Topic: volatile environments

‘Surprise’ is used in the neurosciences to explain a multitude of phenomena: from memory-modification and adaptive learning to attentional shift and exploration. However, different studies refer to different definitions of ‘surprise’, and it remains unclear how these different definitions relate (1) to each other and (2) to different phenomena attributed to surprise. To address the 1st issue, we identify 10 mathematical definitions of surprise in a unifying framework and show how they relate to each other. Importantly, we classify these definitions into four main categories: (i) ‘prediction s

Listeners benefit from integrating prior beliefs with auditory sensory signals according to their relative reliability to reduce effects of stochastic noise. In volatile environments, however, listeners should not integrate when a change of signal source renders their prior beliefs irrelevant. Bayesian causal inference could provide the brain with an optimal strategy for adaptively adjusting its reliance on priors. Mechanistically, it has been suggested that the arousal system modulates the weights between prior and likelihoodaccordingly. We tested these hypotheses in an auditory localization

Predicting the location of expected upcoming stimuli is a key function in sensory processing. Noise in the environment reduces the reliability of sensory input and increases the importance of prior information. Yet, sudden changes in the environment can render this prior information irrelevant. In such cases, observers should reset their beliefs and establish new priors using current sensory evidence. To study these dynamics of perceptual belief updating, we conducted a human EEG experiment (N = 29) investigating auditory spatial localization in noisy volatile environments and analyzed the ass