Topic: response entropy

The role of feedback in sensory systems remains a major puzzle in neuroscience. Classical computational theories such as hierarchical predictive coding[1] or hierarchical Bayesian inference[2] postulate abstract normative goals for the role of feedback connections. However, predictions derived from these theories are typically specified at the level of individual neurons. Whether feedback shapes collective properties of neural populations and how such changes may impact encoding of sensory signals remain unknown. Here we tackle these questions directly by studying the population coding of na

Mirative markers, such as “surprisingly”, are linguistic elements that encode a violation of expectations (Delancey, 1997, 2012; Aikhenvald, 2012). Such markers are used for expectation management during communication, informing the listener about an upcoming unexpected message. Sensitivity to mirative markers relies on two abilities: i) updating expectations upon recognizing a mirative marker, and ii) identifying expectation violations warranting the use of a mirative marker. The aim of this study is to quantify and compare sensitivity to mirative markers in humans and large language models (