account for behavior and propose a model of event expectancy based on the probability density function of events. Our results hold for both vision and audition, suggesting independence of the representation of the two uncertainties from sensory input modality. These findings enrich the understanding of fundamental anticipatory processes and have provocative implications for many aspects of behavior and its neural underpinnings.

The increasing number of casting shows and talent contests in the media over the past years suggests a public interest in rating the quality of vocal performances. In many of these formats, laymen alongside music experts act as judges. Whereas experts' judgments are considered objective and reliable when it comes to evaluating singing voice, little is known about laymen’s ability to evaluate peers. On the one hand, layman listeners–who by definition did not have any formal training or regular musical practice–are known to have internalized the musical rules on which singing accuracy is based. On the other hand, layman listeners’ judgment of their own vocal skills is highly inaccurate. Also, when compared with that of music experts, their level of competence in pitch perception has proven limited. The present study investigates laypersons' ability to objectively evaluate melodies performed by untrained singers. For this purpose, laymen listeners were asked to judge sung melodies. The results were compared with those of music experts who had performed the same task in a previous study. Interestingly, the findings show a high objectivity and reliability in layman listeners. Whereas both the laymen's and experts' definition of pitch accuracy overlap, differences regarding the musical criteria employed in the rating task were evident. The findings suggest that the effect of expertise is circumscribed and limited and supports the view that laypersons make trustworthy judges when evaluating the pitch accuracy of untrained singers.

Humans use sensory input to anticipate events. The brain's capacity to predict cues in time is commonly assumed to be modulated by two uncertainty parameters, the hazard rate (HR) of event probability and the uncertainty in time estimation, which increases with elapsed time.We investigate both assumptions by manipulating event probability density functions (PDF) in three sensory modalities. First we show, contrary to expectation, that perceptual systems use the reciprocal PDF -and not the HR -to model event probability density. Next we demonstrate that temporal uncertainty does not necessarily grow with elapsed time but also diminishes, depending on the event PDF. Finally we show that reaction time (RT) distributions comprise modality-specific and modality-independent components, the latter likely reflecting similarity in processing of probability density across sensory modalities. The results are consistent across vision, audition, and somatosensation, indicating that probability density is more fundamental than hazard rate in terms of the neural operations determining event anticipation and temporal uncertainty. Previous research identified neuronal activitity related to event probability in multiple levels of the cortical hierarchy such as early and higher sensory (V1, V4), association (LIP), motor and other areas. This work proposed that the elementary neuronal computation in estimation of probability across time is the HR. In contrast, our results suggest that the neurobiological implementation of probability estimation is based on a different, much simpler and more stable computation than HR: the reciprocal PDF of events in time.

The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences.