Speaker:Prof. Maria Chait

Time: 13:00 - 14:30, October 24, 2023

Venue:Room 1113, Wangkezhen Building, Peking University

Host: Prof. Huan Luo


Sensitivity to patterns is fundamental to sensory processing, in particular in the auditory system, and a major component of the influential ‘predictive coding’ theory of brain function. Supported by growing experimental evidence, the ‘predictive coding’ framework suggests that perception is driven by a mechanism of inference, based on an internal model of the signal source. Because of the inherently dynamic nature of sound, key attributes of acoustic sources, including identity, state, and meaning are conveyed as a pattern across time. The detection of patterns also allows the system to extrapolate from past experience to form predictions about the most likely nature of sounds to follow, facilitating effective interaction with our environment on multiple perceptually relevant time scales. However, a key element of predictive coding theory - the process through which the brain acquires this model, and its neural underpinnings – remains poorly understood. I will discuss recent brain imaging and behavioural work which focuses on this missing link. Together, these emerging results paint a picture of the brain as a regularity seeker, rapidly extracting and maintaining representations of acoustic structure on multiple time scales and even when these are not relevant to behaviour. A network of auditory cortical frontal and hippocampal sources is implicated in the course of extracting the regularity and maintaining a top down predictive model. The similarity in brain responses across different instantiations of predictability suggest that they may be reflecting general processes linked to predictive perception.


Maria Chait is a Professor of auditory Cognitive Neuroscience at University College London.

Work in her laboratory, at the interface between cognitive and ‘systems’ neuroscience, is using behavioural methods, eye tracking and functional brain imaging (MEG, EEG and fMRI) to understand the role of the auditory system as the brain’s early warning system and to determine how listeners use sounds to learn about, and efficiently interact with their surroundings.