Intro Social media, such as Twitter, has shown great potential to analyze real world events, such as politics, product sentiment and natural disasters. In recent years, social media has emerged in the health community, particularly in public health, as a revolutionary data source for a wide range of problems. Vast amounts of naturalistic population data can be collected through social media muc...

Perceptual systems can be altered by immersing observers in environments with statistical properties that differ from those naturally encountered. Here we present a novel method for placing observers in naturalistic audio visual environments whose statistics can be manipulated in very targeted ways. We present the results of a case study that used this method. Observers were exposed to an envir...

In everyday life, we continuously and effortlessly integrate the multiple sensory inputs from objects in motion. For instance, the sound and the visual percept of vehicles in traffic provide us with complementary information about the location and motion of vehicles. Here, we used high-density electrical mapping and local auto-regressive average (LAURA) source estimation to study the integratio...

Statistical learning, the ability to extract regularities from input (e.g., in language), is likely supported by learners’ prior expectations about how component units co-occur. In this study, we investigated adults’ experience with sublexical their native language influences performance on an empirical learning task. Forty German-speaking adults completed a speech repetition task which they re...

Humans develop rich mental representations that guide their behavior in a variety of everyday tasks. However, it is unknown whether these representations, often formalized as priors in Bayesian inference, are specific for each task or subserve multiple tasks. Current approaches cannot distinguish between these two possibilities because they cannot extract comparable representations across diffe...